defining the function of plant sigma factorsdefining the function of plant sigma factors . this...

Defining the Function of Plant Sigma Factors

This thesis is presented for the degree of Masters of Science (Research)

Tegan Armarego-Marriott

Supervised by Asst./Prof. Kate Howell and Prof. Ian Small

2012

School of Chemistry and Biochemistry

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Declaration

Unless otherwise stated, the work presented in this thesis is my own work. This work

was carried out in the ARC Centre of Excellence in Plant Energy Biology, Discipline

of Biochemistry and Molecular Biology, School of Chemistry and Biochemistry in

the Faculty of Life and Physical Sciences at the University of Western Australia. The

material presented in this thesis has not been submitted for any other degree or

diploma in this or any other institutions.

Tegan Armarego-Marriott

30 August 2013

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Summary Plastid transcription occurs via either a nucleus-encoded (NEP) or plastid-encoded

(PEP) polymerase. PEP requires a nucleus-encoded sigma factor for promoter

recognition, represented by a single member in bacteria, but by a small gene family

in plants. This study investigated the diversification of sigma factors, and the

resultant implications on family member function.

Investigation of sigma factor maintenance across 31 plant species showed the

consistent presence of multiple (generally 6) sigma factors in angiosperms and

supported a mechanism for sigma factor evolution involving late appearance of

SIG4-like proteins. Interrogation of arabidopsis sigma factor transcript expression

across multiple experimental conditions revealed factor-specific profiles, yet

indicated general correlation of transcript accumulation with requirements for

chloroplast gene expression. Plastid mRNA profiling was undertaken for arabidopsis

mutants with defects in individual sigma factor genes, and revealed previously

undefined putative sigma factor activity on multiple gene promoters. Comparative

analysis of profiles suggested a level of sigma factor functional redundancy, which

emphasised the importance of interpreting sigma factor activity in the context of all

family members, and the need to extend future investigations beyond analysis of

single mutants.

Overall, this study suggested a dominant, but somewhat independent, role for SIG2

and SIG6 in transcription of multiple transcripts, and a more redundant role for SIG3.

SIG5 likely acts as a ‘responsive’ sigma factor and SIG1 seems predominantly

involved in responsive regulation of photosystem genes. Finally, a case study

suggested the involvement of SIG4 in regulation of the plastid-encoded NAD(P)H

dehydrogenase-like complex (NDH) genes, an a role for this factor in coordinated

accumulation of the NDH complex.

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Table of Contents

Declaration ........................................................................................................................................ i

Summary .......................................................................................................................................... ii

Table of Contents ............................................................................................................................ iii

List of Abbreviations ..................................................................................................................... vii

CHAPTER 1 General introduction .................................................................................................. 9

1.1 Plastids ....................................................................................................................... 10

1.1.1 Plastid origin and development ...................................................................... 10

1.1.2 The (essential) nature of plastid genomes ...................................................... 10

1.1.3 The role of the plastid in biotechnology ......................................................... 12

1.2 Plastid Gene Expression ................................................................................................ 15

1.2.1 Transcription................................................................................................... 15

1.2.2 RNA processing and turnover ........................................................................ 15

1.2.3 Translation and post-translational processing ................................................ 17

1.2.4 Mechanisms for regulation of plastid gene expression................................... 18

1.3 The Plastid Encoded Polymerase (PEP) ........................................................................ 19

1.4 Sigma Factors ................................................................................................................ 20

1.4.1 General role of sigma factors.......................................................................... 20

1.4.2 Specific function of higher plant sigma factors .............................................. 21

1.5 Aims and Approach ....................................................................................................... 22

CHAPTER 2 Materials and methods ............................................................................................. 24

2.1 Materials ........................................................................................................................ 25

2.1.1 Seed and plant materials ................................................................................. 25

2.1.2 General chemicals, consumables, water, and solutions .................................. 25

2.1.3 Specialised chemicals and consumables ......................................................... 25

2.1.4 Enzymes and Kits ........................................................................................... 25

2.1.5 Oligonucleotides ............................................................................................. 26

2.1.6 Antibodies ...................................................................................................... 26

2.1.7 Equipment ...................................................................................................... 26

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2.1.8 Software .......................................................................................................... 27

2.2 General techniques ........................................................................................................ 28

2.2.1 Polymerase chain reaction (PCR) ................................................................... 28

2.2.2 Agarose gel electrophoresis ............................................................................ 28

2.3 Growth, development, and collection of plant material ................................................ 28

2.3.1 Growth rooms and conditions......................................................................... 28

2.3.2 Growth of arabidopsis on sterile media .......................................................... 28

2.3.3 Growth of arabidopsis on soil ......................................................................... 29

2.3.4 Collection of arabidopsis tissue for RNA extraction ...................................... 29

2.3.5 Development of double-mutants by crossing ................................................. 29

2.4 Nucleic acid techniques ................................................................................................. 29

2.4.1 Analysis of nucleic acid concentration and purity .......................................... 29

2.4.2 Isolation of total RNA .................................................................................... 30

2.4.3 Purification of total RNA (gDNA digestion) ................................................. 30

2.4.4 Precipitation of total RNA .............................................................................. 30

2.4.5 RNA-denaturing agarose gel electorphoresis ................................................. 30

2.4.6 Synthesis of complementary DNA (cDNA) ................................................... 31

2.4.7 Isolation of plant genomic DNA (gDNA) ...................................................... 31

2.5 Quantitative real-time PCR (qPCR) .............................................................................. 32

2.5.1 Preparation and amplification ......................................................................... 32

2.5.2 Data analysis ................................................................................................... 32

CHAPTER 3 Sigma factor conservation: are multiple factors (consistently) present within a species? .......................................................................................................................................... 33

3.1 Chapter Introduction ...................................................................................................... 34

3.2 Aims and Strategies ....................................................................................................... 35

3.3 Results ........................................................................................................................... 35

3.3.1 Definition of sigma factor relationships across plant species ......................... 35

3.4 Chapter Discussion ........................................................................................................ 39

3.4.1 Discussion of chapter methodologies ............................................................. 39

3.4.2 Discussion of chapter results .......................................................................... 40

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CHAPTER 4 Do sigma factors in a single species exhibit temporal-, spatial-, or response-specific expression profiles? .......................................................................................................... 44



4.3 Results ........................................................................................................................... 46

4.3.1 Sigma factor expression as a function of development, tissue type or stimuli:

interrogation of publicly available microarray data ....................................................... 46

4.3.2 ‘Guilt-by-association’: further definition of sigma factor role by identification

of co-expressed genes of known function ...................................................................... 49




CHAPTER 5 Do sigma factors recognise distinct subsets of plastid gene promoters (or are they functionally redundant)? ........................................................................................................ 63



5.3 Results ........................................................................................................................... 67

5.3.1 Definition of physical phenotypes for publicly available single sigma factor

mutant lines .................................................................................................................... 67

5.3.2 Definition of complete plastid mRNA transcript accumulation profiles for

single sigma factor mutants............................................................................................ 67

5.3.3 Definition of sigma factor mutant mRNA accumulation profiles in the context

of transcription units (operons) ...................................................................................... 72

5.3.4 Analysis of plastid transcript accumulations in the context of the sigma factor

family ............................................................................................................................. 80




CHAPTER 6 Sigma factor case study: SIG4, the significant factor in the regulation of the plastid NAD(P)H dehydrogenase-like complex............................................................................. 89

6.1 Introduction ................................................................................................................... 90


6.3 Results ........................................................................................................................... 93

6.3.1 SIG4 is implicated as the significant factor involved in regulation of the NDH

gene group ...................................................................................................................... 93

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6.3.2 Further support for the molecular phenotype of sig4 as resulting from

transcriptional activity of SIG4 ...................................................................................... 93

6.3.3 Making NDH: co-ordinated expression of nucleus-encoded NDH subunit

transcripts and SIG4 ....................................................................................................... 99

6.3.4 Turning on NDH: what induces SIG4 and NDH? ........................................ 104

6.4 Chapter Discussion ...................................................................................................... 107

6.4.1 Discussion of chapter methodologies ........................................................... 107

6.4.2 Discussion of chapter results .................................................................... 109

CHAPTER 7 General discussion ................................................................................................. 112

7.1 Models for sigma factor function ................................................................................ 113

7.2 The roles and responses of (arabidopsis) sigma factors .............................................. 114

7.2.1 The roles and responses of SIG1 .................................................................. 114

7.2.2 The roles and responses of SIG2 and SIG6 .................................................. 115




7.2 Sigma factor family members - breaking down complex interactions ........................ 118

7.3 Conclusions and future directions ............................................................................... 120

CHAPTER 8 References .............................................................................................................. 123

CHAPTER 9 Appendices ............................................................................................................ 136

9.1 Figures ......................................................................................................................... 137

9.2 Tables .......................................................................................................................... 137

9.3 Arabidopsis lines ......................................................................................................... 138

9.4 Oligonucleotides .......................................................................................................... 138

9.5 Solutions and preparations .......................................................................................... 140

9.6 Supplementary figures and tables ................................................................................ 142

9.7 Acknowlegements ....................................................................................................... 156

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List of Abbreviations SCIENTIFIC

β-ME beta-mercaptoethanol

σ sigma factor

µl microlitres

aa amino acid

ALA aminolevulinic acid

ATP adenine triphosphate

attB target site in bacterial genome for lambda phage attachment

BLRP blue light-responsive promoter

BN-PAGE blue-native polyacrylamide gel electrophoresis

bp base pair

cDNA complementary DNA

CET cyclic electron transfer

CR conserved region

DDW double deionised water

DNA deoxyribonucleic acid

DNase deoxyribonuclease

dNTP(s) deoxyribonucleotide(s)

EDTA ethlenediaminetetraacetic acid

et al., and others (et alii)

EtBr ethidium bromide

gDNA genomic DNA

GK_ GABIKat line (followed by a GABIKat identification code)

kb kilo base

MES 2-(N-morpholino)ethanesulfonic acid

MOPS 3-(N-morpholino)propanesulfonic acid

mRNA messanger ribonucleic acid

MS Murishige and Skoog

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NaAc sodium acetate

NAD(P)H nicotinamide adenine dinucleotide (phosphate)

NDH (plastid) NAD(P)H dehydrogenase-like complex

NEP nuclear encoded (RNA) polymerase

PCR polymerase chain reaction

PEP plastid encoded (RNA) polymerase

poly-A poly-adenylated

PSI photosystem I

PSII photosystem II

qPCR quantitative real-time polymerase chain reaction

PSRP ‘plastid specific’ ribosomal protein

RNA ribonucleic acid

Rpm rotations per minute

RpoT T3/T7 phage-like RNA polymerase

rRNA ribosomal ribonucleic acid

RuBisCO ribulose-1,5-bisphosphate carboxylase oxygenase

SA_ Salk line (followed by a Salk identification code)

TP transit peptide

tRNA transfer ribonucleic acid

UCR unconserved region

UTR untranslated region

ycf hypothetical chloroplast open reading frames

OTHER

AU Australia

CPEB Australian Research Council Centre of Excellence, Plant Energy Biology

NSW New South Wales (Australia)

VIC Victoria (Australia)

WA Western Australia (Australia)

CHAPTER 1

General introduction

Chapter 1: General introduction

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1.1 Plastids

1.1.1 Plastid origin and development

The defining characteristic of the photosynthetic eukaryote is its reliance on the

chloroplast, a specialised organelle that is primarily involved in creating energy-rich

molecules using solar energy (reviewed in Neuhaus and Emes (2000), Lopez-Juez

and Pyke (2005)). The chloroplast is a member of a group of organelles known as

plastids, which includes other biosynthetically active members that are sites for

various important metabolic pathways within non-photosynthetic tissues (e.g.

etioplasts, chromoplasts, leucoplasts, amyloplasts). The contemporary double-

membrane bound plastid seen in higher plants, red and green algae, and

glaucophytes, arose more than 1.2 billion years ago (Butterfield, 2000) following a

single primary endosymbiosis of a cyanobacterial ancestor by an ancestral eukaryote

(Palmer, 2003), as first described by Mereschkowski ((1905); Figure 1). Engulfment

was followed by loss of large amounts of plastid genetic material to the nucleus by

lateral gene transfer (Martin, 2003). In the model plant Arabidopsis thaliana

(hereafter referred to by the common name, arabidopsis), for example, at least 1.6 to

9.2% of genes in the nuclear genome have suspected cyanobacterial origin (Rujan

and Martin, 2001). Gene transfer requires specific energetic developments, yet

concedes certain advantages including nuclear primacy in gene regulation (Martin et

al., 1998, Abdallah et al., 2000, Martin et al., 2002, Stegemann and Bock, 2006). The

result is a modern higher-plant plastid, containing just approximately 5% of the

genes found in its cyanobacterial cousins (Kaneko et al., 1996, Martin et al., 2002,

Martin, 2003), which, due to its reliance on non-organellar components, is referred to

as semi-autonomous.

1.1.2 The (essential) nature of plastid genomes

The semi-autonomous modern higher plant plastid has a proteome including

approximately 3,500 proteins, yet the plastid itself typically contains only 120 genes

(Martin et al., 2002). These may be grouped into three functional categories. The first

comprises of genetic system genes, including those for tRNAs, rRNAs, plastid-

encoded RNA polymerase (PEP) subunits, and ribosomal protein subunits, as well as

the genes clpP and matK. The second group includes all photosynthesis-related

genes, such as genes for subunits of photosystem I (PSI) and photosystem II (PSII),

Figure 1: Proposed mechanism for the evolution of the photosynthetic organism.

An ancestral, mitochondriate eukaryote (A), engulfed a cyanobacterium, (B, C) resulting in the formation of an ancestral plastid-containing eukaryote (D). This mechanism was first described by Mereschkowski (1905).

B

Ancestral heterotrophic eukaryote

A C

Ancestral autotrophic eukaryote

D

nucleus

mitochondrion cyanobacterium

plastid


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the cytochrome b6f complex, the ATP synthase, the NAD(P)H dehydrogenase-like

complex (NDH) and the large subunit of RuBisCO (rbcL). Finally, the third group

includes ‘other’ genes such as accD and the three historically named hypothetical

chloroplast open reading frames (ycfs) for which protein products have not yet been

confirmed (Sugiura, 1992, Wolfe et al., 1992) [A complete list of arabiopsis plastid-

encoded genes is shown in Table 1].

In monocotyledonous species, an absence of plastid gene expression may not

severely affect embryo or early seedling development, but results in seedling

lethality in the absence of an external carbon source due to loss of photosynthesis

(Stern et al., 2004). In dicotyledonous species Nicotiana tabacum (tobacco) and

arabidopsis, disrupted plastid expression can result not only in loss of photosynthetic

capacity and arrest of development in typically green tissues, but also in abnormal

floral cell development and seed abortion during embryogenesis (Ahlert et al., 2003,

Legen et al., 2007, Berg et al., 2005). That is to say, expression of the plastid genome

is essential at the plant level.

1.1.3 The role of the plastid in biotechnology

Stable transformation of the plastid, first successfully undertaken in 1988 for

Chlamydomonas reinhardtii (Boynton et al., 1988), and soon followed by

transformation of the higher plant tobacco (Svab et al., 1990), is now possible for an

ever-growing number of important model and crop organisms, including Lactuca

sativa (lettuce: Lelivelt et al. (2005)), Brassica oleracea var. Capitata (cabbage: Liu

et al. (2007)), Brassica napus (rapeseed: Cheng et al. (2010)), Brassica oleracea var.

botrytis (cauliflower: Nugent et al. (2006)), Physcomitrella patens (moss: Sugiura

and Sugita (2004)), Populus alba (poplar: Okumura et al. (2006)), Petunia hybrida

var. Pink Wave (petunia: Zubkot et al. (2004)), Solanum tuberosum (potato: Sidorov

et al. (1999)), Solanum lycopersicum (tomato: Ruf et al. (2001)), Solanum melongena

(eggplant: Singh et al. (2010)), Daucus carota (carrot: Kumar et al.

(2004a)), Gossypium hirsutum (cotton: Kumar et al. (2004b)), Glycine max (soybean:

Dufourmantel et al. (2004)), and (without homoplasty), Oryza sativa (rice: Lee et al.

(2006)). These manipulations include knockout of specific plastid genes (important

in deducing function), replacement of wild-type genes with altered forms, and

insertion of new genes from heterologous sources, the latter two important in

conferring a range of novel functions. Despite the plastid proteome representing


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Table 1: Genes encoded in the Arabidopsis thaliana plastid genome.

The genes and reading frames found in the arabidopsis plastid genome are shown grouped by function.

Gene function Gene name (abbreviation) Genetic system genes Small ribosomal subunit Large ribosomal subunit Plastid encoded polymerase (PEP) subunits Splicing factor Protein degradation rRNA tRNA

rps2, rps3, rps4, rps7, rps8, rps11, rps12, rps14, rps15, rps16, rps18, rps19 rpl2, rpl14, rpl16, rpl20, rpl22, rpl23, rpl32, rpl33, rpl36 rpoA, rpoB, rpoC1, rpoC2 matK clpP rrn16S, rrn23S, rrn5S, rrn4.5S trnA-UGC, trnC-GCA, trnD-GUC, trnE-UUC, trnF-GAA, trnG-GCC, trnG-UCC, trnH-GUG, trnI-CAU, trnI-GAU, trnK-UUU, trnL-CAA, trnL-UAA, trnL-UAG, trnfM-CAU, trnM-CAU, trnN-GUU, trnP-UGG, trnQ-UUG, trnR-ACG, trnR-UCU, trnS-GCU, trnS-GGA, trnS-UGA, trnT-GGU, trnT-UGU, trnV-GAC, trnV-UAC, trnW-CCA, trnY-GUA

Photosynthesis-related genes Photosystem I subunits Photosystem I assembly factors Photosystem II subunits Cytochrome b6f subunits ATP synthase subunits NAD(P)H dehydrogenase-like subunits RuBisCO, large subunit Cytochrome c biogenesis protein Cytochrome c assembly protein

psaA, psaB, psaC, psaI, psaJ ycf3, ycf4 psbA, psbB, psbC, psbD, psbE, psbF, psbH, psbI, psbJ, psbK, psbL, psbM, psbN, psbT petA, petB, petD, petG, petN atpA, atpB, atpE, atpF, atpH, atpI ndhA, ndhB, ndhC, ndhD, ndhE, ndhF, ndhG, ndhH, ndhI, ndhJ, ndhK rbcL ycf10/cemA ycf5

Other genes and ycfs Acetyl-CoA carboxylase subunit Hypothetical conserved open reading frames (unknown function)

accD yc1, ycf2, ycf15


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products of just 120 plastid-encoded genes and only ~10% of the ~30,000 nuclear

genome, plastid transformation confers advantages beyond just the obvious ability to

alter valuable photosynthetic and biosynthetic pathways. Plastid gene insertion,

undertaken by homologous recombination, is precise, and once inserted, genes are

not subject to silencing by RNA interference. Furthermore, through arrangement of

transgenes as polycistronic units, expression of multiple genes - as many as six genes

representing over 6 kb and a seventh antibiotic resistance gene - has been shown to

be functionally possible (Krichevsky et al., 2010). Plastid transformation is safe

relative to nuclear transformation: inheritance of the plastid genome is maternal in

many angiosperm species (Hansen et al., 2007), and thus loss of biological

containment via transmission of plastids through pollen is extremely rare (Ruf et al.,

2007). Finally, expression of transgenes in the plastid can exploit the high innate

translational capacity, with recombinant proteins accumulating in a stable manner to

represent as much as 70% of total leaf protein (Oey et al., 2009), facilitating

‘molecular farming’: the large scale production of important pharmaceutical and

industrial proteins in the plastid (reviewed in Day and Goldschmidt-Clermont (2011),

Maliga and Bock (2011)).

In addition to molecular farming, plastid transformation has already been used for a

range of applications: conferral of resistance and tolerances (including insect

(McBride et al., 1995)), herbicide (Daniell et al., 1998), disease (DeGray et al.,

2001), drought (Lee et al., 2003), salt (Kumar et al., 2004a) and cold (Craig et al.,

2008); enhancement of crop nutritional value (Apel and Bock, 2009); environmental

remediation (Ruiz et al., 2003); and even the conferral of reversible cytoplasmic

male sterility (Ruiz and Daniell, 2005). As such, the vitality of the plastid is limited

not only to the production of energy by photosynthesis, but includes a rapidly

expanding biotechnological role involved in improved production of food, fuels and

pharmaceuticals (reviewed in Maliga and Bock (2011), Clarke and Daniell (2011),

Verma and Daniell (2007), Wang et al. (2009)), the latter of which requires a

thorough understanding of plastid gene expression in order to achieve optimal

results.


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1.2 Plastid Gene Expression

1.2.1 Transcription

RNA synthesis in land plant plastids, while simple relative to that of the nucleus,

involves two types of DNA-dependent RNA polymerases with separate evolutionary

origins, both of which are required for biogenesis and normal function of

photosynthetically-competent chloroplasts (Courtois et al., 2007, Hedtke et al., 1997,

Hedtke et al., 2000, De Santis-MacIossek et al., 1999). The T3-/T7- phage-like

nucleus-encoded RNA polymerase (NEP) is a single subunit enzyme, represented in

arabidopsis by three nucleus-encoded isoforms: one of which is plastid-targeted

(RpoT1, also called RpoTP); one of which is dual-targeted to the plastid and the

mitochondria (RpoT2 or RpoTmp); and one of which is uniquely mitochondrial

(RpoT3 or RpoTm: Hedtke et al. (1997), Hedtke et al. (2000)). The multi-subunit

plastid-encoded RNA polymerase (PEP; discussed further in 1.3) instead shows

homology to the RNA polymerase of eubacteria. Simplistically speaking, NEP and

PEP recognise specific promoters (Figure 2), to regulate production of genetic

system genes, and photosynthesis-related genes, respectively. As such, plastid

development has previously been defined as occurring by a transcriptional cascade:

NEP is responsible for accumulation of plastid ribosomes and PEP, which can in turn

transcribe photosynthesis-related genes (Mullet, 1993). Ultimately, such divisions

and definitions over-simplify reality: NEPs and PEP interact with plastid gene

promoters (which show greater diversity and plasticity than previously understood)

in complex ways, allowing the conditional fine-tuning of plastid gene expression

(Zhelyazkova et al., 2012, Swiatecka-Hagenbruch et al., 2008), as discussed further

in section 1.2.4.

1.2.2 RNA processing and turnover

Plastid transcripts are generally transcribed as polycistronic units, which resemble

the operons of bacteria, but which must be cleaved for the formation of single-gene

transcripts. Additionally, organelle RNAs undergo cis- and trans- splicing for the

removal of introns, processing of 5’ and 3’ ends by exonucleases, and editing: a

process involving cytidine to uridine conversion (reviewed in Monde et al. (2000),

Herrin and Nickelsen (2004)). Many of these processes involve members of the

pentatricopeptide repeat (PPR) family

Figure 2: The dual transcription apparatus of the plant plastid and recognised promoters.

(A) The nuclear-encoded polymerase (NEP) is a single subunit enzyme. Most NEP promoters contain a core YRTA box (type Ia), with some containing an additional GAA motif upstream (type Ib). Type II promoters lack these regions, and instead contain important sequences downstream of transcription start sites (blue arrows) (Swiatecka-Hagenbruch et al., 2007, Swiatecka-Hagenbruch et al., 2008). (B) The plastid-encoded polymerase (PEP) is a multi-subunit bacterial-type enzyme, consisting of plastid-encoded core (α2,β,β’,β’’: shown in green), a nuclear-encoded (blue) sigma factor (σ) required for promoter recognition, as well as up to 50 other nuclear-encoded accessory factors (?). PEP recognises elements with similarity to the bacterial -35 and -10 consensus sequence, and in some cases, additional, more specific cis-elements (orange). Figure adapted from (Schweer, 2010).

B

A

PEP

-35 region -10 region

β''

α

α β β'

DNA

? ?

YRTA box

YRTA box GAA box

Type Ia

Type Ib

Type II

DNA

σ

NEP


17

(Aubourg et al., 2000, Small and Peeters, 2000), sequence-specific RNA binding

proteins implicated in a wide range of functions (reviewed in Schmitz-Linneweber

and Small (2008)), including binding of mRNA 5’ and 3’ termini, which in turn

regulates RNA turnover (Pfalz et al., 2009). RNA degradation occurs by both endo-

and exo-nucleolytic cleavage, and involves poly-adenylation as a mark for

exonucleolytic attack (mechanism reviewed in Monde et al. (2000)).

1.2.3 Translation and post-translational processing

The plastid translational machinery bears high similarity to that of eubacteria,

containing orthologs for all general translation factors required for initiation,

elongation, and release; similar ribosomal proteins, rRNAs, and tRNAs; and mRNAs

that are both uncapped and lacking a poly-adenylated (poly-A) tail (reviewed in

Manuell et al. (2004), Marin-Navarro et al. (2007)). However, the plastid

translational machinery is generally larger: with ribosomal proteins containing short

insertions or extensions at their N- or C-termini, and more complex: the organelle

contains additional ‘plastid-specific’ ribosomal proteins, that have putative structural

or regulatory functions but have no eubacterial orthologs, as well as various other

accessory and mediatory proteins, such as nucleus-encoded activators (Marin-

Navarro et al., 2007, Barkan, 2011). Furthermore, many plastid mRNAs do not

contain Shine-Dalgarno-like sequences in the expected conserved location, required

in eubacteria for the correct positioning and binding of the large ribosomal subunit at

the initiation codon. Instead, substitute elements, including cis-elements allowing

formation of secondary structure in the mRNA, or trans-acting proteins, may

facilitate Shine-Dalgarno-independent translation (Hirose and Sugiura, 1996, Sugiura

et al., 1998).

Protein state may be altered post-translationally by phosphorylation, a process in

plastids most thoroughly understood in terms of thylakoid proteins, but which is now

known to occur on a wide variety of proteins, at many sites, and within all organelle

sub-compartments (reviewed in Ranjeva and Boudet (1987), Bennett (1991)). Protein

degradation occurs by the action of ATP-dependent proteases, such as Clp, FtsH and

Lon, which show homology to bacterial protein degradation machinery, but which

occur as a substantially higher number of isomers, with (likely) differentiated roles

(reviewed in Sakamoto (2006), Vierstra (1993)).


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1.2.4 Mechanisms for regulation of plastid gene expression

In bacterial systems, transcriptional activation acts as a common point of gene

regulation. In the eukaryotic plastid, where transcription and translation are not, as in

bacteria, generally coupled, post-transcriptional control, particularly translation and

post-translational activities, is believed to dominate (Barkan, 2011). Protein

accumulation has been found to show little or no correlation with transcript

accumulation, which in turn may not correlate with transcription rate. For example,

in Chlamydomonas reinhardtii, transcript pools of two plastid genes decreased by as

much as 90% following rifampicin treatment, yet there was no corresponding

decrease in protein synthesis rate (Eberhard et al., 2002), and, in Spinacia oleracea

(spinach), transcriptional activities of genes have been shown to remain unchanged

even when dramatic differences have been seen in mRNA abundances (Deng and

Gruissem, 1987), such as those observed between photosynthetic and non-

photosynthetic tissues (Deng and Gruissem, 1988).

Ultimately, regulation may occur at all steps of gene expression (reviewed in

Mayfield et al. (1995)), and protein levels in at least some species do show a level of

correlation with transcripts (Li et al., 2010). Nonetheless, gene regulation by

transcriptional activation has previously been defined as primarily limited to

responsiveness to light-dark cycles and plastid development, and to affect many

genes in unison (Mayfield et al., 1995).

Recent findings, however, suggest greater complexity of the plastid transcription

machinery than previously thought, which may in turn indicate a greater capacity for,

and role in, plastid gene expression regulation. Both the number and diversity of

promoters is high in the plastid, which has been shown to allow varied transcription

of different individual transcripts and transcript sets (operons) from a range of

promoters, under different internal and external conditions (Swiatecka-Hagenbruch

et al., 2007). For example, NEP units may have an important role in ‘rescuing’ gene

expression when PEP, or either RpoT1 or RpoT2 are deficient and may recognise

non-consensus promoters to do so (Swiatecka-Hagenbruch et al., 2007, Swiatecka-

Hagenbruch et al., 2008). Responsive transcriptional activation of specific genes has

also been reported: for example, the activation of psbD transcription under blue light

(Nagashima et al., 2004b), and the increased transcription of NAD(P)H

dehydrogenase-like complex (NDH) transcripts under photo-oxidative stress


19

(Casano et al., 2001). This latter example suggests the importance of transcription in

gene regulation by defining a two-step process of product up-regulation: the first a

rapid-response involving post-transcriptional activity; and the second involving

transcriptional increases, observed following prolonged stress (Casano et al., 2001).

Conditional transcriptional activity indicates conditional recognition of promoters

followed by transcription initiation. The former of these implies a mechanism for

nuclear control of plastid transcription, requiring the nucleus-encoded polymerase

and/or the nucleus-encoded promoter recognising sigma factors, which make up part

of the PEP complex. Interestingly, sigma factors have previously been shown to be

differentially regulated in response to environmental conditions, and as a result

differentially regulate the transcription of certain genes (for example, Nagashima et

al. (2004b)). Further understanding of the complex interplay between the six sigma

factor family members in arabidopsis (introduced in section 1.4), will elucidate the

complex role of transcriptional activation in controlling plastid gene expression and

plant responses to stimuli.

1.3 The Plastid Encoded Polymerase (PEP) The plastid-encoded RNA polymerase, simplistically described as being involved in

transcription of photosynthesis-related genes, bears sequence and structural

homology to the eubacterial RNA polymerase (Igloia and Kössela, 1992). It consists

of subunits α, β, β’, and β’’, respectively transcribed from the plastid encoded genes

rpoA, rpoB, rpoC1 and rpoC2, equivalent to those units found in Escherichia coli,

except that β’ and β’’ respectively encode regions equivalent to the N- and C-termini

of the bacterial β unit. While etioplast PEP represents this ‘prokaryote-like’

polymerase, the PEP enzyme undergoes structural re-organisation during light-

dependant plastid maturation resulting in a more complex ‘eukaryote-like’ PEP

enzyme, which contains as many as many as 50 nucleus-encoded accessory peptides

(Pfannschmidt and Link, 1994, Pfannschmidt et al., 2000), and appears to bear

different promoter recognition properties (Pfannschmidt and Link, 1997). A recent

study of the Sinapis alba (mustard) PEP suggests just ten of these accessory peptides

are essential: the knockout mutants display a pale phenotype consistent with PEP

deficiency (Steiner et al., 2011). The role of the other peptides is currently poorly

defined, but PEP composition is known to be highly dynamic under developmental,


20

environmental and tissue-based contexts, with variants displaying distinct

biochemical responses and activities (Pfannschmidt et al., 2000, Schweer, 2010,

Allison, 2000), further suggesting flexibility of plastid gene expression at the

transcriptional level. PEP promoter recognition is also similar to that of bacteria in

that it requires a dissociable, prokaryotic-type sigma factor, encoded in plants by the

nucleus.

1.4 Sigma Factors

1.4.1 General role of sigma factors

By definition, sigma factors interact, in a transient manner, with the core PEP

enzyme, forming a holoenzyme capable of specific promoter recognition. Where

species contain multiple family members, PEP-sigma interaction likely occurs at a

similar region within the core and there is evidence for competition between factors

(reviewed in Helmann and Chamberlin (1988)). Holoenzyme formation mediates

promoter recognition: tight DNA binding is not possible by free sigma factors; and

likely allows sigma factor inhibition of PEP-core-mediated transcription of non-

promoter DNA. In the holoenzyme form, the sigma factor may also be involved in

DNA melting of the -10 promoter region (Helmann and Chamberlin, 1988) .

Specific sigma factor activities are attributed to conserved regions (CR) 1-4 in their

protein sequences, which include subregions 2.1 (core-enzyme interaction), 2.4

(recognition of the -10 promoter) and 4.2 (recognition of the -35 promoter), as well

as regions involved in DNA melting (subregion 2.3), recognition of the extended -10

promoter (3.0), inter-region interaction and stabilization (1.2) and inhibition of non-

specific transcription (1.1) (reviewed in Helmann and Chamberlin (1988), Isono et

al. (1997b), Gruber and Gross (2003)). Structurally, plant sigma factors contain

regions divergent from bacterial factors, including an extended N- terminus not

found in bacteria (deemed the unconserved region (UCR)) that has a prominent but

not exclusive role in determining sigma factor functionality (Schweer et al., 2009),

and a transit peptide (TP) for organelle targeting.

E. coli, and closely related bacteria, generally contain a sigma factor, σ70 (Burgess

and Travers, 1969), that is essential for growth. This factor is involved in the

recognition of the -35 element (TTGaca; capital letters indicate greater conservation),


21

and the -10 Pribnow box (TAtaaT) promoters utilised for the majority of cellular

transcription. Additionally, E. coli contains alternative sigma factors, such as σ54, that

coordinate regulation of gene sets from separate promoter sequences under specific

conditions. Non-bacterial sigma factors are grouped based on their similarity to

E. coli σ70 or σ54, which differ from each other in both sequence and transcription

mechanism. Higher plant sigma factors, including those of model plant arabidopsis,

generally show homology to eubacterial σ70 (Isono et al., 1997b, Kanamaru et al.,

1999), and recognise -35/-10 bacterial-like consensus sequence, and, in some cases,

additional more specific cis-elements (Figure 2). σ54 will not be discussed further

(reviewed in Buck et al. (2000), Morett and Segovia (1993)).

1.4.2 Specific function of higher plant sigma factors

Unlike bacteria, higher plants do not have a single, essential sigma factor, but instead

seem to contain sigma factors as multiple members of a small, semi-redundant gene

family, which bear homology to the bacterial σ70. The presence of multiple factors in

a single species suggests several possible models for sigma function, as described

previously (Yao et al., 2003). The first involves different factors exhibiting different

developmental- (temporal) or tissue- (spatial) specific expression profiles. In light of

increasing evidence supporting variation in plastid transcription in response to

various stimuli, this may be extended to include sigma factor expression profiles that

differ also as a function of environmental perturbations. Additionally, or alternatively

(as no proposed function is mutually exclusive), factors may recognise distinct

subsets of promoters, potentially transcribing exclusive transcript sets. Finally,

factors may be redundant (Yao et al., 2003).

The sigma factor family in the model plant arabidopsis contains six members (SIG1-

SIG6). Interestingly, these factors have been shown to differ developmentally, and

by tissue type, with their expression regulated not only at transcriptional, but also at

translational (adjustment of protein abundance), and post-translational (protein

phosphorylation) levels (Brautigam et al., 2011, Gowik et al., 2011, Privat et al.,

2002, Baginsky et al., 1997, Schweer et al., 2010). Furthermore, as well as showing

circadian rhythmicity (Kanamaru et al., 1999) and response to light intensity and

type (Tsunoyama et al., 2004, Isono et al., 1997b, Tanaka et al., 1997, Nagashima et

al., 2004b), sigma accumulation or activity may respond to other conditions less

obviously associated with chloroplast function, including temperature, salt or other


22

osmotic stimuli (Nagashima et al., 2004b), supporting a mechanism for conditional

control of transcription.

Only two of the six arabidopsis sigma factor single mutants, sig2 and sig6, exhibit a

visible phenotype indicating reduced fitness (Fujiwara et al., 2000, Kanamuru et al.,

2001, Nagashima et al., 2004b, Tsunoyama et al., 2004, Ishizaki et al., 2005,

Loschelder et al., 2006). Thorough analysis of plastid transcript accumulation in

these mutants suggests activity of SIG2 (Nagashima et al., 2004a) and SIG6 (Ishizaki

et al., 2005) on the promoters of multiple photosynthesis-related genes. A similarly

comprehensive study has suggested specific activity of SIG3 on psbN (Zghidi et al.,

2007), with other studies indicating the involvement of SIG4 in ndhF transcription

(Favory et al., 2005), and SIG5 in blue-light induced transcription of psbD (Hoffer

and Christopher, 1997, Nagashima et al., 2004b). Finally, the dominant function of

SIG1 seems to be regulation of photosystem stoichiometry through transcriptional

activity on psaA and psbA (Shimizu et al., 2010). As such, heterogeneity of function

has been determined for the arabidopsis sigma factor family.

Nonetheless, there is some evidence of sigma factor member redundancy: separate

factors are involved in the transcriptional activation of single genes, and sigma factor

family members have been shown to complement and rescue, or even compete with

the activity of other members (Privat et al., 2002). For example, in arabidopsis, the

promoter of psbA, is recognised by SIG1, SIG2 and SIG3 (Privat et al., 2002).

Ultimately, while some detail is known about the specificity and mechanisms of

individual sigma factors, the precise way in which sigma factors work in a chorus

with other sigma family members, and as part of the interplay between PEP and NEP

to control plastid transcription, is not completely understood.

1.5 Aims and Approach In the context of the importance of the chloroplast as a photosynthetic organelle and

the plastid as a valuable tool in biotechnological processes, a deeper understanding of

plastid gene expression regulation is required. Thus, the major aim of this project

was to comprehensively analyse sigma factors in parallel to determine sigma factor

family member functions.


23

The work presented here approached the question of sigma factor function in the

context of a previous statement (Yao et al., 2003), which suggests, where multiple

factors are present in one species, three non-exclusive models for function: that

factors exhibit specific contextual expression profiles; that factors recognise distinct

promoter sets; and that factors are functionally redundant. As such, major questions

that arise in defining sigma factor function include:

Are multiple factors (consistently) present within a species?

Do sigma factors in a single species exhibit temporal-, spatial-, or response-

specific expression profiles?

Do sigma factors recognise distinct subsets of plastid gene promoters, or are

factors functionally redundant?

This project focused on analysis of the model plant Arabidopsis thaliana in

answering these questions, utilising the public availability of T-DNA insertion

mutants showing specific down-regulation of single genes, as well as vast databases

defining arabidopsis gene expression in a multitude of contexts, to investigate sigma

factor function by both novel experimental-, and analytical- methods.

Chapter 2: Materials and methods

24

CHAPTER 2

Materials and methods


25

2.1 Materials

2.1.1 Seed and plant materials

Wild-type and mutant seeds were ordered from the European Arabidopsis Stock

Centre (NASC, arabidopsis.org.uk./), with some sigma factor mutants kindly

provided by Dr. Jennifer Schweer (University of Bochum, Germany). The lines used

in this project are listed in section 9.3. Sigma factor double mutants were produced

by crossing (section 2.3.5) as part of this project. With the exception of plant material

used for the initial single replicate of plastid mRNA accumulation by Asst./Prof.

Kate Howell prior to the commencement of this project, all plant material was grown

within the University of Western Australia, by myself, during this project.

2.1.2 General chemicals, consumables, water, and solutions

All general and specialised reagents were of a molecular biology, analytical, or

equivalent grade, obtained from commercial suppliers including: Bio-Rad

(Gladesville, AU); BioScientific (Sydney, AU); Crown Scientific (Minto, AU);

Fisher-Biotech (Wembley, AU); GE Healthcare (Rydalmere, AU); Invitrogen

(Mulgrave, AU); Mirella Research (Brunswick, AU); Promega (Alexandria, AU);

Qiagen (Clifton Hill, AU); Roche (Castle Hill, AU); Scientifix (Cheltenham, AU);

Sigma-Aldrich (Castle Hill, AU). A list of prepared solutions is found in Section 9.5.

Water soluble solutions were prepared with double deionised water, obtained by

purification with an Ibis Technology PURELAB Classic water purification system.

This water was used for all preparations, except those involving RNA elution or re-

suspension, in which case RNase free water (from the QIAGEN RNeasy Plant mini

Kit) was used.

2.1.3 Specialised chemicals and consumables

1 Kb DNA Extension Ladder Invitrogen (Mulgrave, AU)

First Strand buffer Invitrogen (Mulgrave, AU)

2.1.4 Enzymes and Kits

RNeasy Plant mini Kit Qiagen (Clifton Hill, AU)

QIAquick Gel Extraction Kit Qiagen (Clifton Hill, AU)

QIAquick PCR Purification Kit Qiagen (Clifton Hill, AU)

Gateway® BP Clonase® II enzyme mix Invitrogen (Mulgrave, AU)

Gateway® LR Clonase® II enzyme mix Invitrogen (Mulgrave, AU)


26

Turbo DNase kit Ambion, (Scorseby, AU)

Superscript III Reverse Transcriptase Invitrogen (Mulgrave, AU)

pGEM®-T Easy Vector System I Promega (Alexandria, AU)

2.1.5 Oligonucleotides

The oligonucleotides used within this project were purchased from Sigma-Aldrich

(Castle Hill, AU). Oligonucleotides used for qPCR analysis of the chloroplast

genome were designed by Dr Etienne Delannoy prior to the commencement of this

project. Quantprime software was used to design other qPCR primers

(www.quantprime.de/: Arvidsson et al. (2008)). Sigma genotyping primers were

designed using PrimerL (http://signal.salk.edu/tdnaprimers.2.html). All

oligonucleotides used are listed in section 9.4

2.1.6 Antibodies

The NDH subunit antibodies were kindly provided by Professor Toshiharu Shikanai

(Kyoto University, Japan). All other antibodies were ordered by CPEB from

Agrisera (http://www.agrisera.com/).

2.1.7 Equipment

Ball Mill MM301 Ball Mill (Retsch, Newton, USA)

Bead Stainless steel, 5 mm (QIAGEN, Clifton Hill, AU)

Centrifuge Eppendorf 5417R (Crown Scientific, Moorebank, AU)

Eppendorf 5810R (Crown Scientific, Moorebank, AU)

Electrophoresis Cell Mini-PROTEAN Tetra Cell (Bio-Rad, Sydney, AU)

Wide Mini-Sub Cell GT Cell (Bio-Rad, Sydney, AU)

Growth Cabinet Bigfoot Series Growth Cabinet (Biochambers Inc.,

Canada)

Shaker/incubator Innova-40 Incubator Shaker

Belly Dancer undulating orbital shaker Sigma-Aldrich

(Castle Hill, AU)

MaxQ 5000 orbital shaker (Thermo Scientific,

Wilmington, USA).

Laminar Flow Gelaire BH-EN Class II biological safety cabinet

(Gelaire, Sydney, AU)

Lightcycler Roche LC480 (Roche, Castle Hill, AU)

http://www.quantprime.de/

http://signal.salk.edu/tdnaprimers.2.html

http://www.agrisera.com/


27

Spectrophotometer Nanodrop ND-100 spectrophotometer (Thermo

Scientific, Wilmington, USA).

Thermocycler Eppendorf Mastercycler Epgradient S Thermocycler

(Crown Scientific, Moorebank, AU)

Thermomixer Eppendorf Thermomixer Comfort with exchangeable

thermoblocks (Crown Scientific, Moorebank, AU)

Transilluminator Gel-Doc XR Transilluminator (Bio-Rad, Sydney, AU)

Transfer Cell Trans-Blod SD Semi-Dry Electorphoretic Transfer Cell

(Bio-Rad, Sydney, AU)

2.1.8 Software

In silico alignments and digests were performed using the DNASTAR Lasergene

Core Suite, specifically Seqman and Seqbuilder (http://www.dnastar.com/t-products-

lasergene.aspx; Burland (2000)). qPCR data were analysed using the LightCycler

data analysis software (Roche). Publicly available microarray data were analysed

using Genevestigator (https://www.genevestigator.com/; Hruz et al. (2008)), and

online correlation programs: ACT (http://www.arabidopsis.leeds.ac.uk/; Manfield et

al. (2006)), ATTED-II CoExSearch ver. c4.1 (http://atted.jp/; Obayashi et al. (2009)),

BAR Expression Angler (http://bar.utoronto.ca/welcome.htm; Toufighi et al. (2005)),

CressExpress (http://cressexpress.org/; Srinivasasainagendra et al. (2008)),

GeneCAT (http://genecat.mpg.de/; Mutwil et al. (2008)). CressExpress version 3.2

was used, with a Kolmogorov-Smirnov quality control statistic of 0.15, all tissue

types, all experiments and an r2 threshold of 0.36. The probes for the six arabidopsis

sigma factors queried were: 262879_at (SIG1); 264781_at (SIG2); 251929_at (SIG3);

250255_at (SIG4); 249769_at (SIG5); 263846_at (SIG6). Plant sigma-like gene

products were obtained via Phytozome v8.0 (http://www.phytozome.net/: Goodstein

et al. (2012)), and pairwise relationships defined using Clustal Omega

(http://www.ebi.ac.uk/Tools/msa/clustalo/: Larkin et al. (2007), Goujon et al.

(2010)). Trees were built from pairwise relationships using GeneiousPro, (created by

Biomatters http://www.geneious.com/: (2012)), with a consensus tree created form

1000 trees resampled using the bootstrap method and a support threshold defined as

50%.

http://www.dnastar.com/t-products-lasergene.aspx

http://www.dnastar.com/t-products-lasergene.aspx

https://www.genevestigator.com/

http://www.arabidopsis.leeds.ac.uk/

http://atted.jp/

http://bar.utoronto.ca/welcome.htm

http://cressexpress.org/

http://genecat.mpg.de/

http://www.phytozome.net/

http://www.ebi.ac.uk/Tools/msa/clustalo/

http://www.geneious.com/


28

2.2 General techniques

2.2.1 Polymerase chain reaction (PCR)

The standard PCR reaction mixture (10 µL) contained 1 x Taq buffer (9.5), 0.2 mM

of each dNTP (dATP, dCTP, dGTP, dTTP), 0.1 µM of each primer and

1 U/µL Taq polymerase (Biolabs, Arundel, AU). The standard program used for

amplification was 94 °C for 5 minutes; followed by 35-40 cycles of 94 °C for

30 seconds, 52 °C for 30 seconds and 72 °C for 1 minute per kb of product; followed

by 72 °C for 5 minutes. Amplification was undertaken using an Eppendorf

Mastercycler.

2.2.2 Agarose gel electrophoresis

PCR products were separated by gel electrophoresis (Wide Mini-Sub Cell) in a

1% [w/v] agarose/TBE (section 9.5) gel containing 0.5 µg/mL ethidium bromide.

Loading dye (9.5) was added to products to a final concentration of 1 x, and products

run at 120 V in TBE buffering solution against 500 ng of the 1 Kb DNA Extension

Ladder until adequately separated. DNA fragments were visualised and

photographed under ultraviolet light using a Gel-Doc XR Transilluminator.

2.3 Growth, development, and collection of plant material

2.3.1 Growth rooms and conditions

Arabidopsis wild-type and mutant plants were grown under controlled standard and

experimental conditions in specialised growth rooms, or within the Bigfoot Series

Growth Cabinet. Under standard conditions during the photoperiod, light intensity

was 150-200 µE m-2 sec-1, humidity 60%, and temperature 22 °C. During the dark

period (light intensity 0 µE m-2 sec-1), temperature was 16 °C. The photoperiod lasted

8 hours under short day conditions, and 16 hours under long day conditions. For

fluctuating high light (FHL) experiments, light intensity was 650-700 µE m-2 sec-1 for

3 minutes, followed by 150-200 µE m-2 sec-1 for 7 minutes, repeated throughout the

photoperiod, with all other parameters as standard.

2.3.2 Growth of arabidopsis on sterile media

Surface sterilisation of arabidopsis seeds was undertaken in a Gelaire BH-EN

laminar flow. To approximately 100-250 µL of seed in a 2 mL microcentrifuge tube,

1 mL of sterilisation solution (9.5) was added and the product mixed continuously by


29

inversion for 5 minutes. The sterilisation solution was removed, and seeds washed

well: twice with 70% [v/v] ethanol, and once with 100% ethanol. Ethanol was

removed and seeds air-dried completely on sterile filter paper. Sterile seeds were

stored in clean microcentrifuge tubes prior to use. Seeds were sown on sucrose-

supplemented MS growth media (9.5) and imbibed and stratified for approximately

48 hours at 4 °C prior to being placed in the light.

2.3.3 Growth of arabidopsis on soil

Unsterilized seed or arabidopsis seedlings were placed on pre-wet soil (9.5). Plants

were watered as required. Plants grown to maturity were covered in bags as siliques

began to dry, with hand-collected seeds stored in microcentrifuge tubes at room

temperature prior to use.

2.3.4 Collection of arabidopsis tissue for RNA extraction

Seeds were lightly spread or placed equidistance apart and grown on sterile media.

Upon collection, seedlings were removed from the agar medium and aerial tissue of

individual leaves snap-frozen in liquid nitrogen. Samples were stored at -80 °C prior

to use.

2.3.5 Development of double-mutants by crossing

Double sigma factor mutants were generated by crossing single mutants. Briefly,

mature siliques, open flowers and young buds were removed from the mother plants

and developing buds opened gently, petals and sepals removed, and flowers

emasculated. Exposed stigmas were gently brushed with pollen from the father plant,

and siliques allowed to fully develop prior to harvesting. T1 offspring were allowed

to self-fertilized.

2.4 Nucleic acid techniques

2.4.1 Analysis of nucleic acid concentration and purity

Purified nucleic acid concentrations were analysed using a Nanodrop ND-100

Spectrophotometer. The A260 to A280 and A230 to A260 ratios were taken to assess the

purity of DNA and RNA samples. Purity was indicated by an A260/A280 of ~1.8 for

DNA and ~2.0 for RNA and A260/A230 in the range of 2.0-2.2.


30

2.4.2 Isolation of total RNA

A single 5 mm stainless steel bead was added to plant tissue weighing no more than

100 mg, in a 2 mL microfuge tube. Samples were ground to homogeneity (20 Hz, 2x

90 seconds, MM301 Ball Mill), maintained at low temperatures throughout the

process. Total RNA extraction was isolated using the RNeasy Plant Mini Kit

following the manufacturer’s instruction. All additional recommended steps were

undertaken, and RNA was eluted in a 50 µL volume.

2.4.3 Purification of total RNA (gDNA digestion)

The digestion of genomic DNA (gDNA) was undertaken using the Turbo DNase kit

according to the manufacturer’s instructions for standard digestion, except that

samples were incubated at 37 °C for 45, as opposed to 30, minutes. Following

precipitation of the RNA, purity was assessed by PCR using primers targeted at

plastid, mitochondrial and nuclear gDNA, and with arabidopsis genomic DNA as a

template for a positive control reaction. PCR products were separated by agarose gel

electrophoreses and visualised, with the absence of visual product indicating the

absence of gDNA contamination.

2.4.4 Precipitation of total RNA

Following Turbo DNase digestion, total RNA was precipitated by the addition of 0.1

volumes of sodium acetate (NaAc: 3M, pH 5.2) and 2.5 volumes of precooled (-20

°C) 100% ethanol. Samples were incubated at – 20 °C overnight prior to 20 minutes

of centrifugation (Eppendorf 5417R) at 4 °C at 20,000 x g. The supernatant was

discarded and 200 µL of precooled 80% [v/v] ethanol added to each sample.

Following brief, vigorous, vortexing, samples were further centrifuged (10 min, 4 °C,

20,000 x g) and the supernatant once again discarded. Samples were air-dried at

room temperature and RNA resuspended by pipetting in 20 µL of RNase-free water.

RNA samples were stored at -20°C for short periods prior to use, or at -80 °C when

stored for longer periods of time.

2.4.5 RNA-denaturing agarose gel electorphoresis

To approximately 300 ng of RNA was added 3 volumes of RNA loading buffer, and

samples denatured by heating (75 °C, 5 min, Eppendorf Mastercycler Epgradient S

Thermocycler). Samples were maintained on ice until loaded into a

1% [w/v] agarose/MOPS gel (9.5) and run at 120 V in 1 x MOPS until sufficiently


31

separated. Samples were visualised and photographed under ultraviolet light using a

Gel-Doc XR Transilluminator.

2.4.6 Synthesis of complementary DNA (cDNA)

To 1.5 µg of total plant RNA was added 250 ng of oligodT primer (9.4) and 0.5 mM

dNTP, to a final volume of 13 µL. Samples were incubated (Eppendorf Mastercycler

Epgradient S Thermocycler) at 65 °C for five minutes and immediately placed on ice

for a further five minutes. To each sample 7 µL of synthesis mixture containing a

final concentration of 200 U of Superscript III Reverse Transcriptase, 1 x First

Strand buffer, and 5 mM dithiothreitol was added and samples were incubated at

25°C for five minutes, followed by 50 °C for one hour. The enzyme was inactivated

by further incubation at 70 °C for 15 min. Diluted (1 in 20) cDNA was used as a

standard PCR template with primers designed to amplify plastid DNA, in order to

assess the success of synthesis. Product was visualised following separation by

agarose gel electrophoresis, with presence of product indicating successful cDNA

synthesis.

2.4.7 Isolation of plant genomic DNA (gDNA)

Total genomic DNA (gDNA) was isolated from a small mass (5-10 mg) of leaf tissue

using an adapted version of the cetyltrimethylammonium bromide (CTAB)-based

isolation method (Doyle and Doyle, 1990). Briefly, to leaf tissue in a 2 mL

microfuge tube, 400 µL of extraction buffer (9.5) and a 5 mm stainless steel bead

were added. Samples were ground to homogeneity (20 Hz, 2x 90 seconds, MM301

Ball Mill), and centrifuged (Eppendorf 5417R) for two minutes, at 23 °C, 4,000 x g.

Samples were incubated (Eppendorf Thermomixer Comfort) with mixing (15 min,

65°C, 1,000 rpm), 400 µL chlororm:isoamyl alchohol (24:1) was added, and samples

further incubated (30 min, 65°C, 1000 rpm). Following centrifugation (15 min, 4 °C,

20,000 x g,), 100 µL of the upper phase was added to 100 µL isoporopanol and

10 µL of NaAc (3 M, pH 5.2) and briefly mixed by vortexing. Samples were

centrifuged (30 min, 4 °C, 20,000 x g), the supernatant removed and the remaining

pellet washed with 80% [v/v] ethanol. Following a final centrifugation (15 min, 4

°C, 20,000 x g) and removal of ethanol, samples were dried (10 min, 65 °C) and

DNA resuspended with incubation in 40 µL of milliQ water (15 minutes, 23 °C,

1,000 rpm).


32

2.5 Quantitative real-time PCR (qPCR)

2.5.1 Preparation and amplification

qPCR was performed using random- or dT-primed cDNA template, synthesised from

purified, intact, total plant RNA, that had been isolated from plants grown on

sucrose-supplemented media under standard or experimental conditions. qPCR was

performed using a Roche LightCycler 480 in a final reaction volume of 5 µL

consisting of: 0.5 µM primer pair (0.25 µM each); 1 X LightCycler 480 SYBR Green

I Master [Roche]; 0.5 µL of template (cDNA: for plastid genes: 1 in 200 dilution,

random-primed; for nuclear genes: 1 in 20 dilution, oligodT-primed). The program

consisted of denaturation (10 min, 95 °C), 40 amplification cycles (15 sec, 95 °C; 5

sec, 55 °C; 10 sec, 72 °C), melting curve analysis (95 °C for 0 sec, 70 °C for 30 sec

followed by a transition rate of +0.1 °C per cycle and continuous data acquisition),

and cooling (40 °C for 30 sec). Three technical replicates were performed for each

sample.

2.5.2 Data analysis

Data were analysed using the LightCycler data analysis software (Roche). Melt curve

analysis of products was undertaken to ensure specific amplification had occurred.

Crossing point values were calculated under high confidence, against a standard

curve of wild-type Col-0 cDNA (concentrations 10, 1, 0.2 and 0.1 relative to sample

dilutions). Data were normalised against the median or against housekeeping gene

levels.

Chapter 3: Sigma factor conservation: are multiple factors (consistently) present within a species?

33

CHAPTER 3

Sigma factor conservation: are multiple factors (consistently)

present within a species?


34

3.1 Chapter Introduction

Unlike bacteria, which contain a single, essential σ70 factor necessary for growth, the

model plant arabidopsis contains six sigma factors as a small gene family that bear

homology to the bacterial σ70. This homology suggests acquisition of a single

σ70 with the engulfment of a cyanobacterial ancestor by an ancestral, mitochondriate

eukaryote (the formation of the ancestral plastid-containing eukaryote), followed by

movement of the single σ70 gene to the nucleus by lateral gene transfer, and

ultimately, sigma factor diversification.

Previous analysis has shown the presence of multiple sigma factors, bearing

homology to the arabidopsis factors SIG1-SIG6, in other plant species. This has

included the discovery of five sigma factors in Zea mays (maize: Lahiri et al. (1999),

Lahiri and Allison (2000), Beardslee et al. (2002), Tan and Troxler (1999)), two

factors in tobacco (Oikawa et al., 2000), and in the moss Physcomitrella patens Hara

et al. (2001b), Hara et al. (2001a), and a single factor in mustard (Kestermann et al.,

1998), Triticum aestivum (wheat: Morikawa et al. (1999)), Sorghum bicolor

(sorghum: Kroll et al. (1999)), and rice (Tozawa et al., 1998). The presence of

SIG1-, SIG2- and SIG5- like sequences, but not of SIG3, SIG4 and SIG6, in

Physcomitrella patens, has suggested the emergence of these latter factors during

angiosperm development (Shiina et al., 2009). Furthermore, the absence of SIG4 in

the monocotyledon species rice, has been proposed to indicate that evolution of this

factor post-dated the monocot/dicot divergence (Shiina et al., 2009).

At a protein sequence level, conserved region analysis shows SIG1 to be the most

closely related to the primary essential factor of E. coli (Fujiwara et al., 2000). The

genomic sequences of SIG1-SIG4 and SIG6, but not SIG5, contain four conserved

intron sites (Lysenko, 2006). Coupled with the divergent amino acid sequence of

SIG5, this suggests that this factor arose independently from other factors (Hakimi et

al., 2000, Lysenko, 2006).

Due to the lack of sequence data available in previous studies, only a fragmented and

incomplete view of sigma factor evolution and maintenance has been developed. The

recent sequencing of many plant nuclear genomes allows a more comprehensive

analysis of sigma factor evolution across a large number of diverse species. Greater

understanding of the representation of sigma factors in different phylogenetic groups,


35

in particular their maintenance across evolutionary time, would provide important

insight into the function of individual family members.

3.2 Aims and Strategies

The primary aim of my work presented in this chapter was to augment the current

understanding of sigma factor functionality and redundancy by investigating the

appearance, maintenance, and loss of sigma factor family members across

phylogenetically distinct groups. The primary strategy consisted of an in silico

analysis of pairwise similarities between 157 sigma-like sequences from 31 available

green plant nuclear genomes.

3.3 Results

3.3.1 Definition of sigma factor relationships across plant species

To define the relationship of plant sigma factors, 31 available green plant nuclear

genomes representing eleven evolutionarily significant nodes were queried for

translation products homologous to the arabidopsis sigma factor protein SIG1 using

Phytozome v8.0 (http://www.phytozome.net/: Goodstein et al. (2012)). The 245

retrieved sequences were aligned using Clustal Omega

(http://www.ebi.ac.uk/Tools/msa/clustalo/: Larkin et al. (2007), Goujon et al. (2010))

and then hand curated, with sequences showing poor alignment, particularly those

missing conserved sigma factor regions, removed. Where multiple models were

present for a gene, the model best covering conserved regions was retained. The

remaining 157 sequences were realigned in Clustal Omega, and the GeneiousPro,

(created by Biomatters http://www.geneious.com/: Kearse et al. (2012)), treebuilder

tool was utilized to create a neighbour-joining tree under the Jukes-Cantor distance

correction model (Jukes and Cantor, 1969). The single sigma factor of Volvox carteri

was defined as an out-group, and a consensus tree was created from 1000 trees

resampled using the bootstrap method, with a support threshold defined as 50%

(Figure 3).

3.3.1.1 The pairwise tree is congruous with defined phylogenetic relationships between

species

The pairwise tree created is congruous with expected phylogenetic relationships

between taxa (Figure 3). The sigma factors of the algae Volvox carteri and



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37

Chlamydomonas reinhardtii clustered externally, as, to a lesser degree, did the

factors from the lycophyte Selaginella moellendorffii and the moss Physcomitrella

patens. Furthermore, the grasses, Sorghum bicolor, Zea mays, Setaria italic, Oryza

sativa and Brachypodium distachyon, clustered separately from the eudicots, with a

distinct clade representing the Brassicales present within the latter. As such, the

positioning of sigma factors in the constructed pairwise tree may be at least

somewhat representative of the evolutionary divergence of these factors.

3.3.1.2 Embryophyte factors group in six distinctive clades

The two C. reinhardtii and single V. carteri genes and the S.moellindorffii gene

SM117159 clustered externally from the six distinctive clades that contained the

remaining sequences, with none of these four sequences forming a sub-clade (Figure

3). Gene SM117159 is likely mis-annotated: the protein sequence does not begin

with the start codon Met. The gene was maintained following curation due to the

near-complete presence of all conserved regions (only a small section of the N

terminus is missing). Of the six arabidopsis sigma factors, it bears highest sequence

identity to SIG2. The C. reinhardtii and V. carteri genes show putative products

somewhat distinct from other sigma-like proteins, with extended regions at the N-

terminal (V. carteri 20003326m.g and C. reinhardtii Cre03g194950) and the C-

terminal (C. reinhardtii Cre03g193400). Pairwise comparison with the six sigma

factors of arabidopsis indicate these factors bear most similarity to SIG1 (V. carteri

20003326m.g and C. reinhardtii Cre03g194950) and SIG5 (C. reinhardtii

Cre03g193400; data not shown). With the exception of the divergent algal gene

products, and the potentially mis-annotated SM1171559, all retrieved sequences

group as members of one of six distinctive clades. These clades are well defined,

and, interestingly, correspond with the six individual factors found within

arabidopsis.

3.3.1.3 Absence of SIG3-, SIG4- and SIG6- like factors in non-angiosperm lineages

The 31 viridiplantae species include, in addition to the two algal genomes, a

bryophyte Physcomitrella patens, and the lycophyte Selanginella moellendorffii,

with the remaining 27 species representing the diverse angiosperm (flowering plant)

division. Both P. patens and S. moellendorffi contained putative homologues of

arabidopsis SIG1, SIG2 and SIG5, but not of SIG3, SIG4 and SIG6 (Figure 4).

Manihot esculenta Ricinus communis Linum usitatissimum Populus trichocarpa Medicago truncatula Phaseolus vulgaris Glycine max Cucumis sativus Prunus persica Malus domestica Arabidopsis thaliana Arabidopsis lyrata Capsella rubella Brassica rapa Thellungiella halophila Carica papaya Citrus sinensis Citrus clementina Eucalyptus grandis Vitis vinifera Mimulus guttatus Aquilegia coerulea Sorghum bicolor Zea mays Setaria italica Oryza sativa Brachypodium distachyon Selaginella moellendorffii Physcomitrella patens Chlamydomonas reinhardtii Volvox carteri

❶❷❸❹❺❻ ❺ ❶❷❸❹❺❻ ❶❷③④❺⑥ ❷❷ 10038823 and 10014934=❺ ❶❷❸❹⑤❻ ❶❷ ①❷❸❹❺❻ ①❷❸❹❺❻ ❶❷③④❺❻ ❶❷❸❹❺❻ ❶❷❸❹❺❻ ❶❷❸❹❺❻ ❶❹ ❶❷❸❹❺❻ ❶❷❸❹❺❻ 940838=❹ ❶❷❸❹❺❻ ❶❷❸❹❺❻ ❺ ❶❷❸❹❺❻ ❶❷③❹❺❻ ①❷❸❹⑤⑥ ①❷❸④❺⑥ ❶❷❸④❺⑥ A02665=❺ ❶❷❸❹❺❻ ❶❷❸④❺❻ ❺ ①②❸❹❺❻ ❶❷❸④❺❻ ❶❷❸④❺⑥ ZM5G813933=❶ ❶❷❸④❺❻ ❷ ❶❷❸④❺❻ ❷ ❶❷❸④❺❻ ❷ ❶❷③④❺⑥ ❺ 2669721=❶, 117159~❷ ❶❷③④❺⑥ ❷❺ ①②③④⑤⑥ ①②③④⑤⑥

present/absent additional putative

Figure 4: Presence and absence of sigma factors across 31 species.

The presence of one or more of the six groups of plant sigma factors, defined by pairwise grouping with one of the six arabidopsis factors. Presence is indicated by filled black circles, and absence by empty circles. Where species contain a factor excluded from the alignment due to poor alignment with the sigma factor conserved regions, but which otherwise bears homology to a sigma factor (and may represent a mis-annotation), a grey circle is shown, and the gene identified (‘putative’). Where multiple sequences representing a single type of signma factor are present in the genome, additional presence is indicated (‘additional’). Note that V. carteri contains one and C. reinhardtii two sigma factors, which clustered externally to other factors, but most closely resemble SIG1, and SIG1 and SIG5, respectively. SIG3-, SIG4- and SIG6-like factors are absent from non-angiosperm lineages, with SIG4 also not found in the grasses. No factor is conserved across all 31 species, but the maintenance of multiple factors is generally seen. Phylogenetic relationship adapted from (http://www.phytozome.net/: Goodstein et al., (2012)).



39

P. patens contained an additional SIG2-like sequence, most likely a recent

duplication, as the two P. patens SIG2-like products grouped together. Interestingly,

both species contained two SIG5-like products, which formed as separate SIG5 sub-

clades (each containing one factor from each species), indicating early

diversification.

3.3.1.4 Grasses do not contain a SIG4-like factor: putative diversification of SIG2

The five grasses are represented by both C4 species Sorghum bicolor, Zea mays and

Setaria italica and C3 species Oryza sativa and Brachypodium distachyon, none of

which possess a factor bearing homology to SIG4 (Figure 4). Interestingly, S. italica,

O. sativa and B. distachyon contain an additional SIG2-like protein, which group

separately from the SIG2-like protein found in all the grasses (i.e., they are unlikely

to represent gene copies or mis-annotations, but may instead represent a true sub-

clade: Figure 3).

3.3.1.5 Multiple factors, multiple losses, multiple gains

No single factor is conserved across all species (Figure 4). Despite their major role in

arabidopsis development, both SIG2- and SIG6- like proteins are absent in certain

clades: Aquilegia coerulea contains no SIG2, and SIG6-like proteins are absent in

Citrus sinensis, Citrus clementine, Eucalyptus grandis and Zea mays. Conversely,

despite its previous definition as ‘rather functionally redundant’, SIG3- like proteins

have only been ‘lost’ from three genomes: Carica papaya, Glycine max and Linum

usitatissimum. While the absence of multiple sigma-like factors from a single species

is not uncommon (e.g. C. sinesis does not seem to contain a homolog to arabidopsis

SIG1, SIG5 or SIG6), certain sigma factors were not found to be absent

simultaneously (SIG1/SIG3, SIG3/SIG5, SIG4/SIG5 and SIG2/(SIG3, SIG4, SIG5,

SIG6). Certain factors were present in duplicate (or multiple copies) within a

genome: particularly SIG2- and SIG5- like factors, as well as SIG1 (Malus

domestica, Populus trichocarpa) and SIG4 (M. domestica).

3.4 Chapter Discussion

3.4.1 Discussion of chapter methodologies

The recent sequencing of multiple plant nuclear genomes has allowed novel analysis

of the relationship between sigma factors across plant species. However, many of

these genomes are still in the early stages of analysis and review, and it cannot be


40

assumed that the 31 genome sequences interrogated in this study are complete, or

that the genes are correctly annotated. As such, analysis of sigma factor maintenance,

particularly absence of genes or presence of multiple gene copies, may indicate an

incomplete or mis-annotated genome.

Using BLAST to search for protein products, as opposed to genome or coding

sequences, was shown to be more specific for retrieval of sigma-like products with

conserved regions (CRs), which, due to maintenance of CRs between bacterial and

higher plant factors (experimentally shown to display sigma activity), is likely to be a

robust mechanism for identifying unknown sigma factors. Ultimately, however, the

protein products identified are only putative sigma factors.

Treebuilding from amino acids using the Geneious software, as opposed to

nucleotide sequences, allows distance correction only by the Jukes Cantor method,

which assumes equal nucleotide frequency and equal rates of nucleotide substitution,

and does not correct for the higher rate of transcriptional (purine to purine or

pyrimidine to pyrimidine) over transversional (purine to pyrimidine or vice versa)

substitutions (Jukes and Cantor, 1969). As such the resultant tree cannot be said to

truly represent a phylogenetic tree. Nonetheless, it was noted that the pairwise tree

created here contained clades representing those defined previously by true

phylogenetic analysis.

3.4.2 Discussion of chapter results

This chapter presented a pairwise model of sigma factor similarity, and analysed the

presence and absence of factors within species, in the context of evolutionary

relationships. Such analysis has only become possible with the recent availability of

multiple plant nuclear genomes, and has not previously been undertaken in the field.

Although earlier research has demonstrated the grouping of other plant factors with

arabidopsis factors (Allison, 2000, Lysenko, 2006), relationship analyses have

involved only five or six (model) plant species. The fact that all embryophyte factors

group into one of six clades representing the six arabidopsis factors, and that the six

factors are generally maintained across angiosperm evolution, has not previously

been shown.

Several factors appear to be absent and other factors present in duplicate or multiple

copies, although it is difficult to assess if this is a result merely of poor genome


41

coverage or annotation. With rapidly decreasing costs of whole-genome sequencing,

more accurate analysis of sigma factor maintenance should be undertaken and

interpreted in a context of implicated functional redundancy, plasticity, and diversity

of factors within and between species.

While the presence of all six factors was generally seen within dicotyledonous

species, it was noted that SIG4- like proteins were completely absent in the five grass

species investigated. While this factor may have been lost in grasses, it is also

possible that SIG4 has evolved recently, following the monocot/dicot diversification.

Future sequencing of non-grass monocots, as well as other non-angiosperm

embryophytes may further clarify either possibility. P. patens has previously been

defined as containing a SIG1-, SIG2- and SIG5- like proteins, but no SIG3-, SIG4- or

SIG6- like proteins (Lysenko, 2006). My analysis confirmed the previous finding,

yet extended it by determining absence of the latter three factors also in the

lycophyte S. moellendorffii, and thus suggesting that the appearance of these factors

post-dates angiosperm development. Previous studies have identified a single sigma

factor in C. reinhardtii (Cre03.g194950: SIG1-like: Bohne et al. (2006)). In my

work, the presence of an additional SIG5-like factor was noted, suggesting earlier

appearance of this family member than previously believed. Conversely, V. carteri

contained only a SIG1 homolog.

Arabidopsis SIG1 bears greatest sequence identity to the essential E. coli factor, with

genomic sequences of SIG2-4 and SIG6 containing similar conserved intron sites to

that of SIG1, and SIG5 lacking both conserved introns and showing diverse amino

acid sequence (Fujiwara et al., 2000). The presence of a SIG1-like protein in not only

C. reinhardtii but also V. carteri provides new support for the mechanism of sigma

factor divergence from a SIG1-like ancestor (Shiina et al., 2009). SIG5-like factors

are particularly disparate to other family members both in sequence and function, and

it has been proposed that this factor may have originated from an additional (non-

primary) ancestral sigma factor (Lysenko, 2006). Alternatively, it is possible that this

sequence has simply undergone significant diversification. However, this study is the

first to suggest that this appearance may have occurred prior to the development of

the embryophytes. SIG1 potentially diversified into SIG1 and SIG2 prior to the

evolution of flowering plants, with further diversification to form SIG3 and SIG6,

most likely from SIG2 (four intron regions of SIG2, SIG3 and SIG6 are similar:


42

Fujiwara et al. (2000), Lysenko (2006)). The similarity between SIG4 and SIG3

conserved C-terminal regions has suggested that SIG4 derived from SIG3 (Lysenko,

2006), with the current analysis, which indicates an absence of SIG4-like proteins in

five grass species, suggesting divergence following the monocot/dicot split. This

proposed model for sigma factor evolution is summarised in Figure 5.

❶ ❷❸❹❻ ❺

❶ ❺

❶ ❷ ❺

❶ ❷ ❸ ❻ ❺

Development of embryophytes

Development of angiosperms

Development of dicotyledons

Figure 5: Model for sigma factor evolution.

SIG1 and SIG5 evolved independently, likely prior to the development of embryophytes: this study indicated presence of a SIG5-like protein in C. reinhardtii. SIG5 may have arisen from a separate ancestor, or may have simply diversified significantly following development from the primary sigma factor (Lysenko, 2006). SIG2 likely arose from diversification of SIG1 preceding angiosperm development: SIG3-, SIG4- and SIG6-like proteins were not found in the moss P. patens and the lycophyte S. moellendorffii. SIG4-like proteins were absent from five grass species, suggesting possible appearance following the monocot/dicot split. SIG4 may have diversified from SIG3: the C-terminal of SIG4 bears greatest similarity to this family member (Lysenko, 2006). Figure adapted from Shiina et al. (2009).

Ancestral primary sigma factor

Chapter 4: Do sigma factors in a single species exhibit temporal-, spatial, or response- specific expression profiles

44

CHAPTER 4

Do sigma factors in a single species exhibit

temporal-, spatial-, or response-specific expression profiles?


45


A comprehensive analysis of sigma factor conservation across plant species (Chapter

3) indicated that the presence of multiple factors in a single species is common, with

diversification likely happening early in land plant evolution, and multiple factors

maintained consistently across evolutionary time. Such presumed active maintenance

suggests that sigma factors are not entirely functionally redundant, but that the

presence of multiple factors in single species is of some functional advantage.

One of the proposed models for sigma function is that factors of a single family show

differential expression with plant development or tissue type, or in response to

external stimuli. Previous experiments have suggested differential activation of

arabidopsis sigma factor transcripts and proteins in different tissue types, particularly

between green and non-green tissues, and at different developmental stages

(Kanamuru et al., 2001, Privat et al., 2002). Additionally, all six arabidopsis sigma

factors are regulated to some degree by light, with plants demonstrating diminished

transcript abundance under dark adaptation, and recovery when re-illuminated

(Tsunoyama et al., 2004, Isono et al., 1997b, Tanaka et al., 1997). Generally these

patterns, such as the dominance of sigma factors in photosynthesising tissues and the

accumulation of sigma proteins during germination, are seen to be in direct

concordance with the general role of factors in chloroplast gene expression.

Interestingly, arabidopsis sigma factor accumulations have been shown to be

responsive not only to variations in light intensity and quality, but also heat, salt and

other osmotic stimuli (Tsunoyama et al., 2004).

The general view has been that transcription as a mechanism for gene regulation is

dominant primarily at early stages of plastid development, and under conditions of

plastid differentiation. Nonetheless, varied transcription from the diverse and

abundant plastid promoters under different internal and external conditions has been

noted (Swiatecka-Hagenbruch et al., 2007), with transcript plasticity putatively

regulated not only by NEP/PEP switches, but also by the specific promoter-

interactions of individual sigma factor family members within the PEP-holoenzyme

complex. The responsive activity of sigma factors is not unlikely: bacteria contain a

single essential factor required for general gene transcription, but also possess

multiple alternative factors, which regulate transcription of specific gene sets in

response to certain stimuli (Helmann and Chamberlin, 1988).


46

The differential accumulation of sigma factors within a species, in a temporal-,

spatial-, or response- specific manner has been demonstrated to some degree, and

represents both a conceivable model to explain the presence of multiple factors

within a single species, and for plastid transcript regulation. However,

comprehensive experimentation allowing comparative analysis of the differential

accumulations of all sigma members within a species has not been undertaken. For

example, the temporal abundances of arabidopsis SIG1-3 and SIG5 have been

somewhat described, but less in known about SIG4 and SIG6 (Schweer, 2010).

Similarly, investigation of sigma factor spatial presence has been limited and, with

the exception of SIG5, there has been little focus on the response of sigma factors to

changes in environmental conditions.


The primary aim of this chapter involved investigation of variations in arabidopsis

sigma factor expression. This utilized the availability of vast microarray datasets,

providing transcript accumulation data for a large proportion of the arabidopsis

genome measured under multiple and diverse experimental conditions. Visualisation

of integrated data in the context of specific physiological and experimental

conditions using Genevestigator software, and comparison of accumulation patterns

between multiple factors, was used to suggest a more holistic view of sigma factor

function. Sigma factor roles were further investigated using a ‘guilt-by-association’

method: putatively ascribing sigma factor function on the basis of the correlation of

sigma factor expression with the expression of other genes of known function.

4.3 Results

4.3.1 Sigma factor expression as a function of development, tissue type or

stimuli: interrogation of publicly available microarray data

In order to more comprehensively define the transcript accumulations of sigma factor

family members in different contexts, publicly available microarray data was

visualised using Genevestigator (https://www.genevestigator.com/; (Hruz et al.,

2008)), a large, manually curated compendium of expression data, with a focus on

querying multiple databases and grouping data by tissue types, developmental stages,

and perturbations. Visualisations can be seen in supplementary figures and tables

(section 9.6), Specific analysis of arabidopsis sigma factor genes SIG1-SIG6 was



47

undertaken using data collected from experiments utilising the Arabidopsis thaliana

ATH1: 22k array (Affymetrix: http://www.affymetrix.com).

4.3.1.1 Sigma factor transcript abundances vary as a function of development:

SIG5 transcripts show unique abundance patterns among sigma factors

Genevestigator software was used to visualise sigma factor transcript abundance

patterns at different plant developmental stages (supplementary figure 1). Generally,

all factors show lower accumulation at the germinated seed stage, relative to higher

accumulation throughout the major life stages of the plant, with reduced levels

associated with senescence. SIG1, SIG2, SIG3, SIG4 and SIG6 share similar

expression patterns: transcripts are at their highest levels when rosettes are fully

developed. Lower levels are associated with older plant tissue, although higher

transcript abundance is observed (for all but SIG6) as flowers begin to develop.

Factor-specific patterns are also present: for example SIG2 and SIG6 levels in

germinated seed are fairly high, relative to the maximum accumulation seen for these

factors, while accumulation of SIG3 and SIG4, and particularly SIG1, are higher in

tissues taken at later life stages. The expression patterns of SIG5 are notably

disparate from the other factors: transcripts are higher in young rosettes rather than

those that are fully developed, and show their maximum levels in young flowers as

well as higher levels in mature siliques relative to developing siliques.

4.3.1.2 Sigma transcript abundance is differentiated by tissue type: abundance

patterns differ between photosynthetic and reproductive tissues, and are unique in

leaf primordia

Genevestigator software was used to visualise sigma factor transcript abundances in

various tissue types (supplementary figure 2). Sigma factor expression in general is

greater in green than in non-green tissues, the former including inflorescence tissues

(sepal and pedicel). Sigma factor transcript accumulation patterns are markedly

different in inflorescence tissues. Relative to their respective levels in other green

tissues, accumulation of both SIG3 and SIG5 are high in the sepal and the cauline

leaf, with SIG3 at higher levels also in seed tissues, particularly the seed endosperm.

Accumulation patterns are perhaps most unique in leaf primordia: all sigma factors

are highly expressed relative to other green tissues (although SIG1 less so than the

others), with particularly high expression noted for SIG2, as well as SIG4, and to a

lesser degree SIG6.

http://www.affymetrix.com/


48

4.3.1.3 Sigma transcript accumulation is responsive to multiple, diverse stimuli:

support for SIG5 as ‘the stress-induced’ sigma factor

Genevestigator software was used to visualise sigma factor transcript abundances

under various treatments. A focus was placed on conditions where individual sigma

factor abundance was significantly (p<0.05) and notably (greater than two-fold)

perturbed from the respective standard or control (supplementary table 1). Sigma

factor transcript abundances were found to be responsive to a large number of

stimuli, including: biotic stresses (infection); hormone, chemical, elicitor and nutrient

application; changes to light intensity, quality and regime; and a variety of other

abiotic stresses not limited to temperature changes, and gas and water availability.

However, responses were not consistent: not all sigma factors responded to the same

stimuli and when they did, changes did not always occur to the same magnitude or in

the same direction.

Where biotic stimuli or various chemicals, nutrients, elicitors and hormones were

applied, sigma factor transcript accumulation was generally diminished compared

with untreated or mock-treated controls. However, both SIG2 and SIG5 abundances

increased slightly under cadmium chloride treatment (50 μM). Some response was

seen in SIG5 and SIG6 to drought treatment and pH changes, respectively, while

SIG2 alone seemed to respond to iron deficiency, showing a lower accumulation of

transcripts.

Sigma factors were generally responsive to light intensity/quality stimuli, in

particular SIG5, which shows strong accumulation under blue light, red light and UV

pulse treatment. Interestingly, SIG5 is also the only sigma factor to show strong

responsiveness to circadian-rhythm experiments, being highly up-regulated just after,

as opposed to just before dawn. Day length also affects transcript accumulations:

SIG1 and SIG4 accumulated under long day (16 hours) conditions as opposed to

short day (8 hours) while SIG2 and SIG5 displayed a converse response and SIG3

and SIG6 were not perturbed. Consistent with developmental studies, SIG1, SIG2,

SIG4 and SIG6 demonstrate strong accumulation during germination, with SIG6

accumulating rapidly (potentially during stratification), followed by SIG1

accumulation and then SIG2 and SIG4. After exposing the seed to 48 hours of light,

SIG1, SIG2, SIG6 and SIG6 accumulate, while SIG3 abundance does not alter


49

significantly and SIG5 accumulation is diminished in germinating tissue (relative to

stratifying and desiccated seed samples).

Of all six sigma factors, SIG5 accumulation was most responsive to a wide range of

different stimuli and showed the highest fold changes under multiple stimuli

(experimental transcript abundances changed from the control values by more than a

factor of 10). Furthermore, the response was often disparate from that of other

factors. Treatment with syringolin (a cyclic peptide secreted by P. syringae: among

other things its mechanisms involves counteracting stomatal immunity) decreased

sigma factors, especially SIG4, but elicited a strong increase in SIG5 accumulation.

Similarly, SIG1, SIG6 and particular SIG4 expression was decreased under nitrogen

starvation, while SIG5 expression slightly increased under both starvation and

application treatments. All factors had strongly decreased accumulation in Col-0

wild-type under hypoxic (0.1% oxygen) conditions, although SIG5 was separately

found to be strongly induced under anoxic conditions. Furthermore, SIG5 showed

some induction when moved from high to low CO2 conditions, and accumulation

increased under cold treatment, while all other factors increased under certain heat

treatments.

4.3.2 ‘Guilt-by-association’: further definition of sigma factor role by

identification of co-expressed genes of known function

Given that so many arabidopsis genes are annotated as having an unknown function,

co-expression analysis, with its robust statistical power born from use of expression

measurements from large numbers of diverse microarray datasets surveying the

arabidopsis genome, has emerged as a powerful tool for ‘guilt-by-association’ gene

function prediction (reviewed in Usadel et al. (2009)). Multiple publicly available co-

expression databases are available online, with differing methods of data

summarisation, normalisation, quality control and calculating co-expression. To

minimise individual bias, five data-bases were queried individually: ACT

(http://www.arabidopsis.leeds.ac.uk/act/; Manfield et al. (2006)), ATTED-II

(http://atted.jp/; Obayashi et al. (2009)), BAR (http://bar.utoronto.ca; Toufighi et al.

(2005)) CressExpress (http://cressexpress.org/; Srinivasasainagendra et al. (2008)),

GeneCAT (http://genecat.mpg.de/; Mutwil et al. (2008)), with each sigma factor used

as bait to determine the top 50 ranked correlates (refer to supplementary tables 2-6,

section 9.6). Correlates were then ranked on the basis of their presence in five, four

http://www.arabidopsis.leeds.ac.uk/act/


http://atted.jp/

http://atted.jp/

http://bar.utoronto.ca/

http://bar.utoronto.ca/





50

or three of the five examined data-bases (Tables 2-6). Results for SIG4 analysis will

be shown in Chapter 6.

4.3.2.1 Sigma factor transcript expression correlates with expression of

chloroplast-targeted transcripts involved in early chloroplast development and

biosynthetic processes, and stress response processes

Of the transcripts consistently defined as correlating with expression of SIG1-SIG3,

SIG5 and SIG6, the majority have produce a product with either predicted or

experimentally supported location in the chloroplast

(TAIR: http://www.arabidopsis.org/). Transcripts localised to the nucleus, plasma

membrane, peroxisome, mitochondrion, endomembrane, and cytosol were also

represented, but were in a clear minority. Multiple transcripts with function relating

to correct embryo development were identified, while at a molecular level, the

majority of transcripts encode proteins involved in chloroplast formation and

maturation. These included transcripts with protein function in: biosynthetic

pathways, including chlorophyll, heme, carotenoid, fatty acids and hormones;

transport and import, including carbohydrate, protons, proteins and various other

ions; gene expression processes, including transcription, translation and RNA

processing (rRNA processing, PPR proteins); and protein folding, assembly and

stability factors. Many transcripts were generally defined as having products

involved in chloroplast organisation, which included thylakoid organisation. Several

transcripts involved in the physical positioning of the chloroplast were also found,

and, additionally, in the development of the stomata (stomatal morphogenesis).

The role of many transcripts involved some sort of response to biotic or abiotic

factors. The most obvious of these was light, which involved development of

photosystems, light acclimation and rhythmicity (circadian transcripts), as well as

more specific responses to high light, low light, red light and blue light. In addition

to these many transcripts were involved in environmental responses, including to

bacteria and nematodes, wounding, UV and oxidative stress, hormone, salt, sucrose,

temperature and various ions.

Finally, SIG1 expression patterns correlated with expression of two GUN transcripts:

GUN5 (AT5G13630) and GUN4 (AT3G59400) and SIG2 expression correlated with

AGY1/SECA1 (AT4G01800): transcripts with products involved generally in

http://www.arabidopsis.org/

Table 2: Transcripts showing expression correlating with the expression of SIG1.

The top 50 correlates of SIG1 expression were obtained from five online co-expression databases; ACT, ATTED-II (ATTED), BAR Expression Angler (BAR), CressExpress, and GeneCAT). Transcripts were ranked for their common presence in 5, 4, or 3 of the top-50 lists (COMM). The coefficient of determination (r2) is shown for each transcript as determined by individual databases, with transcript ranking shown in brackets. Function and LOC (localisation: N= nucleus, T= thylakoid, TM= thylakoid membrane, C= chloroplast/plastid, PM= plasma membrane, PX= peroxisome, MI= Mitochondrion, G= Golgi apparatus, Y= cytosol) are as defined in TAIR (www.arabidopsis.org).

COMM AGI ACT ATTED BAR CRESS EXPRESS

GENECAT GENE/FUNCTION LOC

5 AT1G12800 0.93 (1) 0.85 (46) 0.90 (1) 0.75 (5) 0.93 (1) UK: RNA BINDING, BIOSYNTH PROCESSES, TRANSCRIPTION C AT4G02530 0.89 (7) 0.86 (40) 0.87 (7) 0.74 (9) 0.89 (11) UK: CAROTENOID/CHLOROPHYLL BIOSYNTH, BACTERIAL DEFENSE C (TM) AT1G22700 0.87 (27) 0.87 (5) 0.88 (3) 0.72 (23) 0.88 (24) UK: TPR PROTEIN INVOLVED IN PSI BIOGENEIS C(TM),

N AT3G18390 0.91 (3) 0.87 (1) 0.86 (20) 0.71 (35) 0.87 (44) EMB1865: RNA BINDING, ENDING DORMANCY, ABSCISIC ACID

RESPONSE C

AT2G34860 0.88 (14) 0.87 (25) 0.87 (10) 0.72 (26) 0.87 (37) EDA3: MEGAGAMETOGENESIS, UNFOLDED PROTEIN BINDING, HEAT SHOCK PROTEIN BINDING

C(TM)

AT2G41680 0.86 (48) 0.84 (28) 0.84 (40) 0.74 (13) 0.89 (8) NTRC: THIORDEOXIN REDUCTASE, REDOX PROTECTION, REGULAT CHLOROPHYLL BIOSYNTHESIS, STARCH BIOSYNTHESIS

C

4 AT1G07320 0.88 (16) 0.88 (4) 0.76 (4) 0.88 (25) EMB2784/RPL4, RIBOSOMAL PROTEIN C, N AT4G01800 0.88 (15) 0.86 (25) 0.74 (7) 0.89 (7) AGY1/SECA1: CHLOROPLAST BIOGENESIS/PHOTOSYNTEHSIS

REGULATION- ABSENCE TRIGGERS RETROGRADE SIGNAL C

AT4G17600 0.90 (4) 0.89 (2) 0.72 (33) 0.88 (21) LIL3:1: LIGHT HARVESTING (PSII), PLASTID ORGANISATION, CHLOROPHYLL BIOSYNTH, BLUE/RED LIGHT, TRANSLATION, RRNA PROCESSING, STOMATAL MORPHOGENESIS

C

AT4G29060 0.87 (14) 0.84 (48) 0.78 (2) 0.90 (4) EMB2726: RNA BINDING, TRANSLATION ELONGATION, CADMIUM ION RESPONSE, ENDING SEED DORMANCY, BIOSYNTH PROCESSES

C

AT1G43560 0.88 (18) 0.86 (12) 0.87 (9) 0.71 (41) TY2:THIOREDOXIN, GLYCEROL ETHER METABOLISM, REDOX REGULATION, LIGHT RESPONSE

C

AT1G62750 0.87 (34) 0.85 (33) 0.73 (19) 0.89 (6) SCOL CHLOROPLAST ORGANISATION, SEED/INFLORESCENCE DEVELOPMENT- ATP/GTP BINDING, NUCLEIC ACID BINDING- TRANSLATION ELONGATION

C

AT4G37510 0.82 (31) 0.83 (50) 0.74 (10) 0.90 (3) UK: RIBONUCLEASE III ACTIVITY, RNA BINDING C AT3G23700 0.88 (2) 0.84 (47) 0.70 (50) 0.87 (41) UK: RNA BINDING, THYLAKOID ORGANISATION, COLD RESPONSE, PSI

ELECTRON TRANSPORT, TRANSCRIPTION

3 AT1G11860 0.88 (10) 0.87 (11 0.73 (20) UK: AMINOMETHYLTRANSFERASE, CADMIUM ION RESPONSE, C, MI AT5G23120 0.89 (8) 0.87 (13) 0.88 (22) HCF136:PSII STABILITY/ASSEMBLY, CADMIUM/RED LIGHT RESPONSE,

CHLOROPHYLL BIOSYNTHESIS, PLASTID ORGINISATION C

AT5G14260 0.87 (22) 0.87 (16) 0.75 (6) UK: RUBISCO METHYLTRANSFERASE C AT5G03940 0.85 (22) 0.74 (8) 0.88 (16) 54CP: SIGNAL SEQUENCE RECOGNITION, PROTEINIMPORT C AT5G08650 0.88 (9) 0.85 (32) 0.89 (5) UK: GTP-BINDING PROTEIN, TRANSLATIONAL ELONGATION C





5 AT1G12800 0.93 (1) 0.85 (46) 0.90 (1) 0.75 (5) 0.93 (1) UK: RNA BINDING, BIOSYNTH PROCESSES, TRANSCRIPTION C AT4G02530 0.89 (7) 0.86 (40) 0.87 (7) 0.74 (9) 0.89 (11) UK: CAROTENOID/CHLOROPHYLL BIOSYNTH, BACTERIAL DEFENSE C (TM) AT1G22700 0.87 (27) 0.87 (5) 0.88 (3) 0.72 (23) 0.88 (24) UK: TPR PROTEIN INVOLVED IN PSI BIOGENEIS C(TM),

N AT3G18390 0.91 (3) 0.87 (1) 0.86 (20) 0.71 (35) 0.87 (44) EMB1865: RNA BINDING, ENDING DORMANCY, ABSCISIC ACID

RESPONSE C

AT2G34860 0.88 (14) 0.87 (25) 0.87 (10) 0.72 (26) 0.87 (37) EDA3: MEGAGAMETOGENESIS, UNFOLDED PROTEIN BINDING, HEAT SHOCK PROTEIN BINDING

C(TM)

AT2G41680 0.86 (48) 0.84 (28) 0.84 (40) 0.74 (13) 0.89 (8) NTRC: THIORDEOXIN REDUCTASE, REDOX PROTECTION, REGULAT CHLOROPHYLL BIOSYNTHESIS, STARCH BIOSYNTHESIS

C

4 AT1G07320 0.88 (16) 0.88 (4) 0.76 (4) 0.88 (25) EMB2784/RPL4, RIBOSOMAL PROTEIN C, N AT4G01800 0.88 (15) 0.86 (25) 0.74 (7) 0.89 (7) AGY1/SECA1: CHLOROPLAST BIOGENESIS/PHOTOSYNTEHSIS

REGULATION- ABSENCE TRIGGERS RETROGRADE SIGNAL C

AT4G17600 0.90 (4) 0.89 (2) 0.72 (33) 0.88 (21) LIL3:1: LIGHT HARVESTING (PSII), PLASTID ORGANISATION, CHLOROPHYLL BIOSYNTH, BLUE/RED LIGHT, TRANSLATION, RRNA PROCESSING, STOMATAL MORPHOGENESIS

C

AT4G29060 0.87 (14) 0.84 (48) 0.78 (2) 0.90 (4) EMB2726: RNA BINDING, TRANSLATION ELONGATION, CADMIUM ION RESPONSE, ENDING SEED DORMANCY, BIOSYNTH PROCESSES

C

AT1G43560 0.88 (18) 0.86 (12) 0.87 (9) 0.71 (41) TY2:THIOREDOXIN, GLYCEROL ETHER METABOLISM, REDOX REGULATION, LIGHT RESPONSE

C

AT1G62750 0.87 (34) 0.85 (33) 0.73 (19) 0.89 (6) SCOL CHLOROPLAST ORGANISATION, SEED/INFLORESCENCE DEVELOPMENT- ATP/GTP BINDING, NUCLEIC ACID BINDING- TRANSLATION ELONGATION

C

AT4G37510 0.82 (31) 0.83 (50) 0.74 (10) 0.90 (3) UK: RIBONUCLEASE III ACTIVITY, RNA BINDING C AT3G23700 0.88 (2) 0.84 (47) 0.70 (50) 0.87 (41) UK: RNA BINDING, THYLAKOID ORGANISATION, COLD RESPONSE, PSI


3 AT1G11860 0.88 (10) 0.87 (11 0.73 (20) UK: AMINOMETHYLTRANSFERASE, CADMIUM ION RESPONSE, C, MI AT5G23120 0.89 (8) 0.87 (13) 0.88 (22) HCF136:PSII STABILITY/ASSEMBLY, CADMIUM/RED LIGHT RESPONSE,

CHLOROPHYLL BIOSYNTHESIS, PLASTID ORGINISATION C

AT5G14260 0.87 (22) 0.87 (16) 0.75 (6) UK: RUBISCO METHYLTRANSFERASE C AT5G03940 0.85 (22) 0.74 (8) 0.88 (16) 54CP: SIGNAL SEQUENCE RECOGNITION, PROTEINIMPORT C AT5G08650 0.88 (9) 0.85 (32) 0.89 (5) UK: GTP-BINDING PROTEIN, TRANSLATIONAL ELONGATION C

Table 3: Transcripts showing expression correlating with the expression of SIG2, continued.




3 AT3G01480 0.87 (9) 0.74 (11) 0.87 (28) CYP38: BACTERIAL RESPONSE, PROTEIN FOLDING, PSII ASSEMBLY/STABILISATION

C

AT1G03475 0.88 (12) 0.82 (41) 0.87 (8) HEMF1/LIN2: REDOX PROCESSES, CHLOROPHYLL/HEME SYNTHESIS C AT1G17220 0.86 (13) 0.72 (32) 0.88 (17) FUG1: TRANSLATION INITIATION, SUPPRESSOR OF VAR2-6, THYLAKOID

ORGANISATION C

AT1G73110 0.86 (39) 0.85 (10) 0.72 (24) UK: ATP CATABOLIC PROCESS C AT1G09340 0.86 (42) 0.86 (21) 0.74 (12) CRB: RNA BINDING, CHLOROPLAST ORGANISATION, CIRCADIUM

RHYTHM, DEFENSE TO BACTERIA, RRNA PROCESSING, COLD RESPONSE C

AT1G67700 0.87 (7) 0.84 (42) 0.87 (29) UK C AT3G54050 0.87 (37) 0.86 (23) 0.73 (21) HCEF1: DEPHOSPHORYLATION, FRUCTOSE/SUCROSE METABOLIC

PROCESSES, COLD RESPONSE, PSI ELECTRON TRANSPORT, CHLOROPLAST RELOCATION

C

AT4G09650 0.87 (32) 0.87 (17) 0.72 (34) ATPD/PDE332: DEFENSE TO BACTERIA, ION TRANSMEMBRANE TRANSPORT, PSI AND PSII ELECTRON TRANPORT, PROTON TRANSPORT, COLD RESPONSE,

C

AT5G06290 0.87 (33) 0.85 (34) 0.73 (18) 2-CYS: DEFENSE TO BACTERIUM, REDOX RESPONSE, COLD RESPONSE, C AT1G80030 0.87 (21) 0.80 (34) 0.87 (34) UK: PROTEIN FOLDING, RESPONSE TO HEAT C AT3G07670 0.84 (15) 0.71 (39) 0.87 (39) UK: RUBISCO METHYLTRANSFERASE FAMILY, THYLAKOID

ORGANISATION C

AT2G47940 0.87 (35) 0.87 (12) 0.70 (49) DEGP2/EMB3117: PROTEASE, CHLOROPLAST ORGANISATION, PSII REPAIR

C, MI

AT4G28080 0.86 (41) 0.84 (41) 0.73 (15) UK: TPR PROTEIN, ABSCISIC ACID RESPONSE N





4 AT1G76730 0.79 (27) 0.77 (2) 0.69 (1) 0.79 (3) COG0212: FOLIC ACID-CONTAINING COMPOUND BIOSYNTEHSIS, REQUIRED FOR EMBRYO VIABILITY

C

AT5G58140 0.80 (11) 0.73 (12) 0.68 (8) 0.75 (16) NPL1: MEMBRANE BOUND SER/THR KINASE, BLUE –LIGHT SIGNALLING, C RELOCATION, STOMATAL MOVEMENT

C, EM, PM

AT1G67840 0.78 (37) 0.76 (1) 0.61 (39) 0.81 (1) CSK: PHOTOSYTESM STOICHIOMETRY ADJUSTMENT, TRANSCRIPTION CONTROL

C

AT5G45170 0.79 (18) 0.62 (49) 0.69 (2) 0.73 (35) UK: HYDROLASE FAMILY C AT3G55630 0.78 (31) 0.7 (7) 0.64 (33) 0.61 (37) DFD: ONE-CARBON METABOLISM Y

3 AT1G71480 0.78 (29) 0.70 (5) 0.77 (7) UK: PROTEIN IMPORT INTO NUCLEUS, CHLOROPHYLL CATABOLISM C,N AT2G30170 0.74 (13) 0.62 (27) 0.80 (2) PBCP: DEPHOSPHORYLATION OF PSII PROTEINS, LIGHT ACCLIMATION C AT2G23390 0.73 (8) 0.65 (12) 0.74 (23) UK: BLUE LIGHT RESPONSE, PROTEIN PHOSPHORYLATION, PROTON

REGULATION C

AT2G30390 0.82 (7) 0.61 (45) 0.77 (8) FC2: HEME BIOSYNTHESIS, MAY OPPERATE IN PHOTOSYNTHETIC CYTOCHROMES

C

AT5G35170 0.7 (46) 0.68 (4) 0.77 (10) UK: NUCLEOTIDE/SIDE METABOLIC PROCESSES, ANAEROBIC RESPIRATION

C

AT1G12250 0.7 (45) 0.67 (6) 0.74 (28) UK: PENTATRICOPEPTIDE REPEAT C AT4G33500 0.82 (6) 0.61 (41) 0.74 (32) UK: SER/THR PHOSPHATASE C AT4G33470 0.79 (20) 0.64 (15) 0.72 (47) HDA14: HISTONE DEACELYATION C AT3G55040 0.79 (19) 0.63 (40) 0.72 (50) GSTL2: PROTEIN GLUTATHIONYLATION C





5 AT3G56290 0.84 (1) 0.76 (3) 0.81 (1) 0.61 (1) 0.82 (1) UK: CHLOROPLAST ORGANISATION MI(?) AT5G50100 0.80 (4) 0.72 (2) 0.75 (6) 0.35 (33) 0.76 (3) UK: PUTATIVE THIOL-DISULPHIDE OXIDOREDUCTASE MI AT2G24540 0.73 (13) 0.74 (1) 0.65 (28) 0.52 (2) 0.74 (5) AFR: REDLIGHT/ SUCROSE RESPONSE, PROTEIN BINDING Y AT1G78510 0.82 (2) 0.66 (23) 0.79 (2) 0.40 (16) 0.72 (10) SPS1: SOLANESYL DIPHOSPHATE SYNTHASE- UBIQUINONE PROCESSES C, EM AT4G37760 0.68 (36) 0.67 (5) 0.75 (5) 0.50 (3) 0.71 (11) SQE3: JASMONIC ACID, WOUNDING RESPONSE- STEROL BIOSYNTH EM AT1G06430 0.69 (29) 0.69 (11) 0.71 (10) 0.41 (12) 0.74 (6) FTSH8: LHC2 (PSII)-CATABOLIC PROCESSES, ATP CATABOLIC, ZINC ION

BINDING C

AT1G17050 0.74 (12) 0.62 (30) 0.71 (9) 0.44 (6) 0.69 (17) SPS2:UBIQUINONE PROCESSES C AT5G67030 0.69 (27) 0.69 (14) 0.65 (27) 0.42 (10) 0.70 (14) ABA1: BIOSYNTH OF ABSCISIC ACID (ABIOTIC STRESS RESPONSE) C AT1G64500 0.68 (34) 0.68 (17) 0.69 (16) 0.38 (21) 0.72 (9) UK: N-TERMINAL MYRISTOYLATION, REDOX PROCESSES- C

RELOCATION, ACTIN FILAMENT BUNDLE ASSEMBLY N

AT2G46340 0.71 (21) 0.6 (19) 0.69 (19) 0.33 (41) 0.69 (16) SPA1: LIGHT-RESPONSIVE PHOTOMORPHOGENESIS SUPRESSOR, RED LIGHT, REGULATION OF PHOTOPERIODISM, FLOWERING

N

AT2G46830 0.80 (3) 0.64 (28) 0.72 (8) 0.35 (31) 0.63 (49) CCA1: CIRCADIAN RHYTHM: RESPONDS TO: ABSCISIC ACID, AUSIN, CADMIUM, COLD, ETHYLENE, GIBBERELLIN, JASMONIC ACID, ORGANIC NITROGEN, SALICYCLIC ACID, SALT STRESS

N

AT1G66330 0.68 (40) 0.62 (35) 0.70 (12) 0.40 (17) 0.68 (20) UK, OXIDATIVE STRESS RESPONSE, LEAF SENESCENCE, MERISTEM VEGETATIVE TO REPRODUCTIVE TRANSITION

C

AT1G02820 0.65 (48) 0.6 (29) 0.61 (48) 0.41 (11) 0.65 (38) ATLEA3: EMBRYO DEVELOPMENT, STRESS RESPONSE C 4 AT1G53090 0.76 (9) 0.75 (4) 0.39 (19) 0.68 (18) SPA4: PROTEIN PHOSPHORYLATION, SUPRESS PHOTOMORPHOGENESIS,

REPRODUCTIVE STRUCTURES N

AT3G24190 0.70 (25) 0.69 (14) 0.45 (4) 0.73 (8) UK: PROTEIN PHOSPHORYLATION C AT5G19850 0.71 (22) 0.69 (17) 0.39 (18) 0.74 (7) UK: ALPHA/BETA HYDROLASE Y AT3G21890 0.74 (11) 0.62 (15) 0.40 (14) 0.66 (31) UK: B-BOX ZINC FINGER, SEQUENCE SPECIFIC DNA BINDING TF

ACTIVITY, UV-B RESPONSE N

AT5G35970 0.69 (18) 0.61 (45) 0.44 (7) 0.74 (4) UK: ATP/DNA BINDING HYDROLASE C AT1G76570 0.77 (5) 0.64 (30) 0.33 (39) 0.68 (19) UK: CHLOROPHYLL A-B BINDING, RESPONSE TO BLUE LIGHT,

RESPONSE TO FAR RED LIGHT C

AT5G64840 0.70 (24) 0.69 (16) 0.68 (22) 0.35 (34) ABCF5: MEMBER OF GCN FAMILY- RESPONSE TO NEMATODE, TRANSPORT

PM

Table 5: Transcripts showing expression correlating with the expression of SIG5, continued.




4 AT5G53970 0.59 (42) 0.66 (26) 0.42 (8) 0.66 (27) TAT7: TYROSINE AMINOTRANSFERASE- VITAMIN E BIOYNTH, AGING INDUCED, CORONATINE INDUCED

Y

AT4G27030 0.65 (49) 0.71 (11) 0.32 (45) 0.70 (12) FADA: SUBSTRATE SPECIFIC PALMITATE DESATURATE, REDOX, RESPONSE TO KARRIKIN

C

AT5G58770 0.68 (39) 0.64 (31) 0.37 (24) 0.68 (23) UK: DOLICHOL/UBIQUINONE BIOSYNTH C AT2G15020 0.68 (38) 0.61 (40) 0.42 (9) 0.66 (32) UK - AT1G79270 0.66 (6) 0.61 (47) 0.36 (30) 0.64 (45) ECT8: UK FUNCTIOON N AT4G31870 0.66 (42) 0.58 (45) 0.67 (23) 0.37 (26) GPX7: GLUTATHION PEROXIDASE, RESPONSE TO KARRIKIN, C

3 AT3G61220 0.70 (26) 0.68 (21) 0.76 (2) SDR1: ALDEHYDE REDUCTASE, REDOX RESPONSE, DEFENSE RESPONSE, RESPONSE TO KARRIKIN,

Y

AT2G31380 0.64 (27) 0.76 (3) 0.35 (32) STH: B-BOX ZINC FINGER, REGULATION OF TRANSCRIPTION, LIGHT SIGNALLING (DE-ETIOLATION), SALT RESPONSE

N

AT5G15850 0.72 (19) 0.62 (36) 0.70 (13) COL1: HOMOLOGOUS TO FLOWERING-TIME GENE CONSTANS, CIRCADIAN RHYTHM, FLOWER DEVELOPMENT

N

AT5G64170 0.76 (8) 0.58 (47) 0.69 (15) UK: DENTIN SIALOPHOSPHOPROTEIN -RELATED N AT3G47420 0.54 (37) 0.37 (22) 0.70 (13) G3PP1: CARBOHYDRATE TRANSPORT- PI RESPONSE PM AT1G19700 0.59 (13) 0.34 (36) 0.67 (25) BEL10: TRANSCRIPTION REGULATOR, PLP (BLUE LIGHT RECEPTOR

PROTEIN) BINDING DIMINISHED UNDER BLUE LIGHT, N N

AT5G62430 0.70 (23) 0.41 (13) 0.64 (43) CDF1: REPRESSES COSTANS (FLOWERING-TIME GENE)- VEGETATIVE TO REPRODUCTIVE GROWTH

N

AT5G42760 0.71 (20) 0.68 (20) 0.33 (42) UK: METHYLTRANSFERASE N AT1G53670 0.64 (29) 0.33 (43) 0.68 (21) MSRB1: N-TERMINAL PROTEIN MYRISTOYLATION, OXIDATIVE STRESS

RESPONSE C

AT1G07010 0.68 (35) 0.62 (41) 0.65 (35) SLP1: CALCINEURIN-LIKE METALLO-PHOSPHOESTERASE, C, PX AT3G21390 0.65 (50) 0.61 (44) 0.37 (25) UK, THIAMIN DIPHOSPHATE CARRIERM MI AT5G58870 0.63 (41) 0.36 (28) 0.63 (50) FTSH9: PSII, PROTEOLYSIS, ATP /PROTEIN CATABOLIC PROCESSES C





4 AT4G29060 0.88 (13) 0.86 (13) 0.81 (2) 0.91 (1) EMB2726: RNA BINDING, TRANSLATION ELONGATION, CADMIUM ION RESPONSE, ENDING SEED DORMANCY, BIOSYNTH PROCESSES

C

3 AT2G03420 0.87 (20) 0.86 (4) 0.82 (1) UK: POSITIVE REGULATION OF TRANSCRIPTION, STOMATAL MORPHOGENESIS

C

AT3G23700 0.90 (2) 0.84 (16) 0.80 (8) UK: RNA BINDING, THYLAKOID ORGANISATION, COLD RESPONSE, PSI ELECTRON TRANSPORT, TRANSCRIPTION

C

AT4G19100 0.81 (5) 0.76 (29) 0.90 (2) PAM68: MRNA MODIFICATION, PHOTOSYNTHESIS, PSII ASSEMBLY C, N AT5G05740 0.87 (16) 0.80 (6) 0.88 (17) EGY2: EMBRYO DEVELOPMENT, PROTEOLYSIS, THYLAKOID

ORGANISATION, VEGETATIVE TO REPRODUCTIVE TRANSITION, STOMATAL MORPHOGENESIS

C (TM)

AT1G17220 0.91 (1) 0.79 (13) 0.87 (28) FUG1: TRANSLATION INITIATION, SUPPRESSOR OF VAR2-6, THYLAKOID ORGANISATION

C

AT3G07670 0.87 (17) 0.82 (31) 0.89 (12) UK: RUBISCO METHYLTRANSFERASE FAMILY, THYLAKOID ORGANISATION

C

AT1G14030 0.82 (43) 0.79 (16) 0.90 (3) LSMT-L:LYSINE METHYLTRANSFERASE, EMBRYO DEVELOPMENT, CHLOROPLAST RELOCATION, BIOSYNTH PATHWAYS

C

AT4G17600 0.86 (28) 0.79 (11) 0.88 (23) LIL3:1: LIGHT HARVESTING (PSII), PLASTID ORGANISATION, CHLOROPHYLL BIOSYNTH, BLUE/RED LIGHT, TRANSLATION, RRNA PROCESSING, STOMATAL MORPHOGENESIS

C (TM)

AT3G47650 0.85 (39) 0.80 (7) 0.88 (18) UK: UNFOLDED PROTEIN/HEAT SHOCK, PSI, PSII, PLASTID ORGANISATION

C

AT4G31850/ AT4G31560

0.89 (3) 0.76 (40) 0.87 (49) PGR3: PPR PROTEIN, TYLAKOID ORGANISATION, BIOSYNTH HCF153: CYTB6F BIOGENESIS

C C (TM)

AT3G55330 0.85 (42) 0.85 (17) 0.76 (35) PPL1: PSBP-LIKE, PSII ASSEMBLY, RRNA PROCESSING, STOMATAL MORPHOGENESIS

C

AT2G37660 0.88 (47) 0.79 (9) 0.87 (50) UK: DEFENSE TO BACTERIA, REDOX, COLD, CHLOROPHYLL BIOSYNTHESIS

C


58

chloroplast biosynthesis, but also implicated in retrograde signalling between the

plastid and the nucleus.

4.3.2.2 Divergent correlations in SIG5

SIG5 correlates show similarity to those of other sigma factors in their role in

response to various kinds of biotic and abiotic stresses. However, unlike other sigma

factor transcript correlation profiles, many SIG5 correlates have products that are

non-plastid localised: a significant proportion being instead targeted to the nucleus.

Furthermore, SIG5 is putatively co-expressed with multiple genes involved in

vegetative to reproductive growth transition, flower development, and two genes

involved in the activation and repression of flowering time. Several SIG5 correlates,

including the gene COL1, homologous to the flowering-time gene CONSTANS, are

also involved in the regulation of circadian rhythm. In comparison, reproduction- and

clock-related transcripts are absent or under-represented in other sigma factor

transcript correlate lists.

4.3.2.3 Eleven transcripts show strong positive correlation with expression of

multiple sigma factors

Multiple transcripts were found among the top correlates of more than one sigma

factor (Table 7). These genes represent a wide variety of functions, such as nucleic

acid binding and processing including translation and transcription involvement,

metabolic processes, general plastid biogenesis and biosynthesis processes and

response to various stimuli. These commonalities may reflect the overlapping roles

of some sigma factors, or may indicate components involved in more general

elements of sigma factor function.



In the absence of known function, understanding the expression pattern of a gene

under particular conditions can implicitly suggest a role. Although the general role of

sigma factors is well defined, the specificities that differentiate family members from

each other are not well understood. Analysis of microarray data allows side-by-side

comparison of transcript accumulation patterns under literally hundreds of

experimental conditions: even following quality curation, Genevestigator ATH1:22k


59

Table 7: Transcripts correlating with expression patterns of multiple sigma factors.

Transcripts found in the top 50 correlate tables of multiple sigma factors. Transcripts were found in in two or more sigma correlate tables as defined by 5, 4 or 3 correlation databases. Presence of these transcripts in the top-50 list of either one (1) or two (2) of the remaining sigma factors is also shown

AGI Correlate Gene/Function

AT1G07010 SIG1, SIG5,

(SIG31)

SLP1: CALCINEURIN-LIKE METALLO-PHOSPHOESTERASE


(SIG12, SIG31)

FUG1: TRANSLATION INITIATION, SUPPRESSOR OF VAR2-6, THYLAKOID

ORGANISATION

AT3G07670 SIG2, SIG6, UK: RUBISCO METHYLTRANSFERASE FAMILY, THYLAKOID

ORGANISATION

AT3G23700 SIG2, SIG4 (SIG62) UK: RNA BINDING, THYLAKOID ORGANISATION, COLD RESPONSE, PSI


AT3G55630 SIG3, SIG4, DFD: FOLYLPOLYGLUTAMATE SYNTHASES INVOLVED IN ONE-CARBON

METABOLISM

AT4G17600 SIG2, SIG6 LIL3:1: LIGHT HARVESTING (PSII), PLASTID ORGANISATION,

CHLOROPHYLL BIOSYNTH, BLUE/RED LIGHT, TRANSLATION, RRNA

PROCESSING, STOMATAL MORPHOGENESIS

AT4G29060 SIG2, SIG6 EMB2726: RNA BINDING, TRANSLATION ELONGATION, CADMIUM ION

RESPONSE, ENDING SEED DORMANCY, BIOSYNTH PROCESSES


(SIG61)

HDA14: HISTONE DEACELYATION


(SIG42)

HCF136:PSII STABILITY/ASSEMBLY, CADMIUM/RED LIGHT RESPONSE,

CHLOROPHYLL BIOSYNTHESIS, PLASTID ORGINISATION

AT5G35970 SIG1, SIG5 UK: ATP/DNA BINDING HYDROLASE

AT5G64840 SIG1, SIG5 ABCF5: MEMBER OF GCN FAMILY- RESPONSE TO NEMATODE, TRANSPORT


60

data represents over 7000 samples. The diversity of such datasets increase the

likelihood of identifying conditions specific to the activity of a chosen gene, with

entire datasets also able to be used together to predict with great statistical robustness

a broader understanding of gene regulation and function. However, as data are

collected from wide sources, even relative ‘control’ conditions are different between

datasets, making it difficult to compare between experiments. In addition, when

comparing multiple transcripts within experiments, comparisons can be made

between patterns of accumulation, but not absolute abundances, as signal intensity is

a function not only of transcript abundance, but also of the efficiency of transcript

hybridisation to the target probe. Interestingly, previous evaluation of sigma factor

expression levels by GUS-promoter analysis and by Northern blotting suggests that

the signal intensities may be somewhat proportional to accumulation: for example

SIG1 and SIG2 have previously been described as highly expressed (compared with

SIG3) (Kanamaru et al., 1999), and SIG5 has been defined as showing intermediate

expression levels to SIG4 (low) and SIG6 (high) at 12 days growth (Fujiwara et al.,

2000). Nonetheless, analysis of microarray data can perhaps best be relied on for a

more holistic view of relative abundances. Moreover, sigma factor expression has

previously been shown to be regulated not only at transcriptional, but also post-

transcriptional and post-translational levels (Brautigam et al., 2011, Gowik et al.,

2011, Privat et al., 2002, Baginsky et al., 1997, Schweer et al., 2010). For example, a

sig2 antisense mutant, while deficient in the SIG2 protein at early stages of growth,

was at later stages able to adjust protein levels to those of the wild-type, despite an

observable reduction in mRNA levels (Privat et al., 2002). Phosphorylation,

occurring at multiple residues, has further been identified as important for sigma

factor activation (Schweer et al., 2010, Baginsky et al., 1997). As such, it should be

remembered that transcription patterns are not always directly indicative of sigma

factor activity.


This chapter took advantage of the large amount of publicly available microarray

data to investigate the potential differentiation in plastid sigma factor regulation, and

thus indicate putative differentiation in sigma factor function. The tissue-dependent

expression of sigma factor transcripts SIG1, SIG2 and SIG3 (Privat et al., 2002),

SIG6 (Ishizaki et al., 2005), and SIG5 (Tsunoyama et al., 2004), have been


61

investigated only in certain tissues, with little information available for SIG4 tissue-

or developmental-specific expression, and, with the exception of studies

investigating blue-light response in SIG5, very little is known about the response of

factors to perturbation. This study is the first to combine publicly available data for

hundreds of different experiments, in order to create a holistic view of sigma factor

family expression.

Differentiation between patterns of expression were seen: SIG3 and SIG5 showed a

tendency to accumulate in ‘non-traditional’ (relative to other factors) tissues,

consistent with reports for SIG3 describing presence in seeds and other non–

photosynthetic tissues (Privat et al., 2002, Isono et al., 1997b, Tanaka et al., 1997) .

Additionally, SIG5 was found to show a different pattern of transcript accumulation

across developmental stages. SIG5 has previously been described as a responsive

factor due to its up regulation under changes in light regime (Schweer, 2010). Here,

although it was shown that all factors bear an element of responsiveness, SIG5 was

shown to be particularly responsive among factors, with the definition of this

response now extended to include a large range of non-light stimuli.

Interestingly, SIG5 has been suggested to accumulate as two alternatively-initiated

transcript pools, one believed to have a plastid- and one a mitochondria-targeted

product, with the latter product accumulating primarily in the flowers (Fujiwara et

al., 2000). While flower-specific accumulation was not seen here, SIG5 was found to

accumulate at the young flower stage of development, and to be particularly

expressed in cauline leaves and sepals. Furthermore, guilt-by-association analysis

shows correlation of SIG5 with multiple flowering-time-related transcripts, and blue-

and redlight stimuli, found here, and previously (Tsunoyama et al., 2004) to

stimulate SIG5 accumulation, is also associated with stimulation of flowering

(Eskins, 1992). Ultimately, however no mitochondrial role has been defined for

sigma factors, and mitochondria do not contain a bacteria-like polymerase.

Furthermore, changes in light quality have direct implications for the plastid

photosystems, with SIG5 already implicated in light-responsive transcription of psbD

(Nagashima et al., 2004b, Hoffer and Christopher, 1997).

Ultimately, the general expression patterns of (particularly non-SIG5) sigma factors

in different contexts were similar: factors were rarely absent or present in a manner


62

differentiating from those of other family members, and transcript presence

dominated in green tissues, with perceived accumulation following germination, high

abundance of factors in formed rosettes, and particularly low presence in senescing

plants, consistent with previous reports (Isono et al., 1997b, Privat et al., 2002,

Tanaka et al., 1997, Kanamaru et al., 1999). The protein SIG2 has been shown to

appear soon after imbibition, but only rapidly accumulate following the freeing of the

leaves (PRIVAT), implying, not surprisingly, a correlation between sigma

accumulation and the requirement for chloroplast (particularly photosynthetic) gene

transcription. Similarly, as the onset of chloroplast degradation, believed to result

from the cessation of chloroplast nucleic acid and protein synthesis as well as altered

protein turnover, is the first visible sign of senescence (Zapata et al., 2005,

Zimmermann and Zentgraf, 2005, Thomas and Stoddart, 1980), it is not surprising

that sigma factor levels are particularly low in senescing plants, even relative to

levels at reproductive maturity. In concordance with this, ‘guilt-by-association’

analysis, a method used for the first time here in defining sigma specificity, indicated

that the majority of sigma factor transcript correlates have products involved in

chloroplast biosynthesis and maintenance process, including many chloroplast gene

expression processes. As such, while sigma factor protein accumulation and activity

analyses are required to investigate potential differentiation of sigma factors at post-

transcriptional levels, transcript accumulations analysed here suggest sigma factor

expression patterns are similar to each other, likely correlating with cellular

requirements for expression of chloroplast genes.

Chapter 5: Do sigma factors recognise distinct subsets of plastid gene promoters (or are they functionally redundant)?

63

CHAPTER 5

Do sigma factors recognise distinct subsets of plastid gene

promoters (or are they functionally redundant)?


64


Higher plants typically contain multiple sigma factors in a single species (Chapter 3),

as a result of diversification from a single ancestral factor. These factors show some

diversity in their contextual transcript expressions (Chapter 4), yet generally

accumulate in a way likely to be reflective of the organism’s requirement for plastid

gene expression. As such, the evolutionary maintenance of multiple factors may

represent an alternative or additional model for sigma factor function: that individual

sigma factors recognise different subsets of promoters, potentially transcribing

exclusive transcript sets.

Analysis of the specific roles of individual factors in transcription has primarily been

undertaken using transcript analysis of sigma factor knockout mutants in the model

plant arabidopsis. Of the six factors, only two mutants, sig2 and sig6 have a visible

phenotype indicative of reduced health: both mutants have a chlorophyll deficient,

growth retarded phenotype in the early stages of development (Privat et al., 2002,

Loschelder et al., 2006). Interestingly, sig6 mutants ‘outgrow’ this phenotype, and

are physically identical to the wild-type at reproductive maturity, while sig2 plants

remain pale (although more chlorophyll is present than in young tissue), and

dwarfed. These two mutants have been shown to be affected in the transcription of

multiple photosynthetic transcripts (Table 8), with differences most prominent during

the early stages of development.

The remaining four sigma factors are believed to be involved in transcription of only

a smaller number of genes and are described commonly as ‘alternative’, ‘general’ or

‘rather functionally redundant’, with single knock-out mutants bearing no visible

phenotype (Table 8). Nonetheless, heterogeneity of function has been defined for all

factors (Tsunoyama et al., 2004), and there is evidence that even ‘alternative’ factors

have an important role, at least under certain conditions. SIG5, for example, shows

specific activity on the promoter of psbD under blue-light stimulus (Tsunoyama et

al., 2004, Hoffer and Christopher, 1997), while SIG3 has been shown to exhibit up-

regulation in SIG2 mutants, and allow partial recovery of the sig2 phenotype (Privat

et al., 2002), suggesting a role beyond the previously described activity on just two

plastid transcripts (petN, trnV: Table 8). The latter case also suggests a level of

redundancy in sigma factor function. Where genes have arisen from duplication of a

single ancestor, it is not unusual for substantial functional redundancy to be

Table 8: Arabidopsis thaliana sigma factors.

A brief summary of the attributes and functions of sigma factors in the model plant arabidopsis. References: 1(Privat et al., 2002), 2 (Yao et al., 2003), 3(Fujiwara et al.,

2000), 4(Shirano et al., 2000), 5 (Kanamaru et al., 1999), 6(Nagashima et al., 2004a) 7(Zghidi et al., 2007), 8(Favory et al., 2005), 9(Ishizaki et al., 2005), 10 (Tsunoyama et al.,

2004), 11 (Nagashima et al., 2004b), 12 (Shimizu et al., 2010), 13 (Loschelder et al., 2006). Note: protein localisation for SIG4 has not been confirmed by GFP or MS, however,

the factor has a clear role in the plastid (Fujiwara et al., 2000, Favroy et al., 2005).

SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 Protein Localisation

Chloroplast stroma1 Chloroplast stroma1 Chloroplast membrane (partially attached) 1

Chloroplast Chloroplast stroma, mitochondria2

Chloroplast3

Knock-out visual phenotype

none

permanent chlorophyll deficiency, dwarfed/ retarded growth 4, 5

none

none

none

chlorophyll deficiency and dwarfed/retarded growth in early stages 9

decreased transcripts

psaJ, trnE-UUC,trnD-GUC, trnM-CAU, trnV-UAC 6

psbN ndhF,ycf?4, ndhG? 8 rbcL, psbA, psbB, psbC, psbD, psbH, psbN, psbT, rrn16,rrn23, rrn5, rrn4, trnE-UUC, trnQ -UUG 9

increased transcripts

‘multiple NEP products’ psaC, petA, atpF, rpoA, rpoB, rpL2, ndhA, ndhB, ycf3, psbI, psbM, psbN, atpA, atpI, rpoC2, rps7, rps12, rps14, ndhG, ndhH, nhdJ, ycf2, ycf4, ycf10 (cemA), ycf156

psaJ?, rpl36?, rpl32? 8 ‘multiple NEP products’ clpP, rps15 ,ndhB, ycf1, rpoB, rpoC1, rpoC2 9

Over-expressor increased transcripts

psaA, psbB, psbEFLJ gene cassette rbcL 10

psbA, trnEYD 10

ndhF 8

psbD psbA 10,11

General role PSI/PSII stoichiometry 12

Activity altered by phosphorylation under redox changes

Multiple photosynthesis-related transcripts Major factor in early development

Functionally redundant? Ability to partially rescue loss of SIG2 function. Membrane localisation required for activity 1

NDH regulation by specific activity on ndhF 8

Blue-light responsive regulation of psbD 10,11

Putative reproductive role 2

Phylogenetically distinct from other family members (no conserved intron sites)2, 3

Multiple photosynthesis-related transcripts 9

Major factor in early development Second/persistent role during vegetative development 13


66

retained for long periods of time (Dean et al., 2008). Sigma factor redundancy has

been suggested by up-regulation of SIG1, SIG3, SIG5 and SIG6 in a sig2 mutant and

by lower accumulation of certain transcripts in multiple mutants, such as the loss of

trnE-UUC in both sig2 and sig6 (Nagashima et al., 2004a, Ishizaki et al., 2005).

Furthermore, in vitro analyses have demonstrated shared binding capacity on

promoter regions, such as the activity of SIG1, SIG2 and SIG3 on the psbA and rbcL

promoters, with factors shown to bind with different efficiencies and compete for

activity (Privat et al., 2002).

It is clear that the current understanding of sigma factors is far from complete. In

particular, the majority of previous studies have focused primarily on single, or an

incomplete set of sigma factors, and generally investigated sigma factor influence on

small sets of plastid genes. While fairly comprehensive transcript analyses have been

undertaken for sig2 (Nagashima et al., 2004a), sig3 (Zghidi et al., 2007), sig4

(Favory et al., 2005) and sig6 (Ishizaki et al., 2005) there is a dearth of information

for the remaining factor mutants. More importantly, these analyses have been

performed independently, under different experimental conditions, making

comparison between factors impossible. In the case of sigma factors, where previous

analysis has suggested a complex and likely overlapping function of family

members, an ability to directly compare mutant transcript profiles could prove

invaluable in elucidating function.


The primary aim of the work presented here was to increase the understanding of

sigma factor activity on plastid gene promoters. The primary strategy utilised the

availability of single knockout mutants for each of the six sigma factors in the model

plant arabidopsis, and involved a comprehensive analysis of plastid mRNA transcript

accumulations by qPCR, measured from mutant populations grown in parallel with

each other and with the wild-type.


67

5.3 Results

5.3.1 Definition of physical phenotypes for publicly available single sigma factor

mutant lines

Sigma factor mutants were obtained and screened for homozygosity from publicly

available Gabi-Kat (Rosso et al., 2003) and Salk (Alonso et al., 2003) stocks prior to

the commencement of this project, and were also kindly provided by Dr Jennifer

Schweer (University of Bochum, Germany). The mutants were represented by the

lines GK_758B02 (sig1), GK_428A06 (sig2), GK_238A06 (sig3), SA_146777

(sig4), SA_141383 (sig5) and GK_242G06 (sig6). Physical phenotype has been

described previously, and multiple times, for each individual single sigma factor

mutant, and as such the descriptions for these lines are included only for completion.

When grown under shortday conditions, sig1, sig3, sig4 and sig5 bear a phenotype

not visually distinctive from that of the wild-type from germination to reproductive

maturity (Figure 6). The mutants sig2 and sig6, conversely, display a pale and

retarded phenotype in the early developmental stages. However, sig6 effectively

‘outgrows’ its mutant phenotype, and visually resembles the wild-type at

reproductive maturity. Sig2 instead remains pale, and is visibly dwarfed at maturity,

despite producing viable seeds (Figure 6).

5.3.2 Definition of complete plastid mRNA transcript accumulation profiles for

single sigma factor mutants

Single sigma mutants were grown on sterile sucrose-supplemented MS media under

short day conditions and were harvested at the end (dusk) of the seventh day of

growth, and cDNA synthesised from total extracted RNA. qPCR was undertaken

using primers designed for all 78 protein-encoding plastid transcripts, and results

were median-corrected and normalised against the wild-type. Results represent the

average of three biological replicates, the first of which was undertaken prior to the

commencement of this project by Asst./Prof. Kate Howell, with the subsequent two

biological replicates, and all data analysis undertaken by myself. In Microsoft Excel,

F-tests were performed to assess variance differences between the wild-type and

mutants (results not shown). Plastid transcript accumulation has been shown to be

particularly robust to perturbation (e.g. during chloroplast-to-chromoplast

conversion: Kahlau and Bock (2008) and absolute levels of most chloroplast


68

Figure 6: Physical phenotype of arabidopsis sigma factor single mutants.

Following 7 days growth short day conditions (A), sig2 and sig6 bear a pale, retarded phenotype, with other sigma mutants resembling the wild-type. Sig6 outgrows this phenotype, and at reproductive maturity (B), resembles the wild-type, while sig2 remains dwarfed and slightly paler throughout its life.

sig1

wild-type

C

A

B

1 cm

6 cm

6 cm

sig2

sig3

sig4

sig5

sig6

sig1

wild-type

sig3

sig4

sig5

sig6

sig2


69

transcripts are high relative to cytosolic transcripts. Hence, small percentage changes

in fact represent large absolute changes. For this reason, Student’s two-tailed t-tests

with unequal variance were undertaken to establish significant (p<0.05) changes, as

opposed to methods more commonly used for nuclear-encoded transcript analysis

(and previously used for plastid transcript analysis in sigma factor investigations),

which define perturbation as change by a factor of greater than 1.5-fold.

5.3.2.1 sig1 has decreased accumulation of multiple Photosystem II transcripts

The single mutant sig1 showed a significant decrease in plastid-encoded photosystem

II transcripts psbB, psbE, psbF, psbL and psbT, to between 0.59 and 0.71 of the level

of the wild-type (Figure 7). Transcript levels of other plastid-encoded PSII subunits

(psbA, psbC, psbD, psbH, psbI, psbJ, psbK, psbM, psbN and psbZ) were not

significantly different(p<0.05) from those of the wild-type. A single transcript of the

cytochrome b6/f complex, petD, also showed significantly decreased levels of

transcripts relative to the wild-type (0.79). Conversely, ndhA and ndhH transcript

levels were slightly higher in the sig1 mutant than the wild-type (1.24, 1.09,

respectively), as were the small ribosomal subunits rps4 and rps11 (1.17, 1.08,

respectively).

5.3.2.2 sig2 and sig6 show similar patterns of decreased accumulation of

photosynthesis-related, and increased accumulation of housekeeping transcripts

Generally, photosynthesis-related transcripts were altered with lower levels of

accumulation, relative to the wild-type, in both sig2 and sig6, including psaA (sig6,

0.78), psaB (sig6, 0.73), psbB (sig2, 0.51), psbC (sig6, 0.53), psbD (sig6, 0.59), psbI

(sig6, 0.52), psbK (sig6, 0.45), psbM (sig6, 0.51), psbT (sig2, 0.55), psbZ (sig6,

0.60), petB (sig2, 0.72), petD (sig2, 0.71, sig6, 0.67), petN (sig6, 0.28), atpB (sig6,

0.77) and ndhF (sig2, 0.82) as well as rbcL (sig6, 1.79) (Figure 7). Conversely,

several photosynthesis-related transcripts showed higher accumulation in sig2: ycf3

(1.33); and in sig6: ndhB (2.44), ndhG (1.45), cemA (1.29), and ycf4 (1.22). Both

mutants exhibited higher accumulation of rpoC2: to 1.76 times that of the wild-type

in sig2, and 2.12 times in sig6, and in the housekeeping gene rps4 (1.42 and 1.47

times, respectively). Similarly, increases were seen in plastid encoded polymerase

subunit transcripts rpoC1 (2.86) and rpoB (1.79) in sig6 (Figure 7).

Figu

re 7

: Pla

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0.12

5

0.250.

5124psaApsaBpsaCpsaIpsaJycf3ycf4

psbApsbBpsbCpsbDpsbEpsbFpsbHpsbIpsbJpsbKpsbL

psbMpsbNpsbTpsbZpetApetBpetDpetGpetI

petNatpAatpBatpEatpFatpHatpI

ndhAndhBndhCndhDndhEndhFndhGndhHndhIndhJndhKrbcL

cemAccsArpS2rpS3rps4rpS7rpS8

rpS11rpS12A

rps14rpS15rpS18rpS19

rpL2rpL14rpL16rpL20rpL22rpL23rpL32rpL33rpL36rpoArpoB

rpoC1rpoC2matKclpP1accDycf1

ycf2.1ycf15

0.12

5

0.250.

5124

psaApsaBpsaCpsaIpsaJycf3ycf4






rpS11rpS12A




ycf2.1ycf15

0.12

5

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5124







rpS11rpS12A




ycf2.1ycf15

0.12

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5124







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ycf2.1ycf15

0.12

5

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5124







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ycf2.1ycf15

0.12

5

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5124







rpS11rpS12A




ycf2.1ycf15

sig1

sig2

sig3

sig4

sig5

sig6

Relative transcript accumulation (mutant/wild-type)


71

5.3.2.3 sig3 analysis suggests previously undescribed role of SIG3 in accumulation

of four plastid transcripts

The sig3 mutant showed significant changes in only four of the nearly 80 plastid

mRNAs profiled (Figure 7). Of these, a transcript level increase was seen in the

photosystem I subunit psaA (1.19 times that of the wild-type), and the photosystem I

assembly protein ycf3 (1.17), but a decrease was seen in psaI (0.97). The protease

subunit clpP1 showed higher levels of transcript (1.09) in the mutant.

5.3.2.4 sig4 has decreased levels of multiple NDH complex transcripts

The sig4 mutant shows significant changes in levels of multiple NDH complex

transcripts, including ndhA (0.17), ndhD (0.79), ndhE (0.69), ndhF (0.31), ndhG

(0.58), ndhH (0.70) and ndhI (0.32), with decreased transcript levels relative to the

wild-type (Figure 7). Transcript levels of the other plastid-encoded NDH complex

transcripts, ndhB, ndhC, ndhJ, and ndhK, were unchanged in the sig4 mutant.

Transcript levels of psaC and psaI were also lower (0.75, 0.84), as was ycf1 (0.81),

while housekeeping transcripts rpl14 and rps8 were slightly higher in the mutant

(1.14, 1.06).

5.3.2.5 sig5 analysis supports previously described psbD regulation and suggests

broader role of SIG5 in plastid transcription

Transcript levels for psbD are significantly decreased in sig5 (0.66) (Figure 7).

Photosystem I transcripts psaA and psaB are similarly decreased (0.87, 0.85), as is

ndhD (0.90). Conversely, ndhK transcript levels are higher than that of the wild-type

(1.06). Multiple housekeeping genes also show higher transcript levels in the sig5

mutant: clpP1 (1.10); matK (1.15); rpoC1 (1.19); rpl16 (1.13); and rpl23 (1.09).

5.3.2.6 Changes in mature transcript accumulation seen by qPCR are unlikely to

be explained by splicing defects

Primers used in qPCR analysis were designed to span exon-exon borders, and as

such quantified levels of mature spliced, but not unspliced transcripts. qPCR analysis

was undertaken for sigma factors mutants sig1-3, sig5 and sig6 using primers

situated within the rpoC1 intron, within intron 1 and intron 2 of clpP, and within

intron 2 of ycf, as well as relevant exon-exon primers (as used for mRNA profile

analysis). Preliminary data undertaken with one biological and three technical

replicates suggests relative levels of spliced and unspliced transcripts differ only


72

slightly from those seen in the wild-type (Figure 8), with no significant accumulation

of unspliced transcripts (indicating a splicing defect) seen.

5.3.3 Definition of sigma factor mutant mRNA accumulation profiles in the

context of transcription units (operons)

Transcript profiling was undertaken for single sigma factor mutants, and many

individual plastid mRNAs were found to have significant (p<0.05) differences in

levels of accumulation when compared to the wild-type. Analysis of the complete set

of plastid mRNAs provided a highly comprehensive insight into the roles of sigma

factors, yet may be seen to exhibit two distinct limitations: first, the loss of biological

context; and second, the loss of statistical power.

Sigma factors aid transcription by binding to the plastid encoded polymerase (PEP)

core enzyme and recognising cis-elements present in gene promoters. Unlike nuclear

genes, plastid genes are generally transcribed from a single upstream promoter as

polycistronic operons, which must be further processed to produce mature RNA. As

such, individual mRNA levels do not only reflect a single transcriptional event, but

also subsequent processing events and thus, do not always accurately represent the

activity of a sigma factor on a promoter. Hence, analysis of individual mRNA

accumulations ignores the biological context of sigma factor- mediated transcription.

Furthermore, undertaking large numbers of t-tests leads to an increased likelihood of

type I errors (in which the null hypothesis, that there is no significant difference

between treatments, is falsely rejected: reviewed in Shaffer (1995)). Analysis of the

complete set of plastid mRNAs involved undertaking 78 individual t-tests for each

mutant (paired with the wild-type). Type I errors can be corrected for (false

discovery rate (FDR) controls), although overly conservative correction may result in

an increase in type II errors (in which the null hypothesis is falsely upheld). Even

under a less-conservative correction, such as Benjamini-Hochberg method

(Benjamini and Hochberg, 1995), significance of the mRNA transcript profile data

analysed here was lost for almost all mRNA changes, excepting only that of ndhA,

ndhI and psaA in sig4 and rps19 in sig1.


73

0.25

0.5

1

2

4

sig1 sig2 sig3 sig5 sig6

rpoc1-spliced

rpoc1-unspliced

clpP1_intron 1-spliced

clpP1_intron 1-unspliced

clpP1_intron 2-spliced

clpP1_intron 2-unspliced

ycf3_intron 2-spliced

ycf3_intron 2-unspliced

Figure 8: Splicing efficiencies at 4 sites in sigma mutants.

qPCR was performed using primers designed to span exon-exon borders, and primers within an intron and exon. Levels of mature, spliced transcript (exon-exon) and unspliced transcript (intron-exon) are shown in single sigma mutants relative to levels in the Col-0 wild-type on a log2 scale. Preliminary data presented here suggests minimal disparity between splicing levels in sigma factor mutants compared to the wild-type.

Accu

mul

atio

n re

lativ

e to

wild

-typ

e, lo

g 2


74

Definition of plastid operons, followed by analysis of mRNA accumulation in the

context of these transcriptional units, not only restores biological context, but also

increases the number of measurements within each t-test pair, and, by reducing the

number of t-tests required for comparative analysis, limits the degree of FDR

correction required.

5.3.3.1 Definition of putative plastid operons and consequent analysis of mRNA

profiles

While flexible use of promoters and production of transcripts have been noted, it is

generally accepted that plastid transcription involves the production of operons,

usually polycistronic, transcribed from a single upstream promoter (Swiatecka-

Hagenbruch et al., 2007). These operons are, however, not well defined in the

literature. Furthermore, very little is known about promoter usage and initiation, and

even less about transcription termination. Despite this, inefficiency of transcription

termination is accepted (Stern and Gruissem, 1987), and recent research

demonstrates the important role of a ribonuclease, RNase J, in compensating for such

inefficiency by removing antisense RNA (Sharwood et al., 2011). As such, a

conservative definition of operons may be created on the assumption that plastid

transcription continues as long as a gene stretch remains unidirectional. This

definition of operons is similar to that previously used (Yada et al., 1999, Taboada et

al., 2010) to predict bacterial operons, with high success.

Putative operons were defined by this mechanism, and named using the most 5’

transcript of the operon (Table 9). qPCR data were re-analysed in the context of these

putatively defined operons, with relative transcript abundances for entire operons

compared and tested (Students t-test, two-tailed, unequal variance) between mutant

and wild-type. Data were further controlled for FDR using the Benjamini-Hochberg

method (Benjamini and Hochberg, 1995).

5.3.3.2 sig1 has decreased accumulation of three putative operons primarily

containing Photosystem II transcripts

The sig1 mutant shows lower accumulation, relative to the wild-type, of three

operons: psbE, psbB and psbH (Figure 9). These operons include the transcripts

psbE-psbF-psbL-psbJ, psbB-psbT and psbH-petB-petD, respectively. Average

operon transcript accumulation is between 0.64 and 0.86 times that of the wild-type.


75

Table 9: Putative Plastid Operons.

Plastid genes are generally transcribed as polycistronic operons, which are not well defined in the literature. The putative operons below are defined as all genes on a single strand until any gene running in the opposite direction (reverse complement) is encountered. tRNA and rRNA are not listed but the orientations of trn and rrn genes were used to define operon boundaries. Operons will be named for the most 5’ transcript (shown in bold), except in the case of the rps16-matK-psbA operon, referred to as matK (rps16 was not measured in experiments).

Putative Operons (transcripts)

rps16 matK psbA

psbK psbI

rpoB rpoC1 rpoC2 rps2 atpI atpH atpF atpA

petN

psbM

psbD psbC psbZ

atpB atpE

ndhC ndhK ndhJ

rps4

ycf3 psaA psaB rps14

rbcL accD psaI ycf4 cemA petA

psbE psbF psbL psbJ

petI petG

psaJ rpl33 rps18

clpP1 rps12A rpl20

psbB psbT

psbN

psbH petB petD

rpl23 rpl2 rps19 rpl22 rps3 rpl16 rpl14 rps8 rpl36 rps11 rpoA

ycf2.1 ycf15

ycf15

rps12c rps7.1 ndhB.1

ycf1

ndhF

rpl32 ccsA

ycf1.2 rps15 ndhH ndhA ndhI ndhG ndhE psaC ndhD

rps12b rps7.2 ndhB2

ycf2.2 orf71

rpl23.2 rpl2.2

Figu

re 9

: Pla

stid

mR

NA

ope

ron

prof

iles f

or si

ngle

sigm

a m

utan

ts.

Sing

le s

igm

a fa

ctor

mut

ants

rep

rese

nted

by

hom

ozyg

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inse

rtion

line

s G

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ig1)

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A06

(si

g2),

GK

_238

A06

(si

g3),

SALK

_146

777

(sig

4), S

ALK

_141

383

(sig

5) a

nd G

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06 (s

ig6)

and

the

Col

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ition

s. cD

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was

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thes

ised

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a ra

ndom

hex

amer

prim

er f

rom

tot

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ext

ract

ed f

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aer

ial

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es,

and

qRTP

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ken.

Dat

a w

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edia

n or

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sam

ples

, an

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raph

as

trans

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. Acc

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utat

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able

9.

Bar

s re

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dard

err

ors.

Ope

ron

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ly (p

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Ben

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ini-H

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ectio

n ar

e sh

own

in re

d.

0.12

5

0.250.

5124

rps16

psbK

rpoB

petN

psbM

psbD

atpB

ndhC

rps4

ycf3

rbcL

psbE

petI

psaJ

clpP1

psbB

psbN

psbH

rpL23

ycf2.1

rps12c

ycf1

ndhF

rpL32

ycf1.2

rps12b

ycf2.2

rpl23.2

0.12

5

0.250.

5124

rps16

psbK

rpoB

petN

psbM

psbD

atpB

ndhC

rps4

ycf3

rbcL

psbE

petI

psaJ

clpP1

psbB

psbN

psbH

rpL23

ycf2.1

rps12c

ycf1

ndhF

rpL32

ycf1.2

rps12b

ycf2.2

rpl23.2

0.12

5

0.250.

5124

rps16

psbK

rpoB

petN

psbM

psbD

atpB

ndhC

rps4

ycf3

rbcL

psbE

petI

psaJ

clpP1

psbB

psbN

psbH

rpL23

ycf2.1

rps12c

ycf1

ndhF

rpL32

ycf1.2

rps12b

ycf2.2

rpl23.2

0.12

5

0.250.

5124

rps16

psbK

rpoB

petN

psbM

psbD

atpB

ndhC

rps4

ycf3

rbcL

psbE

petI

psaJ

clpP1

psbB

psbN

psbH

rpL23

ycf2.1

rps12c

ycf1

ndhF

rpL32

ycf1.2

rps12b

ycf2.2

rpl23.2

0.12

5

0.250.

5124

rps16

psbK

rpoB

petN

psbM

psbD

atpB

ndhC

rps4

ycf3

rbcL

psbE

petI

psaJ

clpP1

psbB

psbN

psbH

rpL23

ycf2.1

rps12c

ycf1

ndhF

rpL32

ycf1.2

rps12b

ycf2.2

rpl23.2

0.12

5

0.250.

5124

rps16

psbK

rpoB

petN

psbM

psbD

atpB

ndhC

rps4

ycf3

rbcL

psbE

petI

psaJ

clpP1

psbB

psbN

psbH

rpL23

ycf2.1

rps12c

ycf1

ndhF

rpL32

ycf1.2

rps12b

ycf2.2

rpl23.2

sig1

sig2

sig3

sig4

sig5

sig6

Relative transcript accumulation (mutant/wild-type), log2


77

Decreases were not seen in operons containing other photosystem II transcripts:

rps16-matK-psbA; psbK-psbI; psbM, psbD-psbC-psbZ or psbN, nor in the other

cytochrome b6/f complex subunit (pet) transcript-containing operons petN, rbcL-

accD-psaI-ycf4-cemA-petA and petI-petG.

5.3.3.3 Operons in sig2 and sig6 showing lower accumulation primarily contain

‘photosynthesis-related’ transcripts, while those showing increased accumulation

primarily contain ‘housekeeping’ transcripts

The sig2 and sig6 mutants showed similarly altered patterns of transcript

accumulation: an increase in ‘housekeeping’ operons and a decrease in

‘photosynthesis’ operons (Figure 9). A greater number of operons were changed in

sig6, and there was some, but not a complete overlap of accumulation patterns,

between mutants. Both sig2 and sig6 showed increased levels of the rpoB-rpoC1-

rpoC2-rps2-atpI-atpH-atpF-atpA operon (1.41 and 1.52 times that of the wild-type,

repectively), and the rpl23-rpl2-rps19-rpl22-rps3-rpl16-rpl14-rps8- rpl36-rps11-

rpoA (1.16, 1.12), which together contain the majority of plastid-encoded PEP and

ribosomal subunits. Sig6 also contained an increased level of rps12-rps7-ndhB, an

operon present in duplicate in the plastid, clpP1-rps12A-rpl20, and the ndh transcript

containing ycf1.2 operon, while sig2 contained higher accumulation of the

monocistronic rps4 (1.42). In both mutants, decreased levels of the psbH (both 0.67)

and psbB (0.53 and 0.66) operons were seen. Sig2 shows further lower accumulation

of the psbE (0.85) and monocistronic ndhF (0.82) operons, while sig6 shows lower

levels of the operons psbD (0.57), psbK (0.49), atpB (0.75), petN (0.28), ndhC

(0.82), psbM (0.51), petI (0.71) and matK (0.69).

5.3.3.4 sig3 shows altered levels of transcripts from two operons

Transcript levels of two operons were altered in sig3 (Figure 9). Transcripts from the

ycf1.2 operon (ycf1.2-rps15-ndhH-ndhA-ndhI-ndhG-ndhE-psaC-ndhD) accumulated

to lower levels (0.85), while those from the ycf3-psaA-psaB-rps14 operon

accumulated to higher levels (1.15).

5.3.3.5 sig4 operon accumulation patterns suggest a dominant role for SIG4 in

ndh transcript accumulation

Transcript accumulation from the three operons containing all plastid-encoded NDH

complex genes (except for the monocistonically transcribed ndhB) was altered in


78

sig4 (Figure 9). Of these, the monocistronic ndhF was significantly reduced (0.31

times that of the wild-type), as were transcripts from the ycf1.2-rps15-ndhH-ndhA-

ndhI-ndhG-ndhE-psaC-ndhD operon (0.67). Conversely, accumulation of transcripts

from the ndhC-ndhK-ndhJ operon was, on average, 1.23 times that of the wild-type.

Accumulation of the transcript of the monocistronic rps4 was also higher (1.23),

while transcripts from the rbcL operon, encoding rbcL-accD-psaI-ycf4-cemA-petA,

were lower than in the wild-type (0.85). Lower accumulation (0.81) was also seen for

transcripts from the monocistronic ycf1.1 operon. However, as qPCR data did not

differentiate between duplicated genes, such a decrease may merely reflect the large

reduction of the ycf1.2 operon.

5.3.3.6 sig5 operon accumulation analysis supports previously the described role of

SIG5 in psbD and psbC accumulation

qPCR analysis supports a significant decrease in the accumulation of psbD (0.66),

psbC (0.79), and psbZ (0.76), of the psbD operon (Figure 9). In addition, the ycf3-

psaA-psaB-rps14 operon was significantly decreased in sig5 (0.88). The rpoB and

rpl23 operons, together containing the majority of plastid-encoded gene involved in

‘housekeeping’ actions, are also increased, but only slightly (both 1.08 times the

wild-type).

5.3.3.7 Reviewing operon definition If operons were correctly defined, and transcription occurred in a simplified manner

where each operon was transcribed from a single upstream promoter, it would be

expected that all transcripts within an operon would show similar patterns of

regulation. In reviewing operon definitions, pairwise comparisons were undertaken

to examine the correlation of transcript accumulations within operons across the six

sigma factors (data not shown). Calculated r 2 values were generally high (>0.70) for

operons containing two, three, or four transcripts, the notable exceptions being

rpl23.2-rpl2.2, ycf3-psaA-psaB-rps14 and rpl32-ccsA. As qPCR only measures

mature transcripts, it is possible that the poor correlation of ycf3 with other

transcripts (relative to their high correlation with each other), may be a result of the

two splicing events required to produce its mature mRNA. Similarly, rpl2 undergoes

splicing, although it is also relevant that this transcript and rpl2 are also present on

another operon (albeit positioned together). ccsA (ycf5) is closely preceded by

tRNALEU, however these transcripts are separated from the 3’ end of rpl32 by 663


79

bps, a fairly long distance in the context of plastid gene spacing. It is possible that

these do not represent a true operon, and is recommended that future operon

definitions also take into consideration gene spacing. Larger operons generally

showed lower pairwise correlations, and may suggest the presence of internal

promoters or a terminating mechanism. For example, in the rbcL-accD-psaI-ycf4-

cemA-petA operon, rbcL accumulation correlates well with that of accD (r2=0.77)

across factors but extremely poorly with all other transcripts (r2<0.35). psaI

accumulates with that of ycf4 (0.82), but not with other transcripts (<0.30), while

cemA and petA accumulation correlate only with eachother (0.82). As such, it is

possible that the rbcL operon instead represents three operons (rbcL-accD, psaI-ycf4,

and cemA-petA). Similarly, in the rpl23-rpl2-rps19-rpl22-rpl16-rpl14-rps8-rpl36-

rps11-rpoA operon, high correlation is seen between rpl16 and the following, but not

the preceding transcripts. Here, however, very little correlation is seen between the

preceding transcripts, although this may partially be the result of gene duplication

and splicing events. Interestingly, two transcripts, psaC, of the ycf2.1 operon, and

atpH of the rpoB operon, have particularly low correlation with other transcripts

within their operon, despite the absence of introns and therefore, no requirement for

splicing.

Finally, visual inspection of operons suggests that certain operons are ‘unlikely’ on

the basis of the presence of genes known to have different functions or different

known accumulations. One example is the psaJ-rpl33-rps18 operon containing both

an important photosynthetic transcript, and housekeeping transcripts. Interestingly,

correlation between these three transcripts is high (~0.70), although further

investigation reveals a 425 bp gap between psaJ and the ribosomal protein

transcripts. As both this operon, and the rpl32-ccsA operon (similarly containing two

transcripts of disparate accumulation) were not found to be affected in any of the six

sigma mutants, the possibility that incorrect definition of operons was producing a

‘false negative’ result was investigated. However, even when accumulations were

investigated in the context of four (psaJ, rpl33-rps18, rpl32 and ccsA), instead of the

previous two operons, no significant change was found across sigma factors, nor was

the ranking and significance of any other operon altered.


80

5.3.4 Analysis of plastid transcript accumulations in the context of the sigma

factor family

Single mutant plastid transcript accumulation analysis was used to suggest putative

function of arabidopsis factors on transcript promoters, with a focus on individual

factor activities. By undertaking growth and experimentation in parallel, this study

additionally allows comparative analysis of sigma activities, and analysis of the

overall function of sigma factors within arabidopsis.

5.3.4.1 Multiple units show altered accumulation in more than one of the single sigma

mutants

Whether analysed in the context of individual transcripts or operons (Table 10),

multiple transcription units were found to be affected in multiple sigma factor

mutants. Generally, housekeeping transcript accumulation was increased in mutants,

potentially indicating a secondary increase in NEP activity, while photosynthesis-

related transcript accumulation was decreased, although this was not always the case.

Where multiple mutants showed changed accumulation, the relative magnitude was

not always the same, nor was the direction: in some instances (psaA, ndhA, ndhG,

and ndhH, and the ndhC operon), transcript accumulation was increased, relative to

the wild-type, in one or more mutants, but decreased in others.

5.3.4.1 Multiple transcripts are not represented in those changed in sigma factor lines

Based on single sigma factor analysis, multiple transcripts were found for which

promoter activity could not be accounted for by any of the six sigma factors in

arabidopsis (Table 11). This was not limited to housekeeping type genes, which

included the essential accD, and multiple ribosomal protein transcripts, but extended

to all transcripts involved in formation of the ATP synthase except for atpB, as well

as units involved in formation of PSI, PSII, and the cytochrome b6/f complex. Fewer

transcripts were unaccounted for under operon analysis (not shown), but important

photosynthetic transcripts were still ‘missing’ (e.g, psbN). It should be noted that no

additional sigma-like factors have been found in arabidopsis, although the activity of

plastid-localised NEPs cannot be ignored.


81

Table 10: Plastid transcripts and operons showing altered accumulation in multiple sigma factor mutants.

Transcripts showing changed accumulation in 3 or 2 separate single sigma mutants. Transcript or operon abundance, relative to wild-type (=1.00) are shown. Values in green show transcripts with decreased accumulation in the sigma mutant, while red values represent increases. Some transcripts show decreased levels, relative to wild-type, in some sigma mutants, yet increased levels in other mutants.

sig1 sig2 sig3 sig4 sig5 sig6 ANALYSIS BY INDIVIDUAL TRANSCRIPTS

3 psaA 1.19 0.87 0.78 petD 0.79 0.71 0.67 rps4 1.17 1.42 1.47

2 clpP1 1.09 1.10 ndhA 1.24 0.17 ndhD 0.79 0.90 ndhF 0.82 0.31 ndhG 0.58 1.45 ndhH 1.09 0.70 psaB 0.85 0.73 psaI 0.93 0.84 psbB 0.71 0.51 psbD 0.66 0.59 psbT 0.68 0.55 rpoC1 1.19 2.86 rpoC2 1.76 2.12 ycf3 1.33 1.17

ANALYSIS BY OPERONS 3 psbB 0.69 0.53 0.66

psbH 0.86 0.67 0.67 rpl23 1.16 1.08 1.23 rpoB 1.41 1.08 1.52 ycf1.2 0.85 0.67 1.38

2 ndhC 1.23 0.82 ndhF 0.82 0.31 psbD 0.73 0.57 psbE 0.64 0.85 rps4 1.15 1.16


82

Table 11: Summary of plastid transcripts accumulation across the six arabidopsis sigma factor mutants.

Transcripts are grouped by function, and identified for decreased (but not increased) accumulation across the six mutants. Multiple transcripts did not show decreased accumulation in any of the six mutants (not lower).

Gene function sig1 sig2 sig3 sig4 sig5 sig6 Not lower Genetic system genes Small ribosomal subunit Large ribosomal subunit PEP subunits Splicing factor Protein degradation

rps2, rps3, rps4, rps7,

rps8, rps11, rps12, rps14, rps15, rps16, rps18, rps19

rpl2, rpl14,

rpl16, rpl20, rpl22, rpl23, rpl32, rpl33,

rpl36 rpoA, rpoB,

rpoC1, rpoC2 matK clpP

Photosynthesis-related genes Photosystem I subunits Photosystem I assembly factors Photosystem II subunits Cytochrome b6f subunits ATP synthase subunits NDH subunits Rubisco, large subunit CytC biogenesis Cyt Cassembly

psbB,psbE, psbF, psbL psbT

petD

psbB,psbT

petB,petD

ndhF

psaI

psaC, psaI

ndhA ndhD ndhE,ndhF ndhG,ndh

H ndhI

psaA,psaB

psbD

psaA psaB

psbC, psbD

psbI, psbK psbM, psbZ

petD,petN

atpB

rbcL

psaJ

ycf3, ycf4

psbA, psbH, psbN,

petA, petG

atpA, atpE, atpF,

atpH, atpI

ndhB, ndhC,

ndhJ, ndhK

ycf10/cemA

ycf5/ccsA Other genes and ycfs Acetyl-CoA carboxylase subunit Hypothetical conserved open reading frames (unknown function)

accD

yc1, ycf2,

ycf15


83



This study not only produced complete mRNA transcript profiles for all six sigma

factor mutants, providing a great deal of previously uncollected data, but also

involved simultaneous growth and analysis of mutants: allowing true side-by-side

comparison of differences in transcript levels. Definition of transcript accumulation

changes in the context of operons increased statistical power (greater number of

samples in t-test pairs) and restored biological context to analyses, which has almost

entirely been ignored in previous studies. However, operons have only been

putatively defined. A review of these operons suggested greater accuracy for smaller

operons than larger operons, the latter of which may have included unknown internal

promoters or transcription termination sites. Some operons contained ‘unlikely’

combinations of elements, such as the presence of both photosynthetic and

housekeeping transcripts. However, to alter operon definition in this context would

add a subjective element that is inappropriate in light of the current poor

understanding of transcript promoter usage and transcript accumulation.

Although housekeeping genes were included in qPCR analyses, accumulation of

these genes across mutants was not found to be robust, excluding them as a method

for normalisation. Transcript accumulations were instead normalised to the median

value of all plastid transcripts. Where multiple transcripts within a mutant have

accumulation altered in a single direction, such as the net decrease in accumulation

of photosynthesis-related transcripts in sig2 and sig6, the median would reflect these

lower values. Hence, normalisation to this median may introduce a bias, dampening

the change seen for down-regulated transcripts, and representing transcripts which

were not decreased as either falsely, or exaggeratedly, up-regulated. Future

investigations could involve more thorough screening for housekeeping genes

showing robust accumulation across sigma factor mutants, and utilize these genes as

a method of normalisation. Alternatively, absolute quantification using a pool of

quantified PCR products as the standard in qPCR could be undertaken.

It should be noted that the transcription profiles generated here are limited in that

they only represent steady state transcript levels. Although the well-defined role of

sigma factors in transcription suggest that changes result exclusively from variation


84

to transcriptional activation or activity, profiles may also represent changes in

degradation of mRNA processing. Implication of sigma factors in these processes is

limited, but not unknown: the presence of accumulated precursor atpB and rrn16 in a

sig6 mutant suggested a (likely indirect) effect on mRNA processing (Ishizaki et al.,

2005).

Finally, while the study of single mutants provides an efficient way to test gene

function, in the case of small gene families where function may be somewhat

redundant, it is possible that the (up-regulated) activity of other family members

may, at least partially, compensate for the loss of the studied member. This may be

partially limited by analysis of transcript changes on the basis of statistical

significance, as opposed to the common method of defining on the basis of ‘large

biological perturbation’ (usually >1.5-fold: which is unsuitable for plastid transcript

analysis generally), but supports a need for alternate methods of assigning sigma

factor function.


Definition of sigma factor recognition of plastid promoters was facilitated by the

availability of single mutants, which were shown to have the physical phenotypes

concordant with previous descriptions. sig2 and sig6 were pale and retarded at early

stages, with sig2, but not sig6 maintaining a mutant phenotype in later life, while

sig1, sig3, sig4 and sig5 displayed a wild-type phenotype (Shirano et al., 2000,

Kanamuru et al., 2001, Ishizaki et al., 2005). A previous study of the sig6

GK_242G06 line observed gradual bleaching of the cotyledons with age (Schweer et

al., 2009), but this was not seen here, likely a result of different growth conditions.

The data generated here represents a significant contribution to the field, which, in

addition to supporting and greatly extending definitions of individual sigma factor

function (Table 12), augmets understanding of sigma factor function in the context of

the sigma factor family. At 7 days short day growth, both sig2 and sig6 were shown

to have significantly reduced accumulation of multiple photosynthetic transcripts

(Table 12). The data supported a previous role for SIG2 in transcription of psbJ, but

extended this role to include transcription of multiple other, primarily PSII-related

genes (Table 12). Similarly, SIG6 is implicated in affecting levels of multiple PSII

transcripts, and rbcL as previously defined, but is identified as having a much greater


85

Table 12: Review of arabidopsis sigma factor function.

Activity of factors was suggested on the basis of transcript accumulations in single mutatns, analysed in the context of either single transcdipts or operons. Where findings of this study support previous reports, transcripts are highlighted in grey. Transcripts proposed to be regulated by factors in previous studies, not supported or analysed in this work, are also shown (reported). References: 1 (Tsunoyama et al., 2004), 2 (Favory et al., 2005), 3 (Nagashima et al., 2004b), 4 (Ishizaki et al., 2005), 5 (Nagashima et al., 2004a), 6 (Shimizu et al., 2010), 7 (Zghidi et al., 2007). *Transcript levels of petB were previously reported as unchanged in mutnat sig2_1 (Shirano et al., 2000, Kanamaru et al., 1999).

SIG1 SIG2 SIG3 SIG4 SIG5 SIG6

TR

AN

SCR

IPT

A

NA

LY

SIS

psbB, psbE, psbF, psbL,

psbT 1

petD

psbB, psbT

petB*,pet

D

ndhF

psaI psaC, psaI

ndhA ndhD ndhE,ndhF2

ndhG 2,ndhH ndhI

psaA,psaB

psbD1,3

psaA psaB

psbC45 psb45

psbI, psbK psbM, psbZ

petD,petN

atpB

rbcL4

OPE

RO

NS

AN

AL

YSI

S

psbB-psbT (Tsunoyama et al., 2004)

psbE-psbF-psbL-psbJ1

psbH-petB-

petD

psbB-psbT

psbE-psbF-psbL-psbJ 5

psbH-

petB-petD

ycf1.2-rps15-ndhH-ndhA-ndhI-ndhG-ndhE-

psaC-ndhD

ndhF 2 ycf1.2-rps15-ndhH-ndhA-ndhI-ndhG 2-ndhE-psaC-ndhD rbcL-accD-psaI-ycf4 2-cemA-petA

psbD1,3

-psbC-psbZ

ycf3-psaA-psaB-rps14

psbB-psbT 4

psbH4-petB-petD,

psbM

psbD4-psb45-

psbZ

psbK-psbI

petN

atpB-atpE

ndhC-ndhK-ndhJ

petI-petG,

rps16-matK-

psbA4

RE

POR

TED

Rrn16, psbA, psbD, psaA, rbcL 6

rbcL 3

psbA 3

trnE, trnD, trnM, trnV 5

psbN 7 psbA1 psbH, psbN, psbT rrn16, rrn23, rrn5, rrn4.5, trnE, trnQ 4


86

role in young seedlings, participating in transcription of genes with products

encoding subunits of PSI, the cytochrome b6f complex and ATP synthase. As such,

the molecular phenotype was found to be more pronounced in sig6, suggesting a

dominant role for this factor, although future studies should investigate relative

activities at different life stages, and in different tissues.

The novel undertaking of parallel growth and analysis of all six mutants allowed

comparison between mutant transcript profiles, and reveals potential similarities in

the action of SIG1 and SIG2. This suggests redundancy between these factors in the

regulation of primarily PSII transcripts. Interestingly, absolute changes were

generally less pronounced in sig1 than sig2, which may be a reflection of the

previously defined low efficiency of SIG1 in promoter recognition (measured

relative to SIG2 and SIG3; Privat et al. (2002)). Alternatively, it is possible that these

factors recognise different promoters. It is recommended that future investigations be

undertaken into promoter recognition for transcripts found to be reduced in both

mutants. This similarity further suggests that the strong phenotype of sig2, not seen

in sig1, cannot be accounted for by mRNA accumulation differences. Instead, it is

likely that this phenotype is primarily attributable to a major loss of trnE involved in

production of the chlorophyll precursor 5-aminolevulinic acid (ALA) previously

reported in sig2 (Nagashima et al., 2004a). However, the general up-regulation of

NEP products in sig2 may suggest a greater PEP deficiency than that identified:

mutants with strong PEP-deficiency have previously been found to display increased

NEP-dependent transcription (Gao et al., 2012, Chi et al., 2008, Chateigner-Boutin et

al., 2008, Zhou et al., 2009), in a mechanism likely involving tRNAGLU signalling

(Hanaoka et al., 2005). Alternatively, up-regulation of NEP products may be

perceived due to bias introduced by median normalisation, as previously discussed.

Further studies should clarify this through housekeeping-gene based normalisation,

with possible investigation into tRNAGLU levels and resultant signalling.

SIG1 is implicated primarily in the regulation of photosystem II genes, by activity on

three operons, consistent with previous reports (Table 12). Investigation into sigma

activity by phosphorylation suggests recognition also of PSI promoters (Shimizu et

al., 2010), not identified here: explicitly that of psaA, a transcript also shown to


87

accumulate in a SIG1 overexpression mutant (Tsunoyama et al., 2004), and activity

on psaA, also not identified. It is possible that the loss of SIG1 activity on these

transcripts is hidden by increased activity in other factors: e.g., SIG5 and SIG6 are

implicated in psaA transcription.

Reports have also defined SIG3 as ‘rather functionally redundant’, and indeed, in this

work, only psaI accumulation was diminished in sig3, with operon analysis

suggesting specific transcriptional activity only on the promoter of ycf1.2-rps15-

ndhH-ndhA-ndhI-ndhG-ndhE-psaC-ndhD. Previous experiments have defined SIG3

as having activity on psbN as well as regulation of psbB and psbT by run-on

transcription of the antisense strand of these products (Zghidi et al., 2007). This

result was not seen in the current study: psbN levels accumulated at 0.97 times that

of the wild-type, and psbB and psbT were not found to have significantly altered

accumulation. These differences are probably due to variations in experimental

design, and accentuate the need for co-ordinated analysis when comparing gene

family functions.

SIG4 has previously been defined as a regulator of the NAD(P)H dehydrogenase-like

complex (NDH) by specific activity on the limiting, monocistronic ndhF (Favory et

al., 2005), as well as putative activity on ycf4 and ndhG promoters. However, the

author could not identify PEP-type promoters in the upstream region of ndhG. The

data obtained here suggests that SIG4 is indeed involved in transcriptional activity of

ycf4 and ndhG, but that it is likely this occurs though activity on the polycistronic

operons ycf1.2-rps15-ndhH-ndhA-ndhI-ndhG-ndhE-psaC-ndhH and rbcL-accD-psaI-

ycf4-cemA-petA. This reiterates the importance of biological context in

transcriptional analysis (Table 12). The further role for SIG4 in NDH transcript

activity suggested here will be investigated and discussed further in chapter 7.

In sig5 the transcripts psbD, psaA, psaB and ndhD were found to be diminished, with

operon analyses implicating SIG5 in activity at the promoters of operons psbD-psbC-

psbZ, consistent with previous descriptions (Hoffer and Christopher, 1997,

Nagashima et al., 2004b) (Table 12), as well as ycf3-psaA-psaB-rps14, not

previously described.

Undertaking experimentation of all mutants in parallel has facilitated comparison of

transcript profiles, and recognises the presence of transcripts changed in multiple


88

mutants, and the presence of several important photosynthetic transcripts not

accounted for by the activity of any of the six factors. While it is noted that many of

the transcripts in the latter group are housekeeping/genetic system genes, and

therefore likely NEP-transcribed, as well as other genes suggested to contain NEP

type promoters (some ATP synthase genes and NDH genes), important photosystem

genes are also ‘unaccounted for’. This may suggest that transcription of the

respective genes involves activity from multiple sigma factors, and that loss of a

single factor in the mutants is accounted for by the putative activity of one or more of

the six other factors. This implied redundancy of sigma factor function will be

debated further in the General Discussion.

Chapter 6: Sigma factor case study: SIG4-, the significant factor in the regulation of the plastid NAD(P)H dehydrogenase-like complex

89

CHAPTER 6

Sigma factor case study: SIG4, the significant factor in the

regulation of the plastid NAD(P)H dehydrogenase-like

complex


90

6.1 Introduction

The Arabidopsis thaliana nuclear genome encodes six plastid-targeted sigma factors,

required by the plastid encoded DNA-dependent RNA polymerase, PEP, for

recognition of promoter regions. SIG4 has previously been defined by Favory et al.

(2005) as being specifically involved in the transcription of ndhF, based on

observations using the sig4 mutant where diminution of ndhF transcript levels,

decreased (>10-fold less) accumulation of NDHH protein and loss of activity of the

NAD(P)H dehydrogenase-like complex (NDH) was observed. Plastid mRNA

transcript accumulation profiles undertaken in this study show reduced accumulation

in the sig4 mutant (SA_14677) not only of ndhF, but also of ndhA, ndhD, ndhE,

ndhG, ndhH and ndhI . By operon analysis, SIG4 activity was implicated in

promoter recognition of the monocistronic ndhF operon and the ycf1.2-rps15-ndhH-

ndhA-ndhI-ndhG-ndhE-psaC-ndhD operon, with transcripts from the ndhC-ndhK-

ndhJ operon showing increased accumulation in the mutant. As such, the role of

SIG4 in regulation of NDH seems broader than previously described, and suggests

that this factor may be specifically involved in transcription of a physiologically

coherent gene group.

NDH is primarily involved in cyclic electron transfer (CET) around photosystem I

(Shikanai et al., 1998, Suorsa et al., 2009). Plastid photosynthesis involves the

conversion of light energy into chemical energy, which in turn drives the formation

of high-energy organic compounds. In linear electron transfer, occurring within the

plastid thylakoid membrane, light energy captured by the photosystem II reaction

centre powers the splitting of water and the resultant transfer of electrons through

plastiquinone, the cytochrome b6f complex, plastocyanin, PSI and ferredoxin to

ultimately create reducing power in the form of NADPH. Concurrent pumping of

protons from the stroma to the thylakoid lumen through the cytochrome b6f complex,

creates a proton gradient which powers the production of ATP via the ATP synthase.

CET around PSI involves the ‘recycling’ of electrons from reduced ferredoxin or

NADPH to plastoquinone and the cytochrome b6f complex, which occurs by one of

two pathways: a pathway involving the protein PGR5, and the NDH-dependent

pathway (reviewed in Munekage et al. (2004)).

CET can generate a proton gradient, and thus ATP, without the accumulation of

reduced species (Suorsa et al., 2009), and as such has an important role in control of


91

cellular NADPH/ATP ratios. This has been found to be a vital factor in C4

metabolism, where NDH-mediated CET is implicated in generating the high

concentrations of ATP required for CO2 concentration, and suggests a role for NDH

in cellular differentiation: NDH is more highly expressed in mesophyll cells in the

NAD-malic enzyme C4 species, and in bundle-sheath cells of the NADP-malic

enzyme species, in accordance with the respective ATP requirements of these

different cell types (Takabayashi et al., 2005, Munekage et al., 2010). Although the

role of CET seems to be less significant in C3 plants, it is nonetheless essential for

photosynthesis (Munekage et al., 2004), having a defined role as a ‘safety-valve’ by

protecting the stroma from over-reduction and thus preventing permanent PS

damage. Interestingly, complete loss of NDH activity has been shown in several

species to result in no visible phenotype (Kamruzzaman Munshi et al., 2005,

Hashimoto et al., 2003, Horvath et al., 2000) when plants are grown under standard

conditions, and, despite close conservation of NDH units from bacteria to the plastids

of higher plants, certain species seem to have lost NDH genes entirely (Wakasugi et

al., 1994), indicating that, under standard growth conditions at least, the PGR5

pathway is sufficient for mediating CET. Nonetheless, it is NDH and not PGR5 that

has been implicated in C4 cellular differentiation (Munekage et al., 2010), and NDH

has been shown to be important not only where PGR5 is in deficit, but also in

environmental stress conditions requiring increased CET, particularly under

photooxidative stress conditions including high or fluctuating light, low humidity

stress and temperature stress (Suorsa et al., 2012, Jin et al., 2009, Munekage et al.,

2002, Miyake et al., 2004, Horvath et al., 2000, Endo et al., 1999).

NDH is a large complex, requiring protein products from 11 plastid transcripts and

multiple nuclear transcripts for core sub-complex formation, as well as many more

nucleus-encoded proteins required for processing, assembly and stability (see Table

13 for a list of known nucleus-encoded proteins involved in NDH formation). The

absence of just one of these may lead to absence of complex formation and rapid

degradation of remaining NDH subunit proteins (Suorsa et al., 2009, Kamruzzaman

Munshi et al., 2005, Hashimoto et al., 2003).


92

Table 13: Nucleus-encoded NDH subunits.

In addition to the 11 NDH complex proteins encoded by the plastid genome, there are at least 34

nucleus-encoded proteins involved in the formation, processing and stability of the NDH complex

(reviewed in (Peng et al., 2011)).

AGI Gene Subcomplex A AT1G70760 NDHL/CRR23 AT4G37925 NDHM AT5G58260 NDHN AT1G74880 NDHO Subcomplex B AT1G15980 NDH48/NDF1/PNSB1 AT1G64770 NDH45/NDF2/PNSB2 AT3G16250 NDF4/PNSB3 AT1G18730 NDF6 AT5G43750 NDH18 Lumenal AT2G39470 PPL2/PNSL1 AT1G14150 PNSL2 AT3G01440 PQL2/PNSL3 AT4G39710 FKB16-2 AT5G13120 ATCYP20-2 Linkers AT1G45474 LHCA5 AT1G19150 LHCA6 Electron Donor Binding AT4G23890 CRR31 AT4G09350 CRRJ AT5G21430 CRRL Other AT2G01918 PQL3 AT5G52100 CRR1 AT1G55370 NDF5 AT2G47910 CRR6 AT5G39210 CRR7 AT2G01590 CRR3 AT3G46790 CRR2 AT2G45350 CRR4 AT5G55740 CRR21 AT1G11290 CRR22 AT1G59720 CRR38 AT5G20935 CRR42 AT4G24770 CP31A AT4G31850 PGR3 AT3G15840 PIFI


93


The primary aim of the work presented in this study was to investigate the role of

SIG4 in regulation of NDH. This included additional examination of mRNA

accumulation defects in the sig4 mutant in the context of mRNA processing by qPCR

analysis and in silico definition of putative PEP-type promoters. A link between

nuclear and plastid gene regulation was examined by investigation of the correlation

between SIG4 and nucleus-encoded NDH transcripts, and in silico examination of

possible consensus sequences regulating expression of SIG4 and nucleus-encoded

NDH subunits. Finally, the link between SIG4 and NDH accumulation was examined

in the context of sigma factor response, by examining their conditional induction

under fluctuating high light.

6.3 Results

6.3.1 SIG4 is implicated as the significant factor involved in regulation of the

NDH gene group

In assessing the putative activity of SIG4 on regulation of a physiologically coherent

gene group, plastid mRNA accumulation data for all sigma factor mutants were

organised into 12 functional groups: ATP synthase, cytochrome b6f complex,

cytochrome c assembly and structure-related (ccsA and cemA), NDH, PSI, PSI

assembly and structure-related (ycf3 and ycf4), PSII, RUBISCO (rbcL), PEP, large

ribosomal proteins, small ribosomal proteins and other factors (ycf1, ycf15, ycf2.1,

accD, clpP and matK). This analysis shows that the sig4 mutant is the only one to

show significantly reduced accumulation of the NDH gene group, while

accumulation increased in sig6 (Figure 10).

6.3.2 Further support for the molecular phenotype of sig4 as resulting from

transcriptional activity of SIG4

qPCR allows analysis of steady-state transcript levels, with transcript accumulations

often interpreted as resulting from transcriptional changes, but also possibly resultant

of changes in downstream processes, including mRNA degradation and processing.

Changes in transcriptional activity cannot be defined unless the activity of these

downstream processes is known. A possible mechanism for activity should also

exist: in the case of sigma factor activity, the presence of PEP-type upstream

0.25

0.5

1

2

4

sig1

sig2

sig3

sig4

sig5

sig6

Figure 10: SIG4 is the significant factor involved in transcription of plastid NDH genes.

Transcript accumulations were analysed in the context of 11 functional gene groups: ATP synthase, cytochrome b6/f complex, cytochrome c assembly and structure- related

(ccsA and cemA), NDH, PSI, PSI assembly and structure-related (ycf3 and ycf4), PSII, RUBISCO (rbcL), PEP, large ribosomal protein, small ribosomal protein and other

factors (ycf1, ycf15, ycf2.1, accD, clpP and matK), with accumulations assessed for significant disruption by two-tailed students t-test, assuming unequal variance.

Significance values (p<0.05) under the Benjamini-Hochberg correction are shown in red. Only the sig4 mutant shows decreased accumulation of the NDH coherent gene

Rela

tive

tran

scrip

t acc

umul

atio

n (m

utan

t/w

ild-t

ype)

, log

2 sca

le


95

promoter units. Although the specific role of sigma factors in transcription is well

defined, with other roles rarely implicated, a previous study has suggested an indirect

effect of SIG6 on mRNA processing (Ishizaki et al., 2005). As differences in ndhA

transcript levels in particular, have commonly been found to be caused by altered

splicing, as opposed to transcription (Asst./ Prof. Kate Howell, pers. comm.), plastid

transcript splicing analysis was undertaken for sig4 mutants. To further support the

molecular phenotype of sig4 as likely resulting from transcriptional activity, the

presence of putative PEP-type promoters was also analysed in upstream regions of

operons disrupted in the sig4 mutant.

6.3.2.1 Splicing defects do not explain the lower levels of mature ndhA transcripts in sig4 While the majority of plastid-encoded transcripts do not contain introns, some,

including the NDH subunit transcripts ndhA and ndhB, do, and must be spliced to

form mature transcripts. Primers used in qPCR analysis were designed to span exon-

exon borders, and as such quantified levels of mature spliced, but not unspliced

transcripts. In order to verify whether the observed differences were a result of

splicing defects, qPCR analysis was undertaken for sig4 using forward and reverse

primers situated within the intron and exon of ndhA, ndhB and petB. Accumulation

of these ‘unspliced’ transcripts was compared with accumulation of spliced

transcripts, measured with previously utilized exon-exon primers for respective

transcripts. Random primed cDNA was synthesised using total extracted RNA from

three biological replicate samples of Col-0 and two of sig4, all grown for 7 days

under short day condition, and qPCR performed with each sample in technical

triplicate, with data normalised to the housekeeping gene 18S. Mature, spliced ndhA

transcripts are largely reduced in the mutant, and the unspliced to spliced ratio is

significantly higher relative to the wild type, suggesting a diminution of splicing

activity (Figure 11). However, unspliced ndhA transcripts are also markedly lower in

the mutant, indicating that the previously observed ndhA differences cannot be

entirely explained by splicing defects. ndhB, and petB, which were not found to have

differing accumulations in the sig4 mutants, show levels of spliced, unspliced, and

unspliced/spliced ratios similar to those of the wild-type.


96

Figure 11: Splicing efficiencies in sig4.

qPCR was performed using primers designed to span exon-exon borders, and primers within the intron and an exon. Levels of mature, spliced transcript and unspliced transcript are shown in sig4 relative to levels in the Col-0 wild-type, relative to levels of the rrn18S transcript. While ndhB and petB accumulations of mature and unspliced transcript, and unspliced/mature ratios, did not differ between the mutant and the wild-type, spliced ndhA transcripts were low in the mutant, and the unspliced/spliced ratio was much greater than in the wild-type. However, unspliced ndhA transcripts were also lower, suggesting that the differences in ndhA accumulation do not primarily result from splicing defects.

0

0.5

1

1.5

2

2.5

3

wild-type

sig4

Accu

mul

atio

n re

lativ

e to

rrn1

8S


97

6.3.2.2 Operons showing changed accumulation in sig4 contain putative PEP-type

consensus sequences in their 5’ regions Previous analysis suggests reduced accumulation of transcripts from the ndhF

monocistronic operon and the polycistronic ycf1.2-rps15-ndhH-ndhA-ndhI-ndhG-

ndhE-psaC-ndhD operon, as well as the rbcL-accD-psaI-ycf4-cemA-petA operon, in

sig4 relative to the wild-type. Accumulation of transcripts from ndhC-ndhK-ndhJ and

the monocistronic rps4 was increased in the mutant. Of these, the 5’ transcription

initiation start site has been defined in arabidopsis for the individual transcripts ndhF

(Favory et al., 2005), ycf1 (Swiatecka-Hagenbruch et al., 2007), rps4 (Swiatecka-

Hagenbruch et al., 2007) and rbcL (Isono et al., 1997a, Gruissem and Zurawski,

1985), but not for ndhC. These previously defined initiation sites are all within

several bases of bacterial-type promoter sequences ‐35 (TTGaca) and ‐10 (TAtaaT).

Due to the known diversity of plastid promoter usage (Swiatecka-Hagenbruch et al.,

2008), and poor understanding of promoter usage in the context of operon

transcription, not only ndhC, but all operons with changed accumulation in sig4,

were searched for putative PEP-type consensus sequences using BPROM, a predictor

of bacterial σ70 promoters with about 80% accuracy (www.softberry.com). The

upstream regions containing the putative promoters of each of these transcription

units were defined as follows: ndhF contains 810 bp, preceded by the termination

codon of rpl32; ycf1.2 contains 320 bp, preceded by trnN; rbcL contains 801 bp

preceded by atpB; and ndhC and rps4 respectively contain 835 and 384 bp and are

preceded by trnV and trnT. In addition to promoters previously described

experimentally, three predicted bacterial promoters were found upstream of the ndhF

operon, one upstream of ycf1.2, two for rbcL, two for ndhC, and two for rps4. As

such, all operons whose expression is altered in sig4 contain PEP-like consensus

sequences in the 5’ intergenic region of the leading (5’) transcript (Figure 12).

However, I could not establish a clear consensus between these promoters in terms of

either -10 region sequence, -35 region sequence, spacing between regions or, where

defined experimentally, spacing between -10 regions and transcriptional start sites.

http://www.softberry.com/


98

>ndhF tcaaaaatgaaaaaaaatttcagtggtataattggatgtcaaagacatttattattttattctttcgtactccgtacgagtttTTTTCTttcaaattttattATATA TTATtttcaaaacaaaaaagacattcaaaagtttcaaacccaacttttttttttaacgtttgaaatccgtatgagagtactcatttaaataatctatactgatagcttatattataaaaaaattataatatttcttcacatcatatgtaaaaaaaacatatcattatagtaatctttcttaaaaaatataaataaaaaaagctcacttagtgtactgaaagacaatcactaaattccacgatgaaaatccattccttaacaatcctaaataatcaaactcaaataactTTGTTTtaggtcaagctttttTTATATAATtaatattaagtttttttttgtcgtggaaatctTTGTTCtattcttaatatatgtaTATAAAttatTgtaatatggaattataattcactttttctgtatttgcataaaatcacaataaaattttatttagtagtaataaaaaaagacaaataaaatcttttgacagtaacttagtaatattttttaatcatttctaatttttttatttgaatatatattgcttttcaaagatttatgaaggattatattaattcgaaaacatttctatttaggtttgaaatcgcgtgcttttttattgtcccctttgaaaaaaaaatatatataTACAAAccagtgaataagaaaAAATAAAATtaagaataaaataaaaaggattttttattttatg >ycf1.2 acaacgggagattagatctcatagagttcaattcccgttctcaacccatgaccaatatgaactcgaagtttccttcgtaacccccggaacttcttcgtagtggctccgttccatgcctaatttaatagggaacctcaaagcggctctatttcattatattccatccatatcccaattccattcatttaatatccctttggtgtcaTTGACAtaagagatgtcgtTTCTAGTCTatctctttctatttctatatATGGAAagttgcaaaatcatcaTATAATaatccaGAaattgaaatagaaaagaaaaaagggaggtttgtg >rbcL aataaaaaaaatatgttaaattttgttacgaattttttcgaatacagaaaaaatcttcgatagcaaattaatcggttaattcaataaaaagtgggagtaagcactcgatttcgttggtcccacccaagcggatgtggaattcaattttttattcattcaatgaaggaatagtcattttcaagctcaactaactgaaacctagttttaaaataaaaaatatatgaataaaaaaattttTTGCGGaaagtcttttatttTTTTATCATaataggaataggcaagcctttgttttatctagcgaattcgaaacggaactttagttatgattcattatttcgatctcattagccttttttttcgtattttcattttagcatatccggttatgcgtcccatttattcatccctttagcaacccccccttgtttttcattttcatggatgaattccgcatattgtcatatctaggatttacatatacaacagatattactgtcaagagtgattttattaatattttaattttaatattaaatatttggatttataaaaagtcaaagattcaaaacttgaaaaagaagtattaggTTGCGCtatacatatgaaagaataTACAATaatgAtgtatttggcgaatcaaatatcatggtctaataaagaataattctgattagttgataattttgtgaaagattcctgtgaaaaaggttaattaaatctattcctaaTTTATGtcgagtagaccttgttgttTTGTTTTATtgcaagaattctaaattcatgacttgtagggagggacttatg >ndhC ActaagaaatttattctaaaaaatcacattaaaatcaaaataattggataaatttttttacttttttttgtattctttatttctaacaggttacttttaattgctcggttcataaaaaaaatttccatatcataaaccataagtcctggggatcgttcagaataaaacggaaaatttcattttatttcaatggagccaatcactatctatcgatatatcgagatagatacttaatttataatttagaataaacctttttcttcattaattttcatagttgtaatttttttatatgaattttcctcgTTCACTagctacaatcaaaaaGTTCATAATactttctttttttttttgtatccccactcaatcttggttactttttttatcacacggccttgtttaaaaataaaaaaagaaatctaattaaattcaaccaaaattcaatctatctaatactaagtaagatgagtatggtaaagtcttactggattttttgatacgtcatcatttaaaaaacgaagagatttttcgaaaaatttttttaaacataaacagaaataaaaaaaattactagttattaatcagattaatattatattattatattagaaactattagtaatagaaacatggaactattaagtaataagtgtactgaaaataagaaatcaataaatcttaaaacgagacgtctaccacaacaaccaaacgaaaaaaaATGATTcgattaacctgaatTTTTGTTTTgactcaagagttctatatcccttgcccaatccactccgattggaattgactaagcgggtattttttccacattcataggagttcgtctatg >rps4 tttccatattttttcgttttttTTTACAtgatttttaatgtacTTTCAAAATcaaagaagattgaaaagacttctttgacctttttccaagagttaccactccatttatattatgtcatataaacttccatattaggaatatatattgggtaaaagagtttgatctttgcaaaattaatcaagaaaataaaggaaaatttttgtgatttagttgatttatatataTTGTATatacaataaaaaaaatctgTATATTgagagAatatatcttcttactctttgtattccaatagtggagtgtatttcacgtcatttatcattatcatttagttcagTTTTAAttttatttagttTTGTACAATttcaatcaaaaaaggagtctttatg

Figure 12: Presence of putative PEP-type promoters in 5’ regions of operons with altered expression in sig4.

5’ intergenic regions were searched for putative PEP-type promoters using BPROM software (www.softberry.com). Putative -35 regions are shown in capital letters, and -10 regions are underlined. Translational start sites are shown in bold. Previous experimentation has suggested transcriptional start sites (highlighted) and putative PEP promoters (in red) for ndhF (Favory et al., 2005), ycf1 (Swiatecka-Hagenbruch et al., 2007), rps4 (Swiatecka-Hagenbruch et al., 2007) and rbcL (Isono et al., 1997a, Gruissem and Zurawski, 1985).

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6.3.3 Making NDH: co-ordinated expression of nucleus-encoded NDH subunit

transcripts and SIG4

The NDH complex requires multiple proteins, both plastid- and nucleus-encoded,

and absence of just one of these may result in loss of complex formation and rapid

degradation of the remaining NDH subunit proteins. The absence of a nucleus-

encoded NDH protein (NDHL) in the sig4 mutant supports this requirement,

suggesting that in the absence of certain plastid NDH proteins or transcripts,

production of nuclear NDH complex protein subunits are either down-regulated, or

products are rapidly degraded. This suggests close coordination between production

of nuclear and plastid products and advocates a role for SIG4, a nucleus-encoded

gene involved in transcription of plastid genes encoding NDH subunits, in this

coordination.

6.3.3.1 SIG4 expression correlates with expression of multiple nucleus-encoded NDH

complex subunits

Co-expression analysis is becoming an increasingly important, and robust, tool for

predicting ‘guilt-by-association’ gene function (reviewed in Usadel et al. (2009)),

suggesting putatively co-regulated genes for a gene of interest. Five online data-

bases (ACT, ATTED-II, BAR, CressExpress and GeneCAT), were queried for the

top 50 correlates to SIG4 transcripts, and these correlating transcripts then ranked on

the basis of their presence in 5, 4 or 3 of the five examined data-bases (Table 14). As

previously described for other sigma factors, the transcripts correlating with SIG4

expression were primarily identified as plastid targeted, with many involved in

general plastid processes and stimulus response. However, the correlation profile of

SIG4 was unique in the dominance of transcripts with products involved in a single

primary process: of the 31 transcripts identified as correlates by at least 3 databases,

13 are identified as being involved in the formation of the plastid NDH complex.

This includes subunits of the NDH sub-complex, as well as products involved in

processing and formation of NDH, and represents a major proportion (38%) of the 34

known NDH nucleus-encoded subunits and protein factors. Many of the remaining

transcripts defined as SIG4 correlates have undefined, or poorly defined functions.


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Table 14: Transcripts showing expressions correlating with the expression of SIG4.

The top 50 correlates of SIG4 expression were obtained from five online co-expression databases; ACT, ATTED-II (ATTED), BAR Expression Angler (BAR), CressExpress (CRESSEx), and GeneCAT. Transcripts were ranked for their common presence in 5, 4, or 3 of the top-50 lists. The coefficient of determination (r2) is shown for each transcript as determined by individual databases, with transcript ranking shown in brackets. 13 of the SIG4 correlates are involved in NDH formation, shown in red. Additionally, several proteins of unknown function, but localised to the chloroplast (C) or chloroplast thylakoid membrane (CTM), were among SIG4 correlates.

AGI ACT ATTED-II BAR CRESSEx GENECAT GENE/FUNCTION

5 AT1G14150 0.85 (7) 0.84 (12) 0.84 (5) 0.84 (1) 0.91 (1) PNSL2

AT5G39210 0.89 (1) 0.87 (2) 0.87 (1) 0.78 (22) 0.88 (9) CRR7

AT5G58260 0.86 (4) 0.81 (27) 0.85 (3) 0.84 (2) 0.89 (4) NDHN

AT3G16250 0.87 (2) 0.84 (22) 0.85 (2) 0.80 (11) 0.89 (6) NDF4

AT1G70760 0.82 (19) 0.79 (50) 0.82 (7) 0.82 (6) 0.88 (11) CRR23

at2g01870 0.83 (13) 0.82 (3) 0.80 (19) 0.76 (45) 0.85 (45) UNKNOWN *CTM

4 AT1G27480 0.85 (8) 0.82 (9) 0.84 (6) 0.87 (18) ALPHA/BETA HYDROLASE

AT1G15980 0.81 (27) 0.81 (8) 0.82 (5) 0.89 (5) NDH48 AT2G39470 0.81 (29) 0.81 (10) 0.83 (3) 0.90 (3) PNSL1

AT5G20935 0.84 (11) 0.84 (1) 0.81 (11) 0.86 (27) CRR42

AT1G26230 0.86 (5) 0.82 (7) 0.78 (37) 0.77 (29) CPN60BETA4

AT5G52780 0.81 (38) 0.81 (6) 0.80 (24) 0.86 (21) UNKNOWN *CTM (DUF3464)

AT3G22210 0.82 (15) 0.81 (34) 0.80 (17) 0.86 (34) UNKNOWN ENDOMEMB.

At1g19150

0.80 (46) 0.78 (46) 0.79 (12) 0.91 (2) LHCA6

AT3G23700 0.80 (42) 0.80 (18) 0.82 (4) 0.85 (48) RNA BINDING COLD RESPONSE

AT5G45680 0.80 (46) 0.80 (27) 0.77 (42) 0.85 (47) FKBP13- PROTEIN FOLDING, C

3 AT1G23400 0.82 (16) 0.80 (4) 0.80 (16) GII INTRON SPLICING, C

At1g74880 0.81 (12) 0.79 (14) 0.88 (13) NDHO

At3g55630 0.87 (3) 0.71 (33) 0.81 (9) FPGS3

AT1G65230 0.81 (28) 0.81 (14) 0.89 (7) UNKNOWN, C

At3g01440 0.81 (36) 0.80 (17) 0.80 (22) PNSL3

AT2G05310 0.81 (34) 0.81 (15) 0.77 (30) UNKNOWN, C

At4g26530 0.77 (18) 0.77 (28) 0.86 (35) ALSOLASE, C

AT4G39710 0.81 (32) 0.80 (26) 0.86 (23) PNSL4

AT2G35370 0.82 (26) 0.81 (13) 0.76 (48) GDCH

AT1G73655 0.81 (31) 0.79 (15) 0.85 (43) FKBP17-3 PROTEIN FOLDING, C

At4g33470 0.81 (30) 0.78 (47) 0.88 (12) HDA14

At1g22630 0.77 (29) 0.77 (33) 0.86 (33) UNKNOWN, C

At3g01660 0.79 (10) 0.76 (46) 0.85 (40) METHYL-TRANSFERASE, U

At2g01590 0.80 (21) 0.77 (35) 0.85 (49) CRR33

AT1G04640 0.80 (43) 0.74 (39) 0.79 (31) LIP2, M


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6.3.3.2 Over-representation of consensus sequences in the 5’region of SIG4 and nucleus-

encoded NDH subunit genes suggests a putative mechanism for co-ordinated expression

Co-ordinated expression of SIG4 and NDH transcripts would require the presence of

common promoter regions. Known Arabidopsis promoter motifs were searched for in

the 1000 base pairs upstream of SIG4 and 32 nucleus-encoded NDH genes

(excluding At4g37925 and AT2G01918, not recognised) using the Arabidopsis

thaliana expression network analysis tool

(Athena, http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/home.pl; O'Connor

et al. (2005)), with no sequence found to be overrepresented. Analysis was also

undertaken using SIG4 and the 13 NDH transcripts showing high correlation of

expression with SIG4 (Table 14), with the same result. The presence of putative

‘unknown promoters’ was then investigated. SCOPE, an online de novo

computational motif discovery program (http://genie.dartmouth.edu/scope/;

(Chakravarty et al., 2007, Carlson et al., 2007)), was utilised for the identification of

degenerate, non-degenerate or bipartite motifs in the 5’regions of SIG4 and 34 genes

involved in NDH complex formation. A ‘control’ group was created including 19

nucleus-encoded genes with products involved in PSI or PSII formation, and a

further 24 nucleus-encoded plastid localised genes. These genes were taken from the

Chloroplast2010 list (http://plastid.msu.edu/about/gene_list.html) and localisation

checked using suba3 (http://suba.plantenergy.uwa.edu.au/). These latter genes were

included on the basis of having: a) plastid localisation according to SUBAcon; b)

both MS and GFP tagging experimental data indicating plastid localisation; c) single,

and not dual localisation. The list of control genes were: AT1G03475;

AT1G06680; AT1G08380; AT1G08490; AT1G12250; AT1G12520; AT1G13270;






AT4G02770; AT4G12800; AT4G21280; AT4G28750; AT5G64040; AT5G66570.

The NDH group of genes were interrogated for the presence of consensus sequences

on the plus or minus strand in the 5’ intergenic region (Table 15). The resulting ten

overrepresented motifs, reduced to include only those with significant values (-log of

http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/home.pl

http://genie.dartmouth.edu/scope/

http://plastid.msu.edu/about/gene_list.html

http://suba.plantenergy.uwa.edu.au/


102

expectation of finding pattern) greater than 10, were queried for representation in the

control group. Four motifs were found in the 5’ region of both SIG4 and (at least 3)

NDH genes. All four sequences showed more significant (significance value; sigV)

and abundant (frequency in group; freq.) representation in the NDH group than the

control group, with only one motif, dkggvc, showing any significance in the control

group (although even here the sigV 5.6 was less than 10, and much lower than that

for the NDH group of 16.3).

Two of these sequences; ttwaaannsnttdw and aawyyttt together account for 22 of the

34 NDH genes queried (~65%). Interestingly, the remaining genes (AT1G11290,

AT1G14150, AT1G18730, AT1G19150, AT2G01918, AT2G39470, AT3G15840,

AT3G46790, AT4G37925, AT5G20935, AT5G21430, AT5G58260) had particularly

short intergenic regions, and all but two contained single or multiple copies of the

motif dkggvc. As such, all but two (94%) of genes contain at least one of three

putative promoter regions in their 5’ intergenic region, all three of which are also

found in the 5’ intergenic region of the SIG4 gene. However, visual analysis of the

positioning of these putative promoters did not reveal any patterns such as distance

between motifs and start sites, presence on either the plus or minus strand, or

relationship between each motif. Furthermore, no pattern was found whereby the 13

NDH transcripts showing specific correlation with SIG4 transcription contained

certain motifs in the genomic 5’ region. When these correlates were analysed

separately, the consensus motif ggnccnd was found to be overrepresented, but was

also overrepresented in the control group (data not shown). The two genes that did

not contain any of the three putative promoter sequences were AT2G39470

(PNSL1), a PsbP-like protein involved in formation of the luminal NDH

subcomplex, and AT4G37925 (NDHM), involved in A sub-complex formation. The

intergenic regions, <200 and <300 bp respectively, did not contain any of the NDH

overrepresented motifs. The possibility of these motifs existing in upstream coding

sequences was investigated, with the presence of the sequences ttwaaannsnttdw,

aawyyttt, and dkggvc searched in the region 1000 bp 5’ of the AT2G39470 and

AT4G37925 initiation codons. AT2G39470 contained a aawyyttt motif (-794 to -

801) and two dkggvc motifs (-766 to -771 -858 to -863, while AT4G37925 was

found to contain a ttwaaannsnttdw motif (-975 to -962), although it is noted that

these motifs were situated well into the coding region of upstream genes.

Table 15: Over-representation of motifs in 5’ regions of nucleus-encoded NDH genes and SIG4.

SCOPE, an online de novo computational motif discovery program (http://genie.dartmouth.edu/scope/; Carlson et al. (2007), Chakravarty et al. (2007)), was utilised to find motifs overrepresented in a group containing the 34 nuclear-encoded NDH genes, and Sig4 (NDH GROUP). Overrepresented motifs were then analysed for interrogation in a control group, consisting of 43 genes with plastid-targeted products. Count, significance value (SIGV) and frequency (FREQ.) of motif is shown for both groups. SIG4 is indicated in red.

Motif NDH GROUP CONTROL GROUP Included in

COUNT SIGV FREQ. COUNT SIGV FREQ.

ttwaaannsnttdw 65 56.9 0.286 5 -22.5 0.116 AT1G59720; AT1G64770; AT1G70760; AT2G47910; AT4G09350;AT4G24770; AT4G39710; AT5G13120; AT5G52100; AT5G13730

aawyyttt 110 33.6 0.657 145 -15.5 0.651 AT1G15980; AT1G45474; AT1G55370; AT1G59720; AT1G64770;AT1G70760; AT1G74880; AT2G01590; AT2G45350; AT2G47910;AT3G01440; AT3G16250; AT4G09350; AT4G23890; AT4G24770;AT4G31850; AT4G39710; AT5G13120; AT5G39210; AT5G43750;AT5G52100; AT5G55740; AT5G13730

aaatchhhnrwrdvhctt 16 19.5 0.057 0 -34.8 0 AT4G09350; AT5G43750

aaggghhndhaaa 20 17.7 0.114 3 -22.5 0.047 AT1G70760; AT2G45350; AT4G09350; AT5G13730

dkggvc 125 17.3 0.857 286 5.6 0.814 AT1G11290; AT1G14150; AT1G15980; AT1G18730; AT1G19150;AT1G45474; AT1G55370; AT1G59720; AT1G64770; AT1G70760;AT2G01590; AT2G01918; AT2G45350; AT2G47910; AT3G01440;AT3G15840; AT3G16250; AT3G46790; AT4G09350; AT4G23890;AT4G24770; AT4G31850; AT4G39710; AT5G13120; AT5G21430;AT5G39210; AT5G43750; AT5G52100; AT5G58260; AT5G13730

aawkccc 32 15 0.429 21 -14 0.302 AT1G18730; AT1G19150; AT1G45474; AT1G55370; AT1G59720;AT1G70760; AT3G15840; AT3G46790; AT4G09350; AT4G23890;AT4G37925; AT5G13120; AT5G39210; AT5G52100; AT5G58260

cnnaaccga 17 14.9 0.286 13 -8.7 0.233 AT1G11290; AT1G19150; AT1G45474; AT1G64770; AT1G70760;AT3G16250; AT4G09350; AT4G24770; AT5G20935; AT5G55740

aaadhcctt 24 14.2 0.086 10 -16.9 0.186 AT3G15840; AT4G09350; AT5G39210

tcchnnbtaaa 19 14.1 0.2 4 -16.9 0.093 AT1G59720; AT1G70760; AT2G47910; AT4G09350; AT4G23890;AT5G43750; AT5G52100

cctywdhaaatc 11 10.2 0.086 0 -24.2 0 AT1G18730; AT4G09350; AT4G37925

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6.3.4 Turning on NDH: what induces SIG4 and NDH?

Combined analysis of microarray experimental data, measuring transcript

abundances across a wide range of conditions, including tissue type, developmental

stage, and various stress/ stimuli-response situations, showed strong correlation

between SIG4 expression and that of nuclear NDH genes. CET is primarily important

under conditions of photo-oxidative stress, when it has been shown to be up-

regulated. The correlation of NDH expression with SIG4, and the role of this factor

in transcription of plastid-encoded NDH subunits, suggests a mechanism whereby

such stresses may induce expression of both nucleus-encoded NDH genes, and SIG4,

the latter of which in turn activates plastid-encoded NDH gene transcription.

Interestingly, previous short-term (3 hour) high light (1000 μE) experiments did not

markedly induce SIG4 or NDH accumulation, but did result in increased

accumulation of the transcripts of the responsive factor SIG5 (viewed in

Genevestigator, data not shown). Higher light conditions, 1600-1800 μE for 3 or 6

hours, resulted in a mild non-dose-dependent induction of SIG4 (1.59, 1.51 times the

control, respectively), but no constant pattern of accumulation across the NDH

transcripts examined (AT1g14150, At5g39210, At5g58260, At3g16250, At1g15980,

At2g39470, At5g20935, At1g26230). Similarly, treatment of the Col-0 wild-type

with 20 mM hydrogen peroxide, for 1 hour did not result in an induction of transcript

accumulation for SIG4 or NDH transcripts.

Interestingly, recent reports indicate that NDH up-regulation under stress occurs via

a two-step mechanism, the first involving post-transcriptional processes, and the

second, for which there is a time-lag, involving increased transcriptional activity

(Casano et al., 2001). As such, I chose long-term (up to a week) analysis of NDH

accumulation under high light conditions. Moreover, recent investigations have

demonstrated the importance of PGR5 under fluctuating light conditions (Suorsa et

al., 2012). Growth under fluctuating high light, as opposed to continuous high light,

provides the plant with high light stimuli while minimising general damage to the

plant and associated effects. Furthermore, fluctuating light is likely to be more

accurately representative of natural growth conditions.

Following growth of arabidopsis Col-0 for 7 days under long day conditions (~120-

200 μE during the 16 hour photoperiod), plants were grown for a further 7 days

under a) continuous light conditions (as for long day, but with a continuous


105

photoperiod) or; b) continuous fluctuating high-light conditions (FHL: 3 mins at

~700 μE followed by 7 mins ~120-200 μE, repeated continuously). Plants grown

under FHL conditions did not exhibit a particularly strong phenotype indicating

reduced fitness, relative to control plants (not shown). Two biological replicates

representing multiple individual plants grown under control and FHL conditions

were harvested immediately prior to the start of the stress period (time=0 h) and at

144 hours, with single samples also taken at 24 and 72 hours following stress

induction. Total RNA was extracted, and cDNA synthesised using oligo-dT or

random primers for assessing nuclear or plastid genes respectively, with qPCR using

the cDNA generated undertaken in technical triplicate. Plastid and nuclear transcript

abundances were analysed following normalisation to housekeeping genes that

showed robust accumulation under stress conditions.

6.3.5.1 A mild fluctuating high light stress induces gradual accumulation of SIG4, and of

nucleus-encoded NDH subunit transcripts

SIG4 was increased under FHL conditions, relative to control conditions (Figure 14).

Accumulation was 2.3 times greater following FHL treatment (t=144 h) than

immediately prior to treatment (t=0). Interestingly, SIG4 also accumulated under

continuous light conditions, although this increase was less pronounced than under

FHL conditions (1.7 times accumulation at t=144, relative to t=0: data not shown).

SIG4 transcript accumulation seems to occur fairly slowly, but in a remarkably

steady manner. Nucleus-encoded NDH subunit transcripts NDH48 (AT1G15980),

NDH45 (AT1G64770), NDHL (AT1G70760), NDHO (AT1G74880) and NDF4

(AT3G16250) were also induced under FHL treatment, although, once again, a

(milder) induction was also seen under continuous light conditions, for all but

NDHO. Interestingly, unlike SIG4, accumulation of NDH complex transcripts

initially seemed to decrease slightly between 0 and 24 or 0 and 72 hours, before

accumulating (Figure 14).

Accumulation of all six sigma factor transcripts was also quantified. Relative to

continuous light conditions, accumulation of SIG4 and SIG5 was seen under FHL

conditions. Interestingly, while SIG4 began to accumulate almost immediately,

although gradually, SIG5 levels did not alter until after 72 hours treatment, after

which a rapid increase was noted. Transcript levels of the other sigma factors were


106

0.5

1

2

0 20 40 60 80 100 120 140 160

NDH48

NDH45

NDHL

NDHO

NDF4

SIG4

0.5

1

2

0 20 40 60 80 100 120 140 160

SIG1

SIG2

SIG3

SIG4

SIG5

SIG6

A

B

Figure 13: Induction of sigma factor transcript accumulation, and of accumulation of nucleus-encoded NDH transcripts under fluctuating high light.

Two biological replicates were taken at t=0 and t=144, with a single replicate taken at t=24 and t=72. Data were normalised to housekeeping genes Rpl5, Por and Ubc and are represented here as values under fluctuating high light (FHL) conditions, relative to values under continuous light conditions. SIG4 accumulation is shown against nuclear NDH transcript accumulation (A) and accumulation of other sigma transcripts (B)

Time following switch from long-day conditions (h)

Tran

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HL/

cont

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107

not greatly altered following 144 hours treatments, although SIG1 accumulation

decreased rapidly between 0 and 24 hours treatment, before slowly recovering to

standard levels.

6.3.5.2 Induction of SIG4 could not be linked to induction of plastid-encoded NDH

transcripts

Patterns of plastid-encoded NDH transcript accumulations were similar between

FHL and continuous light conditions, although unexpectedly, changes were less

pronounced under FHL conditions (Figure 15). While ndhF is induced under FHL

treatment following 144 hours relative to FHL samples prior to treatment, this effect

is not seen following standardisation to the continuous light conditions.



The transcript profile analysis undertaken here suggests a role for SIG4 in

transcription not only of ndhF (previously described; Favory et al. (2005)) but of

multiple plastid-encoded NDH subunit genes (Chapter 5), suggesting sigma factor

control of a physiologically coherent gene group. In light of the particular responsive

role of NDH, it was hypothesised that SIG4 may be involved in coordination of a

response-mediated up-regulation of NDH subunit transcription and thus, activity.

Interestingly, response-mediated control of coherent gene expression has been

suggested, to some degree, for SIG1, which is believed to control PSI stoichiometry

by altered transcriptional activity on PSI and PSII under different oxidative

conditions (Shimizu et al., 2010). However, such a mechanism has not previously

been investigated for SIG4 activity, promoting this factor as an interesting case

study.

Splicing analysis undertaken here supports that the diminution of NDH subunit

transcripts in the sig4 mutant are transcriptional defects, with investigation of PEP-

type promoters suggesting a mechanism for promoter recognition, however,

transcriptional activity cannot be concluded from accumulation profiles in the

absence of additional mRNA processing and degradation information. As such,

future investigations should include more specific measurements of transcription

rates, such as a plastid transcription run-on assay. Although multiple putative PEP-


108

0.25

0.5

1

2

4

0 50 100 150 200

ndhH-A-I-G-E-D

ndhB

ndhC-(K)-J

ndhF

0.25

0.5

1

2

4

0 50 100 150 200

ndhH-A-I-G-E-D

ndhB

ndhC-(K)-J

ndhF

A

B

Time following switch from long-day conditions (h)

Tran

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t acc

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n (F

HL/

cont

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us li

ght),

log 2

Figure 14: Accumulation of plastid NDH transcripts under fluctuating high light and continuous light conditions.

Two biological replicates were taken at t=0 and t=144, with a single replicate taken at t=24 and t=72. Data were normalised to housekeeping genes Rpl5, Por and Ubc and are represented here as values under continuous light conditions (A) and fluctuating high light (FHL) conditions (B). Data points represent the average of values for transcripts within putatively defined operons (ndhK not measured).


109

type promoters were found upstream of the three operons showing diminished

accumulation in sig4, they did not bear sequence similarity to each other. Current

poor understanding of sigma factor promoter sequence recognition makes it difficult

to define promoters by in silico means, and prompts the need for more specific

experimental testing. Ultimately, any variations in the sig4 mutant may result from

defects not-specific to the T-DNA insertion in the SIG4 gene, and must be confirmed

by generation of complemented lines and their subsequent analysis. It should be

noted, however, that a previous study has demonstrated restored accumulation of

ndhF, NDHH protein and NDH complex activity by 35S-SIG4 complementation in

the Wassilewskija mutant sig4-1 (Favory et al., 2005).

This study has generally been limited to analysis of transcript accumulation, as

opposed to analyses of protein accumulation or activity. While a previous study has

already indicated loss of a plastid-encoded NDH protein (NDHH), and almost

complete loss of NDH activity (Favory et al., 2005) further studies should be

undertaken involving more detailed analysis of NDH complex accumulation and

composition by two-dimensional blue-native polyacrylamide gel electrophoresis

(BN-PAGE), and the particular accumulation of different NDH subunit proteins

when induced by FHL. Furthermore, sigma factor proteins have been shown to

accumulate at times independently of transcript abundance and proteins may be post-

translationally controlled by phosphorylation suggesting the need for future analyses

of not only NDH, but also SIG4 at the protein level. As such, the results obtained in

this chapter are somewhat preliminary, yet begin to present a case for a dominant

role of SIG4 in NDH transcription, and strongly suggests that this role be subject to

further investigation.


Plastid transcript profiles undertaken here indicated that SIG4 activity extends

beyond specific action on the promoter of ndhF (defined previously: Favory et al.

(2005)), to include regulation of ndhH-A-I-G-E-D by means of the ycf1.2 operons.

While SIG2 and SIG3 may share activity on ndhF and ycf1.2 operons, respectively,

analysis of transcripts in the context of physiologically coherent gene groups suggest

that SIG4 alone is the primary regulator of the plastid encoded NDH genes. This is

consistent with the previously published observation, that NDHH proteins

accumulates to less than 10% of wild-type levels in a sig4 mutant (Favory et al.,


110

2005), which suggests that loss of SIG4 activity cannot be easily rescued by activity

of another sigma factor. Although measurements of transcription rate, and analysis of

SIG4 complemented lines is required to assert the changes as truly resultant from

transcriptional activity of SIG4 on NDH gene promoters, my work showed that the

changes seen are not due to splicing defects, and demonstrated a mechanism for

PEP-SIG4 activity through the identification of multiple PEP-type promoters 5’ of

genes showing changed accumulation in sig4. Interestingly, none of the putative

promoters defined for ndhF and ycf1.2. (6.3.2, and previously: Favory et al. (2005),

Swiatecka-Hagenbruch et al. (2007)) bear similarity to each other in either sequence

or spacing, and it is proposed that differences between promoters may result in

different efficiencies of SIG4 recognition, which may be reflected in the varying

levels that accumulation was affected for transcript encoded in these operons in sig4.

In the future, promoter recognition could best be investigated by use of in vitro

binding assays.

The T-DNA insertion mutant sig4-1 was previously identified as having lower

accumulation of the NDHH protein, attributed to degradation in the absence of NDH

complex formation, in turn driven by loss of ndhF (Favory et al., 2005). This study

suggests loss of NDHH may be more direct: resulting from lost SIG4 activity on

ycf1.2 (see 5.3.3). Future experimentation involving more extensive examination of

protein subunits by western blotting techniques and two-dimensional BN-PAGE

could confirm relative abundances of the NDH complex, and individual NDH

proteins in this mutant.

Guilt-by-association analysis, undertaken here for the first time in defining sigma

factor function, showed particularly high correlation between expression of SIG4 and

nucleus-encoded NDH transcripts: transcripts of 13 of the 24 identified NDH

nucleus-encoded subunits and protein factors (38 %) where found in the top 50

correlates of 5, 4 or 3 of the 5 queried co-expression databases. Correlation with

NDH transcripts was not found for any of the other sigma factors. Furthermore, no

other sigma factor showed a similar level of correlation with a specific

physiologically coherent gene group. This is strong supporting evidence for the

highly specific role of SIG4 in NDH transcript regulation, and further suggests a

mechanism whereby SIG4 and nucleus-encoded NDHs are expressed in a

coordinated manner. Such coordination may involve one or more of the three


111

consensus motifs, found here to be specifically over-represented in 5’ regions of

SIG4, and NDH genes, however, in the context of poor understanding of gene

promoters these motifs cannot be defined as promoters until extensive

experimentation (e.g. GUS-reporter analysis with native and mutated motifs) has

been undertaken.

Furthermore, SIG4 correlates included multiple transcripts with chloroplast-targeted

products of currently undefined function. Future investigations should include

definition of the function of these products, with particular focus on links to NDH

processing, assembly and stability, as it is possible that the set of factors involved in

such processes is not yet complete.

Combined analysis of microarray experimental data demonstrated high correlation

between SIG4 and nucleus-encoded NDH subunit expression, however, while these

transcripts showed similar expression patterns across developmental- and tissue- type

contexts (data not shown), it was not immediately apparent from microarray data if

any specific conditions induce the expression of both. In light of previous

experimentation, which demonstrated sensitivity of ndh mutants to oxidative stress

conditions (Suorsa et al., 2012, Jin et al., 2009, Munekage et al., 2002, Miyake et al.,

2004, Horvath et al., 2000, Endo et al., 1999), it was hypothesised that NDH may be

up-regulated in these conditions. Although fluctuating high light treatment seemed to

induce SIG4 and nucleus-encoded NDHs, any induction was mild, and no effect was

seen on plastid transcript pools, suggesting a need for further optimisation of

experimental conditions.

Chapter 7: General Discussion

112

CHAPTER 7

General discussion


113

7.1 Models for sigma factor function

The primary aim of this project involved furthering the current understanding of the

function of sigma factor family members in plants. The work was approached in the

context of a previous statement (Yao et al., 2003) suggesting, where multiple sigma

factors are found within one species, several models for function: that factors exhibit

specific contextual expression profiles; that factors recognise distinct promoter sets;

and that factors are functionally redundant.

Are multiple factors (consistently) present within a species? A comprehensive in

silico analysis was undertaken to identify the maintenance of and relationship

between sigma-like factors across 31 green plant species representing 11

phylogenetically distinct clades, and indicated diversification of sigma factors,

followed by strong maintenance of (approximately) six factors across dicotyledonous

species.

Do sigma factors in a single species exhibit specific expression profiles?

Visualisation of arabidopsis sigma factor expression across hundreds of experimental

contexts indicated some specificity between contextual expression of sigma factor

family members, with SIG5 implicated as unique compared to other factors.

Although sigma activity may be altered by translational and post-translational

processes (Schweer et al., 2010), the interrogation of sigma factor expression

undertaken here generally suggests sigma factors accumulate in a manner correlating

with chloroplast gene expression requirements, with this research' novel ‘guilt-by-

association’ analysis supporting function of sigma factors in chloroplast biogenesis

and maintenance.

Do sigma factors recognise distinct subsets of plastid gene promoters (or are they

functionally redundant)? This study defined plastid mRNA accumulation profiles for

all six arabidopsis single sigma factor mutants, grown in parallel, a significant novel

contribution to the field, with data analysed in both transcript and operon contexts.

No two mutants were found to have identical transcript profiles, yet many transcripts

appear to reflect activity by multiple factors.


114

7.2 The roles and responses of (arabidopsis) sigma factors

7.2.1 The roles and responses of SIG1

The primary role of SIG1 is believed to be in the regulation of photosystem

transcripts. Consistent with this role, previous studies (Kanamaru et al., 1999, Privat

et al., 2002) and microarray analysis undertaken here (section 4.5.3), imply rapid

accumulation of SIG1 in germinating seed and consistently high expression across

green tissues, throughout the life of the plant. Furthermore, my ‘guilt-by-association’

analyses indicate high correlation between SIG1 and transcripts with products

involved in photosystem assembly and function. In the sig1 mutant, specific decrease

were seen for multiple PSII transcripts (4.3.6), with analysis of transcripts in the

context of physically coherent gene groups (6.3.1) suggesting additional loss of SIG1

activity on PSI promoters. These findings are consistent with research indicating

maintenance of PS stoichiometry by activity of SIG1 (Shimizu et al., 2010), but

extend the function of SIG1 to include putative transcriptional regulation not only of

psaA and psbB, but of multiple PSII, and potentially PSI genes.

This study demonstrated the presence of SIG1-like proteins in both V. carterii and C.

reihnardtii, with general maintenance across all 31 plant species (3.3.1), indicating

early appearance of this factor. This is consistent with the theory that SIG2, SIG3,

SIG4 and SIG6 appeared by diversification of SIG1 (Lysenko, 2006). In the light of

the high maintenance of functional redundancy of duplicated genes (Dean et al.,

2008), it is probable that SIG1 maintains activity on multiple promoters, yet my

study suggested almost complete redundancy between SIG1 and SIG2 on the basis of

mRNA profiles in mutants (5.3.2 and 5.3.3) as well as more specific redundancy with

other factors: psaA, which may be transcribed by SIG1-PEP (Privat et al., 2002), was

found in my experiments to have decreased accumulation in sig5 and sig6. As such, I

propose that SIG1 may have lost its role as a primary sigma factor following

increasing redundancy with factor diversification. It is possible that the greater

promoter efficiency of other factors (previously described: Privat et al. (2002)) may

also have contributed to loss of primacy. In the context of this work, and recent

studies suggesting regulation of SIG1 activity under varying redox conditions, which

in turn leads to PS stoichiometry regulation (Shimizu et al., 2010), it is proposed that

SIG1 is an alternative, responsive sigma factor.


115

7.2.2 The roles and responses of SIG2 and SIG6

Current plastid mRNA analysis confirmed the role of these factors in transcription of

major photosynthetic groups (5.3.2 and 5.3.3). Evolutionarily speaking, SIG2 and

SIG6 are present and maintained in embryophytes (3.3.1). Previous analysis has

proposed development of SIG6 by diversification of SIG2 (Lysenko, 2006), which

likely explains the high, but not complete overlap in transcript profiles identified here

(5.3.4). Interestingly, my comparative analysis suggests that SIG6 may have a more

dominant role than SIG2, at least at this life stage (5.3.4). Previous studies have

attributed the pale, retarded phenotype of mutants to activity of both SIG2 and SIG6

on trnE promoters (Nagashima et al., 2004a, Ishizaki et al., 2005), not measured

here. Future studies should involve comparative analysis of SIG2 and SIG6 activity

on trnE promoters across development of the plant, to assess if this factor alone can

account for the maintenance of the pale phenotype seen in sig2, but not in sig6

(observed in previous reports and 5.3.1).

Interestingly, a recent study suggests a role for both SIG2 and SIG6, but not other

sigma factors, in retrograde signalling (Woodson et al., 2012), and indeed, guilt-by-

association analysis (4.3.6) found the presence of a transcript whose product was

implicated in retrograde signalling correlated with SIG2 expression (as well as the

correlation of two GUN protein transcripts with SIG1, but not with SIG6). The

majority of characterised GUN proteins involved in retrograde signalling have a

‘double-life’, involved also in chloroplast biosynthetic processes, and it seems

possible that this signalling role confirms the importance of SIG2 and SIG6 as major

factors during chloroplast biogenesis.


SIG3 has been defined as ‘rather functionally redundant’ (Schweer, 2010), and

indeed, in this work, mutant analysis implicated activity on only one mRNA

transcript (5.3.4) or a single operon (5.3.2). SIG3, with SIG4 and SIG6, is believed to

have arisen from diversification of SIG2. Some functional overlap has been noted

between these factors: SIG4 and SIG3 are implicated in ycf2.1 promoter activity on

the basis of mutant studies (5.3.4), and SIG1, SIG2 and SIG3 have demonstrated in

vitro activity on rbcL and psbA (Privat et al., 2002). The fact that rbcL and psaA did

not show low accumulation in sig3 may suggest the functional redundancy of sigma

factors (SIG5 and SIG6 also have proposed psaA activity), and possibly low


116

accumulation or weak activity of SIG3. SIG3 is unique among factors in that its

localisation to the chloroplast membrane is required for activity, and it is believed to

accumulate gradually, with predominant activity in true leaves, as opposed to

cotyledons (Privat et al., 2002). Microarray analysis also suggests accumulation in

non-photosynthetic tissues (4.3.5). As such, it is proposed that SIG3 is an alternative

factor with activity specific to life stages or tissues not commonly investigated in

sigma factor analysis.


The role of SIG4 was discussed in detail in Chapter 7. Briefly, the work undertaken

here extends SIG4 activity to include transcription not only of ndhF (Favory et al.,

2005), but also ndhH-A-I-G-E-D (ycf1.2 operon: 5.3.3). Interestingly, ‘guilt-by-

association’ analysis suggested a strong, previously undefined coordination between

SIG4 and nuclear NDH transcript expression, further supporting a specific role for

this sigma factor in NDH complex regulation. Conditions that induce accumulation

of NDH and SIG4 were not obvious from microarray data, and while preliminary

experiments suggest possible SIG4 and NDH transcript accumulation under

fluctuating high light, this was mild, and no resultant activation of plastid-encoded

NDH transcription was not seen, suggesting the need for further investigation.

While this case study focused on the role of NDH in photo-protection, and response-

based regulation of NDH and SIG4, it is noted that NDH also has a role in altering

cellular ATP concentrations, and has been implicated in differentiation of bundle-

sheath and mesophyll cells in C4 plants (Takabayashi et al., 2005, Munekage et al.,

2010). Recently, Dr Kaisa Kajala (CPEB) demonstrated high relative abundance of

multiple NDH transcripts and also of SIG4, but not SIG1, SIG2 and SIG6 in

mesophyll, as compared with bundle sheath cells of the C4 plant Cleome gynandra

(Dr Kaisa Kajala, pers. comm.). As such, it is possible that SIG4 has an additional

role in driving cellular differentiation in C4 plants. However, my analyses identified

an absence of SIG4-like proteins in three C4 grass plants, S. bicolor, Z. mays and

S. italica, despite similar cell-specific NDH differentiation identified for both Z.

mays (Darie et al., 2006) and S. bicolor (Kubicki et al., 1996). As such, it is possible

that another sigma factor drives this differentiation in these species. A possible

candidate is SIG3, from which SIG4 probably arose (Lysenko, 2006), and which also

was found to have putative activity on the ycf1.2 operon (5.3.4). Also from an


117

evolutionary standpoint, certain species seem to have lost the NDH complex

completely (Wakasugi et al., 1994), and it is recommended that future work

investigates the presence or absence of SIG4-like proteins in these species, and,

where present, the possibility of an alternative role for SIG4.

In the light of the work undertaken here, it is proposed that the primary role of SIG4

is in the highly specific nuclear/plastid coordination of NDH complex accumulation.


SIG5 seems unique among plant sigma factors. Phylogenetic analysis conducted here

indicated appearance very early in plant history (presence in C. reinhardtii; 3.3.1),

and it has been suggested that this factor either arose from an alternative bacterial

sigma factor (not the primary factor from which other family members arose), or that

early appearance from the primary factor was followed by massive diversification

(Fujiwara et al., 2000, Lysenko, 2006). Although my studies suggest that all sigma

factors display some level of responsiveness, SIG5 transcript levels were shown to be

the most highly responsive among all sigma factors to multiple stimuli (4.3.5).

SIG5 has previously been suggested to localise to the mitochondria (Yao et al.,

2003), although there is no proposed role for sigma factors within this organelle.

Although transcript accumulation in flowers was not noted here (4.3.5), SIG5

expression was found in cauline leaf and sepal tissues, and expression was found to

peak at the stage of young flower development (4.3.5). Interestingly, and unlike other

sigma factors, SIG5 expression correlated with multiple transcripts with a defined

role in vegetative to reproductive transitioning, and also in circadian rhythms,

including the flowering-time gene COL1(4.3.6). Since submitting this thesis for

examination, it has become clear through the work of another group, that SIG5 is in

fact involved in the control of circadian rhythms of certain plastid transcripts

(Noordally et al., 2013).

At a molecular level, SIG5 has putative activity on the promoters of ycf3-psaA-psaB-

rps14, and psbD-psbC-psbZ,(5.3.2 and 5.3.3) with regulation of the latter previously

suggested to occur via the blue-light-responsive promoter (Nagashima et al., 2004b,

Hoffer and Christopher, 1997), and SIG5 protein shown to accumulate specifically

under blue light (Tsunoyama et al., 2004). It is interesting to note that blue light has

previously been associated with induction of flowering (Eskins, 1992). Nonetheless,


118

a flowering phenotype was not evident in sig5, and while SIG5 can currently be

defined as a responsive sigma factor, any definition of putative function outside of

plastid gene expression requires further analysis.

7.2 Sigma factor family members - breaking down complex interactions

mRNA analysis from parallel experiments suggested overlapping transcriptional

activity of sigma factors (5.3.4), consistent both with previous reports (e.g. Privat et

al. (2002)) and with the defined maintenance of functional redundancy where genes

have arisen by duplication (Dean et al., 2008). The ability for one sigma factor to

complement or rescue the activity of another is of clear evolutionary advantage to the

plant, yet leads to difficulty in breaking down the complex functions and interactions

of each factor. Here, pairwise comparisons of sigma factor family members were

made using data obtained from mRNA analysis (5.3.2 and 5.3.3), microarray data

mining (4.3) and sigma factor sequences (a possible indirect indicator of function)

These comparisons (Table 16) ratified family member complexity, and further

reveals particular roles of factors: both as individuals and in the context of the 5 other

factors. For example, while SIG2 and SIG6 show high functional correlation, with

transcripts accumulating in similarly across all conditions (tissue, abiotic, biotic,

hormone and light), the relationship between SIG4 and SIG6 is particularly

differentiated by a disparate accumulation of relative transcripts in response to

abiotic factors. Similarly, SIG3 and SIG4 generally show very high functional

correlation, and on the basis of mRNA profiling, seem to impact the accumulation of

plastid mRNA in a similar manner, but are somewhat differentiated in their tissue-

specific accumulation of their transcripts (supporting previous observations: 7.2.3),

as well as response to abiotic factors. While SIG1 and SIG5 show a very low

sequence identity and low functional correlation, their transcripts accumulate in a

similar way under various abiotic and biotic stimuli (Table 16): which is perhaps

unsurprising considering the defined involvement of both factors in PSII subunit

accumulation (7.2.1 and 7.2.5).

Single mutants have an important role in determining protein function, and it is

unsurprising that plant sigma factor analyses have almost entirely involved

characterisation of single sigma factor mutants. Is this method sufficient?

Sigma factor pairs

Sequence data mRNA profiling Microarray data

Genomic CDS Protein Transcript CorCoEf

Operon CorCoEf PCC MR

(all) MR

(tissue) MR

(abiotic) MR

(biotic) MR

(hormone) MR

(light) SIG2 SIG6 56 56 29 0.83 0.79 0.791 36.4 142.5 164.5 79 76 200.6 SIG4 SIG6 63 60 28 0.03 0.08 0.79 66.6 144.5 2321.6 138 375.4 274.3 SIG3 SIG4 63 58 23 0.50 0.68 0.758 93 534 731.7 49.8 261.3 372.5 SIG2 SIG4 69 62 29 0.08 0.13 0.737 105.5 182.3 813.4 791.6 201.4 450.3 SIG3 SIG6 51 50 21 0.04 0.17 0.766 184.8 425.8 2115.8 194.4 1770 400.6 SIG1 SIG2 55 56 25 0.56 0.64 0.79 198 169.6 2358.5 1405.3 418.1 32.1 SIG2 SIG3 55 55 24 0.03 0.00 0.604 226.1 398.8 363.1 1489.1 520.4 582 SIG1 SIG6 53 56 21 0.37 0.33 0.662 354.6 500.1 1178.2 1825.5 1160.8 156.8 SIG1 SIG3 51 55 12 0.16 0.07 0.597 548.2 721.2 4216.7 2030.8 803.8 607.9 SIG1 SIG4 64 57 26 0.10 0.26 0.472 850.6 311.2 19781.4 6429.5 1897.2 759.8 SIG1 SIG5 55 55 19 0.41 0.39 0.53 894.5 5111.8 140.8 248.2 7724.8 2437.7 SIG3 SIG5 56 55 15 0.20 0.04 0.41 4255.1 4979.4 9464 11580.7 4222.7 1624.4 SIG2 SIG5 58 56 22 0.31 0.27 0.285 11484.3 10127.1 17995.8 16005.5 18114.3 3894.4 SIG5 SIG6 53 54 22 0.27 0.21 0.358 14069.6 14106.9 10679.8 19371.3 21787 2326 SIG4 SIG5 61 59 21 0.29 0.26 0.114 17333.1 9487.6 22554.2 20965.2 12640.8 5452.6

Table 16: Relationships between sigma factors.

Sequence similarities for genomic, coding (CDS) and protein sequences are defined by CLUSTAL W pairwise score, representing the number of identities between the two sequences, divided by the alignment length, represented as a percentage. Transcript and Operon correlation coefficients (CorCoEf) are calculated from mRNA profiles (Chapter 5), using Microsoft Excel software. Pearson correlation coefficient (PCC) calculated using ACT (http://www.arabidopsis.leeds.ac.uk/act) software, and mutual rank (MR), calculated using ATTED-II EDGE ANNOTATION (http://atted.jp/). MR is shown for grouped categories of data: tissue, abiotic, biotic, hormone and light related. Column-wise formatting shows values indicating greatest pairwise similarity in red and least similarity in green.

http://www.arabidopsis.leeds.ac.uk/act

http://atted.jp/


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Comparative analysis of sigma factor single mutant mRNA transcript profile may

indicate not: overlap of sigma factor activity on gene promoters (5.3.4) may allow (at

least partial) ‘rescue’ of transcript pools by complementary factors in the absence of

a single family member. This would result in a milder (physical and molecular)

phenotype than expected in the absence of redundancy, and poor assignment of

sigma factor function (high ‘false-negative’ rates). To begin to address this issue, and

its potential amelioration, single mutants were crossed with each other with resultant

offspring allowed to self-fertilize, producing T2 generation progeny putatively

containing a proportion (~1/16) of homozygous double mutants. Seedlings grown on

sterile media for about 1 week were visually screened for plants displaying a severe

phenotype (greater than individual mutants), with particular focus on growth

retardation and deficient greening. Two T2 generation populations, sig2sig6 and

sig5sig3, were specifically identified as containing a proportion of seedlings

(putative double mutants) bearing a white, growth retarded phenotype, which, despite

growth for approximately 2 months, did not reach reproductive maturity (Figure 16).

Furthermore, several other populations contained plants with defects typically

associated with reduced chloroplast health, for example the presence of physically

dwarfed or retarded plants in the sig5sig1 T2 population and the presence of plants

with extremely retarded development and bleached cotyledons in the sig4sig2 T2

population (Figure 16).

These investigations are very much preliminary: putative double mutants were

neither genotyped to confirm homozygosity, nor where mRNA transcript profiles

undertake, however they do promote double mutants as an interesting mechanism for

future analysis of sigma factor function.

7.3 Conclusions and future directions

The research presented here has made a significant contribution towards the

definition of sigma factor family members. Novel investigation was undertaken into

the evolutionary maintenance of sigma-like factors within higher plants, and data

mining used to analyse patterns of expression for all family members, across

hundreds of experimental contexts. Analysis of single mutants, undertaken for the

first time here for all sigma factors in parallel, identified newly recognised putative

sigma activity on multiple promoters, with a preliminary investigation identifying

Figure 15: Visual phenotype of putative double mutants.

Single mutants were crossed with each other with resultant offspring allowed to self-fertilize, producing T2 generation progeny. Multiple plants from the sig2xsig6 and sig5xsig3 T2 generation had an extremely pale, retarded phenotype (A), which did not mature (B), while dwarfed/retarded plants were seen in sig5sig1 T2 population and extremely retarded development and bleached cotyledons in the sig4sig2 T2 (C).

B

C

A

T2 generation of sig2xsig6 T2 generation of sig5xsig3

‘ sig5xsig3’

‘ sig6xsig2’ ‘ sig4xsig2’

‘ sig4xsig2’

wild-type

T2 generation of sig5xsig1 T2 generation of sig4xsig2


122

SIG4, once defined as ‘somewhat functionally redundant’, as putatively involved in

the highly specific responsive regulation of a physiologically coherent gene group.

The work undertaken suggests the importance in undertaking functional analysis of

small gene families in the context of other family members. Double-mutant analysis

may somewhat limit the false-negative quandary of studying small gene family

single mutants, endorsing it as a future technique for studies of sigma factor function.

The levels of sigma transcripts and proteins within individual mutants should be

investigated, with the creation and analysis of transgenic lines containing

overexpression of individual factors in single mutant backgrounds (e.g. 35S-SIG4

sig1) also recommended as a mechanism for further elucidating sigma factor

function. The major findings of this study are limited in their exclusion of tRNAs and

rRNAs, which should be analysed. Ultimately, transcript accumulation changes

should be verified as changes in transcriptional activity by transcription-run-on-

assay. Finally, these changes cannot be attributed to specific sigma factor function in

the absence of complemented lines.

Chapter 8: References

123

CHAPTER 8

References


124

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Chapter 9: Appendices

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CHAPTER 9

Appendices


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9.1 Figures Figure 1: Proposed mechanism for the evolution of the photosynthetic organism. ............... 11 Figure 2: The dual transcription apparatus of the plant plastid and recognised promoters. ... 16 Figure 3: Pairwise grouping of sigma-like factors found in 31 plant species. ....................... 36 Figure 4: Presence and absence of sigma factors across 31 species. ..................................... 38 Figure 5: Model for sigma factor evolution. .......................................................................... 43 Figure 6: Physical phenotype of arabidopsis sigma factor single mutants. ........................... 68 Figure 7: Plastid mRNA transcript profiles for single sigma factor mutants. ........................ 70 Figure 8: Splicing efficiencies at four sites in sigma mutants. .............................................. 73 Figure 9: Plastid mRNA operon profiles for single sigma mutants. ...................................... 76 Figure 10: SIG4 is the significant factor involved in transcription of plastid NDH genes .... 94 Figure 11: Splicing efficiencies in sig4. ................................................................................. 96 Figure 12: Presence of putative PEP-type promoters in 5’ regions of operons with altered expression in sig4. .................................................................................................................. 98 Figure 14: Induction of sigma factor transcript accumulation, and of accumulation of nucleus-encoded NDH transcripts under fluctuating high light. .......................................... 106 Figure 15: Accumulation of plastid NDH transcripts under fluctuating high light and continuous light conditions. ................................................................................................. 108 Figure 16: Visual phenotype of putative double mutants .................................................... 121

9.2 Tables

Table 1: Genes encoded in the Arabidopsis thaliana plastid genome. ................................... 13 Table 2: Transcripts showing expression correlating with the expression of SIG1. .............. 51 Table 3: Transcripts showing expression correlating with the expression of SIG2. .............. 52 Table 4: Transcripts showing expression correlating with the expression of SIG3. .............. 54 Table 5: Transcripts showing expression correlating with the expression of SIG5 ............... 55 Table 6: Transcripts showing expression correlating with the expression of SIG6 ............... 57 Table 7: Transcripts correlating with expression patterns of multiple sigma factors. ........... 59 Table 8: Arabidopsis thaliana sigma factors. ........................................................................ 65 Table 9: Putative Plastid Operons. ......................................................................................... 75 Table 10: Plastid transcripts and operons showing altered accumulation in multiple sigma factor mutants......................................................................................................................... 81 Table 11: Summary of plastid transcripts accumulation across the six arabidopsis sigma factor mutants......................................................................................................................... 82 Table 12: Review of arabidopsis sigma factor function. ........................................................ 85 Table 13: Nucleus-encoded NDH subunits. ........................................................................... 92 Table 14: Transcripts showing expressions correlating with the expression of SIG4. ........ 100 Table 15: Over-representation of motifs in 5’ regions of nucleus-encoded NDH genes and SIG4. .................................................................................................................................... 103 Table 16: Relationships between sigma factors. .................................................................. 119


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9.3 Arabidopsis lines

Wild-type and mutants were ordered from the European Arabidopsis Stock Centre (NASC, arabidopsis.org.uk./), or kindly provided by Dr Jennifer Schweer (University of Bochum, Germany). Disruption Mutant name Line/Construct Sigma KO mutants AGI line referred to as AT1G64860 GK_758B02 sig1 AT1G08540 GK_428A06 sig2 AT3G53920 GK_238A06 sig3 AT5G13730 SA_146777 sig4 AT5G24120 SA_141383 sig5 AT2G36990 GK_242G06 sig6

9.4 Oligonucleotides cDNA synthesis random hexamer NNNNNN oligodT TTTTTT gDNA contamination check type forward primer reverse primer chloroplast gDNA GCTCCGGAGATAGTTCCCTT TTCTAGTTCTATCATCAGCTATGGG nuclear gDNA AACCCTCGTAGATTGGCACA GCACCCTGTTCTTCTTACCG mitochondrial gDNA CTCCAGCCGCTCACTGTAAT TCCGATGAGCAGTCACTCAC plastid mRNA profiling (qPCR) AGI identifier forward primer reverse primer ATCG00020 psbA GAGCAGCAATGAATGCGATA CCTATGGGGTCGCTTCTGTA ATCG00040 matK ATCCTTTGTTGCCAGAATGC TTTTTCTACGCAAGCGGTCT ATCG00065 rps12 TCTCACACCGGGTAAATCCT ATCCGAAACGTCACGAAATC ATCG00070 psbK AGGCCTACGCCTTTTTGAAT CGAAAACTTACAGCGGCTTG ATCG00080 psbI TTTCTCTCTTCATATTTGGATTCCT TTCTTCACGTCCCGGATTAC ATCG00120 atpA CGGAAATCTTACCTCGACCA ATGGGTGACGGTTTGATGAT ATCG00130 atpF GCTCCTTCACGCAGTTCTTC TACTTGGGTCACTGGCCATC ATCG00140 atpH ATCCACTGGTTTCTGCTGCT TTCCTTCTGCCTCAGGTTGT ATCG00150 atpI ATTGGCAAATAGGGGGTTTC GCCGTCAGTTGGAATTGTTT ATCG00160 rps2 GGGCTCGGTGTCATTATGTT TCTTCAACACAGCTGCATCC ATCG00170 rpoC2 ATGGAGCCCGTAAAGGAGTT CGTCTGCTAAGACACGACCA ATCG00180 rpoC1 TCGGATACGAAGATATCAAATGG

TTAGTTATGGGCCTAGCAAAAGA ATCG00190 rpoB AAAAAGCACGGATACGGATG CTTCTTGAATGCCCCGATTA ATCG00210 petN CGCATGGGCTGCTTTAAT GAGTCCACTTCTTCCCCACA ATCG00220 psbM TGCACTCTTCATTCTCGTTCC TCATTTTGACTAACGGTTTTTACG ATCG00270 psbD CACAAATCTTTGGGGTTGCT CCATCCAAGCACGAATACCT ATCG00280 psbC ACTTCCCCACCTAGCCACTT AGCCCAAAACTGCAGAAGAA ATCG00300 psbZ TGCTTTCCAATTGGCAGTTT GTTACTCGACCAACCATCAGG ATCG00330 rps14 AATCCCCACCGCGTAATAGT AACATGCCTGAACCATTTCC ATCG00340 psaB GGACCCCACTACTCGTCGTA ATTGCTAATTGCCCGAAATG ATCG00350 psaA GCCAAGAAATCCTGAATGGA CATCTTGGAACCAAGCCAAT ATCG00360 ycf3 TCCAATACTCAGCGGCTTG TTCGGGCATTAGAACGAAAC ATCG00380 rps4 CGATTGGGTATGGCTTTGAC ATGGTTTGGCAATTCCTCAG ATCG00420 ndhJ CGTTTTCTGGGTTTGGAAAA AGGCCACCCTATCCAACTCT ATCG00430 ndhK GCAGTCCGCATATTGGAAAT CGTGGGACGATACTGGACTT ATCG00440 ndhC TATAGAACCGATCGGGGATG AACTCATTGCCCACGGATAC ATCG00470 atpE TCCACAAGAAGCTCAGCAAA GTGTCCGAGCTCGTCTGAG ATCG00480 atpB CCGTTTCGTACAAGCAGGAT CGGGGTCAGTCAAATCATCT ATCG00490 rbcL GTGTTGGGTTCAAAGCTGGT CATCGGTCCACACAGTTGTC ATCG00500 accD TGTGGATTCAATGCGACAAT TTTTGCGCAGAGTCAATACG ATCG00510 psaI ACTTACCCTCTATTTTTGTGCCTT GAATATGAAGAAATAAAGAAGCCATT ATCG00520 ycf4 TTTCTATGGGATCGCAGGTC GGAAATCCCCAACGAAAAAT ATCG00530 cemA TTTGCCCTGGTTGATCTCTC TTGGATCGTTTCTTTGTGGA


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AGI identifier forward primer reverse primer ATCG00540 petA CAGAGGGCGAATCCATTAAA GCCAAAACAACCGATCCTAA ATCG00550 psbJ CTGGAAGGATTCCTCTTTGG CAGGGATGAACCTAATCCTGA ATCG00560 psbL CAATCAAATCCGAACGAACA GAAATAATTCGAAAATAAAACAGCAA ATCG00570 psbF GGACCTATCCAATTTTTACAGTGC GTTGGATGAACTGCATTGCT ATCG00580 psbE TGTCTGGAAGCACAGGAGAA AACCGGTGCTGACGAATAAC ATCG00590 ORF31 TTTCGGTTTTCTACTAGCAGCTTT GCTTAGACCAATAAACAGAACTGA ATCG00600 petG TCTAATTCCTATTACTTTGGCTGGA CCAACTGATCACCACGTCTG ATCG00630 psaJ ATGGTTCGGTTCGTTAGCAG GGGAAATGTTAATGCATCTGG ATCG00640 rpl33 GCCAAGGGTAAAGATGTTCG TTGATTTCCCCGTGAATTGT ATCG00650 rps18 CAAGCGATCTTTTCGTAGGC AAAGTCACTCTATTCACCCGTCT ATCG00660 rpl20 TCGGAGGCGTAGAACAAAAC CGATGAGCCGAAACTAAAGC ATCG00670 clpP GTCGGAGGAGCAATTACCAA GTGATGGTTTCGCGAAGTTT ATCG00680 psbB CGTGCGACTTTGAAATCTGA TAGCACCATGCCAAATGTGT ATCG00690 psbT GGAAGCATTGGTTTATACATTTCTCT

AAATTTTAGGTGGTTCCCGAAA ATCG00700 psbN GGAAACAGCAACCCTAGTCG CGTGTTCCTCGAATGGATCT ATCG00710 psbH TCTAGATCTGGTCCAAGAAGCA CATTGCAACACCCATCAAAG ATCG00720 petB ATTGGGCGGTCAAAATTGTA AGACGGCCGTAAGAAGAGGT ATCG00730 petD TCCTTTTGCAACTCCTTTGG CCGCTGGTACTGAAACCATT ATCG00740 rpoA GCGATGCGAAGAGCTTTACT CCAGGACCTTGGACACAAAT ATCG00750 rps11 TACTTGTGGATTCCGGGGTA CAGCTCGTTGCATACCTTGA ATCG00760 rpl36 AAATAAGGGCTTCCGTTCGT CCTCGGGTTGGAACAAATTA ATCG00770 rps8 CGACCGGGTCTACGAATCTA ATTTCTCCGCCGATTCTTTT ATCG00780 rpl14 AGCGGGGCTAGAGAATTGAT ACTGCGGCATTGTCATCATA ATCG00790 rpl16 TGTACGACGTGGTGGAAAAA GCATTTTTGATGCCGCTATT ATCG00800 rps3 CAATCCGTATGGGGATCCTA GATCCATTCAACACGTGCAA ATCG00810 rpl22 AAAGCTGAGGTGAACCAAGG TGTCCCATAGGCCTCCACTA ATCG00820 rps19 CACAATGATTGGCCATACGA TTTGGCATGTCCTCGAAAAT ATCG00830 rpl2 CGGACCTCTCCAGAAGGTAAT AAATGGGAAATGCCCTACCT ATCG00840 rpl23 CGGTTATTGGGGAAAAATCA TTTTAACCTTTCCGGGGAGT ATCG00860 ycf2 TAGCCCTCGGTCTATTGGTG GGATCCACTTTTTGGGGAAT ATCG00870 ycf15 GCGAACAACCGGAGCTATTA CCGACATGCGTATTTTTGATT ATCG00890 ndhB CCAGAAGAAGATGCCATTCA TCATCAATGGACTCCTGACG ATCG00900 rps7 AAACTGCAAAATCCGATCCA ATGAGTTGACCCGCCTACAC ATCG01000 ycf1 TTTCGGAAGAAGGGGAAGAT TTCGAACGTGGAATTCATCA ATCG01010 ndhF CGGCGGGTATTTTTCTTGTA GGCTAAACCCCGCTTAATGT ATCG01020 rpl32 CTCGAAAAAGCGTATTCGTAA AA

TGAAAAAGCTTTCAACGATGTC ATCG01040 ccsA CACAATAACTGCGCCAAGTG AACAGAGCGCCATAGCCTAA ATCG01050 ndhD TGGAGAATGGGAATAGATGGAC TCCCGAGAAGAAAATGATCCTA ATCG01060 psaC GAGCATGCCCTACAGACGTA CAGGCGGATTCACATCTCTT ATCG01070 ndhE TGGATTGATCACAAGTCGAAA AGCGGCTGCAATTGCTATAA ATCG01080 ndhG TTGCCTGGACCAATACATGA ACATTTATGGCCCCCACATA ATCG01090 ndhI TTTGCCTGTTGTTGATTGGA ATTGGTAAACGACCCAAAGC ATCG01100 ndhA TTGACGCCACAAATTCCAT TTAGGTGGTCTGCGAGCTG ATCG01110 ndhH ATGGGAAATTCAATGGCAAA TCAAAGCCCCTGCTTTCTAA ATCG01120 rps15 CAGGGGATCCGTTGAATTT CGTTGACGTTTTCCCAGAAT ATCG00920 rrn16 CGGTATCTGGGGAATAAGCA GATTTGACGGCGGACTTAAA ATCG00950 rrn23 GGGCGACTGTTTACCAAAAA TTACCCGACAAGGAATTTCG unspliced transcript primers (qPCR) AGI identifier forward primer reverse primer ATCG00180 rpoC1 TTAGTTATGGGCCTAGCAAAAGA AACTACTTGAGCCGGATGAGA ATCG00670 clpP .1 AATAAGTTGATTCGAGATTTCGGT GAACCGTATGCACCAAAAGG ATCG00670 clpP.2 GTGATGGTTTCGCGAAGTTT TCATTCTGCGAAATAGAAAAACC ATCG00360 ycf3.2 TCCAATACTCAGCGGCTTG AGTTGGTTGTCGAGCCGTAT ATCG01100 ndhA TTGACGCCACAAATTCCAT AGGCCAAGACCTCATGTACG ATCG00890 ndhB CCAGAAGAAGATGCCATTCA AGTCTCATGCACGGTTTTGA ATCG00720 petB TCTTGGAGGGGGAGTAACCT TATGTTGACATGCGGAGGAA stress testing: nuclear NDH and SIG4 AGI identifier forward primer reverse primer AT5G13730 sig4 GCCGCATGACATTGCAGGAAATTG TTTCACCATCTCCTCTGGCCTTG AT1G15980 NDH48 AGACATGATCGGACTCCTCAAAGG GCCGTTGTCATGAACAAGAACGC AT1G64770 NDH45 CACAGTTGATGGTGATGAGAGCAG CTGAAGAGCATCAATGGCGTCTG AT1G70760 NDHL ACAATCTTGGCAGCTCAACTCG TGCTAAGGCTGGATGGTCAATCG


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AT1G74880 NDHO GACAGGAGAGTATGCACTTGTTG AGCATATCTGTTGGGAGCCAAGC AT3G16250 NDH4 TGCGTTCGTCCATTCGGTGTTG TTCTGTCCACCGTTCGCTCTTC housekeeping AGI identifier forward primer reverse primer AT5G25760 UBC TCCGTGGCGATGTACTCATA TCTGACGCACAGGACAATTC AT1G10390 POR CTTCGGTGCCTCAAACTCTC TTGAAGCTCCAAAAGCACCT AT5G39740 RPL5 CAGAAGACCTTTCCGTGCTC CAAACACACGGTTTCCAGTG

9.5 Solutions and preparations

Solutions and preparations are detailed in order coinciding with mention in Chapter 2. Preparation, growth, and collection of Arabidopsis Sterilisation Solution Ethanol 70% [v/v] Triton X-100 0.05% [v/v] Sucrose-supplemented MS growth media MS 0.5x MES 0.05% [w/v] Agar (plant culture quality) 0.7% [w/v] Make up to 900 mL with DDW, pH to 5.7 with KOH and sterilise by autoclaving. Add 100 mL autoclave-sterilized 10% [w/v] sucrose. Soil Shamrock peat 3 volumes Pearlite 1 volume Vermiculite 1 volume Mix well and pre-wet with 1-2 volumes of water prior to use. General Techniques 10 x Taq Buffer Tris (pH 8.0) 100 mM MgCl2 25 mM KCl 200 mM Octylphenoxypolyethoxyethanol 0.5% [v/v] 10 x Tris-Borate-EDTA (TBE) Buffer Tris base 900 mM Boric Acid 900 mM EDTA (pH 8.0) 20 mM Dilute 1 in 10 in DDW for 1 x buffer 1% agarose/TBE Agarose 1% [w/v] Heat until dissolved in1 x TBE buffer. Add 0.5 µg/mL EtBr immediately prior to pouring. Allow to cool until completely set.


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5 x loading dye Glycerol 25% [v/v] Bromophenol blue to colour Add to PCR product to a final concentration of 1 x prior to loading and mix by pipetting. Nucleic Acid Techniques RNA loading buffer Formamide 50% [v/v] Formaldehyde 6.5% [v/v]

Glycerol 20% [v/v] EDTA (pH 8.0) 1.25 mM EtBr 0.005% [v/v] Bromophenol blue to colour Store at -80 °C and defrost prior to use. 10 x MOPS buffer

MOPS 0.2 M NaAC (pH 8.0) 0.05 M EDTA (pH 8.0) 5 mM

Adjust pH to 7.0 with NaOH. Store at 4 °C in the dark. Dispose if solution yellows. Dilute 1 in 10 for 1 x buffer. 1% agarose/MOPS gel

Agarose 1% [w/v] Formaldehyde 1.5% [v/v] MOPS 1 x (final concentration)

Add formaldehyde immediately prior to pouring Extraction buffer (gDNA extraction)

CTAB 2% [v/v] NaCl 1.4 M EDTA (pH 8.0) 20 mM Tris HCl (pH 8.0) 100 mM β-mercaptoethanol (β-ME) 0.2% [v/v]

Store at RT. Add β-ME immediately prior to use.

Supplementary Figure 1: Genevestigator software visualisation of sigma factor transcript accumulation at different developmental stages. Figure from Genevestigator (https://www.genevestigator.com/). Refer to Genevestigator for more detail on experimental conditions.

11000 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0

LOW

MED

IUM

(=IQ

R)

HI

GH



Supplementary Figure 2: Genevestigator software visualisation of sigma factor transcript accumulation in different tissue types. Figure from Genevestigator (https://www.genevestigator.com/). Refer to Genevestigator for more detail on experimental conditions.

seedli ng inflorescence raceme flower >stamen >pistil >petal >sepal pedicel silique seed >embryo >endosperm >testa pericarp shoot infloresc. stem rosette >stem >leaf >axillary bud cauline leaf shoot apex >leaf primordia axillary shoot hypocotyl roots

0 2000 4000 6000 8000

LOW MEDIUM(=IQR) HIGH




143

Supplementary Table 1: Genevestigator software visualisation of experimental treatments under which individual sigma factor abundance was significantly (p<0.05) and notably (greater than two-fold) perturbed from respective standard or control. Figure from Genevestigator (https://www.genevestigator.com/). Refer to Genevestigator for more detail on experimental conditions.

BIOTIC SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 A. brassicicola (penta) / untreated leaf disc samples (penta) -2.1 -6.6 -2.2 B. graminis (ataf1-1) / non-infected rosette leaf samples -2.9 -3.3 -3.0 -6.5 -3.3 B. graminis (Col-0) / non-infected rosette leaf samples -2.2 -3.0 -2.4 -4.5 -3.1 B. tabaci type B / non-infected rosette tissue samples -2.9 -2.4 CaLCuV / non-infected rosette leaf samples -4.5 -2.1 -3.9 E. coli (TUV86-2 fliC) / mock inoculated leaf samples -2.6 G. cichoracearum study 2 (18h) / non-infected whole rosette samples (Col-0) -13.3 G. cichoracearum study 2 (36h) / non-infected whole rosette samples (Col-0) -2.0 -4.2 -46.6 G. cichoracearum study 3 (18h) / non-infected whole rosette samples (edr1) -2.0 -13.3 G. cichoracearum study 3 (36h) / non-infected whole rosette samples (edr1) -2.4 -4.1 -40.1 M. incognita (early) / non-infected root samples (early) -2.1 M. incognita (late) / non-infected root samples (late) -2.1 P. infestans (6h) / mock treated leaf samples (6h) -2.2 -2.3 P. parasitica (6h) / non-infected root samples (Col-0) -4.7 P. parasitica (10.5h) / non-infected root samples (Col-0) -11.2 P. parasitica (30h) / non-infected root samples (Col-0) -4.9 P. syringae pv. maculicola (Col-0) / mock treated leaf samples (Col-0) -4.5 -5.8 -2.5 -17.5 -23.1 P. syringae pv. phaseolicola (24h) / mock inoculated leaf samples (24h) -2.3 -2.5 P. syringae pv. phaseolicola (6h) / mock inoculated leaf samples (6h) -2.1 -2.3 -2.8 -2.3 P. syringae pv. syringae (OE7a-1) / non-infected leaf samples (OE7a-1) -6.5 -32.1 P. syringae pv. syringae study 2 (Col-0) / P. syringae pv. syringae (Col-0) -2.8 -4.3 -3.7 P. syringae pv. syringae study 2 (OE7a-1) / non-infected leaf samples (OE7a-1) -6.9 -36.7 -2.0 P. syringae pv. tomato study 10 (DC3000 hrpA) / mock inoculated leaf samples -2.1 P. syringae pv. tomato study 10 (DC3000 hrpA) / P. syringae pv. tomato study 10 (DC3000) 3.3 6.8 5.3 P. syringae pv. tomato study 10 (DC3000) / mock inoculated leaf samples -4.6 P. syringae pv. tomato study 10 (DC3000) / mock inoculated leaf samples -7.1 -3.5 -14.7 -7.5 P. syringae pv. tomato study 11 (penta) / untreated leaf disc samples (penta) -9.5 P. syringae pv. tomato study 12 (atgsnor1-1) / untreated leaf tissue samples (atgsnor1-1) -3.0 -2.2 -3.6 -2.5 P. syringae pv. tomato study 12 (Col-0) / untreated leaf tissue samples (Col-0) -2.0 -2.6 P. syringae pv. tomato study 12 (sid2) / untreated leaf tissue samples (sid2) -2.7 -3.0 -4.4 -2.2 P. syringae pv. tomato study 14 (DC3000 avrRpm1) / P. syringae pv. tomato study 13 (DC3000 avrRpm1) 2.2 P. syringae pv. tomato study 14 (DC3000 hrpA) / P. syringae pv. tomato study 13 (DC3000 hrpA) 2.3 P. syringae pv. tomato study 14 (DC3000) / P. syringae pv. tomato study 13 (DC3000) 2.5 P. syringae pv. tomato study 15 (DC3000 avrRpm1) / P. syringae pv. tomato study 13 (DC3000 avrRpm1) 2.5 -2.1 12.8 P. syringae pv. tomato study 15 (DC3000 hrpA) / P. syringae pv. tomato study 13 (DC3000 hrpA) 2.3 -2.9 15.0 P. syringae pv. tomato study 15 (DC3000) / P. syringae pv. tomato study 13 (DC3000) 2.1 -3.0 19.4 P. syringae pv. tomato study 2 (DC3000 avrRpm1) / mock inoculated leaf samples (6h) -2.2 -2.1 -2.8 -2.8 P. syringae pv. tomato study 2 (DC3000 avrRpm1) / P. syringae pv. tomato study 2 (DC3000) -2.2 P. syringae pv. tomato study 2 (DC3000 hrcC-) / P. syringae pv. tomato study 2 (DC3000 avrRpm1) 2.2 P. syringae pv. tomato study 3 (DC3000 avrRpm1) / mock inoculated leaf samples (24h) -2.5 -2.1 -3.3 -2.1 P. syringae pv. tomato study 3 (DC3000 avrRpm1) / P. syringae pv. tomato study 3 (DC3000) 2.1 P. syringae pv. tomato study 3 (DC3000 hrcC-) / mock inoculated leaf samples (24h) -2.0 P. syringae pv. tomato study 3 (DC3000 hrcC-) / P. syringae pv. tomato study 3 (DC3000 avrRpm1) -2.3 P. syringae pv. tomato study 3 (DC3000) / mock inoculated leaf samples (24h) -3.3 -3.0 -8.7 3.8 -4.5 P. syringae pv. tomato study 5 (Col-0) / non-infected leaf samples (Col-0) -2.1



144

Supplementary Table 1, continued: Figure from Genevestigator (https://www.genevestigator.com/) BIOTIC SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 P. syringae pv. tomato study 5 (gh3.5-1D) / non-infected leaf samples (gh3.5-1D) -2.5

-2.4 -2.1

P. syringae pv. tomato study 8 (DC3000) / mock inoculated leaf samples -3.4 P. syringae pv. tomato study 8 (DC3118 Cor-) / mock inoculated leaf samples -3.0 P. syringae pv. tomato study 8 (DC3118 Cor-hrps) / P. syringae pv. tomato study 8 (DC3118 Cor-) 3.0 P. syringae pv. tomato study 9 (DC3118 Cor-) / mock inoculated leaf samples -3.1 -6.7 -4.9 P. syringae pv. tomato study 9 (DC3118 Cor-hrps) / P. syringae pv. tomato study 9 (DC3118 Cor-) 2.0 2.7 CHEMICAL AgNO3 / mock treated seedlings -2.0 -2.8 -2.0 Cd study 2 (Col-0) / untreated shoot samples (Col-0) 2.7 4.1 CMP (24h) / solvent treated root culture samples (24h) -3.2 -3.2 CO2 high / untreated leaf samples -2.1 -3.0 dexamethasone study 2 / mock treated 35S::AP3-GR flower buds 3.0 DMTU (20h) / solvent treated cell suspension samples (20h) -2.0 -5.6 fenclorim (24h) / solvent treated root culture samples (24h) -2.3 -3.4 -2.2 fenclorim (4h) / solvent treated root culture samples (4h) -2.2 -2.1 -2.2 furyl acrylate ester / solvent treated seedlings 3.8 lincomycin (Col-0) / untreated seedling samples (Col-0) -2.3 -3.5 norflurazon / untreated seedlings -8.4 norflurazon study 2 (Col-0) / untreated seedlings (Col-0) -3.1 -3.4 -4.8 norflurazon study 2 (gun1-9) / untreated seedlings (gun1-9) 2.1 norflurazon study 2 (gun5) / untreated seedlings (gun5) 2.5 ozone / air treated seedlings -2.0 -2.7 -2.3 ozone / air treated seedlings -2.2 ozone study 2 (Col-0) / fresh air treated leaf samples (Col-0) 2.0 ozone study 3 (Col-0) / fresh air treated leaf samples (Col-0) -2.2 paclobutrazole study 3 / untreated leaf disc samples (Ler) -2.6 -6.9 -3.5 phenanthrene / untreated Col plant samples -2.2 -2.0 -3.1 -2.1 phytoprostane A1 (cell culture) / solvent treated cell culture samples 2.7 phytoprostane A1 (tga2-5-6) / solvent treated (tga2-5-6) seedlings 2.1 syringolin study 2 / solvent treated leaf samples (syl_404_bc2) -2.7 -2.7 -8.1 12.0 -3.8 syringolin study 2 / solvent treated leaf samples (syl_404_bc2) -3.7 syringolin study 3 (late) / solvent treated leaf samples (Col-0; late) -3.9 -5.2 -2.9 -8.1 9.4 -3.5 syringolin study 4 (late) / solvent treated leaf samples (Col-0; late inf.) -2.2 -2.2 -2.1 -2.4 HORMONE ABA (3h) / mock treated seedlings (3h) 6.4

ABA + DMTU (20h) / solvent treated cell suspension samples (20h) 2.2 4.4 ABA study 10 (20h) / ABA + DMTU (20h) -2.8 ABA study 3 (ahg1-1) / untreated seed samples -4.3 ABA study 3 (ahg3-1) / untreated seed samples -3.5 ABA study 3 (Col-0) / untreated seed samples -3.0 ABA study 7 (agb1-2) / solvent treated guard cell samples (agb1-2) 2.6 ABA study 7 (Col-0) / solvent treated guard cell samples (Col-0) 2.6 ABA study 7 (gpa1-4) / solvent treated guard cell samples (gpa1-4) 2.5 ABA study 8 (agb1-2 gpa1-4) / solvent treated leaf samples (agb1-2 gpa1-4) 3.5 -2.6 ABA study 8 (agb1-2) / solvent treated leaf samples (agb1-2) -2.2 2.5 -3.8 ABA study 8 (Col-0) / solvent treated leaf samples (Col-0) -5.3 -3.7 -2.3 -3.6 -6.3 ABA study 8 (gpa1-4) / solvent treated leaf samples (gpa1-4) 4.0 -2.8 BA (Col-0) / vehicle treated shoot samples (Col-0) -5.2 BL study 2 (brx) / mock treated seedlings (brx) 11.2 4.2 3.5 13.4 13.9 IAA study 9 (Bur-0) / untreated seedling samples (Bur-0) -2.2 MeJa study 5 (gai) / untreated leaf disc samples (gai) 2.2 -7.2 3.0 MeJa study 5 (Ler) / untreated leaf disc samples (Ler) -2.4 -3.2 -3.9 -15.5 MeJa study 5 (penta) / untreated leaf disc samples (penta) -2.9 -4.1 -2.9 -17.1 NAA (2h) / untreated leaf disc samples (Col-0) -3.3 NAA + FLG22 (1h) / untreated leaf disc samples (Col-0) -2.2 -3.4 -5.1 -2.7 NAA + FLG22 (2h) / untreated leaf disc samples (Col-0) -2.6 -4.2 -2.9 -4.5 -6.7 -4.2 salicylic acid study 3 / mock treated seedlings -2.0 salicylic acid study 4 (Mt-0) / silwet L77 treated Mt-0 leaf samples (4h) -2.1 salicylic acid study 5 (Van-0) / silwet L77 treated Van-0 leaf samples (28h) -2.6 salicylic acid study 7 (npr1-1 sni1 ssn2-1) / solvent treated whole plant samples (npr1-1 sni1 ssn2-1) -2.2 -30.5 salicylic acid study 8 (Col-0) / mock treated leaf samples (Col-0) -2.0 -2.3 ELICITOR FLG22 (4h) / H2O treated leaf samples (4h) -2.1 -2.3



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Supplementary Table 1, continued: Figure from Genevestigator (https://www.genevestigator.com/) ELICITOR SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 FLG22 + GA (1h) / untreated leaf disc samples (Ler) -2.9 -3.1 -7.2 -3.1 FLG22 + GA (2h) / untreated leaf disc samples (Ler) -2.9 -4.7 -3.3 -3.8 -5.2 FLG22 study 10 (1h) / FLG22 study 10 (0h) -2.0 -2.4 FLG22 study 10 (2h) / FLG22 study 10 (0h) 2.3 FLG22 study 11 (0h) / H2O pretreated leaf disc samples (Ler) -3.5 -5.1 -3.8 FLG22 study 2 (1h) / H2O treated Col-0 seedlings (1h) -2.1 -4.1 -3.0 FLG22 study 2 (3h) / H2O treated Col-0 seedlings (3h) -3.0 -2.6 -2.7 -4.3 FLG22 study 4 (35S:AFB1) / untreated leaf disc samples (35S:AFB1) -2.2 -3.1 -2.1

FLG22 study 4 (35S:miR393) / untreated leaf disc samples (35S:miR393) -2.2 -3.2 -3.6 -2.2 FLG22 study 4 (Col-0) / untreated leaf disc samples (Col-0) -2.9 -5.9 -2.4 FLG22 study 5 (35S:AFB1) / untreated leaf disc samples (35S:AFB1) -2.4 -4.3 -3.7 -7.1 -3.4 FLG22 study 5 (35S:miR393) / untreated leaf disc samples (35S:miR393) -2.2 -4.2 -2.2 -4.9 -5.4 -3.7 FLG22 study 5 (Col-0) / untreated leaf disc samples (Col-0) -3.1 -6.5 -4.8 -11.7 -9.3 FLG22 study 6 (gai) / untreated leaf disc samples (gai) -2.0 FLG22 study 6 (Ler) / FLG22 study 8 (1h) -2.3 -3.5 -5.6 -3.3 -2.9 FLG22 study 6 (Ler) / untreated leaf disc samples (Ler) -2.6 -2.8 -4.7 -2.8 FLG22 study 6 (penta) / untreated leaf disc samples (penta) -2.3 -3.8 -4.2 -10.5 -2.7 -4.5 FLG22 study 7 (gai) / untreated leaf disc samples (gai) -2.1 FLG22 study 7 (Ler) / FLG22 study 8 (2h) -2.8 -3.7 -6.9 -2.3 -5.1 FLG22 study 7 (Ler) / untreated leaf disc samples (Ler) -3.2 -3.8 -4.9 -4.7 FLG22 study 7 (penta) / untreated leaf disc samples (penta) -3.5 -7.2 -4.8 -9.6 -3.6 -9.4 FLG22 study 9 (1h) / FLG22 study 9 (0h) -3.5 -2.2 FLG22 study 9 (2h) / FLG22 study 9 (0h) -2.7 -5.6 -3.8 EF-Tu (elf18) (30min) / untreated whole plant samples (fls2-17) -2.2 EF-Tu (elf18) study 2 (tbf1) / mock treated leaf samples (tbf1) -3.1 -2.5 -2.1 GST-NPP1 (4h) / GST (4h) -2.1 -2.0 HrpZ (4h) / H2O treated leaf samples (4h) -2.4 -2.3 -2.3 -2.8 OGs (1h) / H2O treated Col-0 seedlings (1h) -2.3 -2.2 OTHER 5-AC / solvent treated seedling samples (Ws) -4.9 -2.5 -6.0

pollen tube growth (semi in vivo) / dry mature pollen samples -4.7 pollen tube growth (semi in vivo) / pollen tube growth (in vitro) -3.3 zeatin study 2 (arr10-5:arr12-1) / solvent treated aerial parts (arr10-5:arr12-1) 2.2 zeatin study 2 (Col-0) / solvent treated aerial parts (Col-0) 2.5 zeatin study 3 (ARR22ox) / untreated whole plant samples (ARR22ox) -2.6 -2.5 NUTRIENT sucrose study 3 (acn1-2) / untreated seedlings (acn1-2) -2.3 -4.8

sucrose study 3 (Col-7) / untreated seedlings (Col-7) -4.5 glucose (2h) / untreated seedlings -4.0 glucose (4h) / untreated seedlings -2.0 -4.1 -3.3 nitrate starvation / untreated seedlings -4.3 -10.3 2.9 -4.2 nitrate(15mM) / sucrose(0mM) / root samples ( N-free/suc-free) 3.1 KCl treated root samples (early) / untreated root samples 2.1 KNO3 study 3 / (NH4)2SO4 -3.5 iron deficiency (LZ2) / mock treated root samples (LZ2) -2.4 iron deficiency (LZ4) / mock treated root samples (LZ4) -3.4 -2.4 iron deficiency study 2 (late) / mock treated root samples -2.7 iron deficiency study 2 (late) / mock treated root samples -2.2 sulfur deficiency study 3 (LZ2) / sulfur deficiency study 3 (LZ1) 2.3 sulfur deficiency study 3 (LZ4) / sulfur deficiency study 3 (LZ3) 2.0 mock treated bzip1-1 whole plant samples (dark) / mock treated bzip1-1 whole plant samples (light) 2.8 -3.1 mock treated Col-0 whole plant samples (dark) / mock treated Col-0 whole plant samples (light) 3.0 -3.2 (NH4)2SO4 study 2 (8h) / KNO3 study 5 (8h) -2.9 N depletion (Col-0) / Seedlings grown under N-replete condition (Col-0) -2.7 -3.1 -2.7 nitrate(45mM) / sucrose(90mM) / root samples ( N-free/suc-free) 2.5 KNO3/NH4NO3 study 2 (Col-0) / KNO3/NH4NO3 (Col-0) 3.1 -2.7 LIGHT INTENSITY/QUALITY blue / dark grown Col-0 seedlings 12.1

blue study 2 / low light grown seedlings (Col-0) 5.9 circadian / ethanol / MG132 (Alc::TOC1) / circadian / MG132 (Alc::TOC1) -2.1 circadian / ethanol / MG132 (Col-0) / circadian / MG132 (Col-0) -2.0 circadian / ethanol / MG132 study 2 (Col-0) / circadian / ethanol / MG132 (Col-0) -3.6 circadian / MG132 study 2 (Alc::TOC1) / circadian / MG132 (Alc::TOC1) 2.0 -4.4 circadian / MG132 study 2 (Alc::TOC1) / circadian / MG132 (Alc::TOC1) -7.4 circadian / MG132 study 2 (Col-0) / circadian / MG132 (Col-0) 5.4



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Supplementary Table 1, continued: Figure from Genevestigator (https://www.genevestigator.com/) LIGHT INTENSITY/QUALITY SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 circadian clock (Ca2+)cyt / nicotinamide (61h) / circadian clock (Ca2+)cyt study 4 (C24_LUC_AEQ) 3.8 circadian clock (Ca2+)cyt / nicotinamide (65h) / circadian clock (Ca2+)cyt study 5 (C24_LUC_AEQ) 3.9 circadian clock (Ca2+)cyt / nicotinamide (89h) / circadian clock (Ca2+)cyt study 11 (C24_LUC_AEQ) 3.0 circadian clock study 2 (Ws-0) / circadian clock study 4 (Ws-0) 5.4 circadian clock study 3 (lhy-21cca1-11) / circadian clock study 4 (lhy-21cca1-11) 7.6 dark / 4°C (140-200min) / dark / 21°C (140-200min) 3.8 dark / 4°C (220-280min) / dark / 21°C (220-280min) 7.1 dark / 4°C (300-360min) / dark / 21°C (300-360min) -2.1 dark / 4°C (300-360min) / dark / 21°C (300-360min) 6.4 dark / 4°C (60-120min) / dark / 21°C (60-120min) 2.3 far red / dark grown Col-0 seedlings 2.3 16.4 far red / dark grown Col-0 seedlings 2.7 far red study 2 (+DEX) / dark study 2 (+DEX) 2.0 high light (Col-0) / low light grown seedlings (Col-0) 6.9 high light (cry1) / low light grown seedlings (cry1) 3.5 high light (hy5) / low light grown seedlings (hy5) 5.9 light / low CO2 / dark / low CO2 2.1 light study 2 / dark grown Col-0 seedlings 2.6 2.3 2.3 2.8 light study 3 / dark grown Ler-0 seedlings 2.5 2.5 2.9 6.7 2.2 light study 4 (cli186) / dark grown cli186 seedlings 32.2 light study 5 (cli186) / dark grown cli186 seedlings 44.3 light study 6 (Col-0) / dark grown Col-0 seedlings 5.4 5.6 4.3 2.2 4.1 light study 6 (csn4-1) / dark grown csn4-1 seedlings 2.2 lincomycin+R+B (0.5µmol m-2 s-1) / R+B (0.5µmol m-2 s-1) -2.0 -4.5 -2.7 -3.9 lincomycin+R+B study 2 (0.5µmol m-2 s-1) / R+B study 2 (0.5µmol m-2 s-1) -2.4 -2.9 -5.1 long day (Col-0) / short day study 2 (Col-0) 2.1 -2.2 3.0 -6.9 long day (cs26) / short day study 2 (cs26) -5.9 -20.2 low light / 4°C (140-200min) / low light / 21°C (140-200min) 2.6 low light / 4°C (220-280min) / low light / 21°C (220-280min) -2.6 3.6 low light / 4°C (300-360min) / low light / 21°C (300-360min) -2.8 5.0 low light / 4°C (60-120min) / low light / 21°C (60-120min) 2.2 moderate light / 32°C (300-360min) / moderate light / 21°C (300-360min) 2.2 night extension (intermediate) / untreated rosette samples -2.2 -3.3 night extension (late) / untreated rosette samples -2.4 -5.5 -2.2 -7.7 -2.6 red / dark grown Col-0 seedlings 4.2 red study 2 (1h) / dark grown seedlings (pif1pif3pif4pif5) 13.1 red study 3 (1h) / dark grown seedlings (Col-0) 2.1 55.2 red study 3 (45h) / dark grown seedlings (Col-0) 2.0 3.5 2.4 red study 4 (18h) / dark study 5 (18h) 2.8 5.3 3.3 15.4 red study 4 (1h) / dark study 4 (Col-0) 23.8 shift etiolated seedlings to light study 2 (6h) / shift etiolated seedlings to light study 2 (1h) -12.2 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (0.5h) / lincomycin+R+B (0.5µmol m-2 s-1) 2.8 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (0.5h) / shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (0.5h) -3.7 -3.0 -2.5 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (1h) / lincomycin+R+B (0.5µmol m-2 s-1) 15.9 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (1h) / shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (1h) -3.2 -3.1 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (24h) / lincomycin+R+B study 2 (0.5µmol m-2 s-1) 14.6 2.3 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (24h) / shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (24h) -2.5 -3.3 -3.0 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (4h) / lincomycin+R+B study 2 (0.5µmol m-2 s-1) 14.2 2.2 shift lincomycin+R+B 0.5µmol m-2 s-1 to lincomycin+R+B 60µmol m-2 s-1 (4h) / shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (4h) -2.7 -2.9 shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (1h) / R+B (0.5µmol m-2 s-1) 5.4 shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (24h) / R+B study 2 (0.5µmol m-2 s-1) 4.3 2.1 2.7 shift R+B 0.5µmol m-2 s-1 to R+B 60µmol m-2 s-1 (4h) / R+B study 2 (0.5µmol m-2 s-1) 2.8 3.1 2.6



147

Supplementary Table 1, continued: Figure from Genevestigator (https://www.genevestigator.com/) GERMINATION STUDIES SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 shift SD to LD study 4 (5d) / short day shoot apex samples at 23°C (FRI:flc) -2.1 shortday / long day grown seedlings -2.1 stratification (48h) / desiccated seed samples 3.8 -2.1 7.3 UV filtered WG295 (1h) / seedlings irradiated with 327nm cut-off (1h) 3.7 UV filtered WG305 (1h) / seedlings irradiated with 327nm cut-off (1h) 3.4 UV unfiltered max-310nm (6h) / seedlings irradiated with 327nm cut-off (6h) -2.7 4.3 UV-A / dark grown Col-0 seedlings 6.7 UV-AB / dark grown Col-0 seedlings 13.1 white / dark grown Col-0 seedlings 9.0 germination (12h) / desiccated seed samples 7.0 2.8 4.4 -2.3 8.9 germination (12h) / stratification (48h) 3.4 4.4 germination (1h) / desiccated seed samples 4.4 -2.3 8.4 germination (24h) / desiccated seed samples 7.6 4.7 3.0 6.0 germination (24h) / stratification (48h) 5.7 3.0 germination (48h) / desiccated seed samples 12.5 12.7 4.9 7.2 germination (48h) / stratification (48h) 3.3 15.3 5.0 germination (6h) / desiccated seed samples 5.1 2.6 -2.2 7.5 germination (6h) / stratification (48h) 2.6 OTHER STRESS hypoxia / untreated seedling samples (low light) -2.5 hypoxia study 2 (late) / untreated seedlings (late) 2.9 3.7 hypoxia study 2 (late+recovery) / untreated seedlings (late) 2.0 hypoxia study 6 (ANAC102(KO-1)) / untreated plant samples (ANAC102(KO-1)) -7.6 -20.6 -7.1 -25.9 -18.4 -10.1 hypoxia study 6 (Col-0) / untreated plant samples (Col-0) -8.1 -18.5 -7.9 -29.6 -20.8 -9.4 hypoxia study 7 (35S::HRE1) / 35S::HRE1 seedlings grown under aerobic conditions -3.5 hypoxia study 7 (35S::HRE2) / 35S::HRE2 seedlings grown under aerobic conditions -2.6 hypoxia study 7 (Col-0) / Col-0 seedlings grown under aerobic conditions -2.1 16°C (Col-0) / untreated etiolated seedlings (Col-0) 2.6 2.3 anoxia / untreated seedlings 17.0 shift high CO2 / SD to air CO2 / LD (cat2-1) / shift high CO2 / SD to air CO2 / SD (cat2-1) -4.0 shift high CO2 / SD to air CO2 / LD study 2 (cat2-1) / shift high CO2 / SD to air CO2 / SD study 2 (cat2-1) -2.8 shift high CO2 / SD to air CO2 / LD study 2 (Col-0) / high CO2 / SD (Col-0) 2.6 shift high CO2 / SD to air CO2 / LD study 2 (Col-0) / shift high CO2 / SD to air CO2 / SD study 2 (Col-0) 2.6 shift high CO2 / SD to air CO2 / SD (cat2-1) / high CO2 / SD (cat2-1) 7.1 shift high CO2 / SD to air CO2 / SD study 2 (cat2-1) / high CO2 / SD (cat2-1) 4.7 cold (late) / untreated green tissue samples (late) -4.0 cold study 10 (24h) / untreated seedling samples (soil) 2.9 cold study 3 (24h) / untreated seedlings -2.7 cold study 3 (7d) / untreated seedlings -2.4 cold study 4 (10°C) / 20°C treated rosette samples (6h) 4.2 cold study 4 (8°C) / 20°C treated rosette samples (6h) -2.0 cold study 6 (C24) / 20°C/18°C treated rosette samples (C24) -2.4 cold study 6 (Can) / 20°C/18°C treated rosette samples (Can) -2.8 2.2 cold study 6 (Col-0) / 20°C/18°C treated rosette samples (Col-0) -3.6 cold study 6 (Cvi) / 20°C/18°C treated rosette samples (Cvi) -2.7 cold study 6 (Rsch) / 20°C/18°C treated rosette samples (Rsch) -2.5 cold study 6 (Te) / 20°C/18°C treated rosette samples (Te) -3.0 3.6 cold study 6 (Te) / 20°C/18°C treated rosette samples (Te) 2.7 cold study 7 (sf3) / untreated all aerial tissue samples (sf3) -2.7 cold study 8 (Col-0) / untreated all aerial tissue samples (Col-0) 2.1 cold study 9 (7d) / untreated seedling samples (plate) -2.7 heat study 2 (hsf1/3) / untreated leaf samples (hsf1/3) 3.2 10.0 6.6 8.7 4.6 heat study 2 (ws) / untreated leaf samples (ws) 3.0 8.3 6.2 8.3 4.3 heat study 5 / untreated plant samples -2.1 heat study 6 (Col-0) / untreated all aerial tissue samples (Col-0) -2.1 drought study 2 (Col-0) / untreated leaf samples (Col-0) 7.1 drought study 2 (Trans.) / untreated leaf samples (Trans.) 2.6 drought study 9 (35S::ABF3-48) / untreated 35S::ABF3-48 seedling samples (24h) 2.1 drought study 9 (control-48) / untreated control-48 seedling samples (24h) 2.1 shift to pH 4.6 (24h) / mock treated root samples (24h) -2.0



148

Supplementary Table 1, continued: Figure from Genevestigator (https://www.genevestigator.com/) OTHER STRESS SIG1 SIG2 SIG3 SIG4 SIG5 SIG6 shift to pH 4.6 / protoplasting / shift to pH 4.6 (24h) -2.6 Fe deficiency (Col-0) / untreated root samples (Col-0) -2.1 Fe deficiency (CsUBC13oe) / untreated root samples (CsUBC13oe) -2.3 iron deficiency / protoplasting / iron deficiency study 8 (24h) -12.6 -7.9 -2.2 shift 16°C to 22°C (Ler-0) / 22°C grown Ler-0 plants (4h/20h) -2.1 shift 22°C to optimal temperature / 22°C -2.1 temperature buffering (12°C) / 22°C grown seedling samples (Ws) -2.5 submergence study 2 (7h) / rosette samples of Col-0 shifted to darkness (7h) -2.1 -2.1 light/drought (aox1a(sail)) / untreated leaf samples (aox1a(sail)) 10.2 light/drought (aox1a(salk)) / untreated leaf samples (aox1a(salk)) 6.4 osmotic (late) / untreated green tissue samples (late) -2.1 2.5 -2.1 oxidative study 3 / Tween 20 treated aeral tissue samples -2.6 RBR depletion (RNAi; 12h) / untreated leaf samples (0h) -3.5 3.0 -34.0



149

Supplementary Table 2: Transcripts showing expression patterns correlating with those of SIG1. The top 50 positively correlating transcripts were obtained from five online co-expression programs (ACT: http://www.arabidopsis.leeds.ac.uk/act/, ATTED-II: http://atted.jp/, BAR Expression Angler: http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi, CressExpress: http://cressexpress.org/ and GeneCAT: http://genecat.mpg.de/) using SIG1 as bait. COR is the coefficient of determination (r2). ACT ATTED-II BAR EXPRESSION

ANGLER CRESSEXPRESS GENECAT

AGI COR AGI COR AGI COR AGI COR AGI COR

1 AT5G58870 0.90 AT3G59400 0.83 AT3G54660 0.88 AT1G58290 0.76 AT2G47450 0.87 2 AT5G64840 0.89 AT1G19715 0.73 AT5G64840 0.87 AT4G27700 0.75 AT4G27700 0.87 3 AT3G54660 0.89 AT4G15560 0.78 AT5G58870 0.87 AT5G17230 0.70 AT4G35250 0.86 4 AT5G64940 0.88 AT3G17040 0.77 AT5G35970 0.86 AT4G33010 0.70 AT5G57345 0.85 5 AT1G58290 0.88 AT2G47450 0.80 AT3G01060 0.86 AT4G35250 0.70 AT3G50685 0.85 6 AT1G07010 0.87 AT1G58290 0.71 AT5G67030 0.85 AT5G13630 0.70 AT5G64940 0.85 7 AT2G47450 0.87 AT4G04850 0.72 AT1G58290 0.85 AT2G35260 0.69 AT3G16000 0.84 8 AT1G50250 0.87 AT5G13630 0.80 AT5G64940 0.85 AT1G18060 0.69 AT5G23120 0.84 9 AT3G27050 0.86 AT5G64940 0.75 AT2G47450 0.85 AT1G74470 0.68 AT3G46780 0.84 10 AT3G01060 0.86 AT3G10230 0.70 AT3G27050 0.85 AT5G57345 0.68 AT2G04039 0.84 11 AT5G35970 0.86 AT2G35260 0.79 AT2G04039 0.85 AT4G22890 0.67 AT1G07010 0.84 12 AT2G04039 0.85 AT3G16520 0.73 AT3G59400 0.84 AT5G19940 0.67 AT4G28030 0.84 13 AT5G67030 0.85 AT3G27050 0.69 AT5G42270 0.83 AT5G66570 0.67 AT1G14345 0.84 14 AT5G42070 0.85 AT3G56940 0.80 AT2G26080 0.83 AT5G19220 0.66 AT1G03630 0.84 15 AT2G26080 0.85 AT5G02120 0.80 AT1G07010 0.83 AT2G42690 0.66 AT1G18730 0.84 16 AT5G42270 0.84 AT5G19940 0.78 AT5G13650 0.83 AT5G43750 0.65 AT1G23740 0.84 17 AT3G59400 0.84 AT3G26570 0.75 AT5G42070 0.82 AT2G47450 0.65 AT4G22890 0.84 18 AT5G08650 0.84 AT5G57345 0.74 AT5G08650 0.82 AT5G45170 0.65 AT5G13630 0.84 19 AT1G18060 0.84 AT4G27700 0.78 AT4G35450 0.82 AT5G04140 0.65 AT3G59400 0.83 20 AT4G01800 0.84 AT4G35250 0.78 AT4G01800 0.82 AT4G15560 0.65 AT1G55480 0.83 21 AT5G48220 0.84 AT2G45990 0.68 AT1G18060 0.82 AT5G13650 0.65 AT5G19220 0.83 22 AT5G08740 0.84 AT1G23740 0.76 AT5G13630 0.82 AT5G48790 0.65 AT1G62750 0.83 23 AT4G35450 0.83 AT1G15290 0.69 AT2G34860 0.82 AT5G22830 0.64 AT1G17220 0.83 24 AT1G07180 0.83 AT1G17360 0.53 AT2G34860 0.82 AT5G64940 0.64 AT1G22630 0.83 25 AT1G80030 0.83 AT5G23060 0.78 AT1G51110 0.81 AT1G65230 0.64 AT1G18060 0.83 26 AT4G26860 0.83 AT2G33250 0.69 AT1G12800 0.81 AT1G23740 0.64 AT1G74730 0.83 27 AT3G10230 0.83 AT2G04039 0.76 AT5G59250 0.81 AT1G14345 0.64 AT3G50820 0.83 28 AT5G13650 0.83 AT2G42190 0.62 AT4G02920 0.81 AT5G59250 0.64 AT5G04140 0.83 29 AT5G51020 0.82 AT1G74470 0.76 AT5G57345 0.80 AT4G01050 0.64 AT5G08050 0.82 30 AT1G12800 0.82 AT4G37550 0.62 AT1G45474 0.80 AT1G09340 0.64 AT4G02530 0.82 31 AT1G74730 0.82 AT1G34000 0.73 AT1G06430 0.80 AT2G30950 0.64 AT1G65230 0.82 32 AT1G22850 0.82 AT4G22570 0.62 AT2G35260 0.80 AT1G07010 0.64 AT3G02730 0.82 33 AT1G06430 0.82 AT1G22850 0.71 AT3G61870 0.80 AT4G09650 0.64 AT5G42270 0.82 34 AT1G51110 0.82 AT3G01180 0.64 AT4G34350 0.80 AT1G15820 0.64 AT1G16720 0.82 35 AT2G01110 0.82 AT4G09650 0.77 AT5G04140 0.80 AT5G08050 0.64 AT5G17230 0.82 36 AT3G01180 0.82 AT1G17220 0.77 AT2G21330 0.80 AT3G26570 0.63 AT3G12780 0.82 37 AT5G13630 0.82 AT3G54900 0.67 AT4G26860 0.80 AT4G04640 0.63 AT5G43750 0.82 38 AT5G03900 0.81 AT1G23310 0.74 AT1G08540 0.80 AT3G50820 0.63 AT1G54780 0.82 39 AT4G02920 0.81 AT4G22890 0.76 AT2G01110 0.80 AT2G37240 0.63 AT4G04640 0.82 40 AT2G04270 0.81 AT1G51400 0.74 AT5G23120 0.80 AT1G23310 0.63 AT1G58290 0.82 41 AT5G57960 0.81 AT5G13770 0.71 AT5G17230 0.80 AT4G37930 0.63 AT1G42970 0.82 42 AT5G23120 0.81 AT1G62750 0.75 AT4G28080 0.80 AT1G12250 0.63 AT2G41680 0.82 43 AT2G43750 0.81 AT1G29700 0.71 AT1G22630 0.79 AT2G34460 0.63 AT1G22850 0.82 44 AT1G45474 0.81 AT5G04490 0.66 AT5G67370 0.79 AT5G42270 0.63 AT2G35260 0.82 45 AT5G59250 0.81 AT1G44446 0.68 AT5G62140 0.79 AT3G27925 0.63 AT2G39730 0.82 46 AT1G50450 0.81 AT2G30520 0.60 AT2G29360 0.79 AT5G13770 0.63 AT1G08540 0.82 47 AT5G17230 0.81 AT2G42690 0.69 AT4G11175 0.79 AT3G17040 0.63 AT3G25690 0.82 48 AT5G51720 0.81 AT5G64840 0.67 AT5G64290 0.79 AT3G02730 0.63 AT5G51010 0.82 49 AT4G34350 0.81 AT5G35970 0.66 AT1G09340 0.79 AT3G10060 0.63 AT1G50250 0.82 50 AT2G29360 0.81 AT1G16720 0.69 AT2G37240 0.79 AT1G68010 0.63 AT5G13770 0.82


http://atted.jp/

http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi




150

Supplementary Table 3: Transcripts showing expression patterns correlating with those of SIG2. The top 50 positively correlating transcripts were obtained from five online co-expression programs (ACT: http://www.arabidopsis.leeds.ac.uk/act/, ATTED-II: http://atted.jp/, BAR Expression Angler: http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi, CressExpress: http://cressexpress.org/ and GeneCAT: http://genecat.mpg.de/) using SIG2 as bait. COR is the coefficient of determination (r2). ACT ATTEDII BAR CRESS GENECAT

AGI COR AGI COR AGI COR AGI COR AGI COR 1 AT1G12800 0.93 AT3G18390 0.87 AT1G12800 0.90 AT5G52440 0.78 AT1G12800 0.93 2 AT3G09210 0.91 AT3G23700 0.88 AT4G17600 0.89 AT4G29060 0.78 AT5G28500 0.91 3 AT3G18390 0.91 AT5G52440 0.87 AT1G22700 0.88 AT5G55220 0.76 AT4G37510 0.90 4 AT4G17600 0.90 AT1G44920 0.85 AT1G07320 0.88 AT1G07320 0.76 AT4G29060 0.90 5 AT4G34090 0.90 AT1G22700 0.87 AT5G59250 0.88 AT1G12800 0.75 AT5G08650 0.89 6 AT2G37220 0.90 AT4G34830 0.85 AT2G37220 0.88 AT5G14260 0.75 AT1G62750 0.89 7 AT4G02530 0.89 AT1G67700 0.87 AT4G02530 0.87 AT4G01800 0.74 AT4G01800 0.89 8 AT5G23120 0.89 AT2G35410 0.85 AT1G03475 0.87 AT5G03940 0.74 AT2G41680 0.89 9 AT5G08650 0.88 AT3G01480 0.87 AT1G43560 0.87 AT4G02530 0.74 AT5G45930 0.89 10 AT1G11860 0.88 AT1G73110 0.85 AT2G34860 0.87 AT4G37510 0.74 AT1G04420 0.89 11 AT3G55330 0.88 AT3G29185 0.87 AT1G11860 0.87 AT3G01480 0.74 AT4G02530 0.89 12 AT1G03475 0.88 AT1G43560 0.86 AT2G47940 0.87 AT1G09340 0.74 AT2G36990 0.89 13 AT1G74070 0.88 AT1G17220 0.86 AT5G23120 0.87 AT2G41680 0.74 AT3G56650 0.88 14 AT2G34860 0.88 AT4G29060 0.87 AT1G45474 0.87 AT5G45390 0.73 AT3G16000 0.88 15 AT4G01800 0.88 AT3G07670 0.84 AT5G43750 0.87 AT4G28080 0.73 AT3G14930 0.88 16 AT1G07320 0.88 AT3G01370 0.79 AT5G14260 0.87 AT5G17230 0.73 AT5G03940 0.88 17 AT3G19480

/AT3G194990 0.88 AT3G16000 0.86 AT4G09650 0.87 AT5G08280 0.73 AT1G17220 0.88

18 AT1G43560 0.88 AT5G28500 0.85 AT3G55330 0.87 AT5G06290 0.73 AT3G63490 0.88 19 AT1G14030 0.87 AT2G21280 0.86 AT5G52970 0.86 AT1G62750 0.73 AT1G62780 0.88 20 AT5G59250 0.87 AT4G24090 0.82 AT3G18390 0.86 AT1G11860 0.73 AT3G04760 0.88 21 AT1G80030 0.87 AT1G60990 0.77 AT1G09340 0.86 AT3G54050 0.73 AT4G17600 0.88 22 AT5G14260 0.87 AT5G03940 0.85 AT1G02150 0.86 AT1G42970 0.73 AT5G23120 0.88 23 AT4G31850/

AT4G31860 0.87 AT2G30390 0.82 AT3G54050 0.86 AT1G22700 0.72 AT5G05740 0.88

24 AT1G55370 0.87 AT5G02710 0.84 AT3G27160 0.86 AT1G73110 0.72 AT1G22700 0.88 25 AT5G43750 0.87 AT2G34860 0.87 AT4G01800 0.86 AT1G74970 0.72 AT1G07320 0.88 26 AT1G74730 0.87 AT5G55220 0.86 AT3G04790 0.86 AT2G34860 0.72 AT1G71500 0.88 27 AT1G22700 0.87 AT3G09050 0.82 AT2G40490 0.86 AT4G01050 0.72 AT5G44650 0.87 28 AT1G54500 0.87 AT2G41680 0.84 AT3G19480 0.86 AT4G27600 0.72 AT3G01480 0.87 29 AT3G04790 0.87 AT3G16250 0.86 AT5G45680 0.85 AT4G27700 0.72 AT1G67700 0.87 30 AT1G44920 0.87 AT3G59870 0.71 AT3G46780 0.85 AT1G65260 0.72 AT4G34820 0.87 31 AT4G35450 0.87 AT4G37510 0.82 AT5G08050 0.85 AT1G08520 0.72 AT4G25370 0.87 32 AT4G09650 0.87 AT1G08520 0.85 AT5G08650 0.85 AT1G17220 0.72 AT3G09210 0.87 33 AT5G06290 0.87 AT5G46420 0.79 AT1G62750 0.85 AT4G17600 0.72 AT1G59840 0.87 34 AT1G62750 0.87 AT1G80030 0.80 AT5G06290 0.85 AT4G09650 0.72 AT1G80030 0.87 35 AT2G47940 0.87 AT5G53490 0.85 AT5G45390 0.85 AT3G18390 0.71 AT5G14320 0.87 36 AT3G58140 0.87 AT3G49140 0.82 AT2G38140 0.85 AT2G21280 0.71 AT1G03630 0.87 37 AT3G54050 0.87 AT3G53130 0.83 AT2G23670 0.85 AT2G40490 0.71 AT2G34860 0.87 38 AT1G20810 0.87 AT1G68590 0.86 AT5G07020 0.84 AT2G43560 0.71 AT4G34090 0.87 39 AT1G73110 0.86 AT3G20930 0.80 AT5G44520 0.84 AT3G07670 0.71 AT3G07670 0.87 40 AT5G45680 0.86 AT4G02530 0.86 AT2G41680 0.84 AT1G73060 0.71 AT4G33470 0.87 41 AT4G28080 0.86 AT1G03475 0.82 AT4G28080 0.84 AT1G43560 0.71 AT3G23700 0.87 42 AT1G09340 0.86 AT3G55250 0.83 AT1G67700 0.84 AT4G25080 0.71 AT2G30390 0.87 43 AT1G45474 0.86 AT1G62780 0.85 AT1G15980 0.84 AT4G01310 0.71 AT3G26710 0.87 44 AT1G14345 0.86 AT4G14870 0.81 AT3G11945 0.84 AT5G42270 0.71 AT3G18390 0.87 45 AT1G02150 0.86 AT5G66055 0.76 AT4G35450 0.84 AT5G51110 0.71 AT5G54600 0.86 46 AT3G52380 0.86 AT1G12800 0.85 AT2G47450 0.84 AT1G14345 0.71 AT4G34190 0.86 47 AT1G14270 0.86 AT2G17033 0.75 AT3G23700 0.84 AT3G26710 0.71 AT5G42310 0.86 48 AT2G41680 0.86 AT3G62910 0.85 AT4G29060 0.84 AT4G35250 0.71 AT4G39040 0.86 49 AT5G07020 0.86 AT1G76450 0.86 AT3G61870 0.84 AT2G47940 0.70 AT1G63610 0.86 50 AT5G52970 0.86 AT3G56040 0.67 AT4G37510 0.83 AT3G23700 0.70 AT2G27680 0.86


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151

Supplementary Table 4: Transcripts showing expression patterns correlating with those of SIG3. The top 50 positively correlating transcripts were obtained from five online co-expression programs (ACT: http://www.arabidopsis.leeds.ac.uk/act/, ATTED-II: http://atted.jp/, BAR Expression Angler: http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi, CressExpress: http://cressexpress.org/ and GeneCAT: http://genecat.mpg.de/) using SIG3 as bait. COR is the coefficient of determination (r2). ACT ATTED-II BAR EXPRESSION

ANGLER CRESSEXPRESS GENECAT

AGI COR AGI COR* AGI COR AGI COR AGI COR 1 AT3G02690 0.84 AT1G67840 0.76 AT4G02260 0.80 AT1G76730 0.69 AT1G67840 0.81 2 AT1G56500 0.82 AT1G76730 0.77 AT1G26230 0.72 AT5G45170 0.69 AT1G67840 0.80 3 AT1G71810 0.82 AT2G03390 0.74 ATCG01100 0.72 AT4G37930 0.68 AT1G76730 0.79 4 AT1G54350 0.82 AT4G33630 0.68 AT3G09050 0.71 AT5G35170 0.68 AT5G59750 0.78 5 AT3G25690 0.82 AT2G01620 0.68 AT1G71480 0.70 AT2G03390 0.67 AT1G68830 0.78 6 AT4G33500 0.82 AT2G03550 0.73 AT1G20830 0.70 AT1G12250 0.67 AT3G17470 0.78 7 AT2G30390 0.82 AT3G55630 0.70 AT5G20220 0.68 AT1G65230 0.66 AT1G71480 0.77 8 AT1G07110 0.81 AT2G23390 0.73 AT5G58140 0.68 AT4G22890 0.66 AT2G30390 0.77 9 AT1G14150 0.80 AT3G18500 0.70 259295_AT 0.67 AT1G65260 0.66 AT1G31800 0.77 10 AT3G06510 0.80 AT5G03430 0.68 ATCG00640 0.67 AT1G68010 0.65 AT5G35170 0.77 11 AT5G58140 0.80 AT1G07440 0.71 AT1G06690 0.67 AT5G17230 0.65 AT1G56500 0.76 12 AT4G02260 0.80 AT5G58140 0.73 AT1G74070 0.67 AT2G23390 0.65 AT1G35340 0.76 13 AT1G52870 0.80 AT2G30170 0.74 ATCG00710 0.67 AT2G30950 0.65 AT2G21340 0.76 14 AT2G38330 0.79 AT4G25910 0.72 AT5G48730 0.67 AT4G33010 0.65 AT3G18500 0.76 15 AT3G26085 0.79 AT4G29220 0.63 AT3G57190 0.67 AT4G33470 0.64 AT2G29360 0.76 16 AT1G26230 0.79 AT4G30993 0.66 AT1G69523 0.67 AT2G31040 0.64 AT5G58140 0.75 17 AT5G51020 0.79 AT1G73170 0.56 AT2G21370 0.66 AT4G10300 0.64 AT2G21280 0.75 18 AT5G45170 0.79 AT1G02475 0.70 AT1G79430 0.66 AT1G23310 0.64 AT1G54350 0.75 19 AT3G55040 0.79 AT3G54360 0.61 ATCG00420 0.66 AT1G45474 0.64 AT3G01660 0.75 20 AT4G33470 0.79 AT3G06483 0.63 AT1G04350 0.66 AT1G51110 0.63 AT2G03550 0.75 21 AT5G10470 0.79 AT1G60870 0.60 AT1G49010 0.66 AT1G29700 0.63 AT5G13770 0.75 22 AT5G25630 0.79 245134_S_AT 0.54 AT1G01970 0.65 AT5G47840 0.63 AT1G51110 0.74 23 AT5G54290 0.79 AT5G40060 0.60 ATCG00160 0.65 AT5G59750 0.62 AT2G23390 0.74 24 AT5G58260 0.79 AT3G17470 0.65 AT3G21760 0.65 AT1G32160 0.62 AT2G04039 0.74 25 AT1G64680 0.79 AT2G29320 0.57 ATCG01090 0.65 AT1G35340 0.62 AT4G25910 0.74 26 AT1G70760 0.79 AT3G47430 0.69 AT5G50280 0.65 AT1G17220 0.62 AT1G29700 0.74 27 AT1G76730 0.79 AT2G24520 0.45 ATCG00490 0.65 AT2G30170 0.62 AT1G32160 0.74 28 AT5G36700 0.79 AT3G28080 0.64 ATCG00280 0.65 AT4G04640 0.62 AT1G12250 0.74 29 AT1G71480 0.78 AT4G22200 0.60 ATCG00800 0.65 AT3G12780 0.62 AT5G02830 0.74 30 AT5G03880 0.78 AT2G45740 0.68 ATCG00530 0.64 AT3G19800 0.62 AT1G02475 0.74 31 AT3G55630 0.78 AT1G06460 0.66 AT4G17360 0.64 AT4G23890 0.62 AT1G75100 0.74 32 AT4G17360 0.78 AT1G22630 0.70 AT1G12280 0.64 AT5G13650 0.62 AT4G33500 0.74 33 AT4G10300 0.78 AT4G02120 0.59 AT3G55630 0.64 AT5G09660 0.62 AT4G18810 0.74 34 AT1G05140 0.78 AT2G46580 0.52 AT1G54520 0.64 AT4G14210 0.62 AT3G26085 0.74 35 AT2G32480 0.78 AT3G62410 0.70 AT1G64680 0.64 AT5G05200 0.62 AT5G45170 0.73 36 AT3G17930 0.78 AT1G01320 0.68 ATCG00720 0.64 AT4G02260 0.61 AT3G09050 0.73 37 AT1G67840 0.78 AT4G14070 0.64 AT4G26640 0.64 AT3G55630 0.61 AT1G04350 0.73 38 AT4G27800 0.77 257634_S_AT 0.60 ATCG00790 0.64 AT5G53580 0.61 AT4G09350 0.73 39 AT4G10120 0.77 AT4G23890 0.69 ATCG00130 0.63 AT1G67840 0.61 AT4G04850 0.73 40 AT3G22210 0.77 AT1G65230 0.71 AT3G55040 0.63 AT1G02910 0.61 AT4G22200 0.73 41 AT1G73170 0.77 AT3G01660 0.67 AT5G62990 0.63 AT4G33500 0.61 AT1G80030 0.73 42 AT4G21210 0.77 AT4G34830 0.71 ATCG01050 0.63 AT3G22210 0.61 AT3G27925 0.73 43 AT5G57930 0.77 AT3G07550 0.43 AT5G18240 0.63 AT3G27925 0.61 AT1G23740 0.73 44 AT1G27480 0.77 AT5G08010 0.47 AT1G08810 0.63 AT5G42310 0.61 AT1G07010 0.73 45 AT4G33010 0.77 AT1G12250 0.70 ATCG00020 0.63 AT2G30390 0.61 AT3G17930 0.72 46 AT4G22890 0.77 AT5G35170 0.70 AT1G67280 0.62 AT1G09340 0.61 AT1G56500 0.72 47 AT2G36990 0.77 AT1G27480 0.70 AT4G13550 0.62 AT1G08550 0.61 AT4G33470 0.72 48 AT1G06240 0.76 AT5G11060 0.60 AT1G31190 0.62 AT1G68830 0.61 AT5G01920 0.72 49 AT5G56850 0.76 AT1G18170 0.70 AT5G45170 0.62 AT4G26530 0.61 AT5G44520 0.72 50 AT1G01790 0.76 AT5G57960 0.67 AT1G66840 0.62 AT2G34860 0.60 AT3G55040 0.72


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152

Supplementary Table 5: Transcripts showing expression patterns correlating with those of SIG4. The top 50 positively correlating transcripts were obtained from five online co-expression programs (ACT: http://www.arabidopsis.leeds.ac.uk/act/, ATTED-II: http://atted.jp/, BAR Expression Angler: http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi, CressExpress: http://cressexpress.org/ and GeneCAT: http://genecat.mpg.de/) using SIG4 as bait. COR is the coefficient of determination (r2). ACT ATTED BAR CRESSEXPRESS GENECAT AGI COR AGI COR AGI COR AGI COR AGI COR

1 AT5G39210 0.89 AT5G20935 0.84 AT5G39210 0.87 AT1G14150 0.84 AT1G14150 0.91 2 AT3G16250 0.87 AT5G39210 0.87 AT3G16250 0.85 AT5G58260 0.84 AT1G19150 0.91 3 AT3G55630 0.87 AT2G01870 0.82 AT5G58260 0.85 AT2G39470 0.83 AT2G39470 0.90 4 AT5G58260 0.86 AT1G23400 0.80 AT1G20020 0.84 AT3G23700 0.82 AT5G58260 0.89 5 AT1G26230 0.86 AT2G03550 0.81 AT1G14150 0.84 AT1G15980 0.82 AT1G15980 0.89 6 AT1G20020 0.86 AT5G52780 0.81 AT1G27480 0.84 AT1G70760 0.82 AT3G16250 0.89 7 AT1G14150 0.85 AT1G26230 0.82 AT1G70760 0.82 AT5G09660 0.82 AT1G65230 0.89 8 AT1G27480 0.85 AT3G09050 0.81 AT1G15980 0.81 AT1G76450 0.81 AT1G03630 0.88 9 AT4G18370 0.84 AT1G27480 0.82 AT3G55630 0.81 AT5G53490 0.81 AT5G39210 0.88 10 AT3G09050 0.84 AT3G01660 0.79 AT2G39470 0.81 AT1G68010 0.81 AT3G48420 0.88 11 AT5G20935 0.84 AT1G78995 0.76 AT5G20935 0.81 AT3G16250 0.80 AT1G70760 0.88 12 AT1G18170 0.83 AT1G14150 0.84 AT1G74880 0.81 AT1G19150 0.79 AT4G33470 0.88 13 AT2G01860/


14 AT4G33500 0.83 AT3G63160 0.77 AT1G65230 0.81 AT1G74880 0.79 AT1G55370 0.87 15 AT3G22210 0.82 AT1G73655 0.79 AT2G05310 0.81 AT3G25690 0.79 AT1G09340 0.87 16 AT1G23400 0.82 AT5G02710 0.81 AT1G23400 0.80 AT1G64680 0.79 AT1G67700 0.87 17 AT4G10300 0.82 AT3G01440 0.80 AT3G22210 0.80 AT3G56650 0.79 AT1G18730 0.87 18 AT2G28605 0.82 AT4G26530 0.77 AT3G23700 0.80 AT2G34860 0.79 AT1G27480 0.87 19 AT1G70760 0.82 AT1G08550 0.77 AT2G01870 0.80 AT3G55330 0.79 AT3G56650 0.87 20 AT1G66820 0.82 AT3G20680 0.78 AT5G52100 0.80 AT3G51420 0.79 AT3G48200 0.87 21 AT2G37450 0.82 AT5G57930 0.79 AT2G01590 0.80 AT5G23120 0.79 AT5G52970 0.86 22 AT2G30390 0.82 AT3G16250 0.84 AT3G01440 0.80 AT5G39210 0.78 AT5G09660 0.86 23 AT3G02690 0.82 AT3G04550 0.77 AT3G25690 0.80 AT3G54050 0.78 AT4G39710 0.86 24 AT3G25690 0.82 AT1G07440 0.75 AT5G52780 0.80 AT1G75460 0.78 AT3G01500 0.86 25 AT2G03420 0.82 265704_AT 0.81 AT4G10300 0.80 AT1G32060 0.78 AT5G53490 0.86 26 AT2G35370 0.82 AT1G55370 0.79 AT4G39710 0.80 AT1G32080 0.78 AT3G01480 0.86 27 AT1G15980 0.81 AT5G58260 0.81 AT5G45680 0.80 AT3G47070 0.77 AT5G20935 0.86 28 AT1G65230 0.81 AT5G55740 0.77 AT3G51510 0.79 AT4G26530 0.77 AT2G03550 0.86 29 AT2G39470 0.81 AT1G22630 0.77 AT5G36700 0.79 AT1G26230 0.77 AT3G20680 0.86 30 AT4G33470 0.81 AT1G65420 0.65 AT4G28030 0.79 AT2G05310

/AT4G13500 0.77 AT2G44920 0.86

31 AT1G73655 0.81 AT3G15570 0.72 AT1G04640 0.79 AT2G44920 0.77 AT5G43750 0.86 32 AT4G39710 0.81 263750_AT 0.79 AT2G04700 0.79 AT3G01500 0.77 AT1G16080 0.86 33 AT4G28030 0.81 AT3G55630 0.71 AT2G37450 0.79 AT1G22630 0.77 AT1G22630 0.86 34 AT2G05310 0.81 AT3G22210 0.81 AT5G02710 0.79 AT1G20810 0.77 AT3G22210 0.86 35 AT1G73060/




49 AT5G53580 0.80 AT2G36430 0.61 AT2G31040 0.78 AT4G38970 0.76 AT2G01590 0.85 50 AT1G16880 0.80 AT1G70760 0.79 AT1G18730 0.78 AT2G46820 0.76 AT5G23120 0.85


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153

Supplementary Table 6: Transcripts showing expression patterns correlating with those of SIG5. The top 50 positively correlating transcripts were obtained from five online co-expression programs (ACT: http://www.arabidopsis.leeds.ac.uk/act/, ATTED-II: http://atted.jp/, BAR Expression Angler: http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi, CressExpress: http://cressexpress.org/ and GeneCAT: http://genecat.mpg.de/) using SIG5 as bait. COR is the coefficient of determination (r2). ACT ATTED-II BAR

EXPRESSION ANGLER

CRESSEXPRESS GENECAT

AGI COR AGI COR AGI COR AGI COR AGI COR 1 AT3G56290 0.84 263796_AT 0.74 AT3G56290 0.81 AT3G56290 0.61 AT3G56290 0.82 2 AT1G78510 0.82 AT5G50100 0.72 AT1G78510 0.79 AT2G24540/

AT2G24545 0.52 AT3G61220 0.76

3 AT2G46830 0.80 AT3G56290 0.76 AT2G31380 0.76 AT4G37760 0.50 AT5G50100 0.76 4 AT5G50100 0.80 AT4G13010 0.68 AT1G53090 0.75 AT3G24190 0.45 AT5G35970 0.74 5 AT1G76570 0.77 AT4G37760 0.67 AT4G37760 0.75 AT5G61670 0.45 AT2G24540 0.74 6 AT1G01520 0.77 AT1G79270 0.66 AT5G50100 0.75 AT1G17050 0.44 AT1G06430 0.74 7 AT2G46670

/AT2G46790 0.76 AT5G15910 0.64 AT3G21670 0.74 AT5G35970 0.44 AT5G19850 0.74



21 AT2G46340 0.71 AT4G11570 0.66 AT3G61220 0.68 AT1G64500 0.38 AT1G53670 0.68 22 AT5G19850 0.71 AT1G55960 0.62 AT5G64840 0.68 AT3G47500 0.37 AT1G50250 0.68 23 AT5G62430 0.70 AT1G78510 0.66 AT4G31870 0.67 AT2G26800 0.37 AT5G58770 0.68 24 AT5G64840 0.70 AT5G43150 0.55 AT1G73650 0.67 AT5G58770 0.37 AT1G16720 0.67 25 AT3G24190 0.70 AT3G24170 0.58 AT2G38210 0.66 AT3G21390 0.37 AT1G19700 0.67 26 AT3G61220 0.70 AT4G34350 0.64 AT5G53970 0.66 AT4G31870 0.37 AT2G21970 0.66 27 AT5G67030 0.69 AT2G31380 0.64 AT5G67030 0.65 AT5G43850 0.37 AT5G53970 0.66 28 AT1G05170 0.69 AT2G46830 0.64 AT2G24540 0.65 AT5G58870 0.36 AT5G57040 0.66 29 AT1G06430 0.69 AT1G02820 0.6 AT1G53670 0.64 AT3G17510 0.36 AT2G46735 0.66 30 AT2G21320 0.69 AT1G17050 0.62 AT1G76570 0.64 AT1G79270 0.36 AT2G33250 0.66 31 AT5G64940 0.69 AT5G43850 0.61 AT5G58770 0.64 AT2G46830 0.35 AT3G21890 0.66 32 AT5G52570 0.69 AT5G42810 0.51 AT5G52570 0.63 AT2G31380 0.35 AT2G15020 0.66 33 AT5G15450 0.69 AT3G57020 0.54 AT4G25700 0.63 AT5G50100 0.35 AT1G50020 0.66 34 AT1G64500 0.68 AT5G23730 0.58 AT1G47530 0.63 AT5G64840 0.35 AT1G07250 0.66 35 AT1G07010 0.68 AT1G66330 0.62 AT4G02920 0.63 AT1G16720 0.34 AT1G07010 0.65 36 AT4G37760 0.68 AT5G15850 0.62 AT3G14690 0.63 AT1G19700 0.34 AT1G71480 0.65 37 AT1G18660 0.68 AT3G47420 0.54 AT4G26150 0.62 AT2G41040 0.34 AT1G75100 0.65 38 AT2G15020 0.68 AT5G35460 0.55 AT4G00050 0.62 AT3G11900 0.34 AT1G02820 0.65 39 AT5G58770 0.68 AT3G10420 0.6 AT5G42270 0.62 AT1G76570 0.33 AT5G61670 0.65 40 AT1G66330 0.68 AT2G15020 0.61 AT1G79510 0.62 AT1G06570 0.33 AT2G37970 0.65 41 AT1G07180 0.67 AT5G58870 0.63 AT1G07010 0.62 AT2G46340 0.33 AT2G41120 0.65 42 AT4G31870 0.66 AT5G53970 0.59 AT3G12320 0.61 AT5G42760 0.33 AT5G67370 0.65 43 AT2G32950 0.66 AT2G41250 0.6 AT1G22750 0.61 AT1G53670 0.33 AT5G62430 0.64 44 AT1G70610 0.66 266720_S_AT 0.57 AT3G21390 0.61 AT4G14420 0.33 AT1G79600 0.64 45 AT4G17880 0.66 AT4G31870 0.58 AT5G35970 0.61 AT4G27030 0.32 AT1G79270 0.64 46 AT1G73870 0.65 AT3G16175 0.56 AT1G50250 0.61 AT4G17840 0.32 AT1G22750 0.64 47 AT2G34720 0.65 AT5G64170 0.58 AT1G79270 0.61 AT2G41120 0.32 AT1G32520 0.64 48 AT1G02820 0.65 AT2G21320 0.59 AT1G02820 0.61 AT4G13010 0.32 AT4G26850 0.64 49 AT4G27030 0.65 AT5G59400 0.55 AT2G40400 0.60 AT1G06040 0.32 AT2G46830 0.63 50 AT3G21390 0.65 AT3G09600 0.58 AT3G10230 0.60 AT1G73650 0.32 AT5G58870 0.63


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154

Supplementary Table 7: Transcripts showing expression patterns correlating with those of SIG6. The top 50 positively correlating transcripts were obtained from five online co-expression programs (ACT: http://www.arabidopsis.leeds.ac.uk/act/, ATTED-II: http://atted.jp/, BAR Expression Angler: http://bar.utoronto.ca/ntools/cgi-bin/ntools_expression_angler.cgi, CressExpress: http://cressexpress.org/ and GeneCAT: http://genecat.mpg.de/) using SIG6 as bait. COR is the coefficient of determination (r2). ACT ATTED II BAR EXPRESSION

ANGLER CRESSEXPRESS GENE CAT

AGI COR AGI COR AGI COR AGI COR AGI COR 1 AT1G17220 0.91 AT5G02710 0.87 AT4G24700 0.99 AT2G03410/

AT2G03420 0.82 AT4G29060 0.91

2 AT3G23700 0.90 AT4G38160 0.87 AT1G15080 0.98 AT4G29060 0.81 AT4G19100 0.90 3 AT4G31850/


4 AT5G57930 0.89 265704_AT 0.86 AT5G32450 0.98 AT1G08520 0.81 AT3G29185 0.90 5 AT3G63410 0.89 AT4G19100 0.81 AT2G38880 0.98 AT4G34830 0.80 AT5G03940 0.90 6 AT2G37450 0.89 AT3G20680 0.81 AT4G01570 0.98 AT5G05740 0.80 AT1G12800 0.90 7 AT1G32550 0.88 AT4G34830 0.84 AT1G07970 0.98 AT3G47650 0.80 AT5G02710 0.89 8 AT5G51110 0.88 AT5G46580 0.85 AT5G24400 0.98 AT5G57930 0.80 AT1G05190 0.89 9 AT5G11450 0.88 AT3G62910 0.85 AT3G06790 0.98 AT2G37660 0.79 AT1G62780 0.89 10 AT5G45680 0.88 AT5G39210 0.83 AT3G62330 0.98 AT3G51820 0.79 AT5G44650 0.89 11 AT1G62750 0.88 AT3G49140 0.82 AT2G21195 0.97 AT4G17600 0.79 AT1G08540 0.89 12 AT4G04350 0.88 AT3G04760 0.81 AT5G18570 0.97 AT2G41680 0.79 AT3G07670 0.89 13 AT4G29060 0.88 AT4G29060 0.86 AT4G19400 0.97 AT1G17220 0.79 AT1G07320 0.89 14 AT1G02910 0.88 AT3G47450 0.82 AT3G42090 0.97 AT5G57930 0.79 AT3G04760 0.89 15 AT5G44650 0.88 AT5G52100 0.84 AT3G03490 0.97 AT3G01480 0.79 AT1G74970 0.88 16 AT5G05740 0.87 AT3G23700 0.84 AT3G13940 0.97 AT1G14030 0.79 AT4G34820 0.88 17 AT3G07670 0.87 AT3G55330 0.85 AT4G38890 0.97 AT5G14320 0.78 AT5G05740 0.88 18 AT4G34090 0.87 AT1G01080 0.84 AT4G20170 0.96 AT1G32550 0.78 AT3G47650 0.88 19 AT2G20890 0.87 AT2G36000 0.78 AT3G07400 0.95 AT5G11450 0.78 AT1G59840 0.88 20 AT2G03420 0.87 AT5G28500 0.84 AT1G79750 0.94 AT3G24430 0.78 AT1G62750 0.88 21 AT4G34820 0.86 AT4G14890 0.84 AT1G49530 0.94 AT1G68590 0.78 AT5G57930 0.88 22 AT4G36390 0.86 AT1G05190 0.84 AT5G08180 0.93 AT5G52100 0.77 AT1G04420 0.88 23 AT1G49380 0.86 AT3G56010 0.82 AT5G08300 0.93 AT4G18370 0.77 AT4G17600 0.88 24 AT3G01480 0.86 AT3G12930 0.84 AT1G45170 0.92 AT3G26060 0.77 AT5G14910 0.88 25 AT2G41680 0.86 AT3G03710 0.80 AT1G75950 0.89 AT3G52380 0.77 AT5G14320 0.88 26 AT4G15110 0.86 AT1G74850 0.80 ATMG00580 0.89 AT1G04420 0.77 AT5G53580 0.88 27 AT1G05140 0.86 AT5G22640 0.79 AT5G62740 0.88 AT1G03630 0.77 AT4G37510 0.87 28 AT4G17600 0.86 AT5G57180 0.70 AT1G80280 0.88 AT1G12800 0.77 AT1G17220 0.87 29 AT1G42970 0.86 AT3G22210 0.83 AT2G31910 0.88 AT4G19100 0.76 AT4G39040 0.87 30 AT1G54500 0.86 AT1G60600 0.82 ATCG00670 0.85 AT4G01310 0.76 AT5G54600 0.87 31 AT5G30510 0.85 AT3G07670 0.82 AT3G14460 0.85 AT3G56910 0.76 AT3G15190 0.87 32 AT1G01970 0.85 AT2G29180 0.83 AT3G30230 0.85 AT4G24090 0.76 AT2G33450 0.87 33 AT3G56010 0.85 AT2G37450 0.71 AT1G07770 0.83 AT5G11480 0.76 AT3G56650 0.87 34 AT5G42765 0.85 AT4G11100 0.78 AT3G58170 0.83 AT4G18480 0.76 AT4G14890 0.87 35 AT1G74850 0.85 AT5G03940 0.83 AT1G48060 0.82 AT3G55330 0.76 AT5G55740 0.87 36 AT1G71720 0.85 AT1G08540 0.83 AT5G59910 0.82 AT5G51110 0.76 AT5G11480 0.87 37 AT5G62840 0.85 AT5G44650 0.83 AT5G05010 0.81 AT3G63490 0.76 AT5G39210 0.87 38 AT3G26060 0.85 AT5G55220 0.84 AT5G37420 0.80 AT1G35680 0.76 AT1G48350 0.87 39 AT3G47650 0.85 AT5G55740 0.79 AT2G13020 0.80 AT5G66470 0.76 AT5G55220 0.87 40 AT1G70200 0.85 AT5G11480 0.82 AT1G44760 0.80 AT4G31850 0.76 AT3G12930 0.87 41 AT1G76450 0.85 AT1G68590 0.84 AT5G53430 0.79 AT1G31920 0.76 AT3G63490 0.87 42 AT3G55330 0.85 AT4G39040 0.83 256643_AT 0.79 AT2G24060 0.76 AT5G28500 0.87 43 AT3G55800 0.85 AT1G14030 0.82 AT1G04050 0.79 AT1G14270 0.76 AT2G47940 0.87 44 AT2G21385 0.85 AT1G49975 0.83 AT3G04920 0.79 AT4G28080 0.75 AT2G33180 0.87 45 AT3G52380 0.84 AT2G31890 0.79 AT5G29020 0.79 AT3G15850 0.75 AT4G17560 0.87 46 AT2G34860 0.84 AT4G21190 0.73 AT2G15510 0.79 AT3G26710 0.75 AT2G29180 0.87 47 AT2G37660 0.84 AT4G39620 0.78 AT5G20720 0.79 AT3G63410 0.75 AT1G22700 0.87 48 AT3G08010 0.84 245843_AT 0.68 AT2G12920 0.79 AT1G48350 0.75 AT3G26710 0.87 49 AT5G38520 0.84 AT4G16390 0.80 ATCG00040 0.78 AT3G25920 0.75 AT4G31850 0.87 50 AT4G24770 0.84 245388_AT 0.82 AT4G32080 0.78 AT3G55800 0.75 AT2G37660 0.87


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155

9.7 Acknowlegements

I would like to acknowledge the help given to by my supervisors Kate and Ian.

Thank you particularly to Ian in encouraging me to undertake a Masters, and in

providing insight throughout, and Kate, for helping me on a day-to-day basis. I also

would like to thank all the members of the Small lab who helped me throughout:

Sandra, Cathie, Aaron, Peter, Clement, Sheng and visiting member Oren, all of

whom provided much needed help and encouragement. Thank-you also to John and

Andy for the valuable advice. Finally, particular thanks to Jenny, Jude, Deb, Rosie

and Lyn, who keep things running.

defining the function of plant sigma factorsdefining the function of plant sigma factors . this...

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