analyzing transcription modules in the pathogenic yeast candida albicans elik chapnik yoav amiram...

Analyzing transcription modules in the pathogenic yeast Candida albicans

Elik ChapnikYoav Amiram

Supervisor:Dr. Naama Barkai

Background (1) – C. albicans

• Opportunistic fungal pathogen• Genome was recently sequenced• Lack of sufficient annotation of genes• Distant cousins: S. cerevisiae

– SC is the yeast model organism– SC is used as a model to study CA– comparative genomics: what are the tools?

Genes

Con

ditio

ns

• BLAST• DNA Microarrays

– monitors 1000’s of genes simultaneously

– co-expression patterns canprovide functional links

• Cluster Analysis, SVD– limited size of data sets– mutually exclusive clusters– expression analyzed under all conditions

Background (2) – Tools

• “Transcription Modules” (TMs):– a self-consistent regulatory unit

– co-regulated genes and their regulating conditions

• Signature Algorithm– global decomposition into TMs

– robust, fast

– integration of external data

– if no a-priory information exists, can be applied iteratively (ISA)

Background (2) – Tools

• Expression levels of SC have been measured for over 1000 conditions

• Emerging quantities of CA microarray experiments• Genomes are both fully sequenced

What can be done with all this?1. Large scale expression analysis of CA (Dr. Barkai’s

group and Prof. Judith Berman)

2. Use the homology between SC and CA− focus on selected annotated SC transcription modules− use the information from SC TMs to study CA

Better understanding of CA via SC data

Measures:1. computing pair-wise

correlations between genes in TMs (Pearson correlation coefficient)

Annotating C. albicans ORFs with unknown functions

Main goal of the project (1)

Measures (cont.):2. Search for cis-regulatory elements (CREs) in

the upstream region of genes– find over represented sequence in the upstream

region of genes in the SC modules, using computational DNA pattern recognition methods

– search for previously identified cis-regulatory elements in the CA homologue modules

Main goal of the project (2)

• Programming software: MATLAB 6.5

• Cluster analysis tools: GeneHopping

• Sequence data: Stanford Genome Technology center

• Expression data: C. albicans expression data was provided by Prof. Berman’s lab

• Software for CRE prediction: MEME, TESS, EPD, CONSENSUS

Tools and methods

Generating modules

BLAST

signature algorithm

Yeast Module

Candida Refined Module

Candida Homologue

Module

And the modules are:

-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 1

Identifying co-regulation

Yeast Module

Candida Homologue

Module


Find all pair-wise correlation in the module genes using the Pearson correlation coefficient

Apply statistical significance tests:generate random modules to compute Z-scores

Average Correlation+

Z-score


Z-score


Z-score> <

1. Generate random modules by reshuffling genes in whole genome database

2. Compute average correlations for the random and “real” modules

3. Calculate mean and standard deviation from random modules set

4. Calculate Z-scores of “real” modules5. High Z-score (>2) represents a

statistically significant correlated module

Statistical analysis

BLAST

signature algorithm

Yeast Module


Candida Homologue

Module

Two slides ago…

Yeast Module

Candida Homologue

ModuleRejected

Overlapped

Overlapped


Included

Included

Find common CRE in Yeast

Module Rejected

Identification of cis-regulatory elements

Candida Homologue

ModuleRejected

Overlapped

Yeast Module

Overlapped


Included

Included

Rejected

our prediction for CRE % and Mean CRE in each module

CRE

CRE

CRE

CRE CRE ?

Identification of cis-regulatory elements

Average Correlation 0.34816

Z-Score = 106.9

Results – co-regulation of SC aa Module

Module type

Module nameS. cerevisiae

C. albicans homologue

module

C. albicans refined module

Amino acid Biosynthesis

0.34816 ±0.0029[106.9]

0.043325±0.0038

[7.5693]

0.26942±0.0082

[31.038]

Cell Cycle G10.2921±0.0028

[90.0693]

0.0475±0.0047

[7.0945]

0.18±0.0079

[20.926]

rRNA Processing0.674±0.0045

[142.113]

0.3216±0.0051

[60.2796]

0.3097±0.0023

[127.507]

Proteosome Subunits

0.4211±0.0054

[71.2679]

0.1611±0.0078

[18.8772]

0.2342±0.0045

[48.9743]

0.9-1.0

0.8-0.9

0.7-0.8

0.6-0.7

0.5-0.6

0.4-0.5

0.3-0.4

0.2-0.3

0.1-0.2

0.0-0.1

Mean Correlation±Standard Deviation

[Z-Score]

Results – co-regulation of modules

Amino acid

Biosynthesis(13.7)

Cell Cycle G1

(12.9)

rRNA Processing

(12.6)

Proteosome subunits(11.31)

Amino acidBiosynthesis

(13.7)---

-0.0216±0.0017

[-35.0476]

0.0042±0.0025

[-13.9315]

0.0337±0.0031

[-1.6166]

Cell Cycle G1

(12.9)

-0.0216±0.0017

[-35.0476]---

0.0779±0.0024

[16.1595]

0.0203±0.0025

[-7.2475]

rRNA Processing

(12.6)

0.0042±0.0025

[-13.9315]

0.0779±0.0024

[16.1595]---

-0.1241±0.0033

[-48.9049]


0.0337±0.0031

[-1.6166]

0.0203±0.0025

[-7.2475]

-0.1241±0.0033

[-48.9049]---

Modules are anti-regulated

Modules are co-regulated

Results – co-regulation between SC modules

Amino acid

Biosynthesis(13.7)

Cell Cycle G1

(12.9)

rRNA Processing

(12.6)


Amino acidBiosynthesis

(13.7)---

-0.0078±0.0051

[-4.5555]

0.0622±0.0032

[14.8978]

-2.02E-04±0.0041

[-3.5271]

Cell Cycle G1

(12.9)

-0.0078±0.0051

[-4.5555]---

0.0117±0.0034

[-0.9320

0.0341±0.0041

[4.7324]

rRNA Processing

(12.6)

0.0622±0.0032

[14.8978]

0.0117±0.0034

[-0.9320]---

-0.0028±0.0026

[-6.6787]


-2.02E-04±0.0041

[-3.5271]

0.0341±0.0041

[4.7324]

-0.0028±0.0026

[-6.6787]---

Modules are anti-regulated

Modules are co-regulated

Results – co-regulation between CA modules

Candida Homologue

ModuleRejected

Overlapped

Yeast Module

Overlapped


Included

Included

Rejected

TGACTCCRE

CRE

CRE

CRE CRE ?

Results - cis-regulatory elements in the aa modules

46%, 1.25

34%, 1.06

54%, 1.29

53%, 1.22

29%, 1.00

52%, 1.18

CRE %, Mean CRE

Results – cis-regulatory elements chart

Module type

Module name

S. cerevisiae

C. albicans homologue

module

Rejected genes

Included genes

Overlapped genes

C. albicans refined module

Amino acid Biosynthesis

15646%1.25

9834%1.06

7729%

1

1354%1.285

2152%1.181

3453%1.222

rRNA Processing

12.6

6167%1.585

5542%1.304

944%1.25

21932%1.225

4641%1.315

26534%1.24

Protesosome subunits

10.14

4137%

1

3719%1.428

1118%

1

3816%1.166

2619%1.6

6417%1.363

Protesosome subunits

11.31

4562%1.071

3923%

1

1323%

1

3813%

1

2623%

1

6417%

1

Cell Cycle G1 12.9

12459%1.41

7146%

1

5242%

1

1429%

1

1958%

1

3345%

1

Cell Cycle G1 16.4

15852%1.378

8845%1.025

6740%1.037

1323%

1

2162%

1

3447%

1

# of GenesCRE %

Mean CRE

• Co-regulation:– Different co-regulation schemes can point out

alternative gene function between SC and CA– Investigate the relations between “real” CA modules

and refined CA modules with a similar annotation• cis-regulatory elements:

– CRE as a function of homology– CRE as a function of co-regulation– Low expression of SC CRE as an indicator for

biological importance– Not all CREs are conserved between the organisms:

GCN4 vs. GAL4

Conclusions

• Experimental validation of functional assignment:– verify if the cis-regulatory elements found in

C. albicans are biologically active– test the conservation of function across

homologue modules of S. cerevisiae and C. albicans

Future research tasks

• Naama Barkai – Weizmann Institute

• Judith Berman – University of Minnesota

• Sven Bergmann – Barkai’s group• Jan Ihmels – Barkai’s group

Acknowledgements

analyzing transcription modules in the pathogenic yeast candida albicans elik chapnik yoav amiram...

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