walnut genome analysis - university of …walnutresearch.ucdavis.edu/2009/2009_35.pdf · walnut...

WALNUT GENOME ANALYSIS Jan Dvorak, Ming-Cheng Luo, Mallikarjuna Aradhya, Dianne Velasco, Charles A. Leslie, Sandie L. Uratsu, Monica T. Britton, Russell L. Reagan, Gale H. McGranahan and Abhaya M. Dandekar ABSTRACT The goal of this project is to build a set of comprehensive genomic tools for walnut. These will facilitate a more precise evaluation of breeding populations and will accelerate development of improved walnut cultivars to address the needs of both California growers and the consumers of this important agricultural commodity. Development of these tools includes (1) construction of a physical map of the walnut genome, (2) a detailed survey of walnut gene expression, and (3) fine-scale genetic and association mapping of economically important traits. Two bacterial artificial chromosome (BAC) libraries comprising a total of 129,024 clones (64,512 each) were constructed from Persian walnut (Juglans regia cv. Chandler) DNA. Average insert lengths were 135 kb (HindIII) and 120 kb (MboI) for the two libraries respectively, providing approximately 20x genome coverage. To date 124,890 BAC clones have been fingerprinted using the five-color SNaPshot HICF technology. The fingerprints have been edited, and 113,073 could be used for contig assembly with the FPC program. A total of 916 contigs and 4,830 singletons were obtained. A total of 54,912 BAC end sequences (BES) have also been produced, one BES per BAC. A mapping population of 265 progeny of the cross Chandler’ x ‘Idaho that segregates for all commercially important walnut traits was evaluated with 15 SSRs to verify the parentage of F1 progeny. In addition, the genetic structure of 399 trees among 204 diverse accessions, including 62 elite germplasm used for breeding, was employed in the development of a population for association mapping of walnut traits. A total of 21 cDNA libraries were constructed for the characterization of the walnut transcriptome using next generation DNA sequencing. These genomic tools will significantly strengthen ongoing California walnut breeding efforts by facilitating marker-assisted selection strategies. The use of well-defined markers will significantly increase selection efficiency, the discovery of new genes, and rapid integration of these genes into genetic backgrounds adapted to California environmental conditions, thus accelerating the development of improved walnut cultivars. PROJECT OBJECTIVES

1. Physical mapping of the walnut genome 2. Genetic and association mapping of economically important walnut traits 3. Functional mapping of the walnut genome 4. Development of a ‘Walnut Genome Resource (WGR)’, a web-based knowledge base of

walnut genomic information

California Walnut Board 35 Walnut Research Reports 2009

PROCEDURES Objective 1: Physical mapping of the walnut genome A physical map of the walnut genome will be built concurrent with development of the genetic map. To accomplish the construction of a physical map, walnut genomic DNA fragments were cloned in a bacterial artificial chromosome (BAC) vector. Each BAC clone was fragmented with different restriction enzymes and ordered into contiguous sequences based on the overlap of fragment patterns. Ends of the BAC clones were then sequenced using Sanger DNA sequencing technology. Each of the BAC end sequences (BES) generated by this process is collinear with the BAC segments and thus corresponds to the sequence of nucleotides along a walnut chromosome. The presence of gene sequence tags (GSTs) within the BES will be confirmed through their expression in walnut tissues (Objective 3). The physical map also provides a scaffold upon which to assemble the complete walnut genomic sequence when such sequencing is performed. Objective 2: Genetic and association mapping of economic traits in walnut. Two different approaches were proposed for walnut genome mapping: (1) Linkage analysis of a conventional mapping population derived from a cross between parents that differ for traits under consideration; and (2) Association genetic analysis of a natural population such as a germplasm collection with genotypes of unknown or mixed ancestry that represent a common gene pool. Extensive DNA libraries of both mapping and association mapping populations have been developed. We are currently developing genotypic data using microsatellite polymorphisms to validate the full-sib nature of the mapping population and to assess the genetic structure of the association mapping population. Objective 3: Functional mapping of the walnut genome Genetic and physical maps describe the structure of the genome, but it is also essential to precisely document gene expression and to link specific traits (Objective 2) and GSTs (Objective 1) to underlying metabolic and biochemical processes. A key step toward this is gene transcript sequencing to identify expressed genes. Twenty tissue-specific gene transcript libraries have been constructed using tissue samples collected over the 2008 growing season. These transcripts were copied into DNA, cloned and high-throughput Illumina Solexa sequencing is in progress to generate millions of Expressed Sequence Tags (ESTs). The ESTs will be deposited in public databases, compiled, and annotated with computer analysis to identify genes involved in important metabolic pathways. The ESTs will be analyzed to validate GSTs through their expression pattern in different walnut tissues. Objective 4: Development of a ‘Walnut Genome Resource (WGR)’, a web-based knowledge base of walnut genomic information. A web-based browser is being developed as data from Objectives 1, 2 and 3 begins to accumulate. The database will contain all physical and linkage mapping information as well as all EST sequences and their integration with the walnut physical and genetic maps to better inform the walnut research community and to provide access to these genomic resources.


RESULTS AND DISCUSSION Objective 1: Physical mapping of the walnut genome Physical mapping consists of cloning large genomic DNA fragments in a suitable vector such as a BAC and ordering the fragments so that their sequence reflects the order of nucleotides in a chromosome. The first step in the construction of physical maps is the construction of BAC libraries. Two bacterial artificial chromosome (BAC) libraries were constructed from DNA isolated from in vitro grown shoots of Persian walnut (Juglans regia cv. Chandler). Walnut genomic DNA was fragmented with either HindIII or MboI restriction endonucleases. A total of 129,024 clones, 64,512 per BAC library, were arrayed in 336 384-well plates. The average insert size was around 135 kb and 120 kb for the HindIII and MboI libraries, respectively. Assuming the walnut genome is approximately 800 Mb, these two BAC libraries represent approximately 20x genome equivalents. Each BAC library has been stored in triplicate. BAC fingerprinting and BAC end sequencing were initiated in 2008. We are using a previously developed fluorescence-based, high-throughput BAC DNA fingerprinting technique (Luo et al. 2003) that sizes DNA fragments from each BAC clone by capillary electrophoresis, creating a unique fragment profile or BAC clone fingerprint for each BAC clone (Fig. 1). The “SNaPshot” fragment pattern for each BAC clone, using a different restriction endonuclease, is analyzed using a 96-capillary ABI3730XL robotic DNA sequence analyzer. These BAC fingerprints are rapidly edited using a previously developed computer software (GenoProfiler; You et al. 2006). Another computer program, FPC (Soderlund et al. 2000), searches for overlaps between BAC fingerprints, creating contiguous sequences of BAC clones (contigs). These contigs (Fig. 2) reflect the sequences of nucleotides along individual chromosomes. As of November 20, 2009, 124,890 BAC clones have been fingerprinted with the 5-dye SNaPshot fingerprinting technique. The fingerprints have been edited, and 113,073 could be used for contig assembly with the FPC program. A total of 916 contigs and 4,830 singletons were obtained. A total of 54,912 BAC end sequences (BES) have also been produced, one BES per BAC. Objective 2: Genetic and association mapping of economically important traits in walnut Genotyping of mapping populations to confirm their full-sib origin: The F1 mapping population consisting of 265 individuals of the cross “Chandler x Idaho” has been genotyped and parentage confirmed. We have augmented the DNA and it will be available for the SNP genotyping when the platform is ready in the first quarter of 2010. The phenotypic data on traits of breeding value: (1) Lateral vs. terminal bearing; (2) Leafing and harvesting dates; (3) Nut size; (4) Shell thickness; (5) Shell seal; (6) Plumpness; (7) Fill (nut/kernel ratio); (6) Kernel color and; (7) Yield have been recorded for the second year. Association mapping using the walnut germplasm collection: We have increased the association mapping population of English walnut to 452 trees and they have been genotyped using 21 microsatellite loci. A cluster analysis (CA) of the microsatellite data indicated mild genetic structure within cultivated walnut (Fig. 3). The elite germplasm consisting of cultivars, breeders’ selections, and germplasm frequently used in breeding programs showed moderate differentiation. The Chinese germplasm appeared to be unique and exhibited considerable


divergence and closely allied with SE Asian germplasm. Walnuts from South Asia are found to be the most diverse and there was further evidence of differentiation within this group. A small group of West Asian germplasm is nested within this group. Both South and West Asian germplasm have been extensively used in the California breeding program. Overall, the cultivated walnut (Juglans regia) shows a marginal differentiation and is suitable for association genetic analysis. The principle component analysis (PCA) of the walnut microsatellite data basically confirmed the results of CA and however, the genetic differentiation among the groups is more amplified and elucidated lot clearly (Fig. 4). All the six groups illustrated in the CA were evident in the PCA, but there was significant overlapping among clusters and also the minimum spanning tree superimposed on the PC plot suggested that the there is still significant genetic affinity within and among the groups (Fig. 5). The data has been further analyzed to quantify and describe the genetic diversity in the collection. There is significant deficiency of heterozygotes at all loci as compared to Hardy-Weinberg expected frequencies (Table 1) indicating some level of population substructuring within the collection as illustrated in the cluster analysis. All the six groups exhibited in the CA and PCA showed significant inbreeding within groups suggesting a complex but still mild population structure within the walnut germplasm collection (Table 2). Orthogonal partitioning of genetic variation indicated that the most variation is locked up within groups among individuals (~87%) and only a small proportion of the total variation is explained by genetic differentiation among groups (13%) (Table 3). However, the FST indicated that there is still significant differentiation among groups. Objective 3: Functional mapping of the walnut genome Functional mapping represents a composite profile the transcriptome of walnut. The transcriptome represents the transcribed RNA of any particular organism. In plants, gene expression is both temporally and spatially regulated in different tissues and organ systems. A profile of the transcriptome in a plant organ such as fruit, for example, would sample all mRNA expressed in this organ, and thus represents all genes expressed in fruit. Since only the functional part of the genome is observed, this provides a rapid and direct way to analyze genes that regulate all of the different fruit traits expressed. The first step is the isolation of total RNA from the tissue. Messenger RNA that represents the transcripts of individual genes is about 1-3% of total RNA is first separated using magnetic beads with poly oligo-dT nucleotides that bind to the poly-A tails on mRNA molecules. The mRNA is then chemically fragmented and the single stranded mRNAs are converted to double-stranded cDNA via in vitro cDNA synthesis. Each mRNA population isolated from a particular walnut tissue and converted into a corresponding population of complimentary DNA (cDNA library) represents the mRNA population of a particular plant and tissue at a particular time during development. These cDNA libraries are ligated to adapters so that they can be PCR amplified to create sufficient quantities of molecules that then can be sequenced using the next generation of DNA sequencers that can profile an entire transcriptome in a single run using Solexa technology on an Illumina Genome Analyzer (http://genomecenter.ucdavis.edu/dna_technologies/uhtsequencing.html). Such new technologies are able to generate millions of sequences corresponding to a greater diversity of the mRNA


population at a lower cost than traditional Sanger sequencing. A single library is loaded onto one lane in a GAII sequencer, which generates 10-20 million sequencing reads between 20-80 nucleotides in length from both ends of each cDNA molecule. The resulting sequences will be compiled to generate a reference walnut Unigene set, representing a high percentage of the walnut gene space. For this project, 16 samples of walnut tissue were gathered from Chandler trees in the Stuke block at UC Davis between April and October 2008 (Table 4). Four additional samples were taken from Chandler plant material maintained in the lab of Gale McGranahan. RNA isolation and construction of cDNA libraries for each sample has nearly been completed, with just two libraries remaining to be constructed (Table 4). Each cDNA sample will be sequenced separately so that the profile of genes expressed in each tissue can be determined. Paired-end (85bp x 85bp) sequencing is underway on an Illumina Genome Analyzer using Solexa technology. The sequencing of three libraries has just been completed, yielding 10-20 million paired-end sequences of 20-85 bp in length from each cDNA library. Bioinformatics for sequencing processing will be conducted at the UC Davis Genome Center Bioinformatics Core, where these sequences will be compiled with the 18,000 existing walnut ESTs to generate a Unigene set, which is expected to describe most of the expressed walnut genome. This set of genes will be annotated using Blast2GO (http://blast2go.bioinfo.cipf.es/; Götz et al. 2008). This software package was recently used to annotate the set of 8622 walnut genes compiled in our walnut-nematode project. There, Gene Ontology (GO) categories were assigned to 57% of the sequences, including 18% which were also matched to Enzyme Commission (EC) identifiers. The GO categories and EC identifiers can be used to map the associated proteins onto metabolic pathways. These data can then be used to determine which metabolic pathways are active in each tissue and at various time points in the growing season which is a functional map of the gene activities in walnut. Objective 4: Development of a ‘Walnut Genome Resource (WGR)’, a web-based knowledge base of walnut genomic information A genome resource or knowledgebase is a database that provides access to genetic, physical, and functional mapping data generated in this project. The resource, which is now web accessible (http://walnutgenome.ucdavis.edu/) will have two distinct components: one for visualizing the genetic map and one for visualizing the physical map. The database will provide access to all of the fingerprinting data along with the BAC end sequences (Fig. 1). Tools are available to integrate and represent this information as a physical map showing individual contigs (Fig. 2). The physical map is a scaffold on which we will integrate genetic mapping data of walnut phenotypic information, molecular markers, and expressed genes as that information becomes available. The main objective of functional mapping is gene annotation and functional categorization of ESTs, the first step toward linking specific traits and conditions to metabolic and biochemical processes. Every EST enters a functional mapping pipeline using Blast2GO to assign sequences to metabolic pathways, and in some cases, regulatory roles in quality traits, pathogen resistance and stress response. This data pipeline includes gene set enrichment, a statistical analysis to determine which pathways and functional classes are expressed at higher or lower levels,


compared to the walnut Unigene set, in each tissue sample. Patterns in gene expression are visualized by unsupervised clustering, to reveal patterns in expression alone across several samples, and by functional visualizations. The Pathway Tools Omics Viewer (http://www.plantcyc.org; Zhang et al. 2005), and MapMan (http://mapman.gabipd.org; Thimm et al. 2004) visualization platforms can display high throughput expression data of individual genes and whole pathways in combination with standard pathway maps and graphical classifications of gene functions. We have used MapMan to visualize expression data from experiments on tomato, apple, citrus, and grape, in addition to walnut. REFERENCES Götz S, García-Gómez J.M., Terol J., Williams T.D., Nagaraj S.H., Nueda M.J., Robles M., Talón M.,

Dopazo J., Conesa A. (2008). High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 36:3420-3435.

Luo M.C., Thomas C., You F.M., Hsiao J., Ouyang S., Buell C.R., Malandro M., McGuire P.E., Anderson O.D., Dvorak J. (2003) High-throughput fingerprinting of bacterial artificial chromosomes using the SNaPshot labeling kit and sizing of restriction fragments by capillary electrophoresis. Genomics 82:378-389.

Soderlund C., Humphray S., Dunham A., French L. (2000) Contigs built with fingerprints, markers, and FPCV4.7. Genome Research 10:1772-1787.

Thimm, O., Blasing, O., Gibon, Y., Nagel, A., Meyer, S., Kruger, P., Selbig, J., Muller, L.A., Rhee, S.Y. Stitt, M. (2004). MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. The Plant Journal 37, 914-939.

Yu, J., Pressoir, G., Briggs, W.H., Bi, I.V., Yamasaki, M., Doebley, J.F., McMullen, M.D., Gaut, B.S., Nielsen, D.M., Holland, J.B., Kresovich, S. and Buckler, E.S. (2006). A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet., 38: 203-208.

Zhang, P., Foerster, H., Tissier, C., Mueller, L., Paley, S., Karp, P., Rhee, S.Y. (2005). MetaCyc and AraCyc. Metabolic Pathway Databases for Plant Research. Plant Physiology 138: 27-37.


Table 1. Locus-wide genetic variability in walnut germplasm

Locus #Genotype H(o) H(e) P

WGA001 450 0.62222 0.80766 0.00000

WGA202 437 0.61327 0.83625 0.00000 WGA384 427 0.45902 0.58113 0.00000 WGA331 445 0.58652 0.65681 0.01330 WGA332 451 0.54767 0.64695 0.00011 WGA321 451 0.60310 0.72423 0.00000 WGA009 424 0.65566 0.77891 0.00000 WGA118 449 0.64588 0.79499 0.00000 WGA225 432 0.38889 0.49816 0.00000 WGA004 447 0.58166 0.68289 0.00000 WGA069 451 0.55876 0.81452 0.00000 WGA089 450 0.47778 0.66620 0.00000 WGA349 414 0.28986 0.82987 0.00000 WGA338 450 0.52000 0.55639 0.00975 WGA178 451 0.67184 0.74688 0.00657 WGA318 399 0.34837 0.82008 0.00000 WGA106 450 0.33556 0.42703 0.00011 WGA237 446 0.33632 0.59402 0.00000 WGA071 450 0.34222 0.38149 0.00010 WGA242 450 0.49556 0.65027 0.00000 WGA223 425 0.53412 0.82727 0.00000


Table 2. Group specific fixation indices (inbreeding coefficient)

Group FIS P

China 0.08503 0.000000 SE Asia 0.14087 0.003910 Breeders’ gene pool 0.12687 0.000000 Bred 0.05423 0.076246 W Asia 0.09642 0.001955 S Asia 0.10898 0.000000

Table 3. Orthogonal partitioning of genetic variation within and among groups

Source of Sum of Variance Percentage Fixation variation d.f. squares components of variation index

Among groups 5 523.378 0.70793 13.37** 0.134** Within groups 898 4118.848 4.58669 86.63**

Total 903 4642.226 5.29462


Table 4: Functional mapping of the walnut genome (Objective 3), walnut tissues gathered April to Nov 2008 for cDNA library construction and EST analysis Sample No

Tissue Source

Genotype Developmental Stage

Source Harvest Date

Code cDNA Library

RNA-seq done

1 Vegetative Bud

Chandler Vegetative Tree 4/1/08 VB Yes Done

2 Leaf - Young

Chandler Vegetative Tree 4/15/08 LY Yes Done

3 Root Chandler Vegetative Pot 8/27/08 RT Yes Done 4 Callus

Interior Chandler Vegetative In

Vitro 10/14/08 CI Yes Waiting

5 Callus Exterior

Chandler Vegetative In Vitro

10/14/08 CE Yes Done

6 Pistillate Flower

Chandler Vegetative Tree 4/17/08 FL Yes Done

7 Catkins Chandler Immature Tree 4/1/08 CK Yes Done 8 Somatic

Embryo Chandler Immature In

Vitro 10/14/08 SE Yes Done

9 Leaf- mature

Chandler Vegetative Tree 6/5/08 LM Yes Waiting

10 Leaves Chandler Vegetative Tree 4/17/08 LE Yes Waiting 11 Fruit

immature Mixed Immature Tree 6/5/08 IF Yes Waiting

12 Hull immature

Chandler Immature Tree 6/5/08 HL Yes Waiting

13 Packing Tissue

Chandler Immature Tree 6/5/08 PT Yes Waiting

14 Hull Peel Chandler Mature Tree 9/4/08 HP Yes Waiting 15 Hull

Cortex Chandler Mature Tree 9/4/08 HC Yes Waiting

16 Packing Tissue

Chandler Mature Tree 9/4/08 PK Yes Waiting

17 Pellicle Chandler Mature Tree 9/4/08 PL No No 18 Embryo Mixed Mature Tree 9/4/08 EM Yes Done 19 Leaf – late Chandler Senescent Tree 10/15/08 LS No No 20 Hull –

dehiscing Chandler Senescent Tree 10/15/08 HU Yes Waiting

21 Transition wood

J.nigra Transition Zone

Tree 04/02/08 KW Yes Waiting


Figure 1. Example of a single fingerprint for a walnut BAC clone. To date 65,280 BACs have been fingerprinted with 92% being of high quality suitable for contig assembly.


Figure 2. Example of an assembled contig, containing 557 BAC clones, ca. 4.7 Mb in length.


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0.02

Figure 3. An unrooted tree depicting the genetic structure and differentiation within the walnut (Juglans regia) germplasm collection based on 21 microsatellite loci.


Figure 4. 3D projection of walnut germplasm along the first three principle axes.


Figure 5. 3D projection of walnut germplasm accessions along the first three PC axes with minimum spanning tree superimposed.


walnut genome analysis - university of …walnutresearch.ucdavis.edu/2009/2009_35.pdf · walnut...

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