Michael Gonzales

A reference genome for common bean and genome-wide analysis of dual domestications

Common bean (Phaseolus vulgaris L.) is the most important grain legume for human consumption and has a role in sustainable agriculture owing to its ability to fix atmospheric nitrogen. We assembled 473 Mb of the 587-Mb genome and genetically anchored 98% of this sequence in 11 chromosome-scale pseudomolecules. We compared the genome for the common bean against the soybean genome to find changes in soybean resulting from polyploidy. Using resequencing of 60 wild individuals and 100 landraces from the genetically differentiated Mesoamerican and Andean gene pools, we confirmed 2 independent domestications from genetic pools that diverged before human colonization. Less than 10% of the 74 Mb of sequence putatively involved in domestication was shared by the two domestication events. We identified a set of genes linked with increased leaf and seed size and combined these results with quantitative trait locus data from Mesoamerican cultivars. Genes affected by domestication may be useful for genomics-enabled crop improvement.

Functional genomics of cell elongation in developing cotton fibers.

Cotton fibers are single-celled seed trichomes of major economic importance. Factors that regulate the rate and duration of cell expansion control fiber morphology and important agronomic traits. For genetic characterization of rapid cell elongation in cotton fibers, ∼ 14,000 unique genes were assembled from 46,603 expressed sequence tags (ESTs) from developmentally staged fiber cDNAs of a cultivated diploid species (Gossypium arboreumL.). Conservatively, the fiber transcriptome represents 35–40% of the genes in the cotton genome. In silico expression analysis revealed that rapidly elongating fiber cells exhibit significant metabolic activity, with the bulk of gene transcripts, represented by three major functional groups – cell wall structure and biogenesis, the cytoskeleton and energy/carbohydrate metabolism. Oligonucleotide microarrays revealed dynamic changes in gene expression between primary and secondary cell wall biogenesis showing that fiber genes in the dbEST are highly stage-specific for cell expansion – a conclusion supported by the absence of known secondary cell wall-specific genes from our fiber dbEST. During the developmental switch from primary to secondary cell wall syntheses, 2553 “expansion-associated” fiber genes are significantly down regulated. Genes (81) significantly up-regulated during secondary cell wall synthesis are involved in cell wall biogenesis and energy/carbohydrate metabolism, which is consistent with the stage of cellulose synthesis during secondary cell wall modification in developing fibers. This work provides the first in-depth view of the genetic complexity of the transcriptome of an expanding cell, and lays the groundwork for studying fundamental biological processes in plant biology with applications in agricultural biotechnology.

The Legume Information System (LIS): an integrated information resource for comparative legume biology

The Legume Information System (LIS) (http://www.comparative-legumes.org), developed by the National Center for Genome Resources in cooperation with the USDA Agricultural Research Service (ARS), is a comparative legume resource that integrates genetic and molecular data from multiple legume species enabling cross-species genomic and transcript comparisons. The LIS virtual plant interface allows simplified and intuitive navigation of transcript data from Medicago truncatula, Lotus japonicus, Glycine max and Arabidopsis thaliana. Transcript libraries are represented as images of plant organs in different developmental stages, which are selected to query the analyzed and annotated data. Complex queries can be accomplished by adding modifiers, keywords and sequence names. The LIS also contains annotated genomic data featuring transcript alignments to validate gene predictions as well as motif and similarity analyses. The genomic browser supports comparative analysis via novel dynamic functional annotation comparisons. CMap, developed as part of the GMOD project (http://www.gmod.org/cmap/index.shtml), has been incorporated to support comparative analyses of community linkage and physical map data. LIS is being expanded to incorporate gene expression and biochemical pathways which will be seamlessly integrated forming a knowledge discovery framework.

A comparative epigenomic analysis of polyploidy-derived genes in soybean and common bean

Reference methylomes provide insights into the evolutionary role of DNA methylation in paleopolyploid genomes. Soybean (Glycine max) and common bean (Phaseolus vulgaris) share a paleopolyploidy (whole-genome duplication [WGD]) event, approximately 56.5 million years ago, followed by a genus Glycine-specific polyploidy, approximately 10 million years ago. Cytosine methylation is an epigenetic mark that plays an important role in the regulation of genes and transposable elements (TEs); however, the role of DNA methylation in the fate/evolution of genes following polyploidy and speciation has not been fully explored. Whole-genome bisulfite sequencing was used to produce nucleotide resolution methylomes for soybean and common bean. We found that, in soybean, CG body-methylated genes were abundant in WGD genes, which were, on average, more highly expressed than single-copy genes and had slower evolutionary rates than unmethylated genes, suggesting that WGD genes evolve more slowly than single-copy genes. CG body-methylated genes were also enriched in shared single-copy genes (single copy in both species) that may be responsible for the broad and high expression patterns of this class of genes. In addition, diverged methylation patterns in non-CG contexts between paralogs were due mostly to TEs in or near genes, suggesting a role for TEs and non-CG methylation in regulating gene expression post polyploidy. Reference methylomes for both soybean and common bean were constructed, providing resources for investigating epigenetic variation in legume crops. Also, the analysis of methylation patterns of duplicated and single-copy genes has provided insights into the functional consequences of polyploidy and epigenetic regulation in plant genomes.

Phytophthora functional genomics database (PFGD): functional genomics of phytophthora–plant interactions

The Phytophthora Functional Genomics Database (PFGD; ), developed by the National Center for Genome Resources in collaboration with The Ohio State University-Ohio Agricultural Research and Development Center (OSU-OARDC), is a publicly accessible information resource for Phytophthora–plant interaction research. PFGD contains transcript, genomic, gene expression and functional assay data for Phytophthora infestans, which causes late blight of potato, and Phytophthora sojae, which affects soybeans. Automated analyses are performed on all sequence data, including consensus sequences derived from clustered and assembled expressed sequence tags. The PFGD search filter interface allows intuitive navigation of transcript and genomic data organized by library and derived queries using modifiers, annotation keywords or sequence names. BLAST services are provided for libraries built from the transcript and genomic sequences. Transcript data visualization tools include Quality Screening, Multiple Sequence Alignment and Features and Annotations viewers. A genomic browser that supports comparative analysis via novel dynamic functional annotation comparisons is also provided. PFGD is integrated with the Solanaceae Genomics Database (SolGD; ) to help provide insight into the mechanisms of infection and resistance, specifically as they relate to the genus Phytophthora pathogens and their plant hosts.

Leveraging model legume information to find candidate genes for soybean sudden death syndrome using the legume information system.

Comparative genomics is an emerging and powerful approach to achieve crop improvement. Using comparative genomics, information from model plant species can accelerate the discovery of genes responsible for disease and pest resistance, tolerance to plant stresses such as drought, and enhanced nutritional value including production of anti-oxidants and anti-cancer compounds. We demonstrate here how to use the Legume Information System for a comparative genomics study, leveraging genomic information from Medicago truncatula (barrel medic), the model legume, to find candidate genes involved with sudden death syndrome (SDS) in Glycine max (soybean). Specifically, genetic maps, physical maps, and annotated tentative consensus and expressed sequence tag (EST) sequences from G. max and M. truncatula can be compared. In addition, the recently published M. truncatula genomic sequences can be used to identify M. truncatula candidate genes in a genomic region syntenic to a quantitative trait loci region for SDS in soybean. Genomic sequences of candidate genes from M. truncatula can then be used to identify ESTs with sequence similarities from soybean for primer design and cloning of potential soybean disease causing alleles.

Gene evolutionary trajectories and GC patterns driven by recombination in Zea mays

Recombination occurring during meiosis is critical for creating genetic variation and plays an essential role in plant evolution. In addition to creating novel gene combinations, recombination can affect genome structure through altering GC patterns. In maize (Zea mays) and other grasses, another intriguing GC pattern exists. Maize genes show a bimodal GC content distribution that has been attributed to nucleotide bias in the third, or wobble, position of the codon. Recombination may be an underlying driving force given that recombination sites are often associated with high GC content. Here we explore the relationship between recombination and genomic GC patterns by comparing GC gene content at each of the three codon positions (GC1, GC2, and GC3, collectively termed GCx) to instances of a variable GC-rich motif that underlies double strand break (DSB) hotspots and to meiocyte-specific gene expression. Surprisingly, GCx bimodality in maize cannot be fully explained by the codon wobble hypothesis. High GCx genes show a strong overlap with the DSB hotspot motif, possibly providing a mechanism for the high evolutionary rates seen in these genes. On the other hand, genes that are turned on in meiosis (early prophase I) are biased against both high GCx genes and genes with the DSB hotspot motif, possibly allowing important meiotic genes to avoid DSBs. Our data suggests a strong link between the GC-rich motif underlying DSB hotspots and high GCx genes.