Doing Genetic and Genomic Biology Using the Legume Information System and Associated Resources.

In this chapter, we introduce the main components of the Legume Information System ( https://legumeinfo.org ) and several associated resources. Additionally, we provide an example of their use by exploring a biological question: is there a common molecular basis, across legume species, that underlies the photoperiod-mediated transition from vegetative to reproductive development, that is, days to flowering? The Legume Information System (LIS) holds genetic and genomic data for a large number of crop and model legumes and provides a set of online bioinformatic tools designed to help biologists address questions and tasks related to legume biology. Such tasks include identifying the molecular basis of agronomic traits; identifying orthologs/syntelogs for known genes; determining gene expression patterns; accessing genomic datasets; identifying markers for breeding work; and identifying genetic similarities and differences among selected accessions. LIS integrates with other legume-focused informatics resources such as SoyBase ( https://soybase.org ), PeanutBase ( https://peanutbase.org ), and projects of the Legume Federation ( https://legumefederation.org ).

Genome-wide associations and epistatic interactions for internode number, plant height, seed weight and seed yield in soybean.

BACKGROUND: Breeding programs benefit from information about marker-trait associations for many traits, whether the goal is to place those traits under active selection or to maintain them through background selection. Association studies are also important for identifying accessions bearing potentially useful alleles by characterizing marker-trait associations and allelic states across germplasm collections. This study reports the results of a genome-wide association study and evaluation of epistatic interactions for four agronomic and seed-related traits in soybean. RESULTS: Using 419 diverse soybean accessions, together with genotyping data from the SoySNP50K Illumina Infinium BeadChip, we identified marker-trait associations for internode number (IN), plant height (PH), seed weight (SW), and seed yield per plant (SYP). We conducted a genome-wide epistatic study (GWES), identifying candidate genes that show evidence of SNP-SNP interactions. Although these candidate genes will require further experimental validation, several appear to be involved in developmental processes related to the respective traits. For IN and PH, these include the Dt1 determinacy locus (a soybean meristematic transcription factor), as well as a pectinesterase gene and a squamosa promoter binding gene that in other plants are involved in cell elongation and the vegetative-to-reproductive transition, respectively. For SW, candidate genes include an ortholog of the AP2 gene, which in other species is involved in maintaining seed size, embryo size, seed weight and seed yield. Another SW candidate gene is a histidine phosphotransfer protein - orthologs of which are involved in cytokinin-mediated seed weight regulating pathways. The SYP association loci overlap with regions reported in previous QTL studies to be involved in seed yield. CONCLUSIONS: This study further confirms the utility of GWAS and GWES approaches for identifying marker-trait associations and interactions within a diverse germplasm collection.

A transcriptome-SNP-derived linkage map of Apios americana (potato bean) provides insights about genome re-organization and synteny conservation in the phaseoloid legumes.

KEY MESSAGE: We report a linkage map for Apios americana and describe synteny with selected warm-season legumes. A translocation event in common bean and soybean is confirmed against Apios and Vigna species. Apios (Apios americana; "apios"), a tuberous perennial legume in the Phaseoleae tribe, was widely used as a food by Native Americans. Work in the last 40 years has led to several improved breeding lines. Aspects of the pollination biology (complex floral structure and tripping mechanism) have made controlled crosses difficult, and the previous reports indicated that the plant is likely primarily an outcrosser. We used a pseudo-testcross strategy to construct a genetic map specific to the maternal parent. The map was built using single-nucleotide polymorphism markers identified by comparing the expressed sequences of individuals in the mapping population against a de novo maternal reference transcriptome assembly. The apios map consists of 11 linkage groups and 1121 recombinationally distinct loci, covering ~ 938.6 cM. By sequencing the transcriptomes of all potential pollen parents, we were able to identify the probable pollen donors and to discover new aspects of the pollination biology in apios. No selfing was observed, but multiple pollen parents were seen within individual pods. Comparisons with genome sequences in other species in the Phaseoleae showed extended synteny for most apios linkage groups. This synteny supports the robustness of the map, and also sheds light on the history of the Phaseoleae, as apios is relatively early diverging in this tribe. We detected a translocation event that separates apios and two Vigna species from Phaseolus vulgaris and Glycine max. This apios mapping work provides a general protocol for sequencing-based construction of high-density linkage maps in outcrossing species with heterogeneous pollen parents.

Genomics-assisted characterization of a breeding collection of Apios americana, an edible tuberous legume.

For species with potential as new crops, rapid improvement may be facilitated by new genomic methods. Apios (Apios americana Medik.), once a staple food source of Native American Indians, produces protein-rich tubers, tolerates a wide range of soils, and symbiotically fixes nitrogen. We report the first high-quality de novo transcriptome assembly, an expression atlas, and a set of 58,154 SNP and 39,609 gene expression markers (GEMs) for characterization of a breeding collection. Both SNPs and GEMs identify six genotypic clusters in the collection. Transcripts mapped to the Phaseolus vulgaris genome-another phaseoloid legume with the same chromosome number-provide provisional genetic locations for 46,852 SNPs. Linkage disequilibrium decays within 10 kb (based on the provisional genetic locations), consistent with outcrossing reproduction. SNPs and GEMs identify more than 21 marker-trait associations for at least 11 traits. This study demonstrates a holistic approach for mining plant collections to accelerate crop improvement.

Legume information system (LegumeInfo.org): a key component of a set of federated data resources for the legume family.

Legume Information System (LIS), at http://legumeinfo.org, is a genomic data portal (GDP) for the legume family. LIS provides access to genetic and genomic information for major crop and model legumes. With more than two-dozen domesticated legume species, there are numerous specialists working on particular species, and also numerous GDPs for these species. LIS has been redesigned in the last three years both to better integrate data sets across the crop and model legumes, and to better accommodate specialized GDPs that serve particular legume species. To integrate data sets, LIS provides genome and map viewers, holds synteny mappings among all sequenced legume species and provides a set of gene families to allow traversal among orthologous and paralogous sequences across the legumes. To better accommodate other specialized GDPs, LIS uses open-source GMOD components where possible, and advocates use of common data templates, formats, schemas and interfaces so that data collected by one legume research community are accessible across all legume GDPs, through similar interfaces and using common APIs. This federated model for the legumes is managed as part of the 'Legume Federation' project (accessible via http://legumefederation.org), which can be thought of as an umbrella project encompassing LIS and other legume GDPs.

An ontology approach to comparative phenomics in plants.

BACKGROUND: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. RESULTS: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. CONCLUSIONS: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics that enhances the utility of model genetic organisms and can be readily applied to species with fewer genetic resources and less well-characterized genomes. In addition, these tools should enhance future efforts to explore the relationships among phenotypic similarity, gene function, and sequence similarity in plants, and to make genotype-to-phenotype predictions relevant to plant biology, crop improvement, and potentially even human health.