Scott R. Kalberer

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

BackgroundPlant 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.ResultsWe 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.ConclusionsThe 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.

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.

PeanutBase and Other Bioinformatic Resources for Peanut

Abstract Large-scale genomic data for peanut have only become available in the last few years, with the advent of low-cost sequencing technologies. To make the data accessible to researchers and to integrate across diverse types of data, the International Peanut Genomics Consortium funded the development of PeanutBase, at http://peanutbase.org . This website provides access to genetic maps and markers, locations of quantitative trait loci (QTLs), genome sequences, gene locations and sequences, gene families and correspondences with genes in other species, and descriptions of traits and growth characteristics. The website also provides tools for exploration and analysis, including sequence of genomic and genic sequences, and keyword searches of genes, gene families, and QTL studies. These resources should facilitate breeding advancements in peanut, helping improve crop productivity and there are a variety of resources for peanut research around the web, ranging from tools for basic plant biology to information for growers and various sectors of the peanut industry to resources for plant breeders. Many of these resources are listed and/or maintained at http://peanutbase.org/community .