Ethalinda K. S. Cannon

The genome sequences of Arachis duranensis and Arachis ipaensis , the diploid ancestors of cultivated peanut

Cultivated peanut (Arachis hypogaea) is an allotetraploid with closely related subgenomes of a total size of ∼2.7 Gb. This makes the assembly of chromosomal pseudomolecules very challenging. As a foundation to understanding the genome of cultivated peanut, we report the genome sequences of its diploid ancestors (Arachis duranensis and Arachis ipaensis). We show that these genomes are similar to cultivated peanuts A and B subgenomes and use them to identify candidate disease resistance genes, to guide tetraploid transcript assemblies and to detect genetic exchange between cultivated peanuts subgenomes. On the basis of remarkably high DNA identity of the A. ipaensis genome and the B subgenome of cultivated peanut and biogeographic evidence, we conclude that A. ipaensis may be a direct descendant of the same population that contributed the B subgenome to cultivated peanut.

MaizeGDB: curation and outreach go hand-in-hand

First released in 1991 with the name MaizeDB, the Maize Genetics and Genomics Database, now MaizeGDB, celebrates its 20th anniversary this year. MaizeGDB has transitioned from a focus on comprehensive curation of the literature, genetic maps and stocks to a paradigm that accommodates the recent release of a reference maize genome sequence, multiple diverse maize genomes and sequence-based gene expression data sets. The MaizeGDB Team is relatively small, and relies heavily on the research community to provide data, nomenclature standards and most importantly, to recommend future directions, priorities and strategies. Key aspects of MaizeGDBs intimate interaction with the community are the co-location of curators with maize research groups in multiple locations across the USA as well as coordination with MaizeGDB’s close partner, the Maize Genetics Cooperation—Stock Center. In this report, we describe how the MaizeGDB Team currently interacts with the maize research community and our plan for future interactions that will support updates to the functional and structural annotation of the B73 reference genome.

Maize Metabolic Network Construction and Transcriptome Analysis

A framework for understanding the synthesis and catalysis of metabolites and other biochemicals by proteins is crucial for unraveling the physiology of cells. To create such a framework for Zea mays L. subsp. mays (maize), we developed MaizeCyc, a metabolic network of enzyme catalysts, proteins, carbohydrates, lipids, amino acids, secondary plant products, and other metabolites by annotating the genes identified in the maize reference genome sequenced from the B73 variety. MaizeCyc version 2.0.2 is a collection of 391 maize pathways involving 8889 enzyme mapped to 2110 reactions and 1468 metabolites. We used MaizeCyc to describe the development and function of maize organs including leaf, root, anther, embryo, and endosperm by exploring the recently published microarray‐based maize gene expression atlas. We found that 1062 differentially expressed metabolic genes mapped to 524 unique enzymatic reactions associated with 310 pathways. The MaizeCyc pathway database was created by running a library of evidences collected from the maize genome annotation, gene‐based phylogeny trees, and comparison to known genes and pathways from rice (Oryza sativa L.) and Arabidopsis thaliana (L.) Heynh. against the PathoLogic module of Pathway Tools. The network and the database that were also developed as a community resource are freely accessible online at http://maizecyc.maizegdb.org to facilitate analysis and promote studies on metabolic genes in maize.

MaizeGDB update: new tools, data and interface for the maize model organism database

MaizeGDB is a highly curated, community-oriented database and informatics service to researchers focused on the crop plant and model organism Zea mays ssp. mays. Although some form of the maize community database has existed over the last 25 years, there have only been two major releases. In 1991, the original maize genetics database MaizeDB was created. In 2003, the combined contents of MaizeDB and the sequence data from ZmDB were made accessible as a single resource named MaizeGDB. Over the next decade, MaizeGDB became more sequence driven while still maintaining traditional maize genetics datasets. This enabled the project to meet the continued growing and evolving needs of the maize research community, yet the interface and underlying infrastructure remained unchanged. In 2015, the MaizeGDB team completed a multi-year effort to update the MaizeGDB resource by reorganizing existing data, upgrading hardware and infrastructure, creating new tools, incorporating new data types (including diversity data, expression data, gene models, and metabolic pathways), and developing and deploying a modern interface. In addition to coordinating a data resource, the MaizeGDB team coordinates activities and provides technical support to the maize research community. MaizeGDB is accessible online at http://www.maizegdb.org.

MaizeGDB becomes ‘sequence-centric’

MaizeGDB is the maize research community’s central repository for genetic and genomic information about the crop plant and research model Zea mays ssp. mays. The MaizeGDB team endeavors to meet research needs as they evolve based on researcher feedback and guidance. Recent work has focused on better integrating existing data with sequence information as it becomes available for the B73, Mo17 and Palomero Toluqueño genomes. Major endeavors along these lines include the implementation of a genome browser to graphically represent genome sequences; implementation of POPcorn, a portal ancillary to MaizeGDB that offers access to independent maize projects and will allow BLAST similarity searches of participating projects’ data sets from a single point; and a joint MaizeGDB/PlantGDB project to involve the maize community in genome annotation. In addition to summarizing recent achievements and future plans, this article also discusses specific examples of community involvement in setting priorities and design aspects of MaizeGDB, which should be of interest to other database and resource providers seeking to better engage their users. MaizeGDB is accessible online at http://www.maizegdb.org. Database URL: http://www.maizegdb.org

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.

Chromosome Visualization Tool: A Whole Genome Viewer

CViT (chromosome visualization tool) is a Perl utility for quickly generating images of features on a whole genome at once. It reads GFF3-formated data representing chromosomes (linkage groups or pseudomolecules) and sets of features on those chromosomes. It can display features on any chromosomal unit system, including genetic (centimorgan), cytological (centiMcClintock), and DNA unit (base-pair) coordinates. CViT has been used to track sequencing progress (status of genome sequencing, location and number of gaps), to visualize BLAST hits on a whole genome view, to associate maps with one another, to locate regions of repeat densities to display syntenic regions, and to visualize centromeres and knobs on chromosomes.

POPcorn: An Online Resource Providing Access to Distributed and Diverse Maize Project Data

The purpose of the online resource presented here, POPcorn (Project Portal for corn), is to enhance accessibility of maize genetic and genomic resources for plant biologists. Currently, many online locations are difficult to find, some are best searched independently, and individual project websites often degrade over time—sometimes disappearing entirely. The POPcorn site makes available (1) a centralized, web-accessible resource to search and browse descriptions of ongoing maize genomics projects, (2) a single, stand-alone tool that uses web Services and minimal data warehousing to search for sequence matches in online resources of diverse offsite projects, and (3) a set of tools that enables researchers to migrate their data to the long-term model organism database for maize genetic and genomic information: MaizeGDB. Examples demonstrating POPcorns utility are provided herein.

The MaizeGDB Genome Browser tutorial: one example of database outreach to biologists via video

Video tutorials are an effective way for researchers to quickly learn how to use online tools offered by biological databases. At MaizeGDB, we have developed a number of video tutorials that demonstrate how to use various tools and explicitly outline the caveats researchers should know to interpret the information available to them. One such popular video currently available is ‘Using the MaizeGDB Genome Browser’, which describes how the maize genome was sequenced and assembled as well as how the sequence can be visualized and interacted with via the MaizeGDB Genome Browser. Database URL: http://www.maizegdb.org/