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Gerris buenoi Official Gene set v1.0

    The Gerris buenoi genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The Gerris buenoi research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. The OGS is an integration of automatic gene predictions from Maker (performed by Dan Hughes at Baylor College of Medicine) with manual annotations by the research community (done via the Apollo manual annotation software).

    Hyalella azteca Official Gene Set v1.0

      The Hyalella azteca genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The Hyalella azteca research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. The OGS is an integration of automatic gene predictions from Maker with manual annotations by the research community (via the Apollo manual annotation software).

      Cacao Genome Database

        The release of the cacao genome sequence will provide researchers with access to the latest genomic tools, enabling more efficient research and accelerating the breeding process, thereby expediting the release of superior cacao cultivars. The sequenced genotype, Matina 1-6, is representative of the genetic background most commonly found in the cacao producing countries, enabling results to be applied immediately and broadly to current commercial cultivars.  Matina 1-6 is highly homozygous which greatly reduces the complexity of the sequence assembly process. While the sequence provided is a preliminary release, it already covers 92% of the genome, with approximately 35,000 genes. We will continue to refine the assembly and annotation, working toward a complete finished sequence.

        TreeGenes

          The TreeGenes database provides custom informatics tools to manage the flood of information resulting from high-throughput genomics projects in forest trees from sample collection to downstream analysis. This resource is enhanced with systems that are well connected with federated databases, automated data flows, machine learning analysis, standardized annotations and quality control processes. The database itself contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools.

          Gramene

            Gramene is a curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species.

            Musa Germplasm Information System

              The Musa Germplasm Information System (MGIS) contains key information on Musa germplasm diversity, including passport data, botanical classification, morpho-taxonomic descriptors, molecular studies, plant photographs and GIS information on 4616 accessions managed in 21 collections around the world, making it the most extensive source of information on banana genetic resources.

              Animal Trait Correlation Database (CorrDB)

                A genetic correlation is the proportion of shared variance between two traits that is due to genetic causes; a phenotypic correlation is the degree to which two traits co-vary among individuals in a population. In the genomics era, while gene expression, genetic association, and network analysis provide unprecedented means to decode the genetic basis of complex phenotypes, it is important to recognize the possible effects genetic progress in one trait can have on other traits. This database is designed to collect all published livestock genetic/phenotypic trait correlation data, aimed at facilitating genetic network analysis or systems biology studies.

                i5K Workspace@NAL

                  The i5k Workspace @ NAL is a platform for communities around ‘orphaned’ arthropod genome projects to access, visualize, curate and disseminate their data.

                  Switchgrass ESTs and SNPs

                    As part of our project, “Developing Association Mapping in Polyploid Perennial Biofuel Grasses” (DOE-USDA Plant Feedstock Genomics for Bioenergy Program grant DE-A102-07ER64454)*, two SNP discovery initiatives were carried out. The earlier one (2009) was an approach based on EST sequences. The latest initiative (2011-12) adopted a more powerful approach, based on GBS (Genotyping by Sequencing). We believe that the SNP markers identified in these studies will greatly enhance breeding efforts that target the improvement of key biofuel traits and the development of new switchgrass cultivars.