U.S. flag

An official website of the United States government

Pachypsylla venusta genome annotations v0.5.3

    This dataset presents the Pachypsylla venusta gene set BCM_v_0.5.3. RNA-Seq data was used with additional protein homology data for a MAKER automated annotation of the Pachypsylla venusta genome assembly 1.0.

    Agrilus planipennis genome annotations v0.5.3

      This dataset presents the Agrilus planipennis gene set BCM_v_0.5.3. RNA-Seq data was used with additional protein homology data for a MAKER automated annotation of the Agrilus planipennis genome assembly 1.0. This dataset is free for all use.

      Blattella germanica Official Gene Set OGSv1.0

        The *Blattella germanica* genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The *Blattella germanica* research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0.

        NLET - National Load Estimating Tool

          NLET (National Load Estimating Tool) is a web-based tool for estimating pollutant loads in watersheds across the contiguous United States. This tool helps visualize the effects of land use patterns, cultivated crops, and conservation practices through graphical representation.

          Data from: Genome-wide Association and Genomic Prediction Identifies Soybean Cyst Nematode Resistance in Common Bean Including a Syntenic Region to Soybean Rhg1 Locus

            A panel of single nucleotide polymorphisms (SNPs) for 363 common bean accessions was generated. A genome-wide association study (GWAS) was applied to detect SNPs significantly associated with resistance to Heterodera glycines (HG) also known as the soybean cyst nematode (SCN) in the core collection of common bean, Phaseolus vulgaris. There were 84,416 SNPs identified in 363 common bean accessions.

            Data from: Population structure and genetic diversity within the endangered species Pityopsis ruthii (Asteraceae)

              *Pityopsis ruthii* (Ruth’s golden aster) is a federally endangered herbaceous perennial endemic to the Hiwassee and Ocoee Rivers in southeastern Tennessee, USA. Comprehensive genetic studies providing novel information to conservationists for preservation of the species are lacking. Genetic variation and gene flow were evaluated for 814 individuals from 33 discrete locations using polymorphic microsatellites: seven chloroplast and twelve nuclear. A total of 198 alleles were detected with the nuclear loci and 79 alleles with the chloroplast loci.

              Maize Genetics Cooperation Stock Center Catalog of Stocks

                The Maize Genetics Cooperation Stock Center is operated by USDA/ARS, located at the University of Illinois, Urbana/Champaign, and integrated with the National Plant Germplasm System (NPGS). The center serves the maize research community by collecting, maintaining and distributing seeds of maize genetic stocks, and providing information about maize stocks and the mutations they carry through the Maize Genetics and Genomics Database (MaizeGDB).

                Maize-GAMER: GO Annotations, Methods, Evaluation and Review

                  maize-GAMER is a collaborative project to improve the status of gene functional annotation in maize (*Zea mays*). The project has three main areas of focus, namely * Design a pipeline for the functional annotation of maize genes. * Use manually curated test data to evaluate the annotations and generate a best subset of annotations for use * Design a user friendly review system for the community to provide feedback and endorsements of the annotations

                  BrAPI

                    The Breeding API (BrAPI) Project is an effort to create a RESTful specification to enable interoperability among plant breeding databases. The Breeding API specifies a standard interface for plant phenotype/genotype databases to serve their data to crop breeding applications. It is a shared, open API, to be used by all data providers and data consumers who wish to participate.

                    BAR- The Bio-Analytic Resource for Plant Biology

                      BAR is a collection of web-based, user-friendly tools for exploring, visualizing, and analyzing large datasets from plants. Supported are expression data, Next-Gen sequence data, protein-protein interactions, polymorphisms / conservation, and protein 3-D structures.