Your browser doesn't support javascript.
loading
CottonGen: The Community Database for Cotton Genomics, Genetics, and Breeding Research.
Yu, Jing; Jung, Sook; Cheng, Chun-Huai; Lee, Taein; Zheng, Ping; Buble, Katheryn; Crabb, James; Humann, Jodi; Hough, Heidi; Jones, Don; Campbell, J Todd; Udall, Josh; Main, Dorrie.
Afiliação
  • Yu J; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Jung S; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Cheng CH; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Lee T; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Zheng P; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Buble K; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Crabb J; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Humann J; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Hough H; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
  • Jones D; Cotton Incorporated, Cary, NC 27513, USA.
  • Campbell JT; The Agricultural Research Service of U.S. Department of Agriculture, Florence, SC 29501, USA.
  • Udall J; The Agricultural Research Service of U.S. Department of Agriculture, College Station, TX 77845, USA.
  • Main D; Department of Horticulture, Washington State University, Pullman, WA 99164, USA.
Plants (Basel) ; 10(12)2021 Dec 18.
Article em En | MEDLINE | ID: mdl-34961276
Over the last eight years, the volume of whole genome, gene expression, SNP genotyping, and phenotype data generated by the cotton research community has exponentially increased. The efficient utilization/re-utilization of these complex and large datasets for knowledge discovery, translation, and application in crop improvement requires them to be curated, integrated with other types of data, and made available for access and analysis through efficient online search tools. Initiated in 2012, CottonGen is an online community database providing access to integrated peer-reviewed cotton genomic, genetic, and breeding data, and analysis tools. Used by cotton researchers worldwide, and managed by experts with crop-specific knowledge, it continuous to be the logical choice to integrate new data and provide necessary interfaces for information retrieval. The repository in CottonGen contains colleague, gene, genome, genotype, germplasm, map, marker, metabolite, phenotype, publication, QTL, species, transcriptome, and trait data curated by the CottonGen team. The number of data entries housed in CottonGen has increased dramatically, for example, since 2014 there has been an 18-fold increase in genes/mRNAs, a 23-fold increase in whole genomes, and a 372-fold increase in genotype data. New tools include a genetic map viewer, a genome browser, a synteny viewer, a metabolite pathways browser, sequence retrieval, BLAST, and a breeding information management system (BIMS), as well as various search pages for new data types. CottonGen serves as the home to the International Cotton Genome Initiative, managing its elections and serving as a communication and coordination hub for the community. With its extensive curation and integration of data and online tools, CottonGen will continue to facilitate utilization of its critical resources to empower research for cotton crop improvement.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article