ArticleFrontiers in plant science2021
CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons.
Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- NAC transcription factor GbNTL9 modifies the accumulation and organization of cellulose microfibrils to enhance cotton fiber strength.Journal of advanced research · 2025Article
- A Comprehensive Review of Deep Learning Applications in Cotton Industry: From Field Monitoring to Smart Processing.Plants (Basel, Switzerland) · 2025Review
- Multi-genome comprehensive identification of SSR/SV and development of molecular markers database to serve Sorghum bicolor (L.) breeding.BMC genomic data · 2023Article
- CottonMD: a multi-omics database for cotton biological study.Nucleic acids research · 2023Article
- TeaPVs: a comprehensive genomic variation database for tea plant (Camellia sinensis).BMC plant biology · 2022Article
- Retrieving a disrupted gene encoding phospholipase A for fibre enhancement in allotetraploid cultivated cotton.Plant biotechnology journal · 2022Article
- GRAND: An Integrated Genome, Transcriptome Resources, and Gene Network Database forFrontiers in plant science · 2022Article
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Authors and funding
13 authors.
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Abstract
Cultivated cottons are the most important economic crop, which produce natural fiber for the textile industry. In recent years, the genetic basis of several essential traits for cultivated cottons has been gradually elucidated by decoding their genomic variations. Although an abundance of resequencing data is available in public, there is still a lack of a comprehensive tool to exhibit the results of genomic variations and genome-wide association study (GWAS). To assist cotton researchers in utilizing these data efficiently and conveniently, we constructed the cotton genomic variation database (CottonGVD; http://120.78.174.209/ or http://db.cngb.org/cottonGVD). This database contains the published genomic information of three cultivated cotton species, the corresponding population variations (SNP and InDel markers), and the visualized results of GWAS for major traits. Various built-in genomic tools help users retrieve, browse, and query the variations conveniently. The database also provides interactive maps (e.g., Manhattan map, scatter plot, heatmap, and linkage disequilibrium block) to exhibit GWAS and expression GWAS results. Cotton researchers could easily focus on phenotype-associated loci visualization, and they are interested in and screen for candidate genes. Moreover, CottonGVD will continue to update by adding more data and functions.
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