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COTTONOMICS: a comprehensive cotton multi-omics database
The rapid advancement of sequencing technology, including next-generation sequencing (NGS), has greatly improved sequencing efficiency and decreased cost. Consequently, huge amounts of genomic, transcriptomic and epigenetic data concerning cotton species have been generated and released. These large...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467004/ https://www.ncbi.nlm.nih.gov/pubmed/36094905 http://dx.doi.org/10.1093/database/baac080 |
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author | Dai, Fan Chen, Jiedan Zhang, Ziqian Liu, Fengjun Li, Jun Zhao, Ting Hu, Yan Zhang, Tianzhen Fang, Lei |
author_facet | Dai, Fan Chen, Jiedan Zhang, Ziqian Liu, Fengjun Li, Jun Zhao, Ting Hu, Yan Zhang, Tianzhen Fang, Lei |
author_sort | Dai, Fan |
collection | PubMed |
description | The rapid advancement of sequencing technology, including next-generation sequencing (NGS), has greatly improved sequencing efficiency and decreased cost. Consequently, huge amounts of genomic, transcriptomic and epigenetic data concerning cotton species have been generated and released. These large-scale data provide immense opportunities for the study of cotton genomic structure and evolution, population genetic diversity and genome-wide mining of excellent genes for important traits. However, the complexity of NGS data also causes distress, as it cannot be utilized easily. Here, we presented the cotton omics data platform COTTONOMICS (http://cotton.zju.edu.cn/), an easily accessible web database that integrates 32.5 TB of omics data including seven assembled genomes, resequencing data from 1180 allotetraploid cotton accessions and RNA-sequencing (RNA-seq), small RNA-sequencing (smRNA-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), DNase hypersensitive sites sequencing (DNase-seq) and Bisulfite sequencing (BS-seq). COTTONOMICS allows users to employ various search scenarios and retrieve information concerning the cotton genomes, genomic variation (Single nucleotide polymorphisms (SNPs) and Insertion and Deletion (InDels)), gene expression, smRNA expression, epigenetic regulation and quantitative trait locus (QTLs). The user-friendly web interface offers a variety of modules for storing, retrieving, analyzing and visualizing cotton multi-omics data to diverse ends, thereby enabling users to decipher cotton population genetics and identify potential novel genes that influence agronomically beneficial traits. Database URL: http://cotton.zju.edu.cn |
format | Online Article Text |
id | pubmed-9467004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-94670042022-09-13 COTTONOMICS: a comprehensive cotton multi-omics database Dai, Fan Chen, Jiedan Zhang, Ziqian Liu, Fengjun Li, Jun Zhao, Ting Hu, Yan Zhang, Tianzhen Fang, Lei Database (Oxford) Original Article The rapid advancement of sequencing technology, including next-generation sequencing (NGS), has greatly improved sequencing efficiency and decreased cost. Consequently, huge amounts of genomic, transcriptomic and epigenetic data concerning cotton species have been generated and released. These large-scale data provide immense opportunities for the study of cotton genomic structure and evolution, population genetic diversity and genome-wide mining of excellent genes for important traits. However, the complexity of NGS data also causes distress, as it cannot be utilized easily. Here, we presented the cotton omics data platform COTTONOMICS (http://cotton.zju.edu.cn/), an easily accessible web database that integrates 32.5 TB of omics data including seven assembled genomes, resequencing data from 1180 allotetraploid cotton accessions and RNA-sequencing (RNA-seq), small RNA-sequencing (smRNA-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), DNase hypersensitive sites sequencing (DNase-seq) and Bisulfite sequencing (BS-seq). COTTONOMICS allows users to employ various search scenarios and retrieve information concerning the cotton genomes, genomic variation (Single nucleotide polymorphisms (SNPs) and Insertion and Deletion (InDels)), gene expression, smRNA expression, epigenetic regulation and quantitative trait locus (QTLs). The user-friendly web interface offers a variety of modules for storing, retrieving, analyzing and visualizing cotton multi-omics data to diverse ends, thereby enabling users to decipher cotton population genetics and identify potential novel genes that influence agronomically beneficial traits. Database URL: http://cotton.zju.edu.cn Oxford University Press 2022-09-12 /pmc/articles/PMC9467004/ /pubmed/36094905 http://dx.doi.org/10.1093/database/baac080 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Dai, Fan Chen, Jiedan Zhang, Ziqian Liu, Fengjun Li, Jun Zhao, Ting Hu, Yan Zhang, Tianzhen Fang, Lei COTTONOMICS: a comprehensive cotton multi-omics database |
title | COTTONOMICS: a comprehensive cotton multi-omics database |
title_full | COTTONOMICS: a comprehensive cotton multi-omics database |
title_fullStr | COTTONOMICS: a comprehensive cotton multi-omics database |
title_full_unstemmed | COTTONOMICS: a comprehensive cotton multi-omics database |
title_short | COTTONOMICS: a comprehensive cotton multi-omics database |
title_sort | cottonomics: a comprehensive cotton multi-omics database |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467004/ https://www.ncbi.nlm.nih.gov/pubmed/36094905 http://dx.doi.org/10.1093/database/baac080 |
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