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COTTONOMICS: a comprehensive cotton multi-omics database.

Fan Dai1, Jiedan Chen1,2, Ziqian Zhang1

  • 1Zhejiang Provincial Key Laboratory of Crop Genetic Resources, Institute of Crop Science, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang 310058, China.

Database : the Journal of Biological Databases and Curation
|September 12, 2022
PubMed
Summary
This summary is machine-generated.

The COTTONOMICS platform integrates vast cotton omics data, including genomes and sequencing data, to facilitate research on cotton genetics and trait discovery. This resource aids in understanding cotton population diversity and identifying key genes for agricultural improvement.

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Area of Science:

  • Agricultural Science
  • Genomics
  • Bioinformatics

Background:

  • Advancements in next-generation sequencing (NGS) have generated extensive cotton omics data.
  • The complexity of this data presents challenges for researchers studying cotton genomics and evolution.
  • Existing data resources are fragmented, hindering comprehensive analysis.

Purpose of the Study:

  • To develop COTTONOMICS, an integrated web database for cotton multi-omics data.
  • To provide a user-friendly platform for accessing, analyzing, and visualizing diverse cotton genomic and epigenomic information.
  • To facilitate research on cotton population genetics, genomic structure, and the identification of agronomically important genes.

Main Methods:

  • Integrated 32.5 TB of omics data, including seven assembled genomes and resequencing data from 1180 cotton accessions.
  • Incorporated various sequencing data types: 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).
  • Developed a web interface with modules for data retrieval, analysis, and visualization, supporting searches for genomic variation (SNPs, InDels), gene expression, epigenetic regulation, and quantitative trait loci (QTLs).

Main Results:

  • Established COTTONOMICS (http://cotton.zju.edu.cn/), a comprehensive and accessible database for cotton omics data.
  • Enabled diverse search scenarios for retrieving detailed information on cotton genomes, variations, gene expression, and epigenetic modifications.
  • Provided tools for analyzing and visualizing multi-omics data, supporting in-depth studies of cotton genetics.

Conclusions:

  • COTTONOMICS serves as a valuable resource for the cotton research community.
  • The platform empowers researchers to decipher cotton population genetics and discover novel genes for beneficial traits.
  • Facilitates a deeper understanding of cotton genomic structure, evolution, and diversity.