Evidence map›Paper›PMID 34961276›Full record

ArticlePlants (Basel, Switzerland)2021

CottonGen: The Community Database for Cotton Genomics, Genetics, and Breeding Research.

Jing Yu, Sook Jung, Chun-Huai Cheng, Taein Lee, Ping Zheng, Katheryn Buble, James Crabb, Jodi Humann, Heidi Hough, Don Jones and 3 more

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

87 citing papers in PubMed.

  1. Article
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  5. The Gibberellin 2-Oxidase GeneInternational journal of molecular sciences · 2026
    Article
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  15. Review
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  20. Review

27 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jing YuDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.ORCID 0000-0001-8008-5216
Sook JungDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.ORCID 0000-0003-3968-2769
Chun-Huai ChengDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.
Taein LeeDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.
Ping ZhengDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.
Katheryn BubleDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.
James CrabbDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.
Jodi HumannDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.ORCID 0000-0002-9575-6710
Heidi HoughDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.
Don JonesCotton Incorporated, Cary, NC 27513, USA.
J Todd CampbellThe Agricultural Research Service of U.S. Department of Agriculture, Florence, SC 29501, USA.
Josh UdallThe Agricultural Research Service of U.S. Department of Agriculture, College Station, TX 77845, USA.ORCID 0000-0003-0978-4764
Dorrie MainDepartment of Horticulture, Washington State University, Pullman, WA 99164, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

analysisbig databioinformaticscrop improvementgenotypewhole genome sequence

Identifiers

PMID34961276
PMCPMC8705096

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.