Evidence map›Paper›PMID 34992626›Full record

ArticleFrontiers in plant science2021

CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons.

Zhen Peng, Hongge Li, Gaofei Sun, Panhong Dai, Xiaoli Geng, Xiao Wang, Xiaomeng Zhang, Zhengzhen Wang, Yinhua Jia, Zhaoe Pan and 3 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Zhen PengZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Hongge LiZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Gaofei SunSchool of Computer Science and Information Engineering, Anyang Institute of Technology, Anyang, China.
Panhong DaiZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Xiaoli GengZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Xiao WangZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Xiaomeng ZhangZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Zhengzhen WangZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Yinhua JiaZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Zhaoe PanZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Baojun ChenZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Xiongming DuZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
Shoupu HeZhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

databaseeGWASgeneticsgenomicsGossypiumvariation

Identifiers

PMID34992626
PMCPMC8724205

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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.