Evidence map›Paper›PMID 37123844›Full record

ArticleFrontiers in plant science2023

Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions.

Fenglei Sun, Jun Ma, Weijun Shi, Yanlong Yang

Open access · goldAbstract read
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Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Fenglei SunState Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China.
Jun MaResearch Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China.
Weijun ShiResearch Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China.
Yanlong YangResearch Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China.
Xinjiang Academy of Agricultural Sciences · CNCotton Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drought is one of the major abiotic stresses seriously affecting cotton yield. At present, the main cotton-producing areas in China are primarily arid and semiarid regions. Therefore, the identification of molecular markers and genes associated with cotton yield traits under drought conditions is of great importance for stabilize cotton yield under such conditions. In this study, resequencing data were used to conduct a genome-wide association study (GWAS) on 8 traits of 150 cotton germplasms. Under drought stress, 18 SNPs were significantly correlated with yield traits (single-boll weight (SBW) and seed (SC)), and 8 SNPs were identified as significantly correlated with effective fruit shoot number (EFBN) traits (a trait that is positively correlated with yield). Finally, a total of 15 candidate genes were screened. The combined results of the GWAS and transcriptome data analysis showed that four genes were highly expressed after drought stress, and these genes had significantly increased expression at 10, 15 and 25 DPA of fiber development. qRT-PCR was performed on two samples with drought tolerance extremes (drought-resistant Xinluzao 45 and drought-sensitive Xinluzao 26), revealing that three of the genes had the same differential expression pattern. This study provides a theoretical basis for the genetic analysis of cotton yield traits under drought stress, and provides gene resources for improved breeding of cotton yield traits under drought stress.

Indexed as

candidate genesdrought tolerancegenome-wide associated studySNPsupland cotton

Identifiers

PMID37123844
PMCPMC10130383
OpenAlexW4365148752

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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