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

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...

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Autores principales: Sun, Fenglei, Ma, Jun, Shi, Weijun, Yang, Yanlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130383/
https://www.ncbi.nlm.nih.gov/pubmed/37123844
http://dx.doi.org/10.3389/fpls.2023.1135302
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author Sun, Fenglei
Ma, Jun
Shi, Weijun
Yang, Yanlong
author_facet Sun, Fenglei
Ma, Jun
Shi, Weijun
Yang, Yanlong
author_sort Sun, Fenglei
collection PubMed
description 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.
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spelling pubmed-101303832023-04-27 Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions Sun, Fenglei Ma, Jun Shi, Weijun Yang, Yanlong Front Plant Sci Plant Science 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. Frontiers Media S.A. 2023-04-12 /pmc/articles/PMC10130383/ /pubmed/37123844 http://dx.doi.org/10.3389/fpls.2023.1135302 Text en Copyright © 2023 Sun, Ma, Shi and Yang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Sun, Fenglei
Ma, Jun
Shi, Weijun
Yang, Yanlong
Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
title Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
title_full Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
title_fullStr Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
title_full_unstemmed Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
title_short Genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
title_sort genome-wide association analysis revealed genetic variation and candidate genes associated with the yield traits of upland cotton under drought conditions
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130383/
https://www.ncbi.nlm.nih.gov/pubmed/37123844
http://dx.doi.org/10.3389/fpls.2023.1135302
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