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.
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.
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6 citing papers in PubMed, 10 citations in OpenAlex.
- Article
- Detection of QTLs and QTL-environment interactions for fruit branch number in Upland cotton (Gossypium hirsutum L.) using a restricted two-stage multi-locus genome-wide association study.BMC plant biology · 2026Article
- The effects of substituting organic fertilizer for nitrogen fertilizer on seed cotton yield and soil enzyme activity under drip irrigation.Frontiers in plant science · 2026Article
- Development of a Liquid-Phased Probe Array for Upland Cotton and Its Application in Cultivar Identification.Genes · 2025Article
- Genome-wide analysis for root and leaf architecture traits associated with drought tolerance at the seedling stage in a highly ecologically diverse wheat population.Computational and structural biotechnology journal · 2024Article
- Quantitative trait loci and candidate genes for yield-related traits of upland cotton revealed by genome-wide association analysis under drought conditions.BMC genomics · 2023Article
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4 authors at 2 institutions in 1 country.
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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.
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