Excavation and effect analysis of interaction sites between upland cotton yield and fiber quality traits and environmental factors

Climate change has increased the sensitivity of cropping systems to environmental variability, making the genetic dissection of G$$\times$$E and phenotypic plasticity essential for adaptive breeding. In this study, a recombinant inbred line population of upland cotton was evaluated across 16 environments from multi-year and multi-location field trials to assess the plasticity of yield- and fiber-quality traits. By integrating the Finlay–Wilkinson regression model with CERIS sliding-window analyses, 13 key meteorological factors and 4 principal component variables were identified, together with their effective time windows. QTL mapping based on trait plasticity slopes and environmental response slopes detected 172 environment-associated loci. A major locus at 188 Mb on chr10 influenced boll weight and seed index in response to multiple environmental variables, including photoperiod, cumulative radiation, growing degree days, and the product of radiation and photoperiod, suggesting a key regulatory site for environmental signal perception. Haplotype analysis further supported functional divergence of alleles within this region in relation to environmental adaptation. Overall, this study identifies critical environmental factors shaping cotton yield and fiber quality and reveals multiple G$$\times$$E–related loci underlying environmental responsiveness and phenotypic plasticity, providing a theoretical foundation for environmentally informed precision breeding.

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Publication Details

Journal
BMC Plant Biology
Published
2026-01-14
DOI
https://doi.org/10.1186/s12870-026-08123-7
Primary Topic
Research in Cotton Cultivation
Type
article
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article

Excavation and effect analysis of interaction sites between upland cotton yield and fiber quality traits and environmental factors

Jìngtāo Pān, Jǔwǔ Gōng, Hǎihóng Shāng, Youhua Yuan et al.
BMC Plant Biology
Research in Cotton Cultivation
article

Excavation and effect analysis of interaction sites between upland cotton yield and fiber quality traits and environmental factors

Jìngtāo Pān, Jǔwǔ Gōng, Hǎihóng Shāng, Youhua Yuan, Wànkuí Gǒng, Shuqian Yao, Haoliang Yan, Yang Li, Yuzhen Shi
article en

Abstract

Climate change has increased the sensitivity of cropping systems to environmental variability, making the genetic dissection of G$$\times$$E and phenotypic plasticity essential for adaptive breeding. In this study, a recombinant inbred line population of upland cotton was evaluated across 16 environments from multi-year and multi-location field trials to assess the plasticity of yield- and fiber-quality traits. By integrating the Finlay–Wilkinson regression model with CERIS sliding-window analyses, 13 key meteorological factors and 4 principal component variables were identified, together with their effective time windows. QTL mapping based on trait plasticity slopes and environmental response slopes detected 172 environment-associated loci. A major locus at 188 Mb on chr10 influenced boll weight and seed index in response to multiple environmental variables, including photoperiod, cumulative radiation, growing degree days, and the product of radiation and photoperiod, suggesting a key regulatory site for environmental signal perception. Haplotype analysis further supported functional divergence of alleles within this region in relation to environmental adaptation. Overall, this study identifies critical environmental factors shaping cotton yield and fiber quality and reveals multiple G$$\times$$E–related loci underlying environmental responsiveness and phenotypic plasticity, providing a theoretical foundation for environmentally informed precision breeding.

BMC Plant BiologyVol. 26(1)
Zhengzhou University (CN), Cotton Research Institute (CN), Chinese Academy of Agricultural Sciences (CN)
Climate action
Openalex Percentile: Top 89%
Research in Cotton Cultivation
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Excavation and effect analysis of interaction sites between upland cotton yield and fiber quality traits and environmental factors — Jìngtāo Pān, Jǔwǔ Gōng, et al. · BMC Plant Biology (2026) | TGRS Research Map | TGRS