An Integrated Framework Coupling Hierarchical Hyperspectral i‐trait Screening, Gene Identification, and Functional Validation for Genetic Dissection of Salt Tolerance in Cotton
5 affiliations
- 1State Key Laboratory of Cotton Bio‐Breeding and Integrated Utilization Institute of Cotton Research Chinese Academy of Agricultural Sciences Anyang Henan China
- 2Xinjiang Key Laboratory of Crop Gene Editing and Germplasm Innovation/Northwest Center of the National Technology Innovation Center for Saline‐Alkali Agriculture Institute of Western Agriculture of CAAS Changji Xinjiang China
- 3Henan Sesame Research Center Henan Academy of Agricultural Sciences Zhengzhou Henan China
- 4Wuhan Greenpheno Science and Technology Co., Ltd. Wuhan China
- 5College of Plant Science & Technology Huazhong Agricultural University Wuhan China
Abstract
Cotton is an economically pivotal fiber crop worldwide, but its growth and yield are critically limited by soil salinity. Salt tolerance is a complex quantitative trait, and conventional destructive phenotyping methods have long hindered the efficiency and accuracy of gene discovery and genetic dissection. To overcome this phenotyping bottleneck and establish a streamlined workflow from phenotype to gene, we developed an integrated framework coupling dynamic hyperspectral phenomics, hierarchical trait selection, genome‐wide association study (GWAS), and functional validation, and applied it to dissect the genetic basis of salt tolerance using a natural population of 419 upland cotton accessions. We first confirmed abundant salt tolerance phenotypic diversity in the population via four core physiological traits and their phenotypic plasticity indices. Using time‐series hyperspectral imaging (HSI), we extracted large‐scale image‐derived traits (i‐traits) capturing dynamic physiological responses to salt stress. A three‐tiered screening strategy integrating t‐test, broad‐sense heritability (H²) estimation, and multi‐algorithm machine learning consensus was applied to identify core salt‐responsive i‐traits with biological relevance, genetic stability, and low redundancy. Using these core i‐traits as phenotypic inputs for GWAS, we successfully mapped GhST7 as a key candidate gene. Functional validation via CRISPR/Cas9‐mediated knockout and haplotype‐specific overexpression demonstrated that GhST7 acts as a key regulator of cotton salt stress responses, and natural variation in its promoter region confers differential salt tolerance by modulating gene expression levels. Collectively, this study not only identifies a functionally verified salt tolerance gene with breeding application value, but also establishes a coherent phenomics–genomics–functional validation framework, providing an efficient paradigm for high‐precision genetic dissection of complex stress‐tolerance traits in crops.
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BibTeX
@article{xu2026integrated,
title = {{An Integrated Framework Coupling Hierarchical Hyperspectral i‐trait Screening, Gene Identification, and Functional Validation for Genetic Dissection of Salt Tolerance in Cotton}},
author = {Bowei Xu and Le Liu and Mengli Yu and Yuling Guo and Junli Ye and Jun Zhang and Rumeng Zhao and Jiajie Yang and Wanneng Yang and Yameng Xu and Liqiang Fan and Zuoren Yang},
journal = {Advanced Science},
year = {2026},
month = oct,
doi = {10.1002/advs.78504},
url = {https://doi.org/10.1002/advs.78504},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - An Integrated Framework Coupling Hierarchical Hyperspectral i‐trait Screening, Gene Identification, and Functional Validation for Genetic Dissection of Salt Tolerance in Cotton
AU - Bowei Xu
AU - Le Liu
AU - Mengli Yu
AU - Yuling Guo
AU - Junli Ye
AU - Jun Zhang
AU - Rumeng Zhao
AU - Jiajie Yang
AU - Wanneng Yang
AU - Yameng Xu
AU - Liqiang Fan
AU - Zuoren Yang
PY - 2026
DA - 2026/10/26
JO - Advanced Science
DO - 10.1002/advs.78504
UR - https://doi.org/10.1002/advs.78504
AB - Cotton is an economically pivotal fiber crop worldwide, but its growth and yield are critically limited by soil salinity. Salt tolerance is a complex quantitative trait, and conventional destructive phenotyping methods have long hindered the efficiency and accuracy of gene discovery and genetic dissection. To overcome this phenotyping bottleneck and establish a streamlined workflow from phenotype to gene, we developed an integrated framework coupling dynamic hyperspectral phenomics, hierarchical trait selection, genome‐wide association study (GWAS), and functional validation, and applied it to dissect the genetic basis of salt tolerance using a natural population of 419 upland cotton accessions. We first confirmed abundant salt tolerance phenotypic diversity in the population via four core physiological traits and their phenotypic plasticity indices. Using time‐series hyperspectral imaging (HSI), we extracted large‐scale image‐derived traits (i‐traits) capturing dynamic physiological responses to salt stress. A three‐tiered screening strategy integrating t‐test, broad‐sense heritability (H²) estimation, and multi‐algorithm machine learning consensus was applied to identify core salt‐responsive i‐traits with biological relevance, genetic stability, and low redundancy. Using these core i‐traits as phenotypic inputs for GWAS, we successfully mapped GhST7 as a key candidate gene. Functional validation via CRISPR/Cas9‐mediated knockout and haplotype‐specific overexpression demonstrated that GhST7 acts as a key regulator of cotton salt stress responses, and natural variation in its promoter region confers differential salt tolerance by modulating gene expression levels. Collectively, this study not only identifies a functionally verified salt tolerance gene with breeding application value, but also establishes a coherent phenomics–genomics–functional validation framework, providing an efficient paradigm for high‐precision genetic dissection of complex stress‐tolerance traits in crops.
SN - 2198-3844
ER -