An Integrated Framework Coupling Hierarchical Hyperspectral i ‐trait Screening, Gene Identification, and Functional Validation for Genetic Dissection of Salt Tolerance in Cotton

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.