Wheat diversity reveals new genomic loci and candidate genes for vegetation indices using genome-wide association analysis

Abstract

Wheat (Triticum aestivum L.), a globally essential crop, exhibits high vulnerability to drought stress, particularly within rainfed agricultural systems. Enhancing resilience requires a deeper understanding of the genetic architecture underlying key physiological traits. Spectral vegetation indices provide a high-throughput, non-invasive approach to quantify these traits, but their genetic basis in wheat under drought remains largely unexplored. We conducted a genome-wide association study (GWAS) using 187 bread wheat genotypes evolved and selected across rainfed conditions. This population was phenotyped for 25 vegetation indices and genotyped using a 25K SNP array. Phenotypic data showed significant genetic variation with broad-sense heritability (H{superscript 2}) ranging from 0.19 to 0.95. Comparing phenotype and genotype data identified 812 Bonferroni-significant associations distributed across the A, B and D genomes. A prominent major QTL effect was identified as a hotspot on chromosome 2A, tagged by SNP marker wsnp_Ex_c36049_44083089, was among the strongest associations for 17 vegetation indices, explaining up to 20% of the genotypic variance for key traits like greenness and pigment indices. Candidate gene analysis at this locus identified the co-localization of a LEA_2/NDR1-like gene and a lectin receptor-like kinase with multiple genes involved in terpenoid, phenylpropanoid and primary metabolism, consistent with integrated roles in stress signaling and metabolic acclimation. These data show that vegetation indices are heritable digital phenotypes, which can be employed for the selection and genetic analysis of essential physiological growth parameters under varying and adverse climatic conditions.