Huseynova, I. | bioRxiv Science

bioRxiv2026

Genome-wide association analysis reveals new loci for leaf water status, biomass and plant architectural traits in bread wheat under rainfed conditions

Drought during reproductive development and grain filling is a major constraint to bread wheat productivity in rainfed environments. In the present study, we employed genome-wide association analysis in an untapped diversity panel of wheat genotypes relevant to natural dryland conditions. A total of 186 genotypes were evaluated for drought-related physiological, biomass, and architectural traits under terminal rainfed stress in Azerbaijan. Relative water content, plant height, fresh weight, dry weight, flag leaf length, and flag leaf width were assessed at the milk ripening stage. These data were subjected to genome-wide association analysis using 19,737 SNP markers to identify loci and epistatic interactions involved in the determination of these traits. The panel showed broad phenotypic variation and significant genotypic effects for all traits, with broad-sense heritability ranging from 0.991 for plant height to 0.385 for flag leaf width. GWAS identified a major locus for relative water content on chromosome 2D at SNP marker AX-86184518, which explained 11.94% of the genotypic variation. Candidate-gene analysis highlighted the proximal WEB-family-like gene TraesCS2D03G1001000 as the main candidate gene. Plant height showed strong additive loci, mainly on chromosomes 2A and 4A, whereas biomass and flag leaf traits showed suggestive additive loci and epistatic interactions. These findings provide candidate loci and interaction patterns in the genetic make-up of essential traits, which may facilitate indirect selection in breeding new varieties.

genetics↗

bioRxiv2026

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

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.

plant biology↗