Linking phenotypic diversity to genomic hotspots using multi-environmental GWAS reveals genetic control of agronomic traits and drought resilience in wheat

Abstract

Climate volatility demands wheat varieties with enhanced yield stability. Unraveling the genetic basis of stability, particularly genotype-by-environment (G × E) interactions, is critical in varirty development. We performed a high-resolution genetic analysis on 158 wheat recombinant inbred lines (RILs) for 19 traits across 12 contrasting environments. Using 14,676 SNP markers, we conducted a multi-environment genome-wide association study (GWAS) with Mixed Linear Model (MLM) and Fixed and Random Model Circulating Probability Unification (FarmCPU) models, followed by Linkage Disequilibrium (LD) block, haplotype, and pleiotropy analyses. Phenotypic data showed yield components were environmentally sensitive, while traits like plant height (PH) were strongly controlled by genetic components. Genomic analyses revealed distinct sub-genome architectures. Key results include the identification of 8,092 significant SNP-trait associations and the discovery of 57 environmentally stable, pleiotropic SNPs. Chromosome group 1 (1A, 1B, 1D) was a major hotspot, harboring 32 multi-trait loci. Multi-environment GWAS revealed that the extreme PH effects ( R 2 > 80%) were non-transferable across environments, with R 2 values falling to the 4–15% range in all other environments (E2–E12), indicating that such high values reflect single-environment bias rather than stable QTL effects. The megabase-scale LD blocks indicated extended haplotype conservation, a pattern that may arise from either directional breeding or the inherent recombination limitations of this biparental RIL population,, and haplotype analysis revealed diverse patterns from fixation to high diversity. Haplotype‑level analysis confirmed that many SNPs identified by MLM and FarmCPU are in high LD (e.g., on chromosome 5A for SPAD in E1, over a ~ 190 Mb region), indicating that they tag the same underlying quantitative trait loci (QTL). We prioritized 40 high-confidence candidate genes and confirmed stable QTLs, including a yield QTL on 1A (qGY-1A.1) and a multi-trait region on 2A. This study elucidates the complex genetic architecture of wheat productivity. Our integrated approach disentangled G × E interactions and identified genomic regions under selection. The pleiotropic hubs, stable QTLs, and candidate genes provide a robust framework for marker-assisted breeding, accelerating the development of climate-resilient wheat.