SNP-based Modeling Reveal Breeding and Sowing Co-Adaption Potential in Stabilizing Wheat Phenology under Global Warming

ABSTRACT Global warming is expected to shorten wheat growth duration and reduce yield. However, breeding potential for stabilizing phenology under climate change has been less evaluated for major wheat producing regions. By integrating genome-wide SNPs with the process-based WheatGrow model, we developed a novel framework predicting heading date (HD) across 881 wheat genotypes of three breeding populations in 20 European and Chinese environments‌. This approach yields improved prediction in accuracy for untested genotypes and environments compared to conventional genomic prediction‌. HD predictions indicated future warming will shorten wheat growth periods to heading substantially, while genotypes among the three breeding populations exhibited divergent responses to climate warming across different environments. Ideotypes selection and common SNPs from them change dynamically with the threshold days selection. Under optimized sowing window, about 32-48 % of the genotypes were screened as ideotypes in stabilizing wheat HD across multiple representative sites under future climate warming. Furthermore, 6-46 shared SNPs among these ideotypes were identified for potential ideotype design in future breeding programs. These findings indicated substantial breeding potential in stabilizing wheat phenology under climate warming in China and Europe. Our results provide a novel genotype-to-phenotype framework for optimizing wheat phenology by management practices and ideotype design under climate warming.