Deciphering the regulatory network of carbon isotope discrimination in bread wheat through genome-wide association...

A total of 125 QTL regions and 33 candidate genes associated with carbon isotope discrimination (CID) were identified in wheat, and genomic prediction (GP) achieved high accuracy (Pearson correlation coefficient, PCC = 0.665), providing valuable tools for reeding drought-resilient varieties. Carbon isotope discrimination (CID) is a critical physiological trait that serves as an indicator of water use efficiency (WUE) and drought tolerance in wheat. In this study, the genetic basis of CID was analyzed through genome-wide association studies (GWAS) and genomic prediction (GP) using a diverse panel of 238 wheat varieties. High-density genotyping identified 125 significant quantitative trait loci (QTL) regions and 33 candidate genes, primarily involved in stomatal regulation, drought tolerance, chloroplast development, chlorophyll metabolism, leaf development, and light signaling pathways. Bayesian ridge regression was used to predict CID under normal water (CID_NW), water-limited (CID_WL), rain-fed conditions (CID_RF), and a combined environment (CID_BLUE). The model showed stable performance across environments, with the highest accuracy (Pearson correlation coefficient, PCC = 0.665 for CID_RF) achieved using a genotype matrix containing the SNP with the lowest p-value from each QTL. These findings provide novel insights into the genetic architecture of CID and its potential role in enhancing drought tolerance in wheat. The identified QTL, candidate genes, and predictive models offer a strong foundation for marker-assisted selection (MAS) and genome-wide selection (GS) in wheat breeding programs. These results contribute to the development of drought-resilient wheat varieties, addressing key challenges in global wheat production and food security.