Multi-parent mapping reveals epistatic architecture and elite haplotypes for multi-trait improvement in cotton

Cotton domestication has fixed favorable alleles, often masking cryptic loci and reinforcing genetic trade-offs, particularly between yield and fiber quality, thereby constraining simultaneous trait improvement.

We develop an eight-parent MAGIC population comprising 319 recombinant inbred lines through a 12-year breeding program and integrate it with a panel of 318 Xinjiang cotton cultivars released between 1978 and 2024. High-resolution genomic analyses combining SNP-based and identity-by-descent mapping identify 111 sQTLs and 15 hQTLs associated with 19 agronomic traits across multiple environments. Genome-wide epistasis analysis further identifies over 3,000 cryptic loci, highlighting complex genetic interactions underlying trait variation. Parallel population genomic analyses of Xinjiang cultivars reveal 520 genomic regions consistently shaped by modern breeding selection. Integrating these datasets enabled the construction of a multi-trait optimization framework to prioritize elite genotypes with favorable allele combinations. We validate this framework using cultivars derived from MAGIC parental lines, including Zhuangjiahan902 and Huaxin103, demonstrating coordinated improvement in yield and fiber quality.

This study demonstrates the dual utility of MAGIC populations for high-resolution genetic dissection and breeding application. The integrative framework presented here provides a scalable strategy for resolving genetic trade-offs and achieving coordinated multi-trait improvement in cotton and other major crops.