Combination of QTL mapping and GWAS for fine mapping and gene mining of drought tolerance and seed yield components in faba bean (Vicia faba L.)

Increasing crop yields in the face of climate change is a key goal in faba bean breeding. By integrating multiple data sets, we combine recent QTL and GWAS analyses for yield and drought resistance and uncover the most consistent genomic regions related with these traits. We determine the physical position of the significant markers in the reference faba bean genome and assess the co-localization of significant QTNs with stable QTLs, thus pinpointing the most likely candidate genes. One hundred fifty-two annotated genes, found in 10 overlapping genomic regions, were predicted as faba bean candidate genes for drought and yield related traits and many of them were closely related to genes previously identified and validated in other crops. Several significant markers appear to influence multiple traits, sometimes even seemingly unrelated ones suggesting potential pleiotropy or close physical linkage, although further validation is required. Integrating previously published QTLs and GWAS results for yield and drought related traits and projecting the significant markers onto the physical reference genome we identified overlapping regions and mine candidate genes within those intervals. The results of this study significantly advance our understanding of the genetic architecture of various traits and provide useful information of candidate genes that might have potential for selection in future faba bean breeding programs.