Lessons from a GWAS study of a wheat pre-breeding program: pyramiding resistance alleles to Fusarium crown rot

Much has been published on QTL detection for complex traits using bi-parental and multi-parental crosses (linkage analysis) or diversity panels (GWAS studies). While successful for detection, transferability of results to real applications has proven more difficult. Here, we combined a QTL detection approach using a pre-breeding populations which utilized intensive phenotypic selection for the target trait across multiple plant generations, combined with rapid generation turnover (i.e. speed breeding) to allow cycling of multiple plant generations each year. The reasoning is that QTL mapping information would complement the selection process by identifying the genome regions under selection within the relevant germplasm. Questions to answer were the location of the genomic regions determining response to selection and the origin of the favourable alleles within the pedigree. We used data from a pre-breeding program that aimed at pyramiding different resistance sources to Fusarium crown rot into elite (but susceptible) wheat backgrounds. The population resulted from a complex backcrossing scheme involving multiple resistance donors and multiple elite backgrounds, akin to a MAGIC population (985 genotypes in total, with founders, and two major offspring layers within the pedigree). A significant increase in the resistance level was observed (i.e. a positive response to selection) after the selection process, and 17 regions significantly associated with that response were identified using a GWAS approach. Those regions included known QTL as well as potentially novel regions contributing resistance to Fusarium crown rot. In addition, we were able to trace back the sources of the favourable alleles for each QTL. We demonstrate that QTL detection using breeding populations under selection for the target trait can identify QTL controlling the target trait and that the frequency of the favourable alleles was increased as a response to selection, thereby validating the QTL detected. This is a valuable opportunistic approach that can provide QTL information that is more easily transferred to breeding applications.

Automated summary

The study combined a fast breeding approach with intensive phenotypic selection to detect QTLs controlling Fusarium crown rot resistance in wheat. They identified 17 genomic regions associated with the response to selection, including both known QTLs and potentially novel regions contributing to resistance. The study demonstrated that QTL detection in breeding populations under selection can identify and increase the frequency of favorable alleles, providing valuable information for breeding applications.