Quantitative trait locus mapping and improved resistance to sclerotinia stem rot in a backbone parent of rapeseed (Brassica napus L.)

There are three main challenges to improving sclerotinia stem rot (SSR) resistance in rapeseed (Brassica napus L.). First, breeding materials such as the backbone parents have not been extensively investigated, making the findings of previous studies difficult to directly implement. Second, SSR resistance and flowering time (FT) loci are typically linked; thus, use of these loci requires sacrifice of the rapeseed growth period. Third, the SSR resistance loci in susceptible materials are often neglected, thereby reducing the richness of resistant resources. This study was conducted to investigate the stem resistance, disease index, and FT of a doubled haploid population consisting of 151 lines constructed from the backbone parent 19514A and conventional rapeseed cultivar ZY50 within multiple environments. Quantitative trait locus (QTL) mapping revealed 13 stem resistance QTLs, 9 disease index QTLs, and 20 FT QTLs. QTL meta-analysis showed that uqA04, uqC03.1, and uqC03.2 were repeatable SSR resistance QTLs derived from different parents but not affected by the FT. Based on these three QTLs, we proposed a strategy for improving the SSR resistance of 19514A and ZY50. This study improves the understanding of the resistance to rapeseed SSR and genetic basis of FT and demonstrates that SSR resistance QTLs can be mined from parents with a minimal resistance level difference, thereby supporting the application of backbone parents in related research and resistance improvement.

Automated summary

Improving sclerotinia stem rot (SSR) resistance in rapeseed faces three challenges: limited investigation of breeding materials, linkage between SSR resistance and flowering time, and neglect of resistance loci in susceptible materials. This study mapped multiple QTLs for stem resistance, disease index, and flowering time in a doubled haploid population, and proposed a strategy for resistance improvement based on identified QTLs.