Identifying quantitative trait loci (QTL) associated with lodging resistance in Brassica napus L.
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Abstract
Brassica napus L. (canola and rapeseed) is the world’s second-largest oilseed crop, and it has significant economic importance to Canadian agriculture. However, lodging in canola is a significant agronomic issue, making maintaining high yield and oil quality in B. napus difficult. Discovering genetic regions associated with lodging resistance is essential to understand the mechanism controlling lodging. In this study, quantitative trait loci (QTL) analysis using the composite interval mapping method (ICIM) was conducted using two different doubled haploid (DH) populations. Genomic regions that govern lodging resistance, flowering date, plant height, and maturity date were successfully identified. Within the two populations (Z/B and L/R, which correspond to chapters three and four), QTLs associated with lodging explained 3.34 to 17.31 % and 5.6 to 11.52 % of phenotypic variation, respectively. QTL for lodging were identified on A01, A03, A05, A07, A10, and C01 in the Z/B population, and on A05, C02, C04, C05, and C07 in L/R population. Co-localization of QTL for lodging (LODG), day-to-flower (DTF), plant height (HT), and day-to-maturity (DTM) were found on A01 in Z/B, while no co-localization of QTL between different traits were observed in L/R. Most QTL identified for lodging were aligned with QTL for stem lignin, stem hemicellulose, branch number, sclerotinia stem rot, plant height, stem diameter, and stem breaking force in previous studies. Several of these QTL identified in this study appeared novel, which could be useful for future breeding programs to enhance lodging resistance in B. napus, resulting in improved yield and oil quality. QTL for lodging identified in the current study with phenotypic variation explained over 10 % were utilized to screen for potential candidate transcripts. Transcripts involved in plant cell wall biosynthesis/ modification, root development, cellulose activities, ethylene, auxin gibberellic acid and brassinosteroid signaling are promising candidate genes.