Genome-wide association mapping and genomic prediction for adult stage sclerotinia stem rot resistance in Brassica napus (L) under field environments

• Published in: Scientific reports 2021-11, Vol.11 (1), p.21773-18, Article 21773
• Main Authors: Roy, Jayanta, Shaikh, T. M., del Río Mendoza, Luis, Hosain, Shakil, Chapara, Venkat, Rahman, Mukhlesur
• Format: Article
• Language: English
• Subjects: 631/114; 631/208; 631/449; Algorithms; Ascomycota - physiology; Brassica napus; Brassica napus - genetics; Brassica napus - microbiology; Breeding; Canola; Crop yield; Disease resistance; Disease Resistance - genetics; Flowering; Gene mapping; Genome, Plant; Genome-wide association studies; Genome-Wide Association Study; Genomes; Genomics; Genotypes; Genotyping Techniques; Host-Pathogen Interactions - genetics; Humanities and Social Sciences; Inoculation; Lesions; multidisciplinary; Phenotype; Phenotypes; Phenotypic variations; Phenotyping; Plant Diseases - immunology; Science; Science (multidisciplinary); Single-nucleotide polymorphism; Stem rot
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-01272-9

Sclerotinia stem rot (SSR) is a fungal disease of rapeseed/canola that causes significant seed yield losses and reduces its oil content and quality. In the present study, the reaction of 187 diverse canola genotypes to SSR was characterized at full flowering stage using the agar plug to stem inoculation method in four environments. Genome-wide association study (GWAS) using three different algorithms identified 133 significant SNPs corresponding with 123 loci for disease traits like stem lesion length (LL), lesion width (LW), and plant mortality at 14 (PM_14D) and 21 (PM_21D) days. The explained phenotypic variation of these SNPs ranged from 3.6 to 12.1%. Nineteen significant SNPs were detected in two or more environments, disease traits with at least two GWAS algorithms. The strong correlations observed between LL and other three disease traits evaluated, suggest they could be used as proxies for SSR resistance phenotyping. Sixty-nine candidate genes associated with disease resistance mechanisms were identified. Genomic prediction (GP) analysis with all the four traits employing genome-wide markers resulted in 0.41–0.64 predictive ability depending on the model specifications. The highest predictive ability for PM_21D with three models was about 0.64. From our study, the identified resistant genotypes and stable significant SNP markers will serve as a valuable resource for future SSR resistance breeding. Our study also suggests that genomic selection holds promise for accelerating canola breeding progress by enabling breeders to select SSR resistance genotypes at the early stage by reducing the need to phenotype large numbers of genotypes.