Association mapping of QTLs for sclerotinia stem rot resistance in a collection of soybean plant introductions using a genotyping by sequencing (GBS) approach

• Published in: BMC plant biology 2015-01, Vol.15 (1), p.5-5, Article 5
• Main Authors: Iquira, Elmer, Humira, Sonah, François, Belzile
• Format: Article
• Language: English
• Subjects: Analysis; Ascomycota - physiology; Chromosome Mapping; Chromosomes, Plant - genetics; Disease Resistance - genetics; Genetic Association Studies; Genetic Markers; Genome, Plant; Genotyping Techniques - methods; Glycine max - genetics; Glycine max - microbiology; Linkage Disequilibrium - genetics; Phenotype; Plant Diseases - genetics; Plant Diseases - microbiology; Plant Stems - genetics; Plant Stems - microbiology; Polymorphism, Single Nucleotide - genetics; Principal Component Analysis; Quantitative genetics; Quantitative Trait Loci - genetics; Sclerotinia; Sequence Analysis, DNA
• ISSN: 1471-2229; 1471-2229
• DOI: 10.1186/s12870-014-0408-y

Sclerotinia stem rot (SSR) is the most important soybean disease in Eastern Canada. The development of resistant cultivars represents the most cost-effective means of limiting the impact of this disease. In view of ensuring durable resistance, it is imperative to identify germplasm harbouring different resistance loci and to provide breeders with closely linked molecular markers to facilitate breeding. With this end in view, we assessed resistance using a highly reproducible artificial inoculation method on a diverse collection of 101 soybean lines, mostly composed of plant introductions (PIs) and some of which had previously been reported to be resistant to sclerotinia stem rot. Overall, 50% of the lines exhibited a level of resistance equal to or better than the resistant checks among elite material. Of the 50 lines previously reported to be resistant, only 20 were in this category and a few were highly susceptible under these inoculation conditions. The collection of lines was genetically characterized using a genotyping by sequencing (GBS) protocol that we have optimized for soybean. A total of 8,397 single nucleotide polymorphisms (SNPs) were obtained and used to perform an association analysis for SSR by using a mixed linear model as implemented in the TASSEL software. Three genomic regions were found to exhibit a significant association at a stringent threshold (q = 0.10) and all of the most highly resistant PIs shared the same alleles at these three QTLs. The strongest association was found on chromosome Gm03 (P-value = 2.03 × 10(-6)). The other significantly associated markers were found on chromosomes Gm08 and Gm20 with P-values