Construction of a high-resolution genetic map of Crassostrea gigas: QTL mapping and GWAS applications revealed candidate genes controlling nutritional traits

Abstract

Nutritional traits that directly influence the flavor and nutritional value of the Pacific oyster, Crassostrea gigas (C. gigas), are important economically for their commercial trade. However, few studies have been reported to focus on the genetic analysis of these traits. Both genotyping-by-sequencing (GBS) based genetic maps and quantitative trait locus (QTL) analysis have been conducted for growth and nutritional traits in our previous study. Here, the 190 K Pacific oyster single-nucleotide polymorphism (SNP) array was used for genotyping and the construction of the genetic map. Furthermore, we performed QTL mapping and genome-wide association study (GWAS) for several nutritional traits including composition of 22 fatty acids, glycogen, Zn (zinc) and Se (selenium) using a full-sib family and a natural population. By combining these approaches we obtained complementary results that may advance the current understanding regarding C. gigas nutritional traits. The genetic map contained 7861 SNPs with an average marker interval of 0.31 cM and covered approximately 75% of the oyster genome, thereby representing a high-density genetic map for C. gigas. According to the QTL mapping, a total of 100 QTLs were detected for 22 traits, 15 of which were colocated by the significant SNPs of GWAS. Within these regions, five key genes (OSBPL11, MC5R, KLF3, ADAMTS, INSIG2) were identified to participate in fat metabolism and showed significant phenotypic differences in different genotypes. In addition, 13 genes involved in the synthesis, oxidation, and lipogenesis of fatty acids, as well as in the regulation of glycogen metabolism were excavated from the remaining 85 QTLs. Six of these genes (MC5R, KLF3, PECR, ACSL1, LIPE and AGPAT6) have been reported to be related to meat quality, as well as the fatty acid compositions or milk fat of pig, bovine and goat. Overall, these vital SNPs and candidate genes may serve as a potential resource for selective breeding in the future. Meanwhile, our study certified that conjoint analysis of QTL mapping and GWAS could provide a powerful method to study complex traits in aquatic breeding.