Construction of a high-density genetic map and fine QTL mapping for growth and nutritional traits of Crassostrea gigas

Abstract

BackgroundBoth growth and nutritional traits are important economic traits of Crassostrea gigas (C. gigas) in industry. But few work has been done to study the genetic architecture of nutritional traits of the oyster. In this study, we constructed a high-density genetic map of C. gigas to help assemble the genome sequence onto chromosomes, meanwhile explore the genetic basis for nutritional traits via quantitative trait loci (QTL) mapping.ResultsThe constructed genetic map contained 5024 evenly distributed markers, with an average marker interval of 0.68 cM, thus representing the densest genetic map produced for the oyster. According to the high collinearity between the consensus map and the oyster genome, 1574 scaffold (about 70%) of the genome sequence of C. gigas were successfully anchored to 10 linkage groups (LGs) of the consensus map. Using this high-qualified genetic map, we then conducted QTL analysis for growth and nutritional traits, the latter of which includes glycogen, amino acid (AA), and fatty acid (FA). Overall, 41 QTLs were detected for 17 traits. In addition, six candidate genes identified in the QTL interval showed significant correlation with the traits on transcriptional levels. These genes include growth-related genes AMY and BMP1, AA metabolism related genes PLSCR and GR, and FA metabolism regulation genes DYRK and ADAMTS.ConclusionUsing the constructed high-qualified linkage map, this study not only assembled nearly 70% of the oyster genome sequence onto chromosomes, but also identified valuable markers and candidate genes for growth and nutritional traits, especially for AA and FA that undergone few studies before. These findings will facilitate genome assembly and molecular breeding of important economic traits in C. gigas.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4996-z) contains supplementary material, which is available to authorized users.

Association and Functional Analyses Revealed That PPP1R3B Plays an Important Role in the Regulation of Glycogen Content in the Pacific Oyster Crassostrea gigas

“…Candidate gene association studies showed that six SNPs in the coding region of CgGS were significantly associated with glycogen content (Liu et al, 2017) as well as two SNPs in Cg_GD1 (glycogen debranching enzyme) and one SNP in Cg-GP (glycogen phosphorylase) (She et al, 2015). A high-density genetic map found a QTL explaining 8.6% of glycogen phenotypic variation, and a new gene annotated as a zinc finger protein may participate in glycogen metabolism (Li C. et al, 2018). Many phenotypic variations remain to be explained.…”

“…Glycogen content is a carcass trait that cannot be measured without killing the animal. Indirect selective breeding for glycogen content by morphological traits seems impossible because of the weak correlation between these characteristics, as shown in several studies (Li et al, 2017; Li C. et al, 2018). Thus, molecular breeding is indispensable for the genetic improvement of glycogen content, which requires elucidation of the underlying genetic basis and the identification of genetic variations.…”

Comparative Transcriptome Analysis Reveals Molecular Basis Underlying Fast Growth of the Selectively Bred Pacific Oyster, Crassostrea gigas

“…Genetic linkage maps of the Pacific oyster have been constructed based on a variety of molecular markers, including amplified fragment length polymorphism (AFLP) markers or combinations of AFLP with microsatellite markers (Li and Guo, 2004; Guo et al, 2012), microsatellites markers (Li et al, 2003; Hubert and Hedgecock, 2004; Hubert et al, 2009; Plough and Hedgecock, 2011), SNPs (Sauvage et al, 2007; Wang et al, 2015; Qi et al, 2017), and a combination of microsatellite markers with SNPs (Sauvage et al, 2010; Zhong et al, 2014; Hedgecock et al, 2015). Based on these linkage maps, quantitative trait locus (QTL) mapping studies have been performed to examine the genetic basis of growth-related traits in the Pacific oyster (Prudence et al, 2006; Hedgecock et al, 2007a; Guo et al, 2012; Wang et al, 2016; Li et al, 2018). In most of these studies, numerous QTLs associated with growth traits were reported, indicating that growth in oysters is a highly polygenic trait (Qin et al, 2012; Gutierrez et al, 2018).…”

Comparative genomics reveals evolutionary drivers of sessile life and left-right shell asymmetry in bivalves

“…Regions that failed to be restored to the original assembly or contained an average Hi-C data coverage of less than 0.5% were considered assembly errors, and were broken into smaller scaffolds. Consistency in assembly of Hi-C data based pseudo-chromosomes was assessed by comparisons with a genetic map for the Crassostrea gigas [89] by using software of ALLMAPS [90].…”