Genomic signatures of artificial selection in the Pacific oyster, Crassostrea gigas

太平洋牡蛎(Crassostrea gigas)中人工选择的基因组特征

阅读:1

Abstract

The Pacific oyster, Crassostrea gigas, is an important aquaculture shellfish around the world with great economic and ecological value. Selective breeding programs have been carried out globally to improve production and performance traits, while genomic signatures of artificial selection remain largely unexplored. In China, we performed selective breeding of C. gigas for over a decade, leading to production of several fast-growing strains. In the present study, we conducted whole-genome resequencing of 20 oysters from two fast-growing strains that have been successively selected for 10 generations, and 20 oysters from the two corresponding wild populations. Sequencing depth of >10× was achieved for each sample, leading to identification of over 12.20 million SNPs. The population structures investigated with three independent methods (principal component analysis, phylogenetic tree, and structure) suggested distinct patterns among selected and wild oyster populations. Assessment of the linkage disequilibrium (LD) decay clearly indicated the changes in genetic diversity during selection. Fixation index (F (st)) combined with cross-population composite likelihood ratio (XP-CLR) allowed for identification of 768 and 664 selective sweeps (encompassing 1042 and 872 genes) tightly linked to selection in the two fast-growing strains. KEGG enrichment and functional analyses revealed that 33 genes are important for growth regulation, which act as key components of various signaling pathways with close connection and further take part in regulating the process of cell cycle. This work provides valuable information for the understanding of genomic signatures for long-term selective breeding and will also be important for growth study and genome-assisted breeding of the Pacific oyster in the future.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。