Genome Structural Variation Landscape and Its Selection Signatures in the Fast-growing Strains of the Pacific Oyster, Crassostrea gigas

Mar Biotechnol (NY). 2021 Oct;23(5):736-748. doi: 10.1007/s10126-021-10060-5. Epub 2021 Sep 8.

Abstract

The Pacific oyster (Crassostrea gigas) genome is highly polymorphic and affluent in structural variations (SVs), a significant source of genetic variation underlying inter-individual differences. Here, we used two genome assemblies and 535 individuals of genome re-sequencing data to construct a comprehensive landscape of structural variations in the Pacific oyster. Through whole-genome alignment, 11,087 short SVs and 11,561 copy number variations (CNVs) were identified. While analysis of re-sequencing data revealed 511,170 short SVs and 979,486 CNVs, a total of 63,100 short SVs and 58,182 CNVs were identified in at least 20 samples and regarded as common variations. Based on the common short SVs, both Fst and Pi ratio statistical methods were employed to detect the selective sweeps between 20 oyster individuals from the fast-growing strain and 20 individuals from their corresponding wild population. A total of 514 overlapped regions (8.76 Mb), containing 746 candidate genes, were identified by both approaches, in addition with 103 genes within 61 common CNVs only detected in the fast-growing strains. The GO enrichment and KEGG pathway analysis indicated that the identified candidate genes were mostly associated with apical part of cell and were significantly enriched in several metabolism-related pathways, including tryptophan metabolism and histidine metabolism. This work provided a comprehensive landscape of SVs and revealed their responses to selection, which will be valuable for further investigations on genome evolution under selection in the oysters.

Keywords: Artificial selection; Crassostrea gigas; Fast growth; Structural variation.

MeSH terms

  • Animals
  • Crassostrea / genetics*
  • Crassostrea / growth & development
  • DNA Copy Number Variations
  • Genetic Variation*
  • Genome
  • Genomic Structural Variation*
  • Signal Transduction