High macro-collinearity between Crassostrea angulata and C. gigas genomes was revealed by comparative genetic mapping with transferable EST-SNP markers

Comparative genomics has become an important strategy for transferring genetic information from a well-characterized model species to one that is less described and can facilitate in functional gene mining and genomic evolution. Crassostrea angulata and Crassostrea gigas are closed related species that they can hybridize to produce fertile offspring, and C. gigas has accumulated a considerable number of genetic and genomic resources while C. angulata lags far behind. In the current study, 684 single nucleotide polymorphism (SNP) markers developed from C. gigas expressed sequence tags (ESTs) were used for transferability test in C. angulata, and 635 loci were successfully amplified. Then a genetic linkage map of C. angulata was for the first time constructed using these transferable SNP markers. A total of 988 transferable SNP markers were used for polymorphism screening in a mapping family, and 273 loci were distributed on the genetic map which was composed of 10 linkage groups and estimated 1040.29 cM in total length. The average spacing between markers was 3.96 cM. By comparing the shared EST-SNP marker locations on homologous linkage groups, comparative mapping analysis between the C. angulata genetic map and an integrated map of C. gigas revealed putative macro-collinearity in the two oyster genomes with little difference in markers order. These transferable SNP markers could be applied in genetic diversity and population structure studies, and the genetic map would be useful for quantitative trait loci mapping and genetic improvement through marker-assisted selection for C. angulata.

Automated summary

By transferring SNP markers from Pacific oysters to Crassostrea angulata and constructing a genetic linkage map, putative macro-collinearity between the genomes of the two oyster species was revealed, providing essential tools for studying genetic diversity and mapping quantitative trait loci.