Development, inheritance and evaluation of 55 novel single nucleotide polymorphism markers for parentage assignment in the Pacific oyster (Crassostrea gigas)

Characterization of Eighty-Eight Single-Nucleotide Polymorphism Markers in the Manila Clam Ruditapes philippinarum Based on High-Resolution Melting (HRM) Analysis

Single-nucleotide polymorphisms (SNPs) are the most commonly used DNA markers in population genetic studies. We used the Illumina HiSeq4000 platform to develop single-nucleotide polymorphism (SNP) markers for Manila clam Ruditapes philippinarum using restriction site-associated DNA sequencing (RAD-seq) genotyping. Eighty-eight SNP markers were successfully developed by using high-resolution melting (HRM) analysis, with a success rate of 44%. SNP markers were analyzed for genetic diversity in two clam populations. The observed heterozygosity per locus ranged from 0 to 0.9515, while the expected heterozygosity per locus ranged from 0.0629 to 0.4997. The value of FIS was estimated to be from -0.9643 to 1.0000. The global Fst value was 0.1248 (p < 0.001). After Bonferroni correction, 15 loci deviated significantly from the Hardy-Weinberg equilibrium (p < 0.0006). These SNP markers provide a valuable resource for population and conservation genetics studies in this commercially important species.

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

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.

The future of parentage analysis: From microsatellites to SNPs and beyond

Parentage analysis is a cornerstone of molecular ecology that has delivered fundamental insights into behaviour, ecology and evolution. Microsatellite markers have long been the king of parentage, their hypervariable nature conferring sufficient power to correctly assign offspring to parents. However, microsatellite markers have seen a sharp decline in use with the rise of next-generation sequencing technologies, especially in the study of population genetics and local adaptation. The time is ripe to review the current state of parentage analysis and see how it stands to be affected by the emergence of next-generation sequencing approaches. We find that single nucleotide polymorphisms (SNPs), the typical next-generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP-based parentage analyses published thus far. Many of these papers, particularly the earlier ones, compare the power of SNPs and microsatellites in a parentage context. In virtually every case, SNPs are at least as powerful as microsatellite markers. As few as 100-500 SNPs are sufficient to resolve parentage completely in most situations. We also provide an overview of the analytical programs that are commonly used and compatible with SNP data. As the next-generation parentage enterprise grows, a reliance on likelihood and Bayesian approaches, as opposed to strict exclusion, will become increasingly important. We discuss some of the caveats surrounding the use of next-generation sequencing data for parentage analysis and conclude that the future is bright for this important realm of molecular ecology.

Development of a Medium Density Combined-Species SNP Array for Pacific and European Oysters (Crassostrea gigas and Ostrea edulis)

SNP arrays are enabling tools for high-resolution studies of the genetic basis of complex traits in farmed and wild animals. Oysters are of critical importance in many regions from both an ecological and economic perspective, and oyster aquaculture forms a key component of global food security. The aim of our study was to design a combined-species, medium density SNP array for Pacific oyster (Crassostrea gigas) and European flat oyster (Ostrea edulis), and to test the performance of this array on farmed and wild populations from multiple locations, with a focus on European populations. SNP discovery was carried out by whole-genome sequencing (WGS) of pooled genomic DNA samples from eight C. gigas populations, and restriction site-associated DNA sequencing (RAD-Seq) of 11 geographically diverse O. edulis populations. Nearly 12 million candidate SNPs were discovered and filtered based on several criteria, including preference for SNPs segregating in multiple populations and SNPs with monomorphic flanking regions. An Affymetrix Axiom Custom Array was created and tested on a diverse set of samples (n = 219) showing ∼27 K high quality SNPs for C. gigas and ∼11 K high quality SNPs for O. edulis segregating in these populations. A high proportion of SNPs were segregating in each of the populations, and the array was used to detect population structure and levels of linkage disequilibrium (LD). Further testing of the array on three C. gigas nuclear families (n = 165) revealed that the array can be used to clearly distinguish between both families based on identity-by-state (IBS) clustering parental assignment software. This medium density, combined-species array will be publicly available through Affymetrix, and will be applied for genome-wide association and evolutionary genetic studies, and for genomic selection in oyster breeding programs.

SNP mining in Crassostrea gigas EST data: transferability to four other Crassostrea species, phylogenetic inferences and outlier SNPs under selection

Oysters, with high levels of phenotypic plasticity and wide geographic distribution, are a challenging group for taxonomists and phylogenetics. Our study is intended to generate new EST-SNP markers and to evaluate their potential for cross-species utilization in phylogenetic study of the genus Crassostrea. In the study, 57 novel SNPs were developed from an EST database of C. gigas by the HRM (high-resolution melting) method. Transferability of 377 SNPs developed for C. gigas was examined on four other Crassostrea species: C. sikamea, C. angulata, C. hongkongensis and C. ariakensis. Among the 377 primer pairs tested, 311 (82.5%) primers showed amplification in C. sikamea, 353 (93.6%) in C. angulata, 254 (67.4%) in C. hongkongensis and 253 (67.1%) in C. ariakensis. A total of 214 SNPs were found to be transferable to all four species. Phylogenetic analyses showed that C. hongkongensis was a sister species of C. ariakensis and that this clade was sister to the clade containing C. sikamea, C. angulata and C. gigas. Within this clade, C. gigas and C. angulata had the closest relationship, with C. sikamea being the sister group. In addition, we detected eight SNPs as potentially being under selection by two outlier tests (fdist and hierarchical methods). The SNPs studied here should be useful for genetic diversity, comparative mapping and phylogenetic studies across species in Crassostrea and the candidate outlier SNPs are worth exploring in more detail regarding association genetics and functional studies.