SNP genotypes of two west-Pacific pen shells, Atrina japonica and Atrina lischkeana, and their hybrids
Citation
Sekino, Masashi (2023), SNP genotypes of two west-Pacific pen shells, Atrina japonica and Atrina lischkeana, and their hybrids, Dryad, Dataset, https://doi.org/10.5061/dryad.6m905qg2m
Abstract
Based on the analysis of single nucleotide polymorphisms (SNPs), we examined the occurrence of introgressive hybridization (introgression) between two bivalve species distributed in the west Pacific margin, Atrina japonica (Reeve, 1858) and Atrina lischkeana (Clessin, 1891). With the resulting SNP profiles (1,469 SNPs), we also aimed at identifying genomic regions contributing to their reproductive isolation in a hybrid zone.
Methods
The SNP data was obtained by RAD sequencing (restriction enzyme: SbfI). We followed Sekino et al. (2016) for RAD library construction. The libraries were subjected to short-read sequencing with a NextSeq 500 sequencer in combination with NextSeq 500 High Output Kit (Illumina; 75 cycles of single-end sequencing).
We truncated the resulting short reads to 64 bases including partial SbfI-recognition sequence (six bases) using the subprogram process_radtags of Stacks v1.35 or higher (Catchen et al. 2011). The subsequent variant calling was based on the remaining 58 bases. With FASTX-Toolkit v0.0.14 (http://hannonlab.cshl.edu/fastx_toolkit), low quality reads, which had a base-quality score of less than 20 at 5% or more of the bases, were discarded. Reads retained after this filtering were mapped onto a reference genome of Atrina japonica (Sekino et al. in press; DDBJ/EMBL/GenBank accession numbers, BROG01000001‒BROG01003391; Sequence Read Archive, DRR380487 and DRR380488) based on the MEM algorithm available in BWA v0.7.12 (Li & Durbin 2010) with default parameters. After extracting mapped reads (the subprogram view in SAMtools v0.1.19; Li et al. 2009), we set aside reads with alternative hits (“XA” tag) and chimeric reads (“SA” tag). The resulting data (bam format) were converted to the mpileup format (the subprogram mpileup of SAMtools). Based on the mpileup data, we performed variant calling with the subprogram mpileup2snp of VarScan 2 v2.4.4 (Koboldt et al. 2012). In this computation, the following parameters were set for calling a variant at a position: minimum base-quality score, 30; minimum number of reads that supported a variant, 5; threshold significance value to call a variant (Fisher’s exact test), 0.05. After variant calling and initial filtering, we performed more rigorous SNP filtering as follows (see also Sekino et al. in press):
1. Biallelic sites were selected (VCFtools v0.1.16; Danecek et al. 2011).
2. For each specimen, sites with the coverage depth of < 30 were rejected (VCFtools).
3. Sites with the coverage depth of ≤ D+3√D, where D is the average depth over all SNP sites and specimens, were allowed (Li 2014).
4. Specimens with more than 10% missing genotypes were omitted.
5. Sites with minor allele frequency of > 0.05 across the population samples were selected (VCFtools).
6. Sites that were available in 90% or more of the specimens across the population samples as well as in each population sample were retained.
7. Sites were thinned so that neighboring sites were at least 1 Kb apart in a contig of the reference genome.
8. Sites that were out of Hardy-Weinberg equilibrium (HWE) were removed (an exact test available in VCFtools; critical P of 0.05 without correction of significance level for multiple simultaneous comparisons). The HWE filtering was applied to two population samples of putatively pure species (A. japonica, HKDT; A. lischkeana, GOTO). Sites that failed to meet HWE in either sample or both were omitted.
9. If a pair of sites gave r2 (an indicator of linkage disequilibrium) of > 0.1, one of the two sites was removed (BCFtools v1.8; Li 2011). As with the HWE filtering, this filtering was applied to the HKDT and GOTO samples.
10. If a SNP site was in a contig that had no SbfI-recognition sequence, the site was excluded.
References
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Funding
Japan Society for the Promotion of Science, Award: JSPS KAKENHI 16K07859