Widespread deviant patterns of heterozygosity in whole-genome sequencing due to autopolyploidy, repeated elements, and duplication

Abstract

Most population genomic tools rely on accurate SNP calling and filtering to meet their underlying assumptions. However, genomic complexity, due to structural variants, paralogous sequences and repetitive elements, presents significant challenges in assembling contiguous reference genomes. Consequently, short-read resequencing studies can encounter mismapping issues, leading to SNPs that deviate from Mendelian expected patterns of heterozygosity and allelic ratio. In this study, we employed the ngsParalog software to identify such deviant SNPs in whole-genome sequencing data from four species: Arctic Char (Salvelinus alpinus), Lake Whitefish (Coregonus clupeaformis), Atlantic Salmon (Salmo salar), and the American Eel (Anguilla rostrata), with low (2X) to intermediate (6X) coverage. The analyses revealed that deviant SNPs accounted for up to 62% of all SNPs in salmonid datasets and approximately 10% in the American Eel dataset. These deviant SNPs were particularly concentrated within repetitive elements and genomic regions that had recently undergone rediploidization in salmonids. Additionally, narrow peaks of elevated coverage were ubiquitous along all four reference genomes, encompassed most deviant SNPs and could be partially attributed to transposons and tandem repeats. Including these deviant SNPs in genomic analyses led to highly distorted site frequency spectra, apparent homogenization of populations and underestimating pairwise FST values. Considering the widespread occurrence of deviant SNPs arising from a variety of source, their important impact in estimating population parameters, and the availability of effective tools to identify them, we propose that excluding deviant-SNPs from WGS datasets is required to improve genomic inferences for a wide range of taxa and sequencing depths.

Investigating structural variant, indel and single nucleotide polymorphism differentiation between locally adapted Atlantic salmon populations

“…To identify syntenic regions, we followed the steps described by Dallaire et al. (2023): in summary, we aligned the genome to itself with nucmer (built‐in mapper in MUMmer version 4.0.0; Marçais et al., 2018), then performed synteny analysis with SyMAP (Soderlund et al., 2011), and re‐mapped syntenic blocks to the genome with LASTZ (version 1.04.15; Harris, 2007) to get the homology percentage. We identified repeats and transposable elements using RepeatMasker (version 4.0.8; Smit et al., 2013).…”

Investigating structural variant, indel and single nucleotide polymorphism differentiation between locally adapted Atlantic salmon populations

“…In an effort to better link the genomic context and the confidence in SV calling, we compared the frequency distributions of both high-quality SVs that passed all filtering steps and low-quality, filtered out SVs in two genomic features known to interfere with SV calling: highly similar regions resulting from whole-genome duplication events (e.g., syntenic regions) and repeated content (repeats and transposable elements). To identify syntenic regions, we followed the steps described by Dallaire et al (2023): in summary, we aligned the genome to itself with nucmer (built-in mapper in MUMmer version 4.0.0; Marçais et al, 2018), then performed synteny analysis with SyMAP (Soderlund, Bomhoff & Nelson, 2011), et re-mapped syntenic blocks to the genome with LASTZ (version 1.04.15, Harris, 2007) to get the homology percentage. We identified repeats and transposable elements using RepeatMasker (version 4.0.8).…”