A new framework for detecting copy number variants from single nucleotide polymorphism data: ‘rCNV’, a versatile R package for paralogs and CNVs detection

Abstract

Recent studies show that copy number variants (CNVs), due to their ubiquitous presence in eukaryotes, contribute to phenotypic variation, environmental adaptation, and fuel species divergence at a previously unknown rate. However, the detection of CNVs in genomes, especially in non-model organisms is challenging due to the need for costly genomic resources and complex computational infrastructure. Therefore, to provide researchers with a low-cost and easily accessible resource, we developed a robust statistical framework and an R software package to detect CNVs from SNPs. The methods implemented in the framework use read-depth variation from high throughput sequence data, and relies on the proportion of heterozygotes in populations and their allelic ratios. The framework consists of two main steps: 1) flagging SNP deviants using allelic ratio deviations from the expectation and excess of heterozygotes under Hardy-Weinberg Equilibrium; followed by 2) filtering putative CNVs from deviant SNPs using data-specific statistical approaches. Our framework is well-catered for most GBS technologies (e.g., RADseq, Exome-capture, WGS). As such, it allows calling CNVs from genomes of varying complexity. The framework is implemented in the R package "rCNV" which effortlessly automates the analysis. We tested our models on four datasets obtained from different sequencing technologies (i.e., RADseq: Chinook salmon - Oncorhynchus tshawytscha, American lobster - Homarus americanus, Exome-capture: Norway Spruce - Picea abies, and WGS: Malaria mosquito - Anopheles gambiae). Our models detected CNVs with substantial accuracy and were significantly efficient with statistically low confident data, where average read-depth and number of samples are limited.

Despite structural identity, ace-1 heterogenous duplication resistance alleles are quite diverse in Anopheles mosquitoes

“…While we cannot exclude the existence of D copy-number-alleles, our analyses suggest that this discrepancy may come from how the number of copies were determined in these two studies. Identifying S/R copy number ratio only from the ratio of allelic coverage at a single diagnostic position (here the G119S point mutation, see Grau-Bové et al, 2021) can lead to inaccurate copy-number estimations, especially with low depth of coverage (see simulations in Karunarathne et al, 2023). In our study, using the average depth of coverage across the whole ace-1 gene to assess the number of copies and to deduce the genotype, proved to be more reliable (Supp.…”

Widespread Deviant Patterns of Heterozygosity in Whole-Genome Sequencing Due to Autopolyploidy, Repeated Elements, and Duplication

“…To validate deviant SNPs, we used an alternative to ngsParalog, consisting of two tests adapted from the HDplot method ( McKinney et al 2017 ). We first assessed excesses of heterozygotes based on the ANGSD -doHWE 1 output ( P < 0.05 and F IS < 0), then computed the deviation from the expected allelic ratio in heterozygotes (1:1), following Karunarathne et al (2022) 's implementation of HDplot. In brief, we used individual read ratios for the alternative allele in heterozygotes (genotype probability >0.8) to compute a Z-score for each SNP and compared it to a probability density function with a standard deviation of , where n is the number of heterozygotes.…”

“…The HDplot method ( McKinney et al 2017 ) is now commonly used to detect SNPs that do not conform to expected patterns of Mendelian inheritance by identifying deviations from Hardy–Weinberg Equilibrium (H) or the expected 1:1 allelic ratio in heterozygotes (D). We hereafter refer to such variants as “deviant” SNPs, as opposed to “canonical” SNPs that conform to expected patterns of heterozygosity and allelic ratio for nonduplicated loci (after Karunarathne et al 2022 ).…”

Pitfalls and recommendations for large-scale SNP genotyping in a non-model endangered species: the southern damselflies (Coenagrion mercuriale) as a case study

“…This could indicate that during capture, probes may have hybridised with other non-targeted but genetically close portions of the genome. This may indicate possible paralogues or copy number variant in the southern damselfly genome (Verdu et al, 2016;Karunarathne et al, 2023). Consequently, we discarded sequences resulting from these likely parasitic hybridisations and whose first 40 base pairs did not exactly correspond to probe sequences.…”

“…We hypothesised that extreme values in FIS were due to differences in depth of coverage: strong excess in heterozygotes could be correlated with excessively high depths, indicating possible duplication of the target genome region, whereas biases toward excess in homozygotes could be due to too low sequencing depth, making it impossible to detect alternative variants (Song et al, 2016;Lou and Therkildsen, 2022;Karunarathne et al, 2023). However, there was no clear relationship between loci sequencing depth and the levels of FIS (Figure 3), although loci with a high homozygote excess showed a slight tendency to exhibit low coverage.…”