Thermal adaptation rather than demographic history drives genetic structure inferred by copy number variants in a marine fish

Abstract

Increasing evidence shows that structural variants represent an overlooked aspect of genetic variation with consequential evolutionary roles. Among those, copy number variants (CNVs), including duplicated genomic region and transposable elements (TEs) may contribute to local adaptation and/or reproductive isolation among divergent populations. Those mechanisms suppose that CNVs could be important drivers of population genetic structure, whose study is generally restricted to the use of SNPs. Taking advantage of recent developments allowing CNV analysis from RAD-seq data, we investigated how variation in fitness-related traits, local thermal conditions and demographic history are associated with CNVs, and how subsequent copy number variation drives population genetic structure in a marine fish, the capelin (Mallotus villosus). We collected 1536 DNA samples from 35 sampling sites in the north Atlantic Ocean and identified 6620 CNVs. We found associations between CNVs and the gonadosomatic index, suggesting that duplicated regions could affect female fitness by modulating oocyte production. We also detected 105 CNV candidates associated with water temperature, among which 20% corresponded to genomic regions located within the sequence of protein-coding genes, suggesting local adaptation to cold water by means of gene amplification. We also identified 175 CNVs associated with the divergence of three parapatric glacial lineages, of which 24% were located within protein-coding genes, which might contribute to genetic incompatibilities and ultimately, reproductive isolation. Lastly, our analyses unveiled a hierarchical, complex CNV population structure determined by temperature and local geography, that was very different from that inferred based on SNPs in a previous study. Our findings underscore the complementarity of those two types of markers in population genomics studies.

Environmentally associated chromosomal structural variation influences fine‐scale population structure of Atlantic Salmon (Salmo salar)

“…Chromosomal structural variation is a significant, yet poorly understood source of genetic variation (Wellenreuther et al, 2019) which may underpin complex phenotype and life history variation across a wide range of taxa (Dobigny et al, 2017). In contrast with chromosomal inversions, which have been increasingly associated with adaptive variation (Huang et al, 2019; Jay et al, 2018; Lamichhaney et al, 2016), few well‐documented occurrences of fusion or translocation polymorphisms in wild populations have been reported (see Bidau & Martí, 2002; Cayuela et al, 2020; Dobigny et al, 2017; Wellband et al, 2019). Our study is among the first to report evidence of an adaptive chromosomal translocation influencing spatial structure in the wild.…”

Adaptive and maladaptive genetic diversity in small populations: Insights from the Brook Charr (Salvelinus fontinalis) case study

“…The body of evidence regarding the adaptive role of TEs is growing (Casacuberta & González, 2013). In particular, TEs have been suggested to contribute to adaptation to climate change (Cayuela et al, 2020; Lerat et al., 2019; Rey, Danchin, Mirouze, Loot, & Blanchet, 2016; Shrader & Schmitz, 2019). TEs generate mutations actively by inserting themselves in new genomic locations and passively by acting as targets of ectopic recombination (recombination between homologous sequences that are not at the same position on homologous chromosomes).…”

Genomic signatures of thermal adaptation are associated with clinal shifts of life history in a broadly distributed frog

“…A previous study using similar RAD‐seq‐based CNV analyses showed that putative CNVs often correspond to DNA repeats (Cayuela et al., 2021). Therefore, we investigated the proportion of CNVs which fell into DNA repeats, relative to non‐CNV RAD tags.…”

“…(2020) and Cayuela et al. (2021). The duplicated loci detected by this method can be variant or invariant in copy number among the studied populations.…”

“…(2020) and Cayuela et al. (2021), read counts of putative CNV loci were normalized to account for differences in sequencing effort across all samples. Normalization was performed using the trimmed mean of M‐values method originally described for RNA‐seq count normalization and implemented in the R package edgeR (Robinson & Oshlack, 2010).…”