Dynamic Outlier Slicing Allows Broader Exploration of Adaptive Divergence: A Comparison of Individual Genome and Pool-Seq Data Linked to Humic Adaptation in Perch

Abstract

How genetic variation contributes to adaptation at different environments is a central focus in evolutionary biology. However, most free-living species still lack a comprehensive understanding of the primary molecular mechanisms of adaptation. Here, we characterised the targets of selection associated with drastically different aquatic environments—humic and clear water—in the common freshwater fish, Eurasian perch (Perca fluviatilis). By using whole-genome sequencing (WGS) on a large population dataset (n = 42 populations) and analysing 873,788 SNPs, our primary aim was to uncover novel and confirm known footprints of selection. We compared individual and pooled WGS, and developed a novel approach, termed dynamic outlier slicing, to assess how the choice of outlier-calling stringency influences functional and Gene Ontology (GO) enrichment. By integrating genome-environment association (GEA) analysis with allele frequency-based approaches, we estimated composite selection signals (CSS) and identified 2679 outlier SNPs distributed across 324 genomic regions, involving 468 genes. Dynamic outlier slicing identified robust enrichment signals in five annotation categories (upstream, downstream, synonymous, 5′UTR and 3′UTR) highlighting the crucial role of regulatory elements in adaptive evolution. Furthermore, GO analyses revealed strong enrichment of molecular functions associated with gated channel activity, transmembrane transporter activity and ion channel activity, emphasising the importance of osmoregulation and ion balance maintenance. Our findings demonstrate that despite substantial random drift and divergence, WGS of high number of population pools enabled the identification of strong selection signals associated with adaptation to both humic and clear water environments, providing robust evidence of widespread adaptation. We anticipate that the dynamic outlier slicing method we developed will enable a more thorough exploration of adaptive divergence across a diverse range of species.