Genomic signatures of selection are enriched in differentially expressed genes in sticklebacks adapting to contrasting environments
Clicks: 4
ID: 327226
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
0.9
/100
4 views
3 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #82 of 84 articles by views in genome biology and evolution
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract Whole genome scans have identified numerous adaptive alleles in many species; however, linking these alleles to specific phenotypes remains a major challenge. A promising alternative to direct genotype–phenotype mapping, particularly given the complexities introduced by epistasis, pleiotropy, and environmental variability, is to assess whether differentially expressed genes are enriched in regions of genetic divergence between populations adapted to contrasting environments. Here, we study gene expression patterns in threespine stickleback populations adapting to contrasting environments (marine vs freshwater) and investigate how signatures of selection interact with patterns of gene expression. We performed transcriptomic experiments of the brain and gill tissues of wild-caught sticklebacks sampled from one marine and two freshwater environments using TagSeq. We found that differentially expressed genes in the freshwater environments are enriched for single nucleotide polymorphisms (SNPs) previously identified to be involved in rapid adaptation and F ST outliers. A majority of these SNPs were located in cis -regulatory regions with predicted low to moderate effects on protein function and structure, although we found a high-impact SNP in the gene col8a1b . Genes such as pvalb4 and acsl4a , involved in calcium regulation in the gill and fatty acid metabolism in the brain, respectively, were enriched with SNPs showing signatures of selection. By linking signatures of selection to tissue-specific gene expression patterns, our study bridges the gap between genomic divergence and the molecular mechanisms underlying physiological adaptation to new environments. Significance Statement Understanding how genetic variation translates into adaptive traits remains a central challenge in evolutionary biology. While whole-genome scans routinely identify candidate adaptive alleles, connecting these variants to functional phenotypes is complicated by epistasis, pleiotropy, and environmental effects. Here, we integrate signatures of selection with tissue-specific gene expression in threespine stickleback adapting to contrasting environments (marine and freshwater). We demonstrate that differentially expressed genes in freshwater populations are enriched for previously identified adaptive SNPs and F ST outliers, many of which are located in cis -regulatory regions with predicted low to moderate functional effects. Notably, we identify a high-impact variant leading to a premature stop codon in col8a1b and highlight genes such as pvalb4 and acsl4a that link selection to key physiological processes, including ion regulation in gills and fatty acid metabolism in the brain. By connecting genomic divergence to regulatory and tissue-specific expression changes, this work provides a mechanistic framework for understanding how natural selection shapes complex physiological adaptation.
| Reference Key |
openalex_W7131091932
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Alexander Kwakye, Natalie Dzikowski, Matthew A. Wund, Krishna R. Veeramah |
| Journal | genome biology and evolution |
| Year | 2026 |
| DOI |
10.1093/gbe/evag222
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.