Evidence map›Paper›PMID 42668140›Full record

ArticleGenome biology and evolution2026

Genomic Signatures of Selection Are Enriched in Differentially Expressed Genes in Sticklebacks Adapting to Contrasting Environments.

Alexander Kwakye, Natalie Dzikowski, Matthew A Wund, Krishna R Veeramah

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Article in Genome biology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Alexander KwakyeDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-2646-3973
Natalie DzikowskiDepartment of Molecular Genetics and Microbiology, Duke University, Durham, NC 27710, USA.ORCID 0009-0000-2747-6445
Matthew A WundDepartment of Biology, The College of New Jersey, Ewing, NJ 08628, USA.ORCID 0000-0001-7103-9947
Krishna R VeeramahDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-6768-4000

Funding

Dynamics of Contemporary Genomic Evolution in Replicate Threespine Stickleback PopulationsR01GM124330 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI VEERAMAH, KRISHNA R · 2017 to 2021
$1.6M
NIGMS NIH HHS R01 GM124330NIGMS NIH HHS R01GM124330
6 · The paper itself

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 (DEGs) 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 signatures of selection associated with gene expression evolution during adaptation. 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 DEGs in the freshwater environments harbor single nucleotide polymorphisms (SNPs) previously identified to be involved in rapid adaptation and FST outliers. A majority of these SNPs were located in cis-regulatory regions of the genes 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 and identifies specific pathways that can be targeted for future functional studies.

Indexed as

Adaptation, PhysiologicalSelection, GeneticSmegmamorphaAnimalsFresh WaterGillsPolymorphism, Single NucleotideTranscriptomeCis-regulationDifferential gene expressionFreshwater adaptationGenotype–phenotype mappingThreespine stickleback (Gasterosteus aculeatus)

Identifiers

PMID42668140
PMCPMC13583502

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.