Vasemägi, Anti
- Department of Aquatic Resources (SLU Aqua), Swedish University of Agricultural Sciences
- Estonian University of Life Sciences
Research article2025Peer reviewedOpen access
Ozerov, M. Yu.; Noreikiene, K.; Taube, K.; Gross, R.; Vasemaegi, A.
Although population genomics approaches have been successful in identifying regions of the genome shaped by natural selection, progress in dissecting the molecular mechanisms of adaptive variants and traits has been slow. By integrating multi-tissue (gill, spleen, olfactory rosette, whole eye, and liver) transcriptomes from 16 wild Eurasian perch (Perca fluviatilis) populations and previously identified footprints of selection, we prioritise tissues, candidate genes, and putative SNP-gene expression associations potentially involved in the humic adaptation of this keystone freshwater fish. Over 5000 differentially expressed genes (DEGs) were discovered across the five tissues. A significant excess of outlier SNPs among DEGs found in the gill and spleen tissues indicated their potential involvement in humic adaptation. Next, we identified 2640 cis-eQTLs, and observed significant enrichment of outliers among expression-associated SNPs (eSNPs) in spleen and olfactory rosette tissues, as well as in all tissues combined. Several eQTLs were found in the regions showing the strongest signals of selection, which also harboured DEGs (chr. 5: PLAGL2, chr. 7: PPP1R8, TCHH). Thus, our integrative analyses enabled us to pinpoint specific organs that potentially play a key role in adaptation, prioritise candidate genes under divergent selection based on their expression patterns, and identify links between SNPs and transcript abundance variation. We expect that by combining evolutionary and functional genomics perspectives this work provides a practical framework for understanding the genetic basis of phenotypic diversification and adaptation across a wide range of species.
DEGs; eQTLs; fish; genomics; omics; perch; transcriptome
Molecular Ecology
2025
Publisher: WILEY
Genetics and Genomics
Ecology
https://res.slu.se/id/publ/140948