bioRxivGenomicsPreprint
Testing for parallel genomic and epigenomic footprints of adaptation to urban life in a passerine bird
Aude E. CaizerguesiD, Jérémy Le LuyeriD, Arnaud GrégoireiD, Marta SzulkiniD, Juan Carlos SeñariD, Anne CharmantieriD, Charles PerrieriD
Abstract
Identifying the molecular mechanisms involved in rapid adaptation to novel environments and determining their predictability are central questions in Evolutionary Biology and pressing issues due to rapid global changes. Complementary to genetic responses to selection, faster epigenetic variations such as modifications of DNA methylation may play a substantial role in rapid adaptation. In the context of rampant urbanization, joint examinations of genomic and epigenomic mechanisms are still lacking. Here, we investigated genomic (SNP) and epigenomic (CpG methylation) responses to urban life in a passerine bird, the Great tit (Parus major). To test whether urban evolution is predictable (i.e parallel) or involves mostly non-parallel molecular processes among cities, we analysed three distinct pairs of city and forest Great tit populations across Europe. Results reveal a polygenic response to urban life, with both many genes putatively under weak divergent selection and multiple differentially methylated regions (DMRs) between forest and city great tits. DMRs mainly overlapped transcription start sites and promotor regions, suggesting their importance in the modulation gene expression. Both genomic and epigenomic outliers were found in genomic regions enriched for genes with biological functions related to nervous system, immunity, behaviour, hormonal and stress responses. Interestingly, comparisons across the three pairs of city-forest populations suggested little parallelism in both genetic and epigenetic responses. Our results confirm, at both the genetic and epigenetic levels, hypotheses of polygenic and largely non-parallel mechanisms of rapid adaptation in new environments such as urbanized areas.
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: differential expression
- approach: statistical model
- Citations
- 6
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