Local selection signals in the genome of blue tits emphasize regulatory and neuronal evolution

Understanding the genomic landscape of adaptation is central to understanding microevolution in wild populations. Genomic targets of selection and the underlying genomic mechanisms of adaptation can be elucidated by genome-wide scans for past selective sweeps or by scans for direct fitness associations. We sequenced and assembled 150 haplotypes of 75 blue tits (Cyanistes caeruleus) of a single Central European population by a linked-read technology. We used these genome data in combination with coalescent simulations (i) to estimate an historical effective population size of similar to 250,000, which recently declined to similar to 10,000, and (ii) to identify genome-wide distributed selective sweeps of beneficial variants probably originating from standing genetic variation (soft sweeps). The genes linked to these soft sweeps, but also those linked to hard sweeps based on new beneficial mutants, showed a significant enrichment for functions associated with gene expression and transcription regulation. This emphasizes the importance of regulatory evolution in the population's adaptive history. Soft sweeps were further enriched for genes related to axon and synapse development, indicating the significance of neuronal connectivity changes in the brain potentially linked to behavioural adaptations. A previous scan of heterozygosity-fitness correlations revealed a consistent negative effect on arrival date at the breeding site for a single microsatellite in the MDGA2 gene. Here, we used the haplotype structure around this microsatellite to explain the effect as a local and direct outbreeding effect of a gene involved in synapse development.

Automated summary

Understanding the genomic landscape of adaptation is crucial for understanding microevolution in wild populations. Through scans and simulations, researchers have found that soft sweeps and hard sweeps are associated with gene expression and synaptic development. This highlights the importance of regulatory evolution in the population's adaptive history.