Genomic processes underlying rapid adaptation of a natural Chironomus riparius population to unintendedly applied experimental selection pressures.

Evolve and Resquence (E&R) studies are a useful tool to study genomic processes during rapid adaptation, e.g., in the framework of adaptive responses to global climate change. We applied different thermal regimes to a natural Chironomus riparius (Diptera) population in an E&R framework to infer its evolutionary potential for rapid thermal adaptation. We exposed two replicates to three temperatures each (14°C, 20°C and 26°C) for more than two years, the experiment thus lasting 22, 44 or 65 generations, respectively. The two higher temperatures presented a priori moderate, respectively strong selection pressures. Life-cycle fitness tests revealed no appreciable adaptation to thermal regimes but a common adaptation of all six replicates probably due to the rearing conditions, presumably increased larval density and water quality. Genomic analyses showed a strong, genome-wide selective response in all replicates (mean s of selected SNPs = 0.305). This genomic response was significantly similar at all genomic levels among all replicates (SNPs, 10 kb windows, genes, exons, regions of elevated allele frequency change [REA]). The intersections among the replicates exposed to the same temperature were either insignificant or underrepresented. This confirmed a selective response to identical selection pressure(s), however, not to thermal regime. Genes closest to the SNP with the highest selection coefficient per REA were enriched for GO terms related to ion transport, regulation of transcription and signal transduction, which supported the presumed acting selection pressures. Our study showed the evolutionary potential for rapid adaptation by genome-wide and probably polygenic selection on standing genetic variation in C. riparius. However, because of the impossibility to accurately predict the acting selective regime in evolutionary experiments, we discuss the sobering perspectives for inferring the evolutionary potential of natural populations with this approach.