bioRxivEvolutionary Biology
Evidence for admixture and rapid evolution during glacial climate change in an alpine specialist
Y.-M. Weng, D. H. Kavanaugh, P. L. Ralph, G. Patterson, S. D. Schoville
Abstract
The pace of current climate change is expected to be problematic for alpine flora and fauna, as their adaptive capacity may be limited by small population size. Yet despite substantial genetic drift following post-glacial recolonization of alpine habitats, alpine species are notable for their success in surviving highly heterogeneous environments. Population genomic analyses demonstrating how alpine species have adapted to novel environments with limited genetic diversity remain rare, yet are important in understanding the potential for species to respond to contemporary climate change. In this study, we explored the evolutionary history of alpine ground beetles in the Nebria ingens complex, including the demographic and adaptive changes that followed the last glacier retreat. Using whole genome data from hundreds of beetles, to test alternative models of evolutionary divergence in the species complex, we found evidence that the Nebria ingens complex has been formed by past admixture of lineages responding to glacial cycles. Recolonization of alpine sites involved a distributional range shift to higher elevation, which was accompanied by a reduction in suitable habitat and the emergence of complex spatial genetic structure. We also used genome-wide association and genotype-environment association methods to look for genetic pathways involved in adaptation to heterogeneous new environments during this range shift. The identified genes were enriched for functions broadly associated with abiotic stress responses, with strong evidence for adaptation to hypoxia-related pathways. The results demonstrate that despite rapid environmental changes, alpine beetles in the N. ingens complex have shown rapid physiological evolution.
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- approach: statistical model
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