期刊
MOLECULAR ECOLOGY
卷 27, 期 11, 页码 2576-2593出版社
WILEY
DOI: 10.1111/mec.14709
关键词
environmental association analysis; insects; Ischnura; landscape genomics; local adaptation; range expansion
资金
- FP7 People: Marie-Curie Actions
- Crafoordska Stiftelsen
- Svenska Forskningsradet Formas
- Stiftelsen Oscar och Lili Lamms Minne
- Wenner-Gren Foundation
- Erik Philip-Sorensens
Insect distributions are shifting rapidly in response to climate change and are undergoing rapid evolutionary change. We investigate the molecular signatures underlying local adaptation in the range-expanding damselfly, Ischnura elegans. Using a landscape genomic approach combined with generalized dissimilarity modelling (GDM), we detect selection signatures on loci via allelic frequency change along environmental gradients. We analyse 13,612 single nucleotide polymorphisms (SNPs), derived from restriction site-associated DNA sequencing (RADseq), in 426 individuals from 25 sites spanning the I.elegans distribution in Sweden, including its expanding northern range edge. Environmental association analysis (EAA) and the magnitude of allele frequency change along the range expansion gradient revealed significant signatures of selection in relation to high maximum summer temperature, high mean annual precipitation and low wind speeds at the range edge. SNP annotations with significant signatures of selection revealed gene functions associated with ongoing range expansion, including heat shock proteins (HSP40 and HSP70), ion transport (V-ATPase) and visual processes (long-wavelength-sensitive opsin), which have implications for thermal stress response, salinity tolerance and mate discrimination, respectively. We also identified environmental thresholds where climate-mediated selection is likely to be strong, and indicate that I.elegans is rapidly adapting to the climatic environment during its ongoing range expansion. Our findings empirically validate an integrative approach for detecting spatially explicit signatures of local adaptation along environmental gradients.
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