Phylogeography and phenotypic wing shape variation in a damselfly across populations in Europe.
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Yildirim Y, Kristensson D, Outomuro D, Mikolajewski D, Rödin Mörch P, Sniegula S, Johansson F
BMC Ecol Evol 24 (1) 19 [2024-02-03; online 2024-02-03]
Describing geographical variation in morphology of organisms in combination with data on genetic differentiation and biogeography can provide important information on how natural selection shapes such variation. Here we study genetic structure using ddRAD seq and wing shape variation using geometric morphometrics in 14 populations of the damselfly Lestes sponsa along its latitudinal range in Europe. The genetic analysis showed a significant, yet relatively weak population structure with high genetic heterozygosity and low inbreeding coefficients, indicating that neutral processes contributed very little to the observed wing shape differences. The genetic analysis also showed that some regions of the genome (about 10%) are putatively shaped by selection. The phylogenetic analysis showed that the Spanish and French populations were the ancestral ones with northern Swedish and Finnish populations being the most derived ones. We found that wing shape differed significantly among populations and showed a significant quadratic (but weak) relationship with latitude. This latitudinal relationship was largely attributed to allometric effects of wing size, but non-allometric variation also explained a portion of this relationship. However, wing shape showed no phylogenetic signal suggesting that lineage-specific variation did not contribute to the variation along the latitudinal gradient. In contrast, wing size, which is correlated with body size in L. sponsa, had a strong negative correlation with latitude. Our results suggest a relatively weak population structure among the sampled populations across Europe, but a clear differentiation between south and north populations. The observed geographic phenotypic variation in wing shape may have been affected by different local selection pressures or environmental effects.
NGI Uppsala (SNP&SEQ Technology Platform) [Service]
National Genomics Infrastructure [Service]
PubMed 38308224
DOI 10.1186/s12862-024-02207-4
Crossref 10.1186/s12862-024-02207-4
pmc: PMC10838002
pii: 10.1186/s12862-024-02207-4