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Taliadoros D, Soares AER, Dias G, Bunikis I, Pippel M, Olsson A, Mosbech MB, Heintz J, Lager N, Strand AS, Pettersson M, Pettersson OV, Lantz H, Cederberg B, Lindblad-Toh K, Webster MT
Mol. Ecol. - (-) e70204 [2025-12-12; online 2025-12-12]
Population genomics can reveal trends and drivers of biodiversity loss, but it is still unclear how best to use measures of genome variation to understand population vulnerability in insects. Here we study genome variation in three species of Anthophora bees that show contrasting population trends in northern Europe. Two species, Anthophora plagiata and Anthophora retusa , have experienced declines and recoveries of different magnitudes in the last 50 years, whereas a third species, Anthophora quadrimaculata , has relative population stability. We generate highly contiguous genome assemblies and use them to study genome variation in 136 samples of these species collected throughout Sweden. We find exceedingly low genetic variation in A. plagiata , which has experienced a severe recent bottleneck, but high genetic variation in A. retusa , despite a similar recent population trajectory. Fragmented populations of the threatened species A. plagiata appear isolated from each other, but in A. retusa, there is a lack of deep population structure among geographically separated subpopulations. We infer population size in the distant past using MSMC2 and recent past using GONE. These methods are remarkably concordant and indicate ancient fluctuations in population size dating back to the Pleistocene, with moderate expansions in the past century in all three species. These results are comparable to some other studies of endangered insects, which have experienced population declines that predate the modern era. We detect long blocks of identity-by-state in A. plagiata , indicative of severe recent inbreeding. Translocations between isolated populations of this species could have a positive effect on their resilience.
NGI Stockholm (Genomics Applications) [Service]
NGI Stockholm (Genomics Production) [Service]
National Genomics Infrastructure [Service]
PubMed 41387163
DOI 10.1111/mec.70204
Crossref 10.1111/mec.70204