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The 1986 Chernobyl nuclear disaster initiated a series of catastrophic events resulting in long-term and widespread environmental contamination. We characterize the genetic structure of 302 dogs representing three free-roaming dog populations living within the power plant itself, as well as those 15 to 45 kilometers from the disaster site. Genome-wide profiles from Chernobyl, purebred and free-breeding dogs, worldwide reveal that the individuals from the power plant and Chernobyl City are genetically distinct, with the former displaying increased intrapopulation genetic similarity and differentiation. Analysis of shared ancestral genome segments highlights differences in the extent and timing of western breed introgression. Kinship analysis reveals 15 families, with the largest spanning all collection sites within the radioactive exclusion zone, reflecting migration of dogs between the power plant and Chernobyl City. This study presents the first characterization of a domestic species in Chernobyl, establishing their importance for genetic studies into the effects of exposure to long-term, low-dose ionizing radiation.

AimThe Saimaa ringed seal (Pusa hispida saimensis) is endemic to Lake Saimaa in Finland. The subspecies is thought to have originated when parts of the ringed seal population of the Baltic region were trapped in lakes emerging due to post-glacial bedrock rebound around 9,000 years ago. During the 20th century, the population experienced a drastic human-induced bottleneck. Today encompassing a little over 400 seals with extremely low genetic diversity, it is classified as endangered. Our main aim was to evaluate the role of the 20th century bottleneck in the erosion of genetic diversity in the Saimaa seal population. We also evaluated connections with other ringed seals from the Baltic Sea, Lake Ladoga, North America, Svalbard and the White Sea.LocationLake Saimaa, Finland, together with the Baltic Sea and the Arctic Ocean.MethodsWe sequenced sections of the mitochondrial control region from 60 up to 125 years old museum specimens of the Saimaa ringed seal. The generated dataset was combined with publicly available sequences. We studied how genetic variation has changed through time in this subspecies, and how it is phylogenetically related to other ringed seal populations.ResultsWe observed temporal fluctuations in haplotype frequencies and loss of haplotypes accompanied by a recent reduction in female effective population size. In apparent contrast with the traditionally held view of the Baltic origin of the population, the Saimaa ringed seal mtDNA variation shows also affinities to North American ringed seals.Main conclusionsOur results suggest that the Saimaa ringed seal has experienced recent genetic drift associated with small population size. The results further suggest that extant Baltic ringed seals do not represent well the ancestral population of the Saimaa ringed seal, which calls for re-evaluation of the deep history of this subspecies.

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1–8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located. © 2022, The Author(s). 8028-00005B; IP DKRVO 2019-2023, MK000094862; 220457/Z/20/Z, ERC-2013-StG-337574-UNDEAD, ERC-2019-StG-853272-PALAEOFARM; 075-15-2021-1069; European Molecular Biology Organization, EMBO: 217223/Z/19/Z; Vallee Foundation; Velux Fonden; Wellcome Trust, WT; Francis Crick Institute, FCI: FC001595; Horizon 2020 Framework Programme, H2020: 796877; Medical Research Council, MRC; Natural Environment Research Council, NERC: 210119/Z/18/Z, NE/K003259/1, NE/K005243/1, NE/S00078X/1, NE/S007067/1; Cancer Research UK, CRUK; European Research Council, ERC: 852558; Grantová Agentura České Republiky, GA ČR: 15-06446S; Svenska Forskningsrådet Formas: 2018-01640; Knut och Alice Wallenbergs Stiftelse; Vetenskapsrådet, VR: 681396, BELSPO B2/191/P2/ICHIE; Russian Science Foundation, RSF: 16-18-10265-RNF, 20-17-00033, 21-18-00457-RNF, 310763; Science for Life Laboratory, SciLifeLab; Narodowa Agencja Wymiany Akademickiej, NAWA: PPN/PPO/2018/1/00037 This work was supported by grants to P. Skoglund from the European Research Council (grant no. 852558), the Erik Philip Sörensen Foundation and the Science for Life Laboratory, Swedish Biodiversity Program, made available by support from the Knut and Alice Wallenberg Foundation. A.B., L.S., P. Swali and P. Skoglund were supported by Francis Crick Institute core funding (FC001595) from Cancer Research UK, the UK Medical Research Council and the Wellcome Trust. P. Skoglund was also supported by the Vallee Foundation, the European Molecular Biology Organisation and the Wellcome Trust (217223/Z/19/Z). Computations were supported by SNIC-UPPMAX. We also acknowledge support from Science for Life Laboratory, the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure funded by the Swedish Research Council and the Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We thank the Yukon gold mining community and First Nations, including the Tr’ondëk Hwëch’in, for continued support of our palaeontology research in the Yukon Territories, Canada. We thank the Danish National High-Throughput Sequencing Centre and BGI-Europe for assistance in sequencing data generation and the Danish National Supercomputer for Life Sciences–Computerome ( https://computerome.dtu.dk ) for computational resources. We thank National Museum Wales for continued sampling support. M. Germonpré acknowledges support from the Brain.be 2.0 ICHIE project (BELSPO B2/191/P2/ICHIE). M.T.P.G. was supported by the European Research Council (grant no. 681396). M.-H.S.S. was supported by the Velux Foundations through the Qimmeq Project, the Aage og Johanne Louis-Hansens Fond and the Independent Research Fund Denmark (8028-00005B). L.D. acknowledges support from FORMAS (2018-01640). D.W.G.S. received funding for this project from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement no. 796877. M.P. was supported by the Polish National Agency for Academic Exchange–NAWA (grant no. PPN/PPO/2018/1/00037). V.J.S. was supported by the University of Zurich’s University Research Priority Program ‘Evolution in Action: From Genomes to Ecosystems’. This research was done with the participation of ZIN RAS (grant no. 075-15-2021-1069). We are grateful to the museum of the Institute of Plant and Animal Ecology UB RAS (Ekaterinburg, Russia) for provision of samples. R.P.J. and C.O’D. were supported by the Standing Committee for Archaeology of the Royal Irish Academy through the Archaeological Excavation Research Grant Scheme. E.Y.P., P.N. and V.V.P. are supported by the Russian Science Foundation (grant no. 16-18-10265-RNF and 21-18-00457-RNF). Y.V.K. was supported by the Russian Science Foundation (grant no. 20-17-00033). M.H. was supported by the European Research Council (consolidator grant GeneFlow no. 310763). M.L.-G. was supported by the Czech Science Foundation GAČR (grant no. 15-06446S) and institutional financing of the Moravian Museum from the Czech Ministry of Culture (IP DKRVO 2019-2023, MK000094862). L.S. is supported by the Sir Henry Wellcome fellowship (220457/Z/20/Z). We thank Staatliches Museum für Naturkunde Stuttgart for sample access. L.F. and G.L. were supported by European Research Council grants (ERC-2013-StG-337574-UNDEAD and ERC-2019-StG-853272-PALAEOFARM) and Natural Environmental Research Council grants (NE/K005243/1, NE/K003259/1, NE/S007067/1 and NE/S00078X/1). L.F. was also supported by the Wellcome Trust (210119/Z/18/Z). This research was funded in whole, or in part, by the Wellcome Trust (FC001595). For the purpose of open access, the author has applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission.

Adaptive evolution is a process in which variation that confers an evolutionary advantage in a specific environmental context arises and is propagated through a population. When investigating this process, researchers have mainly focused on describing advantageous phenotypes or putative advantageous genotypes. A recent increase in molecular data accessibility and technological advances has allowed researchers to go beyond description and to make inferences about the mechanisms underlying adaptive evolution. In this systematic review, we discuss articles from 2016 to 2022 that investigated or reviewed the molecular mechanisms underlying adaptive evolution in vertebrates in response to environmental variation. Regulatory elements within the genome and regulatory proteins involved in either gene expression or cellular pathways have been shown to play key roles in adaptive evolution in response to most of the discussed environmental factors. Gene losses were suggested to be associated with an adaptive response in some contexts. Future adaptive evolution research could benefit from more investigations focused on noncoding regions of the genome, gene regulation mechanisms, and gene losses potentially yielding advantageous phenotypes. Investigating how novel advantageous genotypes are conserved could also contribute to our knowledge of adaptive evolution.

Hybridization, defined as breeding between two distinct taxonomic units, can have an important effect on the evolutionary patterns in cross-breeding taxa. Although interspecific hybridization has frequently been considered as a maladaptive process, which threatens species genetic integrity and survival via genetic swamping and outbreeding depression, in some cases hybridization can introduce novel adaptive variation and increase fitness. Most studies to date focused on documenting hybridization events and analyzing their causes, while relatively little is known about the consequences of hybridization and its impact on the parental species. To address this knowledge gap, we conducted a systematic review of studies on hybridization in mammals published in 2010–2021, and identified 115 relevant studies. Of 13 categories of hybridization consequences described in these studies, the most common negative consequence (21% of studies) was genetic swamping and the most common positive consequence (8%) was the gain of novel adaptive variation. The total frequency of negative consequences (49%) was higher than positive (13%) and neutral (38%) consequences. These frequencies are biased by the detection possibilities of microsatellite loci, the most common genetic markers used in the papers assessed. As negative outcomes are typically easier to demonstrate than positive ones (e.g., extinction vs hybrid speciation), they may be over-represented in publications. Transition towards genomic studies involving both neutral and adaptive variation will provide a better insight into the real impacts of hybridization.

Social structure plays a crucial role in determining a species’ dispersal patterns and genetic structure. Cetaceans show a diversity of social and mating systems, but their effects on dispersal and genetic structure are not well known, in part because of technical difficulties in obtaining robust observational data. Here, we combine genetic profiling and GIS analysis to identify patterns of kin distribution over time and space, to infer mating structure and dispersal patterns in short-beaked common dolphins (Delphinus delphis). This species is highly social, and exhibits weak spatial genetic structure in the Northeast Atlantic and Mediterranean Sea, thought to result from fluid social structure and low levels of site fidelity. We found that although sampled groups were not composed of closely related individuals, close kin were frequently found in the same geographic location over several years. Our results suggest that common dolphin exhibits some level of site fidelity, which could be explained by foraging for temporally varying prey resource in areas familiar to individuals. Dispersal from natal area likely involves long-distance movements of females, as males are found more frequently than females in the same locations as their close kin. Long-distance dispersal may explain the near panmixia observed in this species. By analysing individuals sampled in the same geographic location over multiple years, we avoid caveats associated with divergence-based methods of inferring sex-biased dispersal. We thus provide a unique perspective on this species’ social structure and dispersal behaviour, and how it relates to the observed low levels of population genetic structure in European waters. Significance statement Movement patterns and social interactions are aspects of wild animal’s behaviour important for understanding their ecology. However, tracking these behaviours directly can be very challenging in wide-ranging species such as whales and dolphins. In this study, we used genetic information to detect how patterns of kin associations change in space and time, to infer aspects of movement and social structure. We identified previously unknown site fidelity, and suggested that dispersal usually involves females, travelling long distances from the natal area. Our data analysis strategy overcomes known limitations of previously used genetic inference methods, and provides a new approach to identify differences in dispersal between the sexes, which contribute to better understanding of the species’ behaviour and ecology. In this case, we suggest that females are more likely to disperse than males, a pattern unusual amongst mammals. Electronic supplementary material The online version of this article (doi:10.1007/s00265-017-2351-z) contains supplementary material, which is available to authorized users.

Genetic variability, kin structure and demography of a population are mutually dependent. Population genetic theory predicts that under demographically stable conditions, neutral genetic variability reaches equilibrium between gene flow and drift. However, density fluctuations and non-random mating, resulting e.g. from kin clustering, may lead to changes in genetic composition over time. Theoretical models also predict that changes in kin structure may affect aggression level and recruitment, leading to density fluctuations. These predictions have been rarely tested in natural populations. The aim of this study was to analyse changes in genetic variability and kin structure in a local population of the root vole (Microtus oeconomus) that underwent a fourfold change in mean density over a 6-year period. Intensive live-trapping resulted in sampling 88% of individuals present in the study area, as estimated from mark-recapture data. Based on 642 individual genotypes at 20 microsatellite loci, we compared genetic variability and kin structure of this population between consecutive years. We found that immigration was negatively correlated with density, while the number of kin groups was positively correlated with density. This is consistent with theoretical predictions that changes in kin structure play an important role in population fluctuations. Despite the changes in density and kin structure, there was no genetic differentiation between years. Population-level genetic diversity measures did not significantly vary in time and remained relatively high (H(E) range: 0.72-0.78). These results show that a population that undergoes significant demographic and social changes may maintain high genetic variability and stable genetic composition.