A SNP chip to detect introgression in wildcats allows accurate genotyping of single hairs

Genotyping non-invasively collected samples is challenging. Nevertheless, genetic monitoring of elusive species like the European wildcat (Felis silvestris silvestris) mainly relies on such samples. Wildcats are likely threatened through introgression with domestic cats (F. silvestris catus). To determine introgression based on single cat hairs, we developed a 96.96 Fluidigm single nucleotide polymorphism (SNP) genotyping array chip. To estimate the accuracy of this method, we compared genotypes of 17 cats called with both Sanger sequencing and Fluidigm. When Sanger sequencing genotypes were considered as a reference, the genotyping error rate with Fluidigm was 0.9 %. We subsequently compared 16 hair samples to tissue samples of the same individual. When the tissue samples were used as a reference, the genotyping error rate in hair samples was 1.6 %. This low error rate allowed reliable recognition of individuals and correct assessment of introgression levels. Thus, the genotyping method presented in this paper is suitable for non-invasively collected samples. It will help conservationists to monitor the introgression rate in wildcat populations based on non-invasive hair sampling and subsequently to conduct effective conservation measures

A SNP chip to detect introgression in wildcats allows accurate genotyping of single hairs

Genotyping non-invasively collected samples is challenging. Nevertheless, genetic monitoring of elusive species like the European wildcat (Felis silvestris silvestris) mainly relies on such samples. Wildcats are likely threatened through introgression with domestic cats (F. silvestris catus). To determine introgression based on single cat hairs, we developed a 96.96 Fluidigm single nucleotide polymorphism (SNP) genotyping array chip. To estimate the accuracy of this method, we compared genotypes of 17 cats called with both Sanger sequencing and Fluidigm. When Sanger sequencing genotypes were considered as a reference, the genotyping error rate with Fluidigm was 0.9%. We subsequently compared 16 hair samples to tissue samples of the same individual. When the tissue samples were used as a reference, the genotyping error rate in hair samples was 1.6%. This low error rate allowed reliable recognition of individuals and correct assessment of introgression levels. Thus, the genotyping method presented in this paper is suitable for non-invasively collected samples. It will help conservationists to monitor the introgression rate in wildcat populations based on non-invasive hair sampling and subsequently to conduct effective conservation measures

Urban colonization through multiple genetic lenses: The city‐fox phenomenon revisited

Urbanization is driving environmental change on a global scale, creating novel environments for wildlife to colonize. Through a combination of stochastic and selective processes, urbanization is also driving evolutionary change. For instance, difficulty in traversing human‐modified landscapes may isolate newly established populations from rural sources, while novel selective pressures, such as altered disease risk, toxicant exposure, and light pollution, may further diverge populations through local adaptation. Assessing the evolutionary consequences of urban colonization and the processes underlying them is a principle aim of urban evolutionary ecology. In the present study, we revisited the genetic effects of urbanization on red foxes (Vulpes vulpes) that colonized Zurich, Switzerland. Through use of genome‐wide single nucleotide polymorphisms and microsatellite markers linked to the major histocompatibility complex (MHC), we expanded upon a previous neutral microsatellite study to assess population structure, characterize patterns of genetic diversity, and detect outliers associated with urbanization. Our results indicated the presence of one large evolutionary cluster, with substructure evident between geographic sampling areas. In urban foxes, we observed patterns of neutral and functional diversity consistent with founder events and reported increased differentiation between populations separated by natural and anthropogenic barriers. We additionally reported evidence of selection acting on MHC‐linked markers and identified outlier loci with putative gene functions related to energy metabolism, behavior, and immunity. We concluded that demographic processes primarily drove patterns of diversity, with outlier tests providing preliminary evidence of possible urban adaptation. This study contributes to our overall understanding of urban colonization ecology and emphasizes the value of combining datasets when examining evolutionary change in an increasingly urban world

Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals

Funding: Hoge Veluwe great tits: the NIOO-KNAW, ERC, and numerous funding agencies; Wytham great tits: Biotechnology and Biological Sciences Research Council, ERC, and the UK Natural Environment Research Council (NERC).The rate of adaptive evolution, the contribution of selection to genetic changes that increase mean fitness, is determined by the additive genetic variance in individual relative fitness. To date, there are few robust estimates of this parameter for natural populations, and it is therefore unclear whether adaptive evolution can play a meaningful role in short-term population dynamics. We developed and applied quantitative genetic methods to long-term datasets from 19 wild bird and mammal populations and found that, while estimates vary between populations, additive genetic variance in relative fitness is often substantial and, on average, twice that of previous estimates. We show that these rates of contemporary adaptive evolution can affect population dynamics and hence that natural selection has the potential to partly mitigate effects of current environmental change.PostprintPeer reviewe

Limited mass‐independent individual variation in resting metabolic rate in a wild population of snow voles (Chionomys nivalis)

Resting metabolic rate (RMR) is a potentially important axis of physiological adaptation to the thermal environment. However, our understanding of the causes and consequences of individual variation in RMR in the wild is hampered by a lack of data, as well as analytical challenges. RMR measurements in the wild are generally characterized by large measurement errors and a strong dependency on mass. The latter is problematic when assessing the ability of RMR to evolve independently of mass. Mixed models provide a powerful and flexible tool to tackle these challenges, but they have rarely been used to estimate repeatability of mass‐independent RMR from field data. We used respirometry to obtain repeated measurements of RMR in a long‐term study population of snow voles (Chionomys nivalis) inhabiting an environment subject to large circadian and seasonal fluctuations in temperature. Using both uni‐ and bivariate mixed models, we quantify individual repeatability in RMR and decompose repeatability into mass‐dependent and mass‐independent components, while accounting for measurement error. RMR varies among individuals, that is, is repeatable (R = .46) and strongly co‐varies with BM. Indeed, much of the repeatability of RMR is attributable to individual variation in BM, and the repeatability of mass‐independent RMR is reduced by 41% to R = .27. These empirical results suggest that the evolutionary potential of RMR independent of mass may be severely constrained. This study illustrates how to leverage bivariate mixed models to model field data for metabolic traits, correct for measurement error and decompose the relative importance of mass‐dependent and mass‐independent physiological variation

Limited mass-independent individual variation in resting metabolic rate in a wild population of snow voles (Chionomys nivalis)

Resting metabolic rate (RMR) is a potentially important axis of physiological adaptation to the thermal environment. However, our understanding of the causes and consequences of individual variation in RMR in the wild is hampered by a lack of data, as well as analytical challenges. RMR measurements in the wild are generally characterized by large measurement errors and a strong dependency on mass. The latter is problematic when assessing the ability of RMR to evolve independently of mass. Mixed models provide a powerful and flexible tool to tackle these challenges, but they have rarely been used to estimate repeatability of mass-independent RMR from field data. We used respirometry to obtain repeated measurements of RMR in a long-term study population of snow voles (Chionomys nivalis) inhabiting an environment subject to large circadian and seasonal fluctuations in temperature. Using both uni- and bivariate mixed models, we quantify individual repeatability in RMR and decompose repeatability into mass-dependent and mass-independent components, while accounting for measurement error. RMR varies among individuals, i.e. is repeatable (R=0.46), and strongly co-varies with BM. Indeed, much of the repeatability of RMR is attributable to individual variation in BM, and the repeatability of mass-independent RMR is reduced by 41% to R=0.27. These empirical results suggest that the evolutionary potential of RMR independent of mass may be severely constrained. This study illustrates how to leverage bivariate mixed models to model field data for metabolic traits, correct for measurement error, and decompose the relative importance of mass-dependent and mass-independent physiological variation

A robust sequencing assay of a thousand amplicons for the high‐throughput population monitoring of Alpine ibex immunogenetics

Polymorphism for immune functions can explain significant variation in health and reproductive success within species. Drastic loss in genetic diversity at such loci constitutes an extinction risk and should be monitored in species of conservation concern. However, effective implementations of genome-wide immune polymorphism sets into high-throughput genotyping assays are scarce. Here, we report the design and validation of a microfluidics-based amplicon sequencing assay to comprehensively capture genetic variation in Alpine ibex (Capra ibex). This species represents one of the most successful large mammal restorations recovering from a severely depressed census size and a massive loss in diversity at the major histocompatibility complex (MHC). We analysed 65 whole-genome sequencing sets of the Alpine ibex and related species to select the most representative markers and to prevent primer binding failures. In total, we designed ~1,000 amplicons densely covering the MHC, further immunity-related genes as well as randomly selected genome-wide markers for the assessment of neutral population structure. Our analysis of 158 individuals shows that the genome-wide markers perform equally well at resolving population structure as RAD-sequencing or low-coverage genome sequencing data sets. Immunity-related loci show unexpectedly high degrees of genetic differentiation within the species. Such information can now be used to define highly targeted individual translocations. Our design strategy can be realistically implemented into genetic surveys of a large range of species. In conclusion, leveraging whole-genome sequencing data sets to design targeted amplicon assays allows the simultaneous monitoring of multiple genetic risk factors and can be translated into species conservation recommendations

Consequences of natal philopatry for reproductive success and mate choice in an Alpine rodent

Quantifying the interaction between dispersal, kinship, and genetic structure can provide insights into the factors that shape kin-structured mammal societies. Here, we first employ a combination of 8 years of capture¿mark¿recapture and molecular data to characterize the spatial and genetic relationships among female snow voles ( Chionomys nivalis ) in a population located in the Swiss Alps. Subsequently, we examine the individual-level consequences of kin structure in terms of fitness and mating patterns. Behavioral data, relatedness estimates, and spatial autocorrelation analyses indicate that females show strong philopatry, with spatially clustered females being characterized by high levels of genetic relatedness, leading to significant small-scale (<30 m) spatial genetic structure (SGS). In line with selection favoring female philopatry, dispersing females had a lower fitness compared with philopatric individuals. However, we found a negative association between female reproductive success and the number of neighboring females. This suggests that female kin clustering does not constitute an adaptive strategy in this species, but rather that site tenacity is a by-product of the costs of dispersal. Although dispersal is frequently invoked as a means to avoid inbreeding, our results provide no evidence for premating inbreeding avoidance, which is in line with previous studies on mammals. Instead, in the majority of years, we observed that pairs were more-closely related than expected by chance. However, we found that both males and females with related partners had reduced reproductive success, suggesting the existence of inbreeding depression and/or postmating inbreeding avoidance mechanisms. On the whole, our results show how quantification of SGS within populations can provide insights into individual dispersal behavior and its fitness consequences, and into the ways in which social and genetic structure interacts to shape the evolution of free-living populations.This study was supported by grants from the “Basler Stiftung für Biologische Forschung,” the “Claraz Stiftung,” the University of Zurich, and the Swiss National Science Foundation (SNF; grant 31003A_141110). V.G.-N. was supported by a Forschungskredit Postdoc of the University of Zurich (FK-14-103)