Extensive population decline in the Tasmanian devil predates European settlement and devil facial tumour disease

The Tasmanian devil (Sarcophilus harrisii) was widespread in Australia during the Late Pleistocene but is now endemic to the island of Tasmania. Low genetic diversity combined with the spread of devil facial tumour disease have raised concerns for the species’ long-term survival. Here, we investigate the origin of low genetic diversity by inferring the species'' demographic history using temporal sampling with summary statistics, full-likelihood and approximate Bayesian computation methods. Our results show extensive population declines across Tasmania correlating with environmental changes around the last glacial maximum and following unstable climate related to increased ‘El Niño–Southern Oscillation’ activity.     

A Novel Approach for Choosing Summary Statistics in Approximate Bayesian Computation

The choice of summary statistics is a crucial step in approximate Bayesian computation (ABC). Since statistics are often not sufficient, this choice involves a trade-off between loss of information and reduction of dimensionality. The latter may increase the efficiency of ABC. Here, we propose an approach for choosing summary statistics based on boosting, a technique from the machine-learning literature. We consider different types of boosting and compare them to partial least-squares regression as an alternative. To mitigate the lack of sufficiency, we also propose an approach for choosing summary statistics locally, in the putative neighborhood of the true parameter value. We study a demographic model motivated by the reintroduction of Alpine ibex (Capra ibex) into the Swiss Alps. The parameters of interest are the mean and standard deviation across microsatellites of the scaled ancestral mutation rate (θ_anc = 4N_eu) and the proportion of males obtaining access to matings per breeding season (ω). By simulation, we assess the properties of the posterior distribution obtained with the various methods. According to our criteria, ABC with summary statistics chosen locally via boosting with the L₂-loss performs best. Applying that method to the ibex data, we estimate θ^anc≈1.288 and find that most of the variation across loci of the ancestral mutation rate u is between 7.7 × 10⁻⁴ and 3.5 × 10⁻³ per locus per generation. The proportion of males with access to matings is estimated as ω^≈0.21, which is in good agreement with recent independent estimates.     

A coalescent model of background selection with recombination,demography and variation in selection coefficients

There is increasing evidence that background selection, the effects of the elimination of recurring deleterious mutations by natural selection on variability at linked sites, may be a major factor shaping genome-wide patterns of genetic diversity. To accurately quantify the importance of background selection, it is vital to have computationally efficient models that include essential biological features. To this end, a structured coalescent procedure is used to construct a model of background selection that takes into account the effects of recombination, recent changes in population size and variation in selection coefficients against deleterious mutations across sites. Furthermore, this model allows a flexible organization of selected and neutral sites in the region concerned, and has the ability to generate sequence variability at both selected and neutral sites, allowing the correlation between these two types of sites to be studied. The accuracy of the model is verified by checking against the results of forward simulations. These simulations also reveal several patterns of diversity that are in qualitative agreement with observations reported in recent studies of DNA sequence polymorphisms. These results suggest that the model should be useful for data analysis.     

Fitness effects of derived deleterious mutations in four closely related wild tomato species with spatial structure

A key issue in evolutionary biology is an improved understanding of the genetic mechanisms by which species adapt to various environments. Using DNA sequence data, it is possible to quantify the number of adaptive and deleterious mutations, and the distribution of fitness effects of new mutations (its mean and variance) by simultaneously taking into account the demography of a given species. We investigated how selection functions at eight housekeeping genes of four closely related, outcrossing species of wild tomatoes that are native to diverse environments in western South America (Solanum arcanum, S. chilense, S. habrochaites and S. peruvianum). We found little evidence for adaptive mutations but pervasive evidence for strong purifying selection in coding regions of the four species. In contrast, the strength of purifying selection seems to vary among the four species in non-coding (NC) regions (introns). Using F(ST)-based measures of fixation in subdivided populations, we suggest that weak purifying selection has affected the NC regions of S. habrochaites, S. chilense and S. peruvianum. In contrast, NC regions in S. arcanum show a distribution of fitness effects with mutations being either nearly neutral or very strongly deleterious. These results suggest that closely related species with similar genetic backgrounds but experiencing contrasting environments differ in the variance of deleterious fitness effects.     

“Colonization routes and demographic history of Chirostoma humboldtianum in the central Mexican plateau”

In the present study we evaluate the population structure and potential colonization routes of the silverside Chirostoma humboldtianum through approximate Bayesian computations. Six microsatellite loci were amplified in a total of 288 individuals from six different locations covering the complete geographic distribution of the species. Additionally, two mitochondrial DNA markers, a D loop control region and cytochrome b were amplified in a subset of 107 individuals. The results found with microsatellites allow recovering well-structured populations that have experienced a drastic reduction in the effective population size. On the other hand, mtDNA sequences showed a moderate phylogeographic structure with shared haplotypes between geographic localities and signalsof a slight increase in the effective population size. Finally, the approximate Bayesian computation analysis performed with both datasets suggested a west-to-east colonization route for the species in Central Mexico.     

Colonization history of the Swiss Rhine basin by the bullhead (Cottus gobio): inference under a Bayesian spatially explicit framework

The present distribution of freshwater fish in the Alpine region has been strongly affected by colonization events occurring after the last glacial maximum (LGM), some 20 000 years ago. We use here a spatially explicit simulation framework to model and better understand their colonization dynamics in the Swiss Rhine basin. This approach is applied to the European bullhead ( Cottus gobio ), which is an ideal model organism to study fish past demographic processes since it has not been managed by humans. The molecular diversity of eight sampled populations is simulated and compared to observed data at six microsatellite loci under an approximate Bayesian computation framework to estimate the parameters of the colonization process. Our demographic estimates fit well with current knowledge about the biology of this species, but they suggest that the Swiss Rhine basin was colonized very recently, after the Younger Dryas some 6600 years ago. We discuss the implication of this result, as well as the strengths and limits of the spatially explicit approach coupled to the approximate Bayesian computation framework.     

A range-wide genetic bottleneck overwhelms contemporary landscape factors and local abundance in shaping genetic patterns of an alpine butterfly (Lepidoptera: Pieridae: Colias behrii)

Spatial and environmental heterogeneity are major factors in structuring species distributions in alpine landscapes. These landscapes have also been affected by glacial advances and retreats, causing alpine taxa to undergo range shifts and demographic changes. These nonequilibrium population dynamics have the potential to obscure the effects of environmental factors on the distribution of genetic variation. Here, we investigate how demographic change and environmental factors influence genetic variation in the alpine butterfly Colias behrii. Data from 14 microsatellite loci provide evidence of bottlenecks in all population samples. We test several alternative models of demography using approximate Bayesian computation (ABC), with the results favouring a model in which a recent bottleneck precedes rapid population growth. Applying independent calibrations to microsatellite loci and a nuclear gene, we estimate that this bottleneck affected both northern and southern populations 531–281 years ago, coinciding with a period of global cooling. Using regression approaches, we attempt to separate the effects of population structure, geographical distance and landscape on patterns of population genetic differentiation. Only 40% of the variation in F_ST is explained by these models, with geographical distance and least‐cost distance among meadow patches selected as the best predictors. Various measures of genetic diversity within populations are also decoupled from estimates of local abundance and habitat patch characteristics. Our results demonstrate that demographic change can have a disproportionate influence on genetic diversity in alpine species, contrasting with other studies that suggest landscape features control contemporary demographic processes in high‐elevation environments.