Leveraging whole genome sequencing data for demographic inference with approximate Bayesian computation

Accounting for historical demographic features, such as the strength and timing of gene flow and divergence times between closely related lineages, is vital for many inferences in evolutionary biology. Approximate Bayesian computation (ABC) is one method commonly used to estimate demographic parameters. However, the DNA sequences used as input for this method, often microsatellites or RADseq loci, usually represent a small fraction of the genome. Whole genome sequencing (WGS) data, on the other hand, have been used less often with ABC, and questions remain about the potential benefit of, and how to best implement, this type of data; we used pseudo‐observed data sets to explore such questions. Specifically, we addressed the potential improvements in parameter estimation accuracy that could be associated with WGS data in multiple contexts; namely, we quantified the effects of (a) more data, (b) haplotype‐based summary statistics, and (c) locus length. Compared with a hypothetical RADseq data set with 2.5 Mbp of data, using a 1 Gbp data set consisting of 100 Kbp sequences led to substantial gains in the accuracy of parameter estimates, which was mostly due to haplotype statistics and increased data. We also quantified the effects of including (a) locus‐specific recombination rates, and (b) background selection information in ABC analyses. Importantly, assuming uniform recombination or ignoring background selection had a negative effect on accuracy in many cases. Software and results from this method validation study should be useful for future demographic history analyses.     

EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS

Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Heterosis in Cepaea

A test has been made of the association of heterozygosity with shell breadth in the polymorphic snail Cepaea nemoralis. The material was collected by C. B. Goodhart from a series of paired sites at which individuals reached different adult breadths. Dominant phenotypes, in which a large fraction was heterozygous, had a greater breadth and lower variance than recessive phenotypes regardless of whether the measurement was of shell ground colour, banding or the double recessive vs. the rest. Most of the difference was contributed by samples from the habitat where animals reached the largest size. The result is consistent with existence of heterotic sections of chromosome that include the colour and banding loci, and may help to explain the persistence of the polymorphism.  © 2007 The Linnean Society of London, Biological Journal of the Linnean Society , 2007, 90 , 49–53.     

Stable isotopic niche predicts fitness of prey in a wolf–deer system

Interindividual variation in niche presents a potentially central object on which natural selection can act. This may have important evolutionary implications because habitat use governs a suite of selective forces encountered by foragers. In a free-living native black-tailed deer, Odocoileus hemionus , population from coastal British Columbia, we used stable isotope analysis to identify individual variation in foraging niche and investigated its relationship to fitness. Using an intragenerational comparison of surviving and nonsurviving O. hemionus over 2 years of predation by wolves, Canis lupus, we detected resource-specific fitness. Individuals with isotopic signatures that suggested they foraged primarily in cedar ( Thuja plicata )-dominated and low-elevation hemlock ( Tsuga heterophylla )-dominated forest stands were more likely to be killed by C. lupus . High-quality forage in T. plicata stands, as indexed by protein content, may be involved in maintaining this foraging phenotype. Moreover, nonsurvivors diverged more than survivors from median isotopic signatures, suggesting selection against foraging specialization. Stable isotope analysis provides a novel opportunity to integrate ecological and selective landscapes in order to identify underlying ecological mechanisms of selection and provide insight into the maintenance of variability.  © 2007 The Linnean Society of London, Biological Journal of the Linnean Society , 2007, 90 , 125–137.     

VARIABLE SELECTION ON EUROSTA'S GALL SIZE,I: THE EXTENT AND NATURE OF VARIATION IN PHENOTYPIC SELECTION

Natural fluctuations in environmental conditions are likely to induce variation in the intensity or direction of natural selection. A long-term study of the insect, Eurosta solidaginins Fitch (Diptera; Tephritidae), which induces stem galls on the perennial herb Solidago altissima (Asteraceae) was performed to explore the patterns of variation in phenotypic selection. The intensity of selection imposed by parasitoids and predators on gallmaking larvae, for gall size, was measured across 16 populations over the course of 4 generations, for a total of 64 population-generations. Directional selection was quantified by i, the selection intensity, and variance selection by j‘, a measure of the intensity of selection on phenotypic variance. Size-dependent attack by parasitoids caused upward directional selection (mean i_p = 0.42; SE = 0.023), while size-dependent bird attack favored larvae that induced smaller galls (mean i_b = -0.07; SE = 0.013. The mean net directional selection intensity was 0.35 (SE = 0.030), which indicates that insects inducing larger galls are generally favored by selection. The opposing patterns of size-dependent attack resulted in stabilizing selection in half the population generations, with an overall average. j‘ of -0.11 (SE = 0.078). The magnitude of directional selection was strongly influenced by the population mean gall size and weakly by the optimal gall size. The intensity of variance selection was strongly influenced by the shape of the fitness function, with sigmoidal and Gaussian-like shapes causing greater depletion of phenotypic variance.