Allele Frequency Trajectories Research Articles

Selection-Like Biases Emerge in Population Models with Recurrent Jackpot Events.

Evolutionary dynamics driven out of equilibrium by growth, expansion, or adaptation often generate a characteristically skewed distribution of descendant numbers: the earliest, the most advanced, or the fittest ancestors have exceptionally large number of descendants, which Luria and Delbrück called "jackpot" events. Here, I show that recurrent jackpot events generate a deterministic median bias favoring majority alleles, which is akin to positive frequency-dependent selection (proportional to the log ratio of the frequencies of mutant and wild-type alleles). This fictitious selection force results from the fact that majority alleles tend to sample deeper into the tail of the descendant distribution. The flip side of this sampling effect is the rare occurrence of large frequency hikes in favor of minority alleles, which ensures that the allele frequency dynamics remains neutral in expectation, unless genuine selection is present. The resulting picture of a selection-like bias compensated by rare big jumps allows for an intuitive understanding of allele frequency trajectories and enables the exact calculation of transition densities for a range of important scenarios, including population-size variations and different forms of natural selection. As a general signature of evolution by rare events, fictitious selection hampers the establishment of new beneficial mutations, counteracts balancing selection, and confounds methods to infer selection from data over limited timescales.

Inferring Allele Frequency Trajectories from Ancient DNA Indicates That Selection on a Chicken Gene Coincided with Changes in Medieval Husbandry Practices.

Ancient DNA provides an opportunity to infer the drivers of natural selection by linking allele frequency changes to temporal shifts in environment or cultural practices. However, analyses have often been hampered by uneven sampling and uncertainties in sample dating, as well as being confounded by demographic processes. Here, we present a Bayesian statistical framework for quantifying the timing and strength of selection using ancient DNA that explicitly addresses these challenges. We applied this method to time series data for two loci: TSHR and BCDO2, both hypothesised to have undergone strong and recent selection in domestic chickens. The derived variant in TSHR, associated with reduced aggression to conspecifics and faster onset of egg laying, shows strong selection beginning around 1,100 years ago, coincident with archaeological evidence for intensified chicken production and documented changes in egg and chicken consumption. To our knowledge, this is the first example of preindustrial domesticate trait selection in response to a historically attested cultural shift in food preference. For BCDO2, we find support for selection, but demonstrate that the recent rise in allele frequency could also have been driven by gene flow from imported Asian chickens during more recent breed formations. Our findings highlight that traits found ubiquitously in modern domestic species may not necessarily have originated during the early stages of domestication. In addition, our results demonstrate the importance of precise estimation of allele frequency trajectories through time for understanding the drivers of selection.

Bayesian Inference of Natural Selection from Allele Frequency Time Series.

The advent of accessible ancient DNA technology now allows the direct ascertainment of allele frequencies in ancestral populations, thereby enabling the use of allele frequency time series to detect and estimate natural selection. Such direct observations of allele frequency dynamics are expected to be more powerful than inferences made using patterns of linked neutral variation obtained from modern individuals. We developed a Bayesian method to make use of allele frequency time series data and infer the parameters of general diploid selection, along with allele age, in nonequilibrium populations. We introduce a novel path augmentation approach, in which we use Markov chain Monte Carlo to integrate over the space of allele frequency trajectories consistent with the observed data. Using simulations, we show that this approach has good power to estimate selection coefficients and allele age. Moreover, when applying our approach to data on horse coat color, we find that ignoring a relevant demographic history can significantly bias the results of inference. Our approach is made available in a C++ software package.

Inferring Selection Intensity and Allele Age from Multilocus Haplotype Structure

It is a challenging task to infer selection intensity and allele age from population genetic data. Here we present a method that can efficiently estimate selection intensity and allele age from the multilocus haplotype structure in the vicinity of a segregating mutant under positive selection. We use a structured-coalescent approach to model the effect of directional selection on the gene genealogies of neutral markers linked to the selected mutant. The frequency trajectory of the selected allele follows the Wright-Fisher model. Given the position of the selected mutant, we propose a simplified multilocus haplotype model that can efficiently model the dynamics of the ancestral haplotypes under the joint influence of selection and recombination. This model approximates the ancestral genealogies of the sample, which reduces the number of states from an exponential function of the number of single-nucleotide polymorphism loci to a quadratic function. That allows parameter inference from data covering DNA regions as large as several hundred kilo-bases. Importance sampling algorithms are adopted to evaluate the probability of a sample by exploring the space of both allele frequency trajectories of the selected mutation and gene genealogies of the linked sites. We demonstrate by simulation that the method can accurately estimate selection intensity for moderate and strong positive selection. We apply the method to a data set of the G6PD gene in an African population and obtain an estimate of 0.0456 (95% confidence interval 0.0144−0.0769) for the selection intensity. The proposed method is novel in jointly modeling the multilocus haplotype pattern caused by recombination and mutation, allowing the analysis of haplotype data in recombining regions. Moreover, the method is applicable to data from populations under exponential growth and a variety of other demographic histories.

The alternative fitness sets which preserve allele trajectories: a general treatment.

A general solution is presented of the problem of specifying all alternative, generally frequency-dependent, (absolute) fitness sets which give rise to the same allele frequency changes and population dynamics as a given fitness set. The one- and two-locus cases are analyzed in detail and the method is then extended to the n-locus case. It is shown that if biological constraints can be used to specify the mean fitness of the population and the relative fitnesses of the heterozygotes, then the allele frequency trajectories determine a unique fitness set.

Alternative fitness models with the same allele frequency dynamics.

For any set of one- or two-locus genotypic fitnesses there are alternative sets, usually frequency-dependent and often with quite different biological meanings, that give rise to the same equations for change of allele or haplotype frequencies. Therefore, it is not possible to distinguish among alternative fitness models from allele or haplotype frequency trajectories or equilibrium distributions. For a single locus and for two loci when linkage equilibrium can be assumed, a simple procedure generates some of the alternative fitness sets.

The estimation of epistasis in components of fitness in experimental populations of drosophila melanogaster II. Assessment of meiotic drive, viability, fecundity and sexual selection.

An analysis of fitness components was performed on laboratory populations of Drosophila melanogaster bearing Curly and Plum marked second chromosome inversions with two genetic backgrounds. Selective differences between Curly, Plum, Curly-Plum, and wild phenotypes were partitioned into meiotic drive, viability, fecundity and mating success. Although no significant meiotic drive was detected, there were significant differences between genotypes in the other three components. Interlocus interactions in fertility and sexual selection components were measured, and statistics to quantify epistasis at these levels of fitness were devised. Significant fitness interactions between genes on the Curly and Plum inversions in viability, fecundity, and sexual selection were found. These results were qualitatively consistent with the maximum likelihood fitness estimates found previously. The expected allele frequency trajectories computed from the estimated components adequately fitted the observed selection trajectories.