Basic Life Science Research Associate, Biology
Organisms can often adapt surprisingly quickly to evolutionary challenges, such as the application of pesticides or antibiotics, suggesting an abundant supply of adaptive genetic variation. In these situations, adaptation should commonly produce 'soft' selective sweeps, where multiple adaptive alleles sweep through the population at the same time, either because the alleles were already present as standing genetic variation or arose independently by recurrent de novo mutations. Most well-known examples of rapid molecular adaptation indeed show signatures of such soft selective sweeps. Here, we review the current understanding of the mechanisms that produce soft sweeps and the approaches used for their identification in population genomic data. We argue that soft sweeps might be the dominant mode of adaptation in many species.
View details for DOI 10.1016/j.tree.2013.08.003
View details for Web of Science ID 000326666200007
View details for PubMedID 24075201
SLiM is an efficient forward population genetic simulation designed for studying the effects of linkage and selection on a chromosome-wide scale. The program can incorporate complex scenarios of demography and population substructure, various models for selection and dominance of new mutations, arbitrary gene-structure, and user-defined recombination maps.
View details for DOI 10.1534/genetics.113.152181
View details for Web of Science ID 000322578000018
View details for PubMedID 23709637
Population genomic studies have shown that genetic draft and background selection can profoundly affect the genome-wide patterns of molecular variation. We performed forward simulations under realistic gene-structure and selection scenarios to investigate whether such linkage effects impinge on the ability of the McDonald-Kreitman (MK) test to infer the rate of positive selection (α) from polymorphism and divergence data. We find that in the presence of slightly deleterious mutations, MK estimates of α severely underestimate the true rate of adaptation even if all polymorphisms with population frequencies under 50% are excluded. Furthermore, already under intermediate rates of adaptation, genetic draft substantially distorts the site frequency spectra at neutral and functional sites from the expectations under mutation-selection-drift balance. MK-type approaches that first infer demography from synonymous sites and then use the inferred demography to correct the estimation of α obtain almost the correct α in our simulations. However, these approaches typically infer a severe past population expansion although there was no such expansion in the simulations, casting doubt on the accuracy of methods that infer demography from synonymous polymorphism data. We propose a simple asymptotic extension of the MK test that yields accurate estimates of α in our simulations and should provide a fruitful direction for future studies.
View details for DOI 10.1073/pnas.1220835110
View details for Web of Science ID 000320328700068
View details for PubMedID 23650353
Synonymous sites are generally assumed to be subject to weak selective constraint. For this reason, they are often neglected as a possible source of important functional variation. We use site frequency spectra from deep population sequencing data to show that, contrary to this expectation, 22% of four-fold synonymous (4D) sites in Drosophila melanogaster evolve under very strong selective constraint while few, if any, appear to be under weak constraint. Linking polymorphism with divergence data, we further find that the fraction of synonymous sites exposed to strong purifying selection is higher for those positions that show slower evolution on the Drosophila phylogeny. The function underlying the inferred strong constraint appears to be separate from splicing enhancers, nucleosome positioning, and the translational optimization generating canonical codon bias. The fraction of synonymous sites under strong constraint within a gene correlates well with gene expression, particularly in the mid-late embryo, pupae, and adult developmental stages. Genes enriched in strongly constrained synonymous sites tend to be particularly functionally important and are often involved in key developmental pathways. Given that the observed widespread constraint acting on synonymous sites is likely not limited to Drosophila, the role of synonymous sites in genetic disease and adaptation should be reevaluated.
View details for DOI 10.1371/journal.pgen.1003527
View details for PubMedID 23737754
General parameters of selection, such as the frequency and strength of positive selection in natural populations or the role of introgression, are still insufficiently understood. The house mouse (Mus musculus) is a particularly well-suited model system to approach such questions, since it has a defined history of splits into subspecies and populations and since extensive genome information is available. We have used high-density single-nucleotide polymorphism (SNP) typing arrays to assess genomic patterns of positive selection and introgression of alleles in two natural populations of each of the subspecies M. m. domesticus and M. m. musculus. Applying different statistical procedures, we find a large number of regions subject to apparent selective sweeps, indicating frequent positive selection on rare alleles or novel mutations. Genes in the regions include well-studied imprinted loci (e.g. Plagl1/Zac1), homologues of human genes involved in adaptations (e.g. alpha-amylase genes) or in genetic diseases (e.g. Huntingtin and Parkin). Haplotype matching between the two subspecies reveals a large number of haplotypes that show patterns of introgression from specific populations of the respective other subspecies, with at least 10% of the genome being affected by partial or full introgression. Using neutral simulations for comparison, we find that the size and the fraction of introgressed haplotypes are not compatible with a pure migration or incomplete lineage sorting model. Hence, it appears that introgressed haplotypes can rise in frequency due to positive selection and thus can contribute to the adaptive genomic landscape of natural populations. Our data support the notion that natural genomes are subject to complex adaptive processes, including the introgression of haplotypes from other differentiated populations or species at a larger scale than previously assumed for animals. This implies that some of the admixture found in inbred strains of mice may also have a natural origin.
View details for DOI 10.1371/journal.pgen.1002891
View details for Web of Science ID 000308529300048
View details for PubMedID 22956910
Selective sweeps are typically associated with a local reduction of genetic diversity around the adaptive site. However, selective sweeps can also quickly carry neutral mutations to observable population frequencies if they arise early in a sweep and hitchhike with the adaptive allele. We show that the interplay between mutation and exponential amplification through hitchhiking results in a characteristic frequency spectrum of the resulting novel haplotype variation that depends only on the ratio of the mutation rate and the selection coefficient of the sweep. On the basis of this result, we develop an estimator for the selection coefficient driving a sweep. Since this estimator utilizes the novel variation arising from mutations during a sweep, it does not rely on preexisting variation and can also be applied to loci that lack recombination. Compared with standard approaches that infer selection coefficients from the size of dips in genetic diversity around the adaptive site, our estimator requires much shorter sequences but sampled at high population depth to capture low-frequency variants; given such data, it consistently outperforms standard approaches. We investigate analytically and numerically how the accuracy of our estimator is affected by the decay of the sweep pattern over time as a consequence of random genetic drift and discuss potential effects of recombination, soft sweeps, and demography. As an example for its use, we apply our estimator to deep sequencing data from human immunodeficiency virus populations.
View details for DOI 10.1534/genetics.112.138461
View details for Web of Science ID 000308999300018
View details for PubMedID 22491190
Molecular adaptation is typically assumed to proceed by sequential fixation of beneficial mutations. In diploids, this picture presupposes that for most adaptive mutations, the homozygotes have a higher fitness than the heterozygotes. Here, we show that contrary to this expectation, a substantial proportion of adaptive mutations should display heterozygote advantage. This feature of adaptation in diploids emerges naturally from the primary importance of the fitness of heterozygotes for the invasion of new adaptive mutations. We formalize this result in the framework of Fisher's influential geometric model of adaptation. We find that in diploids, adaptation should often proceed through a succession of short-lived balanced states that maintain substantially higher levels of phenotypic and fitness variation in the population compared with classic adaptive walks. In fast-changing environments, this variation produces a diversity advantage that allows diploids to remain better adapted compared with haploids despite the disadvantage associated with the presence of unfit homozygotes. The short-lived balanced states arising during adaptive walks should be mostly invisible to current scans for long-term balancing selection. Instead, they should leave signatures of incomplete selective sweeps, which do appear to be common in many species. Our results also raise the possibility that balancing selection, as a natural consequence of frequent adaptation, might play a more prominent role among the forces maintaining genetic variation than is commonly recognized.
View details for DOI 10.1073/pnas.1114573108
View details for Web of Science ID 000298289400081
View details for PubMedID 22143780
Comparative genomics has become widely accepted as the major framework for the ascertainment of functionally important regions in genomes. The underlying paradigm of this approach is that most of the functional regions are assumed to be under selective constraint, which in turn reduces the rate of evolution relative to neutrality. This assumption allows detection of functional regions through sequence conservation. However, constraint does not always lead to sequence conservation. When purifying selection is weak and mutation is biased, constrained regions can even evolve faster than neutral sequences and thus can appear to be under positive selection. Moreover, conservation estimates depend also on the orientation of selection relative to mutational biases and can vary over time. In the light of recent data of the ubiquity of mutational biases and weak selective forces, these effects should reduce the power of conservation analyses to define functional regions using comparative genomics data. We argue that the estimation of true mutational biases and the use of explicit evolutionary models are essential to improve methods inferring the action of natural selection and functionality in genome sequences.
View details for DOI 10.1093/gbe/evr032
View details for Web of Science ID 000295693200004
View details for PubMedID 21498884
Adaptation in eukaryotes is generally assumed to be mutation-limited because of small effective population sizes. This view is difficult to reconcile, however, with the observation that adaptation to anthropogenic changes, such as the introduction of pesticides, can occur very rapidly. Here we investigate adaptation at a key insecticide resistance locus (Ace) in Drosophila melanogaster and show that multiple simple and complex resistance alleles evolved quickly and repeatedly within individual populations. Our results imply that the current effective population size of modern D. melanogaster populations is likely to be substantially larger (> or = 100-fold) than commonly believed. This discrepancy arises because estimates of the effective population size are generally derived from levels of standing variation and thus reveal long-term population dynamics dominated by sharp--even if infrequent--bottlenecks. The short-term effective population sizes relevant for strong adaptation, on the other hand, might be much closer to census population sizes. Adaptation in Drosophila may therefore not be limited by waiting for mutations at single sites, and complex adaptive alleles can be generated quickly without fixation of intermediate states. Adaptive events should also commonly involve the simultaneous rise in frequency of independently generated adaptive mutations. These so-called soft sweeps have very distinct effects on the linked neutral polymorphisms compared to the standard hard sweeps in mutation-limited scenarios. Methods for the mapping of adaptive mutations or association mapping of evolutionarily relevant mutations may thus need to be reconsidered.
View details for DOI 10.1371/journal.pgen.1000924
View details for Web of Science ID 000279805200003
View details for PubMedID 20585551
Investigating spatial patterns of loci under selection can give insight into how populations evolved in response to selective pressures and can provide monitoring tools for detecting the impact of environmental changes on populations. Drosophila is a particularly good model to study adaptation to environmental heterogeneity since it is a tropical species that originated in sub-Saharan Africa and has only recently colonized the rest of the world. There is strong evidence for the adaptive role of Transposable Elements (TEs) in the evolution of Drosophila, and TEs might play an important role specifically in adaptation to temperate climates. In this work, we analyzed the frequency of a set of putatively adaptive and putatively neutral TEs in populations with contrasting climates that were collected near the endpoints of two known latitudinal clines in Australia and North America. The contrasting results obtained for putatively adaptive and putatively neutral TEs and the consistency of the patterns between continents strongly suggest that putatively adaptive TEs are involved in adaptation to temperate climates. We integrated information on population behavior, possible environmental selective agents, and both molecular and functional information of the TEs and their nearby genes to infer the plausible phenotypic consequences of these insertions. We conclude that adaptation to temperate environments is widespread in Drosophila and that TEs play a significant role in this adaptation. It is remarkable that such a diverse set of TEs located next to a diverse set of genes are consistently adaptive to temperate climate-related factors. We argue that reverse population genomic analyses, as the one described in this work, are necessary to arrive at a comprehensive picture of adaptation.
View details for DOI 10.1371/journal.pgen.1000905
View details for Web of Science ID 000277354200022
View details for PubMedID 20386746
The rates and patterns of spontaneous mutation are fundamental parameters of molecular evolution. Current methodology either tries to measure such rates and patterns directly in mutation-accumulation experiments or tries to infer them indirectly from levels of divergence or polymorphism. While experimental approaches are constrained by the low rate at which new mutations occur, indirect approaches suffer from their underlying assumption that mutations are effectively neutral. Here I present a maximum-likelihood approach to estimate mutation rates from large-scale polymorphism data. It is demonstrated that the method is not sensitive to demography and the distribution of selection coefficients among mutations when applied to mutations at sufficiently low population frequencies. With the many large-scale sequencing projects currently underway, for instance, the 1000 genomes project in humans, plenty of the required low-frequency polymorphism data will shortly become available. My method will allow for an accurate and unbiased inference of mutation rates and patterns from such data sets at high spatial resolution. I discuss how the assessment of several long-standing problems of evolutionary biology would benefit from the availability of accurate mutation rate estimates.
View details for DOI 10.1534/genetics.109.105692
View details for Web of Science ID 000270214000024
View details for PubMedID 19528323
Transposable elements (TEs) constitute a substantial fraction of the genomes of many species, and it is thus important to understand their population dynamics. The strength of natural selection against TEs is a key parameter in understanding these dynamics. In principle, the strength of selection can be inferred from the frequencies of a sample of TEs. However, complicated demographic histories, such as found in Drosophila melanogaster, could lead to a substantial distortion of the TE frequency distribution compared with that expected for a panmictic, constant-sized population. The current methodology for the estimation of selection intensity acting against TEs does not take into account demographic history and might generate erroneous estimates especially for TE families under weak selection. Here, we develop a flexible maximum likelihood methodology that explicitly accounts both for demographic history and for the ascertainment biases of identifying TEs. We apply this method to the newly generated frequency data of the BS family of non-long terminal repeat retrotransposons in D. melanogaster in concert with two recent models of the demographic history of the species to infer the intensity of selection against this family. We find the estimate to differ substantially compared with a prior estimate that was made assuming a model of constant population size. Further, we find there to be relatively little information about selection intensity present in the derived non-African frequency data and that the ancestral African subpopulation is much more informative in this respect. These findings highlight the importance of accounting for demographic history and bear on study design for the inference of selection coefficients generally.
View details for DOI 10.1093/molbev/msn270
View details for Web of Science ID 000263420900005
View details for PubMedID 19033258