How reliable are empirical genomic scans for selective sweeps?

Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection

Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.

Temporal challenges in detecting balancing selection from population genomic data

The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Teaser Text

Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.

Admixture has obscured signals of historical hard sweeps in humans

The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.

Recommendations for improving statistical inference in population genomics

The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.

Strong neutral sweeps occurring during a population contraction

A strong reduction in diversity around a specific locus is often interpreted as a recent rapid fixation of a positively selected allele, a phenomenon called a selective sweep. Rapid fixation of neutral variants can however lead to a similar reduction in local diversity, especially when the population experiences changes in population size, e.g. bottlenecks or range expansions. The fact that demographic processes can lead to signals of nucleotide diversity very similar to signals of selective sweeps is at the core of an ongoing discussion about the roles of demography and natural selection in shaping patterns of neutral variation. Here, we quantitatively investigate the shape of such neutral valleys of diversity under a simple model of a single population size change, and we compare it to signals of a selective sweep. We analytically describe the expected shape of such "neutral sweeps" and show that selective sweep valleys of diversity are, for the same fixation time, wider than neutral valleys. On the other hand, it is always possible to parametrize our model to find a neutral valley that has the same width as a given selected valley. Our findings provide further insight into how simple demographic models can create valleys of genetic diversity similar to those attributed to positive selection.

Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies

We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.

Soft selective sweeps: Addressing new definitions, evaluating competing models, and interpreting empirical outliers

The ability to accurately identify and quantify genetic signatures associated with soft selective sweeps based on patterns of nucleotide variation has remained controversial. We here provide counter viewpoints to recent publications in PLOS Genetics that have argued not only for the statistical identifiability of soft selective sweeps, but also for their pervasive evolutionary role in both Drosophila and HIV populations. We present evidence that these claims owe to a lack of consideration of competing evolutionary models, unjustified interpretations of empirical outliers, as well as to new definitions of the processes themselves. Our results highlight the dangers of fitting evolutionary models based on hypothesized and episodic processes without properly first considering common processes and, more generally, of the tendency in certain research areas to view pervasive positive selection as a foregone conclusion.

Genome resequencing reveals rapid, repeated evolution in the Colorado potato beetle

Insecticide resistance and rapid pest evolution threatens food security and the development of sustainable agricultural practices, yet the evolutionary mechanisms that allow pests to rapidly adapt to control tactics remains unclear. Here we examine how a global super-pest, the Colorado potato beetle (CPB), Leptinotarsa decemlineata, rapidly evolves resistance to insecticides. Using whole genome resequencing and transcriptomic data focused on its ancestral and pest range in North America, we assess evidence for three, non-mutually exclusive models of rapid evolution: pervasive selection on novel mutations, rapid regulatory evolution, and repeated selection on standing genetic variation. Population genomic analysis demonstrates that CPB is geographically structured, even among recently established pest populations. Pest populations exhibit similar levels of nucleotide diversity, relative to non-pest populations, and show evidence of recent expansion. Genome scans provide clear signatures of repeated adaptation across CPB populations, with especially strong evidence of selection on insecticide resistance genes in different populations. Analyses of gene expression show that constitutive upregulation of candidate insecticide resistance genes drives distinctive population patterns. CPB evolves insecticide resistance repeatedly across agricultural regions, leveraging similar genetic pathways but different genes, demonstrating a polygenic trait architecture for insecticide resistance that can evolve from standing genetic variation. Despite expectations, we do not find support for strong selection on novel mutations, or rapid evolution from selection on regulatory genes. These results suggest that integrated pest management practices must mitigate the evolution of polygenic resistance phenotypes among local pest populations, in order to maintain the efficacy and sustainability of novel control techniques.

Temperature-dependent genetics of thermotolerance between yeast species

Many traits of industrial and basic biological interest arose long ago, and manifest now as fixed differences between a focal species and its reproductively isolated relatives. In these systems, extant individuals can hold clues to the mechanisms by which phenotypes evolved in their ancestors. We harnessed yeast thermotolerance as a test case for such molecular-genetic inferences. In viability experiments, we showed that extant Saccharomyces cerevisiae survived at temperatures where cultures of its sister species S. paradoxus died out. Then, focusing on loci that contribute to this difference, we found that the genetic mechanisms of high-temperature growth changed with temperature. We also uncovered an enrichment of low-frequency variants at thermotolerance loci in S. cerevisiae population sequences, suggestive of a history of non-neutral selective forces acting at these genes. We interpret these results in light of models of the evolutionary mechanisms by which the thermotolerance trait arose in the S. cerevisiae lineage. Together, our results and interpretation underscore the power of genetic approaches to explore how an ancient trait came to be.

Sporadic occurrence of recent selective sweeps from standing variation in humans as revealed by an approximate Bayesian computation approach

During their dispersals over the last 100,000 years, modern humans have been exposed to a large variety of environments, resulting in genetic adaptation. While genome-wide scans for the footprints of positive Darwinian selection have increased knowledge of genes and functions potentially involved in human local adaptation, they have globally produced evidence of a limited contribution of selective sweeps in humans. Conversely, studies based on machine learning algorithms suggest that recent sweeps from standing variation are widespread in humans, an observation that has been recently questioned. Here, we sought to formally quantify the number of recent selective sweeps in humans, by leveraging approximate Bayesian computation and whole-genome sequence data. Our computer simulations revealed suitable ABC estimations, regardless of the frequency of the selected alleles at the onset of selection and the completion of sweeps. Under a model of recent selection from standing variation, we inferred that an average of 68 (from 56 to 79) and 140 (from 94 to 198) sweeps occurred over the last 100,000 years of human history, in African and Eurasian populations, respectively. The former estimation is compatible with human adaptation rates estimated since divergence with chimps, and reveals numbers of sweeps per generation per site in the range of values estimated in Drosophila. Our results confirm the rarity of selective sweeps in humans and show a low contribution of sweeps from standing variation to recent human adaptation.

Revisiting the notion of deleterious sweeps

It has previously been shown that, conditional on its fixation, the time to fixation of a semi-dominant deleterious autosomal mutation in a randomly mating population is the same as that of an advantageous mutation. This result implies that deleterious mutations could generate selective sweep-like effects. Although their fixation probabilities greatly differ, the much larger input of deleterious relative to beneficial mutations suggests that this phenomenon could be important. We here examine how the fixation of mildly deleterious mutations affects levels and patterns of polymorphism at linked sites-both in the presence and absence of interference amongst deleterious mutations-and how this class of sites may contribute to divergence between-populations and species. We find that, while deleterious fixations are unlikely to represent a significant proportion of outliers in polymorphism-based genomic scans within populations, minor shifts in the frequencies of deleterious mutations can influence the proportions of private variants and the value of FST after a recent population split. As sites subject to deleterious mutations are necessarily found in functional genomic regions, interpretations in terms of recurrent positive selection may require reconsideration.

Effects of Selection at Linked Sites on Patterns of Genetic Variability

Patterns of variation and evolution at a given site in a genome can be strongly influenced by the effects of selection at genetically linked sites. In particular, the recombination rates of genomic regions correlate with their amount of within-population genetic variability, the degree to which the frequency distributions of DNA sequence variants differ from their neutral expectations, and the levels of adaptation of their functional components. We review the major population genetic processes that are thought to lead to these patterns, focusing on their effects on patterns of variability: selective sweeps, background selection, associative overdominance, and Hill–Robertson interference among deleterious mutations. We emphasize the difficulties in distinguishing among the footprints of these processes and disentangling them from the effects of purely demographic factors such as population size changes. We also discuss how interactions between selective and demographic processes can significantly affect patterns of variability within genomes.

Sweeps in time: leveraging the joint distribution of branch lengths

Current methods of identifying positively selected regions in the genome are limited in two key ways: the underlying models cannot account for the timing of adaptive events and the comparison between models of selective sweeps and sequence data is generally made via simple summaries of genetic diversity. Here, we develop a tractable method of describing the effect of positive selection on the genealogical histories in the surrounding genome, explicitly modeling both the timing and context of an adaptive event. In addition, our framework allows us to go beyond analyzing polymorphism data via the site frequency spectrum or summaries thereof and instead leverage information contained in patterns of linked variants. Tests on both simulations and a human data example, as well as a comparison to SweepFinder2, show that even with very small sample sizes, our analytic framework has higher power to identify old selective sweeps and to correctly infer both the time and strength of selection. Finally, we derived the marginal distribution of genealogical branch lengths at a locus affected by selection acting at a linked site. This provides a much-needed link between our analytic understanding of the effects of sweeps on sequence variation and recent advances in simulation and heuristic inference procedures that allow researchers to examine the sequence of genealogical histories along the genome.

Evolutionary genetics of skin pigmentation in African populations

Skin color is a highly heritable human trait, and global variation in skin pigmentation has been shaped by natural selection, migration and admixture. Ethnically diverse African populations harbor extremely high levels of genetic and phenotypic diversity, and skin pigmentation varies widely across Africa. Recent genome-wide genetic studies of skin pigmentation in African populations have advanced our understanding of pigmentation biology and human evolutionary history. For example, novel roles in skin pigmentation for loci near MFSD12 and DDB1 have recently been identified in African populations. However, due to an underrepresentation of Africans in human genetic studies, there is still much to learn about the evolutionary genetics of skin pigmentation. Here, we summarize recent progress in skin pigmentation genetics in Africans and discuss the importance of including more ethnically diverse African populations in future genetic studies. In addition, we discuss methods for functional validation of adaptive variants related to skin pigmentation.

Human adaptation, demography and cattle domestication: an overview of the complexity of lactase persistence in Africa

Lactase persistence (LP) is a genetically-determined trait that is prevalent in African, European and Arab populations with a tradition of animal herding and milk consumption. To date, genetic analyses have identified several common variants that are associated with LP. Furthermore, data have indicated that these functional alleles likely have been maintained in pastoralist populations due to the action of recent selection, exemplifying the ongoing evolution of anatomically modern humans. Additionally, demographic history has also played a role in the geographic distribution of LP and associated alleles in Africa. In particular, the migration of ancestral herders and their subsequent admixture with local populations were integral to the spread of LP alleles and the culture of pastoralism across the continent. The timing of these demographic events was often correlated with known major environmental changes and/or the ability of domesticated cattle to resist/avoid infectious diseases. This review summarizes recent advances in our understanding of the genetic basis and evolutionary history of LP, as well as the factors that influenced the origin and spread of pastoralism in Africa.

The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects

Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data

Whether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population of Drosophila melanogaster (DGRP) allowed us to rediscover three known cases of adaptation at the loci Ace, Cyp6g1, and CHKov1 known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harris et al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and that instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps in D. melanogaster are first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that most demographic models employed in such analyses are necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require a large number of free parameters.

The impact of purifying and background selection on the inference of population history: problems and prospects

Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

Population Genomics on the Fly: Recent Advances in Drosophila

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field.

Population genetics of the freshwater fish Prochilodus magdalenae (Characiformes: Prochilodontidae), using species-specific microsatellite loci

Prochilodus magdalenae is a freshwater fish endemic to the Colombian Magdalena-Cauca and Caribbean hydrographic basins. The genetic structure patterns of populations of different members of Prochilodus and the historic restocking of its depleted natural populations suggest that P. magdalenae exhibits genetic stocks that coexist and co-migrate throughout the rivers Magdalena, Cauca, Cesar, Sinú and Atrato. To test this hypothesis and explore the levels of genetic diversity and population demography of 725 samples of P. magdalenae from the studied rivers, we developed a set of 11 species-specific microsatellite loci using next-generation sequencing, bioinformatics, and experimental tests of the levels of diversity of the microsatellite loci. The results evidenced that P. magdalenae exhibits high genetic diversity, significant inbreeding coefficient ranging from 0.162 to 0.202, and signs of erosion of the genetic pool. Additionally, the population genetic structure constitutes a mixture of genetic stocks heterogeneously distributed along the studied rivers, and moreover, a highly divergent genetic stock was detected in Chucurí, Puerto Berrío and Palagua that may result from restocking practices. This study provides molecular tools and a wide framework regarding the genetic diversity and structure of P. magdalenae, which is crucial to complement its baseline information, diagnosis and monitoring of populations, and to support the implementation of adequate regulation, management, and conservation policies.

A joint analysis strategy reveals genetic changes associated with artificial selection between egg-type and meat-type ducks

Egg-type ducks and meat-type ducks are predominantly commercial or indigenous and have been subjected to artificial directional selection. These two duck types differ substantially in body shape, production performance and reproductivity. However, the genetic changes associated with phenotypic differences remain unclear. Here, we compared the two duck types at the genomic and transcriptomic levels. We identified a large number of SNPs and genes in genomic divergent regions in terms of F_ST and θπ values. The corresponding genes were mainly enriched in embryonic development function and metabolic pathway. RNA-seq analysis also revealed differential gene expression in the liver and gonads. The differentially expressed genes were functionally associated with signal transmission and substance metabolism respectively. Furthermore, we found that seven genes were related to differentiation between the two types by both g genome and transcriptome analysis and were plausible candidate genes. These genes were annotated to GO categories of cell development and disease immunity. These findings will enable a better understanding of the artificial selection history of meat and egg ducks and provide a valuable resource for future research on the breeding of these two lineages.

Background Selection Does Not Mimic the Patterns of Genetic Diversity Produced by Selective Sweeps

It is increasingly evident that natural selection plays a prominent role in shaping patterns of diversity across the genome. The most commonly studied modes of natural selection are positive selection and negative selection, which refer to directional selection for and against derived mutations, respectively. Positive selection can result in hitchhiking events, in which a beneficial allele rapidly replaces all others in the population, creating a valley of diversity around the selected site along with characteristic skews in allele frequencies and linkage disequilibrium among linked neutral polymorphisms. Similarly, negative selection reduces variation not only at selected sites but also at linked sites, a phenomenon called background selection (BGS). Thus, discriminating between these two forces may be difficult, and one might expect efforts to detect hitchhiking to produce an excess of false positives in regions affected by BGS. Here, we examine the similarity between BGS and hitchhiking models via simulation. First, we show that BGS may somewhat resemble hitchhiking in simplistic scenarios in which a region constrained by negative selection is flanked by large stretches of unconstrained sites, echoing previous results. However, this scenario does not mirror the actual spatial arrangement of selected sites across the genome. By performing forward simulations under more realistic scenarios of BGS, modeling the locations of protein-coding and conserved noncoding DNA in real genomes, we show that the spatial patterns of variation produced by BGS rarely mimic those of hitchhiking events. Indeed, BGS is not substantially more likely than neutrality to produce false signatures of hitchhiking. This holds for simulations modeled after both humans and Drosophila, and for several different demographic histories. These results demonstrate that appropriately designed scans for hitchhiking need not consider BGS's impact on false-positive rates. However, we do find evidence that BGS increases the false-negative rate for hitchhiking, an observation that demands further investigation.

Genetic Signatures of Evolutionary Rescue by a Selective Sweep

One of the most useful models in population genetics is that of a selective sweep and the consequent hitch-hiking of linked neutral alleles. While variations on this model typically assume constant population size, many instances of strong selection and rapid adaptation in nature may co-occur with complex demography. Here, we extend the hitch-hiking model to evolutionary rescue, where adaptation and demography not only co-occur but are intimately entwined. Our results show how this feedback between demography and evolution determines-and restricts-the genetic signatures of evolutionary rescue, and how these differ from the signatures of sweeps in populations of constant size. In particular, we find rescue to harden sweeps from standing variance or new mutation (but not from migration), reduce genetic diversity both at the selected site and genome-wide, and increase the range of observed Tajima's D values. For a given initial rate of population decline, the feedback between demography and evolution makes all of these differences more dramatic under weaker selection, where bottlenecks are prolonged. Nevertheless, it is likely difficult to infer the co-incident timing of the sweep and bottleneck from these simple signatures, never mind a feedback between them. Temporal samples spanning contemporary rescue events may offer one way forward.

Considering Genomic Scans for Selection as Coalescent Model Choice

First inspired by the seminal work of Lewontin and Krakauer (1973. Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74(1):175-195.) and Maynard Smith and Haigh (1974. The hitch-hiking effect of a favourable gene. Genet Res. 23(1):23-35.), genomic scans for positive selection remain a widely utilized tool in modern population genomic analysis. Yet, the relative frequency and genomic impact of selective sweeps have remained a contentious point in the field for decades, largely owing to an inability to accurately identify their presence and quantify their effects-with current methodologies generally being characterized by low true-positive rates and/or high false-positive rates under many realistic demographic models. Most of these approaches are based on Wright-Fisher assumptions and the Kingman coalescent and generally rely on detecting outlier regions which do not conform to these neutral expectations. However, previous theoretical results have demonstrated that selective sweeps are well characterized by an alternative class of model known as the multiple-merger coalescent. Taken together, this suggests the possibility of not simply identifying regions which reject the Kingman, but rather explicitly testing the relative fit of a genomic window to the multiple-merger coalescent. We describe the advantages of such an approach, which owe to the branching structure differentiating selective and neutral models, and demonstrate improved power under certain demographic scenarios relative to a commonly used approach. However, regions of the demographic parameter space continue to exist in which neither this approach nor existing methodologies have sufficient power to detect selective sweeps.

Selective Sweeps Under Dominance and Inbreeding

A major research goal in evolutionary genetics is to uncover loci experiencing positive selection. One approach involves finding 'selective sweeps' patterns, which can either be 'hard sweeps' formed by de novo mutation, or 'soft sweeps' arising from recurrent mutation or existing standing variation. Existing theory generally assumes outcrossing populations, and it is unclear how dominance affects soft sweeps. We consider how arbitrary dominance and inbreeding via self-fertilization affect hard and soft sweep signatures. With increased self-fertilization, they are maintained over longer map distances due to reduced effective recombination and faster beneficial allele fixation times. Dominance can affect sweep patterns in outcrossers if the derived variant originates from either a single novel allele, or from recurrent mutation. These models highlight the challenges in distinguishing hard and soft sweeps, and propose methods to differentiate between scenarios.

The evolution of metabolism: How to test evolutionary hypotheses at the genomic level

The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.

Recent population genomic insights into the genetic basis of arsenic tolerance in humans: the difficulties of identifying positively selected loci in strongly bottlenecked populations

Recent advances in genomics have enabled researchers to shed light on the evolutionary processes driving human adaptation, by revealing the genetic architectures underlying traits ranging from lactase persistence, to skin pigmentation, to hypoxic response, to arsenic tolerance. Complicating the identification of targets of positive selection in modern human populations is their complex demographic history, characterized by population bottlenecks and expansions, population structure, migration, and admixture. In particular, founder effects and recent strong population size reductions, such as those experienced by the indigenous peoples of the Americas, have severe impacts on genetic variation that can lead to the accumulation of large allele frequency differences between populations due to genetic drift rather than natural selection. While distinguishing the effects of demographic history from selection remains challenging, neglecting neutral processes can lead to the incorrect identification of candidate loci. We here review the recent population genomic insights into the genetic basis of arsenic tolerance in Andean populations, and utilize this example to highlight both the difficulties pertaining to the identification of local adaptations in strongly bottlenecked populations, as well as the importance of controlling for demographic history in selection scans.

Multiple selective sweeps of ancient polymorphisms in and around LTα located in the MHC class III region on chromosome 6

BACKGROUND

Lymphotoxin-α (LTα), located in the Major Histocompatibility Complex (MHC) class III region on chromosome 6, encodes a cytotoxic protein that mediates a variety of antiviral responses among other biological functions. Furthermore, several genotypes at this gene have been implicated in the onset of a number of complex diseases, including myocardial infarction, autoimmunity, and various types of cancer. However, little is known about levels of nucleotide variation and linkage disequilibrium (LD) in and near LTα, which could also influence phenotypic variance. To address this gap in knowledge, we examined sequence variation across ~ 10 kilobases (kbs), encompassing LTα and the upstream region, in 2039 individuals from the 1000 Genomes Project originating from 21 global populations.

RESULTS

Here, we observed striking patterns of diversity, including an excess of intermediate-frequency alleles, the maintenance of multiple common haplotypes and a deep coalescence time for variation (dating > 1.0 million years ago), in global populations. While these results are generally consistent with a model of balancing selection, we also uncovered a signature of positive selection in the form of long-range LD on chromosomes with derived alleles primarily in Eurasian populations. To reconcile these findings, which appear to support different models of selection, we argue that selective sweeps (particularly, soft sweeps) of multiple derived alleles in and/or near LTα occurred in non-Africans after their ancestors left Africa. Furthermore, these targets of selection were predicted to alter transcription factor binding site affinity and protein stability, suggesting they play a role in gene function. Additionally, our data also showed that a subset of these functional adaptive variants are present in archaic hominin genomes.

CONCLUSIONS

Overall, this study identified candidate functional alleles in a biologically-relevant genomic region, and offers new insights into the evolutionary origins of these loci in modern human populations.

The Demographic History of African Drosophila melanogaster

As one of the most commonly utilized organisms in the study of local adaptation, an accurate characterization of the demographic history of Drosophila melanogaster remains as an important research question. This owes both to the inherent interest in characterizing the population history of this model organism, as well as to the well-established importance of an accurate null demographic model for increasing power and decreasing false positive rates in genomic scans for positive selection. Although considerable attention has been afforded to this issue in non-African populations, less is known about the demographic history of African populations, including from the ancestral range of the species. While qualitative predictions and hypotheses have previously been forwarded, we here present a quantitative model fitting of the population history characterizing both the ancestral Zambian population range as well as the subsequently colonized west African populations, which themselves served as the source of multiple non-African colonization events. We here report the split time of the West African population at 72 kya, a date corresponding to human migration into this region as well as a period of climatic changes in the African continent. Furthermore, we have estimated population sizes at this split time. These parameter estimates thus represent an important null model for future investigations in to African and non-African D. melanogaster populations alike.

Environmental Association Identifies Candidates for Tolerance to Low Temperature and Drought

Barley (Hordeum vulgare ssp. vulgare) is cultivated from the equator to the Arctic Circle. The wild progenitor species, Hordeum vulgare ssp. spontaneum, occupies a relatively narrow latitudinal range (∼30 - 40° N) primarily at low elevation (< 1,500 m). Adaptation to the range of cultivation has occurred over ∼8,000 years. The genetic basis of adaptation is amenable to study through environmental association. An advantage of environmental association in a well-characterized crop is that many loci that contribute to climatic adaptation and abiotic stress tolerance have already been identified. This provides the opportunity to determine if environmental association approaches effectively identify these loci of large effect. Using published genotyping from 7,864 SNPs in 803 barley landraces, we examined allele frequency differentiation across multiple partitions of the data and mixed model associations relative to bioclimatic variables. Using newly generated resequencing data from a subset of these landraces, we tested for linkage disequilibrium (LD) between SNPs queried in genotyping and SNPs in neighboring loci. Six loci previously reported to contribute to adaptive differences in flowering time and abiotic stress in barley and six loci previously identified in other plant species were identified in our analyses. In many cases, patterns of LD are consistent with the causative variant occurring in the immediate vicinity of the queried SNP. The identification of barley orthologs to well-characterized genes may provide a new understanding of the nature of adaptive variation and could permit a more targeted use of potentially adaptive variants in barley breeding and germplasm improvement.

Gene-dense autosomal chromosomes show evidence for increased selection

Purifying selection tends to reduce nucleotide and haplotype diversity leading to increased linkage disequilibrium. However, detection of evidence for selection is difficult as the signature is confounded by wide variation in the recombination rate which has a complex relationship with selection. The effective bottleneck time (the ratio of the linkage disequilibrium map to the genetic map in Morgans) controls for variability in the recombination rate. Reduced effective bottleneck times indicate stronger residual linkage disequilibrium, consistent with increased selection. Using whole genome sequence data from one European and three Sub-Saharan African human populations we find, in the African samples, strong correlations between high gene densities and reduced effective bottleneck time for autosomal chromosomes. This suggests that gene-dense autosomes have been subject to increased purifying selection reducing effective bottleneck times compared to gene-poor autosomes. Although previous studies have shown unusually strong linkage disequilibrium for the sex chromosomes variation within the autosomes has not been recognised. The strongest relationship is between effective bottleneck time and the density of essential genes, which are likely targets of greater selective pressure (p = 0.006, for the 22 autosomes). The magnitude of the reduction in chromosome-specific effective bottleneck times from the least to the most gene-dense autosomes is ~17-21% for Sub-Saharan African populations. The effect size is greater in Sub-Saharan African populations, compared to a European sample, consistent with increased efficiency of selection in populations with larger effective population sizes which have not been subject to intense population bottlenecks as experienced by populations of European ancestry. The findings highlight the value of deeper analyses of selection within Sub-Saharan African populations.

Artificial selection causes significant linkage disequilibrium among multiple unlinked genes in Australian wheat

Australia has one of the oldest modern wheat breeding programs worldwide although the crop was first introduced to the country in 1788. Breeders selected wheat with high adaptation to different Australian climates, while ensuring satisfactory yield and quality. This artificial selection left distinct genomic signatures that can be used to retrospectively understand breeding targets, and to detect economically important alleles. To study the effect of artificial selection on modern cultivars and cultivars released in different Australian states, we genotyped 482 Australian cultivars representing the history of wheat breeding in Australia since 1840. Computer simulation showed that 86 genomic regions were significantly affected by artificial selection. Characterization of 18 major genes known to affect wheat adaptation, yield, and quality revealed that many were affected by artificial selection and contained within regions under selection. Similarly, many reported QTL and genes for yield, quality, and adaptation were also contained in regions affected by artificial selection. These included TaCwi-A1, TaGw2-6A, Sus-2B, TaSus1-7A, TaSAP1-7A, Glu-A1, Glu-B1, Glu-B3, PinA, PinB, Ppo-D1, Psy-A1, Psy-A2, Rht-A1, Rht-B1, Ppd-D1, Vrn-A1, Vrn-B1, and Cre8. Interestingly, 17 regions affected by artificial selection were in moderate-to-high linkage disequilibrium with each other with an average r 2 value of 0.35 indicating strong simultaneous selection on specific alleles. These regions included Glu-B1, TaGw2-6A, Cre8, Ppd-D1, Rht-B1, Vrn-B1, TaSus1-7A, TaSAP1-7A, and Psy-A1 plus multiple QTL affecting wheat yield and yield components. These results highlighted the effects of the long-term artificial selection on Australian wheat germplasm and identified putative regions underlying important traits in wheat.

An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method CLUES treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele's age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1.

Measuring viability selection from prospective cohort mortality studies: A case study in maritime pine

By changing the genetic background available for selection at subsequent life stages, stage-specific selection can define adaptive potential across the life cycle. We propose and evaluate here a neutrality test and a Bayesian method to infer stage-specific viability selection coefficients using sequential random genotypic samples drawn from a longitudinal cohort mortality study, within a generation. The approach is suitable for investigating selective mortality in large natural or experimental cohorts of any organism in which individual tagging and tracking are unfeasible. Numerical simulation results indicate that the method can discriminate loci under strong viability selection, and provided samples are large, yield accurate estimates of the corresponding selection coefficients. Genotypic frequency changes are largely driven by sampling noise under weak selection, however, compromising inference in that case. We apply the proposed methods to analyze viability selection operating at early recruitment stages in a natural maritime pine (Pinus pinaster Ait.) population. We measured temporal genotypic frequency changes at 384 candidate-gene SNP loci among seedlings sampled from the time of emergence in autumn until the summer of the following year, a period with high elimination rates. We detected five loci undergoing allele frequency changes larger than expected from stochastic mortality and sampling, with putative functions that could influence survival at early seedling stages. Our results illustrate how new statistical and sampling schemes can be used to conduct genomic scans of contemporary selection on specific life stages.

Footprints of adaptive evolution revealed by whole Z chromosomes haplotypes in flycatchers

Detecting positive selection using genomic data is critical to understanding the role of adaptive evolution. Of particular interest in this context is sex chromosomes since they are thought to play a special role in local adaptation and speciation. We sought to circumvent the challenges associated with statistical phasing when using haplotype-based statistics in sweep scans by benefitting from that whole chromosome haplotypes of the sex chromosomes can be obtained by resequencing of individuals of the hemizygous sex. We analyzed whole Z chromosome haplotypes from 100 females from several populations of four black and white flycatcher species (in birds, females are ZW and males ZZ). Based on integrated haplotype score (iHS) and number of segregating sites by length (nSL) statistics, we found strong and frequent haplotype structure in several regions of the Z chromosome in each species. Most of these sweep signals were population-specific, with essentially no evidence for regions under selection shared among species. Some completed sweeps were revealed by the cross-population extended haplotype homozygosity (XP-EHH) statistic. Importantly, by using statistically phased Z chromosome data from resequencing of males, we failed to recover the signals of selection detected in analyses based on whole chromosome haplotypes from females; instead, what likely represent false signals of selection were frequently seen. This highlights the power issues in statistical phasing and cautions against conclusions from selection scans using such data. The detection of frequent selective sweeps on the avian Z chromosome supports a large role of sex chromosomes in adaptive evolution.

Population genomics of rapid evolution in natural populations: polygenic selection in response to power station thermal effluents

BACKGROUND

Examples of rapid evolution are common in nature but difficult to account for with the standard population genetic model of adaptation. Instead, selection from the standing genetic variation permits rapid adaptation via soft sweeps or polygenic adaptation. Empirical evidence of this process in nature is currently limited but accumulating.

RESULTS

We provide genome-wide analyses of rapid evolution in Fundulus heteroclitus populations subjected to recently elevated temperatures due to coastal power station thermal effluents using 5449 SNPs across two effluent-affected and four reference populations. Bayesian and multivariate analyses of population genomic structure reveal a substantial portion of genetic variation that is most parsimoniously explained by selection at the site of thermal effluents. An FST outlier approach in conjunction with additional conservative requirements identify significant allele frequency differentiation that exceeds neutral expectations among exposed and closely related reference populations. Genomic variation patterns near these candidate loci reveal that individuals living near thermal effluents have rapidly evolved from the standing genetic variation through small allele frequency changes at many loci in a pattern consistent with polygenic selection on the standing genetic variation.

CONCLUSIONS

While the ultimate trajectory of selection in these populations is unknown and we survey only a minority of genomic loci, our findings suggest that polygenic models of adaptation may play important roles in large, natural populations experiencing recent selection due to environmental changes that cause broad physiological impacts.

Signatures of Selection in Admixed Dairy Cattle in Tanzania

Multiple studies have investigated selection signatures in domestic cattle and other species. However, there is a dearth of information about the response to selection in genomes of highly admixed crossbred cattle in relation to production and adaptation to tropical environments. In this study, we evaluated 839 admixed crossbred cows sampled from two major dairy regions in Tanzania namely Rungwe and Lushoto districts, in order to understand their genetic architecture and detect genomic regions showing preferential selection. Animals were genotyped at 150,000 SNP loci using the Geneseek Genomic Profiler (GGP) High Density (HD) SNP array. Population structure analysis showed a large within-population genetic diversity in the study animals with a high degree of variation in admixture ranging between 7 and 100% taurine genes (dairyness) of mostly Holstein and Friesian ancestry. We explored evidence of selection signatures using three statistical methods (iHS, XP-EHH, and pcadapt). Selection signature analysis identified 108 candidate selection regions in the study population. Annotation of these regions yielded interesting genes potentially under strong positive selection including ABCG2, ABCC2, XKR4, LYN, TGS1, TOX, HERC6, KIT, PLAG1, CHCHD7, NCAPG, and LCORL that are involved in multiple biological pathways underlying production and adaptation processes. Several candidate selection regions showed an excess of African taurine ancestral allele dosage. Our results provide further useful insight into potential selective sweeps in the genome of admixed cattle with possible adaptive and productive importance. Further investigations will be necessary to better characterize these candidate regions with respect to their functional significance to tropical adaptations for dairy cattle.

Microsatellite loci development and population genetics in Neotropical fish Curimata mivartii (Characiformes: Curimatidae)

The Curimatidae family plays an ecological role in the recycling and distribution of nutrients and constitutes a major food source for several commercially important fishes. Curimata mivartii, a member of this family, is considered a short-distance migratory species (≤100 km), categorized by the International Union for Conservation of Nature as a near threatened species, based on its declining population densities and habitat disturbance and fragmentation. Since population genetics and species-specific molecular tools remain unknown for all members of the Curimatidae family, this study developed a set of microsatellite loci and studied the population genetics of C. mivartii in the lower section of the Colombian Magdalena-Cauca basin. The results showed high levels of genetic diversity and evidence of gene flow even between locations separated over 350 km. This information provides a baseline for designing conservation and management programs for C.mivartii and constitutes the first study of population genetics in Curimatidae.

Detecting Adaptation with Genome-Scale Molecule Evolutionary Analysis: An Educational Primer for Use with "RNA Interference Pathways Display High Rates of Adaptive Protein Evolution in Multiple Invertebrates"

Hosts and pathogens impose coevolutionary pressure on each other as pathogens strive to establish themselves and hosts seek to suppress infection. RNA interference (RNAi) is a mechanism by which cells repress viruses and transposable elements, thereby serving as a form of immune defense. Previous studies have shown that antiviral RNAi genes evolve extraordinarily quickly in the fruit fly Drosophila melanogaster, suggesting that they may adaptively coevolve with viruses and transposable elements. An article by Palmer and colleagues extends this observation to nematodes and multiple insects. Their article can be combined with this Primer to demonstrate the use of comparative genomics and molecular evolutionary analyses in the measurement of natural selection.

Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal

Adaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. The results of genome-wide association analyses and tests for polygenic adaptations showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.

Assessing genetic architecture and signatures of selection of dual purpose Gir cattle populations using genomic information

Gir is one of the main cattle breeds raised in tropical South American countries. Strong artificial selection through its domestication resulted in increased genetic differentiation among the countries in recent years. Over the years, genomic studies in Gir have become more common. However, studies of population structure and signatures of selection in divergent Gir populations are scarce and need more attention to better understand genetic differentiation, gene flow, and genetic distance. Genotypes of 173 animals selected for growth traits and 273 animals selected for milk production were used in this study. Clear genetic differentiation between beef and dairy populations was observed. Different criteria led to genetic divergence and genetic differences in allele frequencies between the two populations. Gene segregation in each population was forced by artificial selection, promoting isolation, and increasing genetic variation between them. Results showed evidence of selective forces in different regions of the genome. A total of 282 genes were detected under selection in the test population based on the fixation index (Fst), integrated haplotype score (iHS), and cross-population extend haplotype homozygosity (XP-EHH) approaches. The QTL mapping identified 35 genes associated with reproduction, milk composition, growth, meat and carcass, health, or body conformation traits. The investigation of genes and pathways showed that quantitative traits associated to fertility, milk production, beef quality, and growth were involved in the process of differentiation of these populations. These results would support further investigations of population structure and differentiation in the Gir breed.

Adaptive Landscape of Protein Variation in Human Exomes

The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles experienced a reversal of fortune in the human lineage. We explored nonadaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Many nonadaptive hypotheses were tested, but failed to explain the data, which suggests that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This suggestion is supported by the fact that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of nonneutral candidate variants in the human proteome. We expect this collection to be enriched in beneficial variation. The EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.

An Evolutionary Genomic Perspective on the Breeding of Dwarf Chickens

The evolutionary history for dwarfism in chickens remains an enigma. Herein, we explore the evolution of the Serama, the smallest breed of chicken. Leveraging comparative population genomics, analyses identify several genes that are potentially associated with the growth and development of bones and muscles. These genes, and in particular both POU1F1 and IGF1, are under strong positive selection. Three allopatric dwarf bantams (Serama, Yuanbao, and Daweishan) with different breeding-histories, form distinct clusters and exhibit unique population structures. Parallel genetic mechanisms underlay their variation in body size. These findings provide insights into the multiple and complex pathways, depending on genomic variation, that chicken can take in response to aviculture selection for dwarfism.

Targeted resequencing reveals genomic signatures of barley domestication

Barley (Hordeum vulgare) is an established model to study domestication of the Fertile Crescent cereals. Recent molecular data suggested that domesticated barley genomes consist of the ancestral blocks descending from multiple wild barley populations. However, the relationship between the mosaic ancestry patterns and the process of domestication itself remained unclear. To address this knowledge gap, we identified candidate domestication genes using selection scans based on targeted resequencing of 433 wild and domesticated barley accessions. We conducted phylogenetic, population structure, and ancestry analyses to investigate the origin of the domesticated barley haplotypes separately at the neutral and candidate domestication loci. We discovered multiple selective sweeps that occurred on all barley chromosomes during domestication in the background of several ancestral wild populations. The ancestry analyses demonstrated that, although the ancestral blocks of the domesticated barley genomes were descended from all over the Fertile Crescent, the candidate domestication loci originated specifically in its eastern and western parts. These findings provided the first molecular evidence implicating multiple wild or protodomesticated lineages in the process of barley domestication initiated in the Levantine and Zagros clusters of the origin of agriculture.

Exome Sequencing Provides Evidence of Polygenic Adaptation to a Fat-Rich Animal Diet in Indigenous Siberian Populations

Siberia is one of the coldest environments on Earth and has great seasonal temperature variation. Long-term settlement in northern Siberia undoubtedly required biological adaptation to severe cold stress, dramatic variation in photoperiod, and limited food resources. In addition, recent archeological studies show that humans first occupied Siberia at least 45,000 years ago; yet our understanding of the demographic history of modern indigenous Siberians remains incomplete. In this study, we use whole-exome sequencing data from the Nganasans and Yakuts to infer the evolutionary history of these two indigenous Siberian populations. Recognizing the complexity of the adaptive process, we designed a model-based test to systematically search for signatures of polygenic selection. Our approach accounts for stochasticity in the demographic process and the hitchhiking effect of classic selective sweeps, as well as potential biases resulting from recombination rate and mutation rate heterogeneity. Our demographic inference shows that the Nganasans and Yakuts diverged ∼12,000-13,000 years ago from East-Asian ancestors in a process involving continuous gene flow. Our polygenic selection scan identifies seven candidate gene sets with Siberian-specific signals. Three of these gene sets are related to diet, especially to fat metabolism, consistent with the hypothesis of adaptation to a fat-rich animal diet. Additional testing rejects the effect of hitchhiking and favors a model in which selection yields small allele frequency changes at multiple unlinked genes.

Adaptation to infectious disease exposure in indigenous Southern African populations

Genetic analyses can provide information about human evolutionary history that cannot always be gleaned from other sources. We evaluated evidence of selective pressure due to introduced infectious diseases in the genomes of two indigenous southern African San groups-the ‡Khomani who had abundant contact with other people migrating into the region and the more isolated Ju|'hoansi. We used a dual approach to test for increased selection on immune genes compared with the rest of the genome in these groups. First, we calculated summary values of statistics that measure genomic signatures of adaptation to contrast selection signatures in immune genes and all genes. Second, we located regions of the genome with extreme values of three selection statistics and examined these regions for enrichment of immune genes. We found stronger and more abundant signals of selection in immune genes in the ‡Khomani than in the Ju|'hoansi. We confirm this finding within each population to avoid effects of different demographic histories of the two populations. We identified eight immune genes that have potentially been targets of strong selection in the ‡Khomani, whereas in the Ju|'hoansi, no immune genes were found in the genomic regions with the strongest signals of selection. We suggest that the more abundant signatures of selection at immune genes in the ‡Khomani could be explained by their more frequent contact with immigrant groups, which likely led to increased exposure and adaptation to introduced infectious diseases.