Multiple instances of ancient balancing selection shared between humans and chimpanzees

A probabilistic method for testing and estimating selection differences between populations

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection.

A novel locus of resistance to severe malaria in a region of ancient balancing selection

The high prevalence of sickle haemoglobin in Africa shows that malaria has been a major force for human evolutionary selection, but surprisingly few other polymorphisms have been proven to confer resistance to malaria in large epidemiological studies. To address this problem, we conducted a multi-centre genome-wide association study (GWAS) of life-threatening Plasmodium falciparum infection (severe malaria) in over 11,000 African children, with replication data in a further 14,000 individuals. Here we report a novel malaria resistance locus close to a cluster of genes encoding glycophorins that are receptors for erythrocyte invasion by P. falciparum. We identify a haplotype at this locus that provides 33% protection against severe malaria (odds ratio = 0.67, 95% confidence interval = 0.60-0.76, P value = 9.5 × 10(-11)) and is linked to polymorphisms that have previously been shown to have features of ancient balancing selection, on the basis of haplotype sharing between humans and chimpanzees. Taken together with previous observations on the malaria-protective role of blood group O, these data reveal that two of the strongest GWAS signals for severe malaria lie in or close to genes encoding the glycosylated surface coat of the erythrocyte cell membrane, both within regions of the genome where it appears that evolution has maintained diversity for millions of years. These findings provide new insights into the host-parasite interactions that are critical in determining the outcome of malaria infection.

USP38, FREM3, SDC1, DDC, and LOC727982 Gene Polymorphisms and Differential Susceptibility to Severe Malaria in Tanzania

Populations exposed to Plasmodium falciparum infection develop genetic mechanisms of protection against severe malarial disease. Despite decades of genetic epidemiological research, the sickle cell trait (HbAS) sickle cell polymorphism, ABO blood group, and other hemoglobinopathies remain the few major determinants in severe malaria to be replicated across different African populations and study designs. Within a case-control study in a region of high transmission in Tanzania (n = 983), we investigated the role of 40 new loci identified in recent genome-wide studies. In 32 loci passing quality control procedures, we found polymorphisms in USP38, FREM3, SDC1, DDC, and LOC727982 genes to be putatively associated with differential susceptibility to severe malaria. Established candidates explained 7.4% of variation in severe malaria risk (HbAS polymorphism, 6.3%; α-thalassemia, 0.3%; ABO group, 0.3%; and glucose-6-phosphate dehydrogenase deficiency, 0.5%) and the new polymorphisms, another 4.3%. The regions encompassing the loci identified are promising targets for the design of future treatment and control interventions.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach.

Trans-species polymorphism in humans and the great apes is generally maintained by balancing selection that modulates the host immune response

Known examples of ancient identical-by-descent genetic variants being shared between evolutionarily related species, known as trans-species polymorphisms (TSPs), result from counterbalancing selective forces acting on target genes to confer resistance against infectious agents. To date, putative TSPs between humans and other primate species have been identified for the highly polymorphic major histocompatibility complex (MHC), the histo-blood ABO group, two antiviral genes (ZC3HAV1 and TRIM5), an autoimmunity-related gene LAD1 and several non-coding genomic segments with a putative regulatory role. Although the number of well-characterized TSPs under long-term balancing selection is still very small, these examples are connected by a common thread, namely that they involve genes with key roles in the immune system and, in heterozygosity, appear to confer genetic resistance to pathogens. Here, we review known cases of shared polymorphism that appear to be under long-term balancing selection in humans and the great apes. Although the specific selective agent(s) responsible are still unknown, these TSPs may nevertheless be seen as constituting important adaptive events that have occurred during the evolution of the primate immune system.

Immunology in wild nonmodel rodents: an ecological context for studies of health and disease

Transcriptomic methods are set to revolutionize the study of the immune system in naturally occurring nonmodel organisms. With this in mind, the present article focuses on ways in which the use of 'nonmodel' rodents (not the familiar laboratory species) can advance studies into the classical, but ever relevant, epidemiologic triad of immune defence, infectious disease and environment. For example, naturally occurring rodents are an interesting system in which to study the environmental stimuli that drive the development and homeostasis of the immune system and, by extension, to identify where these stimuli are altered in anthropogenic environments leading to the formation of immunopathological phenotypes. Measurement of immune expression may help define individual heterogeneity in infectious disease susceptibility and transmission and facilitate our understanding of infection dynamics and risk in the natural environment; furthermore, it may provide a means of surveillance that can filter individuals carrying previously unknown acute infections of potential ecological or zoonotic importance. Finally, the study of immunology in wild animals may reveal interactions within the immune system and between immunity and other organismal traits that are not observable under restricted laboratory conditions. Potentiating much of this is the possibility of combining gene expression profiles with analytical tools derived from ecology and systems biology to reverse engineer interaction networks between immune responses, other organismal traits and the environment (including symbiont exposures), revealing regulatory architecture. Such holistic studies promise to link ecology, epidemiology and immunology in natural systems in a unified approach that can illuminate important problems relevant to human health and animal welfare and production.

Contrasted patterns of variation and evolutionary convergence at the antiviral OAS1 gene in old world primates

The oligoadenylate synthetase 1 (OAS1) enzyme acts as an innate sensor of viral infection and plays a major role in the defense against a wide diversity of viruses. Polymorphisms at OAS1 have been shown to correlate with differential susceptibility to several infections of great public health significance, including hepatitis C virus, SARS coronavirus, and West Nile virus. Population genetics analyses in hominoids have revealed interesting evolutionary patterns. In Central African chimpanzee, OAS1 has evolved under long-term balancing selection, resulting in the persistence of polymorphisms since the origin of hominoids, whereas human populations have acquired and retained OAS1 alleles from Neanderthal and Denisovan origin. We decided to further investigate the evolution of OAS1 in primates by characterizing intra-specific variation in four species commonly used as models in infectious disease research: the rhesus macaque, the cynomolgus macaque, the olive baboon, and the Guinea baboon. In baboons, OAS1 harbors a very low level of variation. In contrast, OAS1 in macaques exhibits a level of polymorphism far greater than the genomic average, which is consistent with the action of balancing selection. The region of the enzyme that directly interacts with viral RNA, the RNA-binding domain, contains a number of polymorphisms likely to affect the RNA-binding affinity of OAS1. This strongly suggests that pathogen-driven balancing selection acting on the RNA-binding domain of OAS1 is maintaining variation at this locus. Interestingly, we found that a number of polymorphisms involved in RNA-binding were shared between macaques and chimpanzees. This represents an unusual case of convergent polymorphism.

Aberrant Time to Most Recent Common Ancestor as a Signature of Natural Selection

Natural selection inference methods often target one mode of selection of a particular age and strength. However, detecting multiple modes simultaneously, or with atypical representations, would be advantageous for understanding a population's evolutionary history. We have developed an anomaly detection algorithm using distributions of pairwise time to most recent common ancestor (TMRCA) to simultaneously detect multiple modes of natural selection in whole-genome sequences. As natural selection distorts local genealogies in distinct ways, the method uses pairwise TMRCA distributions, which approximate genealogies at a nonrecombining locus, to detect distortions without targeting a specific mode of selection. We evaluate the performance of our method, TSel, for both positive and balancing selection over different time-scales and selection strengths and compare TSel's performance with that of other methods. We then apply TSel to the Complete Genomics diversity panel, a set of human whole-genome sequences, and recover loci previously inferred to be under positive or balancing selection.

Trans-Species Polymorphism in Immune Genes: General Pattern or MHC-Restricted Phenomenon?

Immunity exhibits extraordinarily high levels of variation. Evolution of the immune system in response to host-pathogen interactions in particular ecological contexts appears to be frequently associated with diversifying selection increasing the genetic variability. Many studies have documented that immunologically relevant polymorphism observed today may be tens of millions years old and may predate the emergence of present species. This pattern can be explained by the concept of trans-species polymorphism (TSP) predicting the maintenance and sharing of favourable functionally important alleles of immune-related genes between species due to ongoing balancing selection. Despite the generality of this concept explaining the long-lasting adaptive variation inherited from ancestors, current research in TSP has vastly focused only on major histocompatibility complex (MHC). In this review we summarise the evidence available on TSP in human and animal immune genes to reveal that TSP is not a MHC-specific evolutionary pattern. Further research should clearly pay more attention to the investigation of TSP in innate immune genes and especially pattern recognition receptors which are promising candidates for this type of evolution. More effort should also be made to distinguish TSP from convergent evolution and adaptive introgression. Identification of balanced TSP variants may represent an accurate approach in evolutionary medicine to recognise disease-resistance alleles.

Trans-species polymorphism at antimicrobial innate immunity cathelicidin genes of Atlantic cod and related species

Natural selection, the most important force in evolution, comes in three forms. Negative purifying selection removes deleterious variation and maintains adaptations. Positive directional selection fixes beneficial variants, producing new adaptations. Balancing selection maintains variation in a population. Important mechanisms of balancing selection include heterozygote advantage, frequency-dependent advantage of rarity, and local and fluctuating episodic selection. A rare pathogen gains an advantage because host defenses are predominantly effective against prevalent types. Similarly, a rare immune variant gives its host an advantage because the prevalent pathogens cannot escape the host's apostatic defense. Due to the stochastic nature of evolution, neutral variation may accumulate on genealogical branches, but trans-species polymorphisms are rare under neutrality and are strong evidence for balancing selection. Balanced polymorphism maintains diversity at the major histocompatibility complex (MHC) in vertebrates. The Atlantic cod is missing genes for both MHC-II and CD4, vital parts of the adaptive immune system. Nevertheless, cod are healthy in their ecological niche, maintaining large populations that support major commercial fisheries. Innate immunity is of interest from an evolutionary perspective, particularly in taxa lacking adaptive immunity. Here, we analyze extensive amino acid and nucleotide polymorphisms of the cathelicidin gene family in Atlantic cod and closely related taxa. There are three major clusters, Cath1, Cath2, and Cath3, that we consider to be paralogous genes. There is extensive nucleotide and amino acid allelic variation between and within clusters. The major feature of the results is that the variation clusters by alleles and not by species in phylogenetic trees and discriminant analysis of principal components. Variation within the three groups shows trans-species polymorphism that is older than speciation and that is suggestive of balancing selection maintaining the variation. Using Bayesian and likelihood methods positive and negative selection is evident at sites in the conserved part of the genes and, to a larger extent, in the active part which also shows episodic diversifying selection, further supporting the argument for balancing selection.

Long-Term Balancing Selection in LAD1 Maintains a Missense Trans-Species Polymorphism in Humans, Chimpanzees, and Bonobos

Balancing selection maintains advantageous genetic and phenotypic diversity in populations. When selection acts for long evolutionary periods selected polymorphisms may survive species splits and segregate in present-day populations of different species. Here, we investigate the role of long-term balancing selection in the evolution of protein-coding sequences in the Homo-Pan clade. We sequenced the exome of 20 humans, 20 chimpanzees, and 20 bonobos and detected eight coding trans-species polymorphisms (trSNPs) that are shared among the three species and have segregated for approximately 14 My of independent evolution. Although the majority of these trSNPs were found in three genes of the major histocompatibility locus cluster, we also uncovered one coding trSNP (rs12088790) in the gene LAD1. All these trSNPs show clustering of sequences by allele rather than by species and also exhibit other signatures of long-term balancing selection, such as segregating at intermediate frequency and lying in a locus with high genetic diversity. Here, we focus on the trSNP in LAD1, a gene that encodes for Ladinin-1, a collagenous anchoring filament protein of basement membrane that is responsible for maintaining cohesion at the dermal-epidermal junction; the gene is also an autoantigen responsible for linear IgA disease. This trSNP results in a missense change (Leucine257Proline) and, besides altering the protein sequence, is associated with changes in gene expression of LAD1.

Emergence of long-term balanced polymorphism under cyclic selection of spatially variable magnitude

A fundamental question in evolutionary biology is what promotes genetic variation at nonneutral loci, a major precursor to adaptation in changing environments. In particular, balanced polymorphism under realistic evolutionary models of temporally varying environments in finite natural populations remains to be demonstrated. Here, we propose a novel mechanism of balancing selection under temporally varying fitnesses. Using forward-in-time computer simulations and mathematical analysis, we show that cyclic selection that spatially varies in magnitude, such as along an environmental gradient, can lead to elevated levels of nonneutral genetic polymorphism in finite populations. Balanced polymorphism is more likely with an increase in gene flow, magnitude and period of fitness oscillations, and spatial heterogeneity. This polymorphism-promoting effect is robust to small systematic fitness differences between competing alleles or to random environmental perturbation. Furthermore, we demonstrate analytically that protected polymorphism arises as spatially heterogeneous cyclic fitness oscillations generate a type of storage effect that leads to negative frequency dependent selection. Our findings imply that spatially variable cyclic environments can promote elevated levels of nonneutral genetic variation in natural populations.

Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.

Impact of past climatic changes and resource availability on the population demography of three food-specialist bees

Past climate change is known to have strongly impacted current patterns of genetic variation of animals and plants in Europe. However, ecological factors also have the potential to influence demographic history and thus patterns of genetic variation. In this study, we investigated the impact of past climate, and also the potential impact of host plant species abundance, on intraspecific genetic variation in three codistributed and related specialized solitary bees of the genus Melitta with very similar life history traits and dispersal capacities. We sequenced five independent loci in samples collected from the three species. Our analyses revealed that the species associated with the most abundant host plant species (Melitta leporina) displays unusually high genetic variation, to an extent that is seldom reported in phylogeographic studies of animals and plants. This suggests a potential role of food resource abundance in determining current patterns of genetic variation in specialized herbivorous insects. Patterns of genetic variation in the two other species indicated lower overall levels of diversity, and that M. nigricans could have experienced a recent range expansion. Ecological niche modelling of the three Melitta species and their main host plant species suggested a strong reduction in range size during the last glacial maximum. Comparing observed sequence data with data simulated using spatially explicit models of coalescence suggests that M. leporina recovered a range and population size close to their current levels at the end of the last glaciation, and confirms recent range expansion as the most likely scenario for M. nigricans. Overall, this study illustrates that both demographic history and ecological factors may have contributed to shape current phylogeographic patterns.

Ancient and recent selective pressures shaped genetic diversity at AIM2-like nucleic acid sensors

AIM2-like receptors (ALRs) are a family of nucleic acid sensors essential for innate immune responses against viruses and bacteria. We performed an evolutionary analysis of ALR genes (MNDA, PYHIN1, IFI16, and AIM2) by analyzing inter- and intraspecies diversity. Maximum-likelihood analyses indicated that IFI16 and AIM2 evolved adaptively in primates, with branch-specific selection at the catarrhini lineage for IFI16. Application of a population genetics–phylogenetics approach also allowed identification of positive selection events in the human lineage. Positive selection in primates targeted sites located at the DNA-binding interface in both IFI16 and AIM2. In IFI16, several sites positively selected in primates and in the human lineage were located in the PYD domain, which is involved in protein–protein interaction and is bound by a human cytomegalovirus immune evasion protein. Finally, positive selection was found to target nuclear localization signals in IFI16 and the spacer region separating the two HIN domains. Population genetic analysis in humans revealed that an IFI16 genic region has been a target of long-standing balancing selection, possibly acting on two nonsynonymous polymorphisms located in the spacer region. Data herein indicate that ALRs have been repeatedly targeted by natural selection. The balancing selection region in IFI16 carries a variant with opposite risk effect for distinct autoimmune diseases, suggesting antagonistic pleiotropy. We propose that the underlying scenario is the result of an ancestral and still ongoing host–pathogen arms race and that the maintenance of susceptibility alleles for autoimmune diseases at IFI16 represents an evolutionary trade-off.

African glucose-6-phosphate dehydrogenase alleles associated with protection from severe malaria in heterozygous females in Tanzania

X-linked Glucose-6-phosphate dehydrogenase (G6PD) A- deficiency is prevalent in sub-Saharan Africa populations, and has been associated with protection from severe malaria. Whether females and/or males are protected by G6PD deficiency is uncertain, due in part to G6PD and malaria phenotypic complexity and misclassification. Almost all large association studies have genotyped a limited number of G6PD SNPs (e.g. G6PD202 / G6PD376), and this approach has been too blunt to capture the complete epidemiological picture. Here we have identified 68 G6PD polymorphisms and analysed 29 of these (i.e. those with a minor allele frequency greater than 1%) in 983 severe malaria cases and controls in Tanzania. We establish, across a number of SNPs including G6PD376, that only female heterozygotes are protected from severe malaria. Haplotype analysis reveals the G6PD locus to be under balancing selection, suggesting a mechanism of protection relying on alleles at modest frequency and avoiding fixation, where protection provided by G6PD deficiency against severe malaria is offset by increased risk of life-threatening complications. Our study also demonstrates that the much-needed large-scale studies of severe malaria and G6PD enzymatic function across African populations require the identification and analysis of the full repertoire of G6PD genetic markers.

Glucose-6-phosphate dehydrogenase (G6PD) is an essential enzyme that protects red blood cells from oxidative damage. Numerous genetic variants of G6PD, residing in the X chromosome, are found among African populations: mutations causing A- deficiency can lead to serious clinical outcomes (including hemolytic anemia) but also confer protection against severe malaria. Epidemiological studies have used some of the genetic markers that cause A- deficiency to establish who is protected from severe malaria, with differing results. Whether females, with one or two copies of mutant genes, males with one copy, or both genders are protected is uncertain. This uncertainty is due to G6PD and malaria phenotypic complexity and misclassification, and to genetic differences between populations and the limited numbers of genetic markers (usually 2) considered. In this study we analysed more than 30 G6PD genetic markers in 506 Tanzanian children with severe malaria and 477 without malaria. We found that only females with one normal and one mutant copy of the gene (heterozygotes) were protected from severe malaria. Further, we established that the G6PD gene is under evolutionary pressure with the likely mechanism being selection by malaria. Our work demonstrates that studies of severe malaria and G6PD enzymatic function across African populations require, in addition to complete and accurate G6PD phenotypic classification, the identification and analysis of the full repertoire of G6PD genetic markers.

Footprints of ancient-balanced polymorphisms in genetic variation data from closely related species

When long-lasting, balancing selection can lead to “trans-species” polymorphisms that are shared by two or more species identical by descent. In such cases, the gene genealogy at the selected site clusters by allele instead of by species, and nearby neutral sites also have unusual genealogies because of linkage. While this scenario is expected to leave discernible footprints in genetic variation data, the specific patterns remain poorly characterized. Motivated by recent findings in primates, we focus on the case of a biallelic polymorphism under ancient balancing selection and derive approximations for summaries of the polymorphism data from two species. Specifically, we characterize the length of the segment that carries most of the footprints, the expected number of shared neutral single nucleotide polymorphisms (SNPs), and the patterns of allelic associations among them. We confirm the accuracy of our approximations by coalescent simulations. We further show that for humans and chimpanzees—more generally, for pairs of species with low genetic diversity levels—these patterns are highly unlikely to be generated by neutral recurrent mutations. We discuss the implications for the design and interpretation of genome scans for ancient balanced polymorphisms in primates and other taxa.

Causes of natural variation in fitness: evidence from studies of Drosophila populations

DNA sequencing has revealed high levels of variability within most species. Statistical methods based on population genetics theory have been applied to the resulting data and suggest that most mutations affecting functionally important sequences are deleterious but subject to very weak selection. Quantitative genetic studies have provided information on the extent of genetic variation within populations in traits related to fitness and the rate at which variability in these traits arises by mutation. This paper attempts to combine the available information from applications of the two approaches to populations of the fruitfly Drosophila in order to estimate some important parameters of genetic variation, using a simple population genetics model of mutational effects on fitness components. Analyses based on this model suggest the existence of a class of mutations with much larger fitness effects than those inferred from sequence variability and that contribute most of the standing variation in fitness within a population caused by the input of mildly deleterious mutations. However, deleterious mutations explain only part of this standing variation, and other processes such as balancing selection appear to make a large contribution to genetic variation in fitness components in Drosophila.

Population genetics of Anopheles coluzzii immune pathways and genes

Natural selection is expected to drive adaptive evolution in genes involved in host–pathogen interactions. In this study, we use molecular population genetic analyses to understand how natural selection operates on the immune system of Anopheles coluzzii (formerly A. gambiae “M form”). We analyzed patterns of intraspecific and interspecific genetic variation in 20 immune-related genes and 17 nonimmune genes from a wild population of A. coluzzii and asked if patterns of genetic variation in the immune genes are consistent with pathogen-driven selection shaping the evolution of defense. We found evidence of a balanced polymorphism in CTLMA2, which encodes a C-type lectin involved in regulation of the melanization response. The two CTLMA2 haplotypes, which are distinguished by fixed amino acid differences near the predicted peptide cleavage site, are also segregating in the sister species A. gambiae (“S form”) and A. arabiensis. Comparison of the two haplotypes between species indicates that they were not shared among the species through introgression, but rather that they arose before the species divergence and have been adaptively maintained as a balanced polymorphism in all three species. We additionally found that STAT-B, a retroduplicate of STAT-A, shows strong evidence of adaptive evolution that is consistent with neofunctionalization after duplication. In contrast to the striking patterns of adaptive evolution observed in these Anopheles-specific immune genes, we found no evidence of adaptive evolution in the Toll and Imd innate immune pathways that are orthologously conserved throughout insects. Genes encoding the Imd pathway exhibit high rates of amino acid divergence between Anopheles species but also display elevated amino acid diversity that is consistent with relaxed purifying selection. These results indicate that adaptive coevolution between A. coluzzii and its pathogens is more likely to involve novel or lineage-specific molecular mechanisms than the canonical humoral immune pathways.

A neutrality test for detecting selection on DNA methylation using single methylation polymorphism frequency spectrum

Inheritable epigenetic mutations (epimutations) can contribute to transmittable phenotypic variation. Thus, epimutations can be subject to natural selection and impact the fitness and evolution of organisms. Based on the framework of the modified Tajima’s D test for DNA mutations, we developed a neutrality test with the statistic “D^m” to detect selection forces on DNA methylation mutations using single methylation polymorphisms. With computer simulation and empirical data analysis, we compared the D^m test with the original and modified Tajima’s D tests and demonstrated that the D^m test is suitable for detecting selection on epimutations and outperforms original/modified Tajima’s D tests. Due to the higher resetting rate of epimutations, the interpretation of D^m on epimutations and Tajima’s D test on DNA mutations could be different in inferring natural selection. Analyses using simulated and empirical genome-wide polymorphism data suggested that genes under genetic and epigenetic selections behaved differently. We applied the D^m test to recently originated Arabidopsis and human genes, and showed that newly evolved genes contain higher level of rare epialleles, suggesting that epimutation may play a role in origination and evolution of genes and genomes. Overall, we demonstrate the utility of the D^m test to detect whether the loci are under selection regarding DNA methylation. Our analytical metrics and methodology could contribute to our understanding of evolutionary processes of genes and genomes in the field of epigenetics. The Perl script for the “D^m” test is available at http://fanlab.wayne.edu/ (last accessed December 18, 2014).

Inference of gorilla demographic and selective history from whole-genome sequence data

Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection.

Interspecific introgressive origin of genomic diversity in the house mouse

We report on a genome-wide scan for introgression between the house mouse (Mus musculus domesticus) and the Algerian mouse (Mus spretus), using samples from the ranges of sympatry and allopatry in Africa and Europe. Our analysis reveals wide variability in introgression signatures along the genomes, as well as across the samples. We find that fewer than half of the autosomes in each genome harbor all detectable introgression, whereas the X chromosome has none. Further, European mice carry more M. spretus alleles than the sympatric African ones. Using the length distribution and sharing patterns of introgressed genomic tracts across the samples, we infer, first, that at least three distinct hybridization events involving M. spretus have occurred, one of which is ancient, and the other two are recent (one presumably due to warfarin rodenticide selection). Second, several of the inferred introgressed tracts contain genes that are likely to confer adaptive advantage. Third, introgressed tracts might contain driver genes that determine the evolutionary fate of those tracts. Further, functional analysis revealed introgressed genes that are essential to fitness, including the Vkorc1 gene, which is implicated in rodenticide resistance, and olfactory receptor genes. Our findings highlight the extent and role of introgression in nature and call for careful analysis and interpretation of house mouse data in evolutionary and genetic studies.

Sexually antagonistic polymorphism in simultaneous hermaphrodites

In hermaphrodites, pleiotropic genetic trade-offs between female and male reproductive functions can lead to sexually antagonistic (SA) selection, where individual alleles have conflicting fitness effects on each sex function. Although an extensive theory of SA selection exists for dioecious species, these results have not been generalized to hermaphrodites. We develop population genetic models of SA selection in simultaneous hermaphrodites, and evaluate effects of dominance, selection on each sex function, self-fertilization, and population size on the maintenance of polymorphism. Under obligate outcrossing, hermaphrodite model predictions converge exactly with those of dioecious populations. Self-fertilization in hermaphrodites generates three points of divergence with dioecious theory. First, opportunities for stable polymorphism decline sharply and become less sensitive to dominance with increased selfing. Second, selfing introduces an asymmetry in the relative importance of selection through male versus female reproductive functions, expands the parameter space favorable for the evolutionary invasion of female-beneficial alleles, and restricts invasion criteria for male-beneficial alleles. Finally, contrary to models of unconditionally beneficial alleles, selfing decreases genetic hitchhiking effects of invading SA alleles, and should therefore decrease these population genetic signals of SA polymorphisms. We discuss implications of SA selection in hermaphrodites, including its potential role in the evolution of "selfing syndromes."

Genomic evidence of rapid and stable adaptive oscillations over seasonal time scales in Drosophila

In many species, genomic data have revealed pervasive adaptive evolution indicated by the fixation of beneficial alleles. However, when selection pressures are highly variable along a species' range or through time adaptive alleles may persist at intermediate frequencies for long periods. So called “balanced polymorphisms” have long been understood to be an important component of standing genetic variation, yet direct evidence of the strength of balancing selection and the stability and prevalence of balanced polymorphisms has remained elusive. We hypothesized that environmental fluctuations among seasons in a North American orchard would impose temporally variable selection on Drosophila melanogaster that would drive repeatable adaptive oscillations at balanced polymorphisms. We identified hundreds of polymorphisms whose frequency oscillates among seasons and argue that these loci are subject to strong, temporally variable selection. We show that these polymorphisms respond to acute and persistent changes in climate and are associated in predictable ways with seasonally variable phenotypes. In addition, our results suggest that adaptively oscillating polymorphisms are likely millions of years old, with some possibly predating the divergence between D. melanogaster and D. simulans. Taken together, our results are consistent with a model of balancing selection wherein rapid temporal fluctuations in climate over generational time promotes adaptive genetic diversity at loci underlying polygenic variation in fitness related phenotypes.

Herein, we investigate the genomic basis of rapid adaptive evolution in response to seasonal fluctuations in the environment. We identify hundreds of polymorphisms (seasonal SNPs) that undergo dramatic shifts in allele frequency – on average between 40 and 60% – and oscillate between seasons repeatedly over multiple years, likely inducing high levels of genome-wide genetic differentiation. We provide evidence that seasonal SNPs are functional, being both sensitive to an acute frost event and associated with two stress tolerance traits. Finally, we show that some seasonal SNPs are possibly ancient balanced polymorphisms. Taken together, our results suggest that environmental heterogeneity can promote the long-term persistence of functional polymorphisms within populations that fuels fast directional adaptive response at any one time.

Fast evolution from precast bricks: genomics of young freshwater populations of threespine stickleback Gasterosteus aculeatus

Adaptation is driven by natural selection; however, many adaptations are caused by weak selection acting over large timescales, complicating its study. Therefore, it is rarely possible to study selection comprehensively in natural environments. The threespine stickleback (Gasterosteus aculeatus) is a well-studied model organism with a short generation time, small genome size, and many genetic and genomic tools available. Within this originally marine species, populations have recurrently adapted to freshwater all over its range. This evolution involved extensive parallelism: pre-existing alleles that adapt sticklebacks to freshwater habitats, but are also present at low frequencies in marine populations, have been recruited repeatedly. While a number of genomic regions responsible for this adaptation have been identified, the details of selection remain poorly understood. Using whole-genome resequencing, we compare pooled genomic samples from marine and freshwater populations of the White Sea basin, and identify 19 short genomic regions that are highly divergent between them, including three known inversions. 17 of these regions overlap protein-coding genes, including a number of genes with predicted functions that are relevant for adaptation to the freshwater environment. We then analyze four additional independently derived young freshwater populations of known ages, two natural and two artificially established, and use the observed shifts of allelic frequencies to estimate the strength of positive selection. Adaptation turns out to be quite rapid, indicating strong selection acting simultaneously at multiple regions of the genome, with selection coefficients of up to 0.27. High divergence between marine and freshwater genotypes, lack of reduction in polymorphism in regions responsible for adaptation, and high frequencies of freshwater alleles observed even in young freshwater populations are all consistent with rapid assembly of G. aculeatus freshwater genotypes from pre-existing genomic regions of adaptive variation, with strong selection that favors this assembly acting simultaneously at multiple loci.

Adaptation to novel environments is a keystone of evolution. There is only a handful of natural and experimental systems in which the process of adaptation has been studied in detail, and each studied system brings its own surprises with regard to the number of loci involved, dynamics of adaptation, extent of interactions between loci and of parallelism between different adapting populations. The threespine stickleback is an excellent model organism for evolutionary studies. Marine-derived freshwater populations of this species have consistently acquired a specific set of morphological, physiological and behavioral traits allowing them to reside in freshwater for their whole lifespan. Previous studies identified several genomic regions responsible for this adaptation. Here, using whole-genome sequencing, we compare the allele frequencies at such regions in four derived freshwater populations of known ages: two natural, and two artificially established in 1978. Knowledge of population ages allows us to infer the strength of selection that acted at these loci. Adaptation of threespine stickleback to freshwater is typically fast, and is driven by strong selection favoring pre-existing alleles that are likely present in the ancestral marine population at low frequencies; however, some of the adaptation may also be due to young population-specific alleles.

Missing heritability of common diseases and treatments outside the protein-coding exome

Genetic factors strongly influence risk of common human diseases and treatment outcomes but the causative variants remain largely unknown; this gap has been called the 'missing heritability'. We propose several hypotheses that in combination have the potential to narrow the gap. First, given a multi-stage path from wellness to disease, we propose that common variants under positive evolutionary selection represent normal variation and gate the transition between wellness and an 'off-well' state, revealing adaptations to changing environmental conditions. In contrast, genome-wide association studies (GWAS) focus on deleterious variants conveying disease risk, accelerating the path from off-well to illness and finally specific diseases, while common 'normal' variants remain hidden in the noise. Second, epistasis (dynamic gene-gene interactions) likely assumes a central role in adaptations and evolution; yet, GWAS analyses currently are poorly designed to reveal epistasis. As gene regulation is germane to adaptation, we propose that epistasis among common normal regulatory variants, or between common variants and less frequent deleterious variants, can have strong protective or deleterious phenotypic effects. These gene-gene interactions can be highly sensitive to environmental stimuli and could account for large differences in drug response between individuals. Residing largely outside the protein-coding exome, common regulatory variants affect either transcription of coding and non-coding RNAs (regulatory SNPs, or rSNPs) or RNA functions and processing (structural RNA SNPs, or srSNPs). Third, with the vast majority of causative variants yet to be discovered, GWAS rely on surrogate markers, a confounding factor aggravated by the presence of more than one causative variant per gene and by epistasis. We propose that the confluence of these factors may be responsible to large extent for the observed heritability gap.

Lineage sorting in apes

Recombination allows different parts of the genome to have different genealogical histories. When a species splits in two, allelic lineages sort into the two descendant species, and this lineage sorting varies along the genome. If speciation events are close in time, the lineage sorting process may be incomplete at the second speciation event and lead to gene genealogies that do not match the species phylogeny. We review different recent approaches to model lineage sorting along the genome and show how it is possible to learn about population sizes, natural selection, and recombination rates in ancestral species from application of these models to genome alignments of great ape species.

New frontiers in the study of human cultural and genetic evolution

In this review, we discuss the dynamic linkages between culture and the genetic evolution of the human species. We begin by briefly describing the framework of gene-culture coevolutionary (or dual-inheritance) models for human evolutionary change. Until recently, the literature on gene-culture coevolution was composed primarily of mathematical models and formalized theory describing the complex dynamics underlying human behavior, adaptation, and technological evolution, but had little empirical support concerning genetics. The rapid progress in the fields of molecular genetics and genomics, however, is now providing the kinds of data needed to produce rich empirical support for gene-culture coevolutionary models. We briefly outline how theoretical and methodological progress in genome sciences has provided ways for the strength of selection on genes to be evaluated, and then outline how evidence of selection on several key genes can be directly linked to human cultural practices. We then describe some exciting new directions in the empirical study of gene-culture coevolution, and conclude with a discussion of the role of gene-culture evolutionary models in the future integration of medical, biological, and social sciences.

Advantageous diversity maintained by balancing selection in humans

Most human polymorphisms are neutral or slightly deleterious, but some genetic variation is advantageous and maintained in populations by balancing selection. Considered a rarity and overlooked for years, balanced polymorphisms have recently received renewed attention with several lines of evidence showing their relevance in human evolution. From theoretical work on its role in adaptation to empirical studies that identify its targets, recent developments have showed that balancing selection is more prevalent than previously thought. Here we review these developments and discuss their implications in our understanding of the influence of balancing selection in human evolution. We also review existing evidence on the biological functions that benefit most from advantageous diversity, and the functional consequences of these variants. Overall, we argue that balancing selection must be considered an important selective force in human evolution.

A model-based approach for identifying signatures of ancient balancing selection in genetic data

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

In the past, balancing selection was a topic of great theoretical interest that received much attention. However, there has been little focus toward developing methods to identify regions of the genome that are under balancing selection. In this article, we present the first set of likelihood-based methods that explicitly model the spatial distribution of polymorphism expected near a site under long-term balancing selection. Simulation results show that our methods outperform commonly-used summary statistics for identifying regions under balancing selection. Finally, we performed a scan for balancing selection in Africans and Europeans using our new methods and identified a gene called FANK1 as our top candidate outside the HLA region. We hypothesize that the maintenance of polymorphism at FANK1 is the result of segregation distortion.

Detecting recent positive selection with high accuracy and reliability by conditional coalescent tree

Studies of natural selection, followed by functional validation, are shedding light on understanding of genetic mechanisms underlying human evolution and adaptation. Classic methods for detecting selection, such as the integrated haplotype score (iHS) and Fay and Wu's H statistic, are useful for candidate gene searching underlying positive selection. These methods, however, have limited capability to localize causal variants in selection target regions. In this study, we developed a novel method based on conditional coalescent tree to detect recent positive selection by counting unbalanced mutations on coalescent gene genealogies. Extensive simulation studies revealed that our method is more robust than many other approaches against biases due to various demographic effects, including population bottleneck, expansion, or stratification, while not sacrificing its power. Furthermore, our method demonstrated its superiority in localizing causal variants from massive linked genetic variants. The rate of successful localization was about 20-40% higher than that of other state-of-the-art methods on simulated data sets. On empirical data, validated functional causal variants of four well-known positive selected genes were all successfully localized by our method, such as ADH1B, MCM6, APOL1, and HBB. Finally, the computational efficiency of this new method was much higher than that of iHS implementations, that is, 24-66 times faster than the REHH package, and more than 10,000 times faster than the original iHS implementation. These magnitudes make our method suitable for applying on large sequencing data sets. Software can be downloaded from https://github.com/wavefancy/scct.

Error-prone polymerase activity causes multinucleotide mutations in humans

About 2% of human genetic polymorphisms have been hypothesized to arise via multinucleotide mutations (MNMs), complex events that generate SNPs at multiple sites in a single generation. MNMs have the potential to accelerate the pace at which single genes evolve and to confound studies of demography and selection that assume all SNPs arise independently. In this paper, we examine clustered mutations that are segregating in a set of 1092 human genomes, demonstrating that the signature of MNM becomes enriched as large numbers of individuals are sampled. We estimate the percentage of linked SNP pairs that were generated by simultaneous mutation as a function of the distance between affected sites and show that MNMs exhibit a high percentage of transversions relative to transitions, findings that are reproducible in data from multiple sequencing platforms and cannot be attributed to sequencing error. Among tandem mutations that occur simultaneously at adjacent sites, we find an especially skewed distribution of ancestral and derived alleles, with GC → AA, GA → TT, and their reverse complements making up 27% of the total. These mutations have been previously shown to dominate the spectrum of the error-prone polymerase Pol ζ, suggesting that low-fidelity DNA replication by Pol ζ is at least partly responsible for the MNMs that are segregating in the human population. We develop statistical estimates of MNM prevalence that can be used to correct phylogenetic and population genetic inferences for the presence of complex mutations.

Great ape genomics

The great ape families are the species most closely related to our own, comprising chimpanzees, bonobos, gorillas, and orangutans. They live exclusively in tropical rainforests in Central Africa and the islands of Southeast Asia. Due to their close evolutionary relationship with humans, great apes share many cognitive, physiological, and morphological similarities with humans. The members of the great ape family make obvious models to facilitate the further understanding about humans' biology and history. This review will discuss how the recent addition of genome-wide data from great apes has furthered humans' understanding of these species and humanity, especially in the realm of evolutionary genetics.

Nonhuman primate models in the genomic era: a paradigm shift

Because of their strong similarities to humans across physiologic, developmental, behavioral, immunologic, and genetic levels, nonhuman primates are essential models for a wide spectrum of biomedical research. But unlike other animal models, nonhuman primates possess substantial outbred genetic variation, reducing statistical power and potentially confounding interpretation of results in research studies. Although unknown genetic variation is a hindrance in studies that allocate animals randomly, taking genetic variation into account in study design affords an opportunity to transform the way that nonhuman primates are used in biomedical research. New understandings of how the function of individual genes in rhesus macaques mimics that seen in humans are greatly advancing the rhesus macaques utility as research models, but epistatic interaction, epigenetic regulatory mechanisms, and the intricacies of gene networks limit model development. We are now entering a new era of nonhuman primate research, brought on by the proliferation and rapid expansion of genomic data. Already the cost of a rhesus macaque genome is dwarfed by its purchase and husbandry costs, and complete genomic datasets will inevitably encompass each rhesus macaque used in biomedical research. Advancing this outcome is paramount. It represents an opportunity to transform the way animals are assigned and used in biomedical research and to develop new models of human disease. The genetic and genomic revolution brings with it a paradigm shift for nonhuman primates and new mandates on how nonhuman primates are used in biomedical research.

The relevance of HLA sequencing in population genetics studies

Next generation sequencing (NGS) is currently being adapted by different biotechnological platforms to the standard typing method for HLA polymorphism, the huge diversity of which makes this initiative particularly challenging. Boosting the molecular characterization of the HLA genes through efficient, rapid, and low-cost technologies is expected to amplify the success of tissue transplantation by enabling us to find donor-recipient matching for rare phenotypes. But the application of NGS technologies to the molecular mapping of the MHC region also anticipates essential changes in population genetic studies. Huge amounts of HLA sequence data will be available in the next years for different populations, with the potential to change our understanding of HLA variation in humans. In this review, we first explain how HLA sequencing allows a better assessment of the HLA diversity in human populations, taking also into account the methodological difficulties it introduces at the statistical level; secondly, we show how analyzing HLA sequence variation may improve our comprehension of population genetic relationships by facilitating the identification of demographic events that marked human evolution; finally, we discuss the interest of both HLA and genome-wide sequencing and genotyping in detecting functionally significant SNPs in the MHC region, the latter having also contributed to the makeup of the HLA molecular diversity observed today.

How much of the variation in the mutation rate along the human genome can be explained?

It has been claimed recently that it may be possible to predict the rate of de novo mutation of each site in the human genome with a high degree of accuracy [Michaelson et al. (2012), Cell 151: 1431−1442]. We show that this claim is unwarranted. By considering the correlation between the rate of de novo mutation and the predictions from the model of Michaelson et al., we show there could be substantial unexplained variance in the mutation rate. We investigate whether the model of Michaelson et al. captures variation at the single nucleotide level that is not due to simple context. We show that the model captures a substantial fraction of this variation at CpG dinucleotides but fails to explain much of the variation at non-CpG sites.

Balancing selection in species with separate sexes: insights from Fisher's geometric model

How common is balancing selection, and what fraction of phenotypic variance is attributable to balanced polymorphisms? Despite decades of research, answers to these questions remain elusive. Moreover, there is no clear theoretical prediction about the frequency with which balancing selection is expected to arise within a population. Here, we use an extension of Fisher's geometric model of adaptation to predict the probability of balancing selection in a population with separate sexes, wherein polymorphism is potentially maintained by two forms of balancing selection: (1) heterozygote advantage, where heterozygous individuals at a locus have higher fitness than homozygous individuals, and (2) sexually antagonistic selection (a.k.a. intralocus sexual conflict), where the fitness of each sex is maximized by different genotypes at a locus. We show that balancing selection is common under biologically plausible conditions and that sex differences in selection or sex-by-genotype effects of mutations can each increase opportunities for balancing selection. Although heterozygote advantage and sexual antagonism represent alternative mechanisms for maintaining polymorphism, they mutually exist along a balancing selection continuum that depends on population and sex-specific parameters of selection and mutation. Sexual antagonism is the dominant mode of balancing selection across most of this continuum.

Human genome variability, natural selection and infectious diseases

The recent availability of large-scale sequencing DNA data allowed researchers to investigate how genomic variation is distributed among populations. While demographic factors explain genome-wide population genetic diversity levels, scans for signatures of natural selection pinpointed several regions under non-neutral evolution. Recent studies found an enrichment of immune-related genes subjected to natural selection, suggesting that pathogens and infectious diseases have imposed a strong selective pressure throughout human history. Pathogen-mediated selection often targeted regulatory sites of genes belonging to the same biological pathway. Results from these studies have the potential to identify mutations that modulate infection susceptibility by integrating a population genomic approach with molecular immunology data and large-scale functional annotations.

Genome-wide inference of ancestral recombination graphs

The complex correlation structure of a collection of orthologous DNA sequences is uniquely captured by the "ancestral recombination graph" (ARG), a complete record of coalescence and recombination events in the history of the sample. However, existing methods for ARG inference are computationally intensive, highly approximate, or limited to small numbers of sequences, and, as a consequence, explicit ARG inference is rarely used in applied population genomics. Here, we introduce a new algorithm for ARG inference that is efficient enough to apply to dozens of complete mammalian genomes. The key idea of our approach is to sample an ARG of [Formula: see text] chromosomes conditional on an ARG of [Formula: see text] chromosomes, an operation we call "threading." Using techniques based on hidden Markov models, we can perform this threading operation exactly, up to the assumptions of the sequentially Markov coalescent and a discretization of time. An extension allows for threading of subtrees instead of individual sequences. Repeated application of these threading operations results in highly efficient Markov chain Monte Carlo samplers for ARGs. We have implemented these methods in a computer program called ARGweaver. Experiments with simulated data indicate that ARGweaver converges rapidly to the posterior distribution over ARGs and is effective in recovering various features of the ARG for dozens of sequences generated under realistic parameters for human populations. In applications of ARGweaver to 54 human genome sequences from Complete Genomics, we find clear signatures of natural selection, including regions of unusually ancient ancestry associated with balancing selection and reductions in allele age in sites under directional selection. The patterns we observe near protein-coding genes are consistent with a primary influence from background selection rather than hitchhiking, although we cannot rule out a contribution from recurrent selective sweeps.

Natural selection and infectious disease in human populations

Infectious pathogens are among the strongest selective forces that shape the human genome. Migrations and cultural changes in the past 100,000 years exposed populations to dangerous new pathogens.

Host genetics influences susceptibility to infectious disease. Evolutionary adaptations for resistance and symbiosis may underlie common immune-mediated diseases.

Signatures of selection and methods to detect them vary with the age, geographical spread and virulence of the pathogen.

A history of selection on a trait adds power to association studies by driving the emergence of common alleles of strong effect. Combining selection and association metrics can further increase power.

Genome-wide association studies (GWASs) of susceptibility to pathogens that are moderately old (1,000–50,000 years ago), geographically limited in history and exerted strong positive selective pressure will have the most power if GWASs can be done in the historically affected population.

An understanding of host–pathogen interactions can inform the development of new therapies for both infectious diseases and common immune-mediated diseases.

The impact of various infectious agents on human survival and reproduction over thousands of years has exerted selective pressure on numerous regions of the human genome. This Review describes how such signatures of selection can be detected and integrated with data from complementary approaches, such as genome-wide association studies, to provide biological insights into host–pathogen interactions.

The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology.

Positive selection drives accelerated evolution of mosquito salivary genes associated with blood-feeding

The saliva of bloodsucking animals contains dozens to hundreds of proteins that counteract their hosts' haemostasis, inflammation and immunity. It was previously observed that salivary proteins involved in haematophagy are much more divergent in their primary sequence than those of housekeeping function, when comparisons were made between closely related organisms. While this pattern of evolution could result from relaxed selection or drift, it could alternatively be the result of positive selection driven by the intense pressure of the host immune system. We investigated the polymorphism of five different genes associated with blood-feeding in the mosquito Anopheles gambiae and obtained evidence in four genes for sites with signatures of positive selection. These results add salivary gland genes from bloodsucking arthropods to the small list of genes driven by positive selection.

Identifying the genes underlying quantitative traits: a rationale for the QTN programme

The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the 'QTN programme' and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution.

Disease consequences of human adaptation

Adaptive evolution has provided us with a unique set of characteristics that define us as humans, including morphological, physiological and cellular changes. Yet, natural selection provides no assurances that adaptation is without human health consequences; advantageous mutations will increase in frequency so long as there is a net gain in fitness. As such, the current incidence of human disease can depend on previous adaptations. Here, I review genome-wide and gene-specific studies in which adaptive evolution has played a role in shaping human genetic disease. In addition to the disease consequences of adaptive phenotypes, such as bipedal locomotion and resistance to certain pathogens, I review evidence that adaptive mutations have influenced the frequency of linked disease alleles through genetic hitchhiking. Taken together, the links between human adaptation and disease highlight the importance of their combined influence on functional variation within the human genome and offer opportunities to discover and characterize such variation.