An Approximate Markov Model for the Wright-Fisher Diffusion and Its Application to Time Series Data.

The joint and accurate inference of selection and demography from genetic data is considered a particularly challenging question in population genetics, since both process may lead to very similar patterns of genetic diversity. However, additional information for disentangling these effects may be obtained by observing changes in allele frequencies over multiple time points. Such data are common in experimental evolution studies, as well as in the comparison of ancient and contemporary samples. Leveraging this information, however, has been computationally challenging, particularly when considering multilocus data sets. To overcome these issues, we introduce a novel, discrete approximation for diffusion processes, termed mean transition time approximation, which preserves the long-term behavior of the underlying continuous diffusion process. We then derive this approximation for the particular case of inferring selection and demography from time series data under the classic Wright-Fisher model and demonstrate that our approximation is well suited to describe allele trajectories through time, even when only a few states are used. We then develop a Bayesian inference approach to jointly infer the population size and locus-specific selection coefficients with high accuracy and further extend this model to also infer the rates of sequencing errors and mutations. We finally apply our approach to recent experimental data on the evolution of drug resistance in influenza virus, identifying likely targets of selection and finding evidence for much larger viral population sizes than previously reported.

Influenza virus drug resistance: a time-sampled population genetics perspective.

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

On detecting incomplete soft or hard selective sweeps using haplotype structure.

We present a new haplotype-based statistic (nSL) for detecting both soft and hard sweeps in population genomic data from a single population. We compare our new method with classic single-population haplotype and site frequency spectrum (SFS)-based methods and show that it is more robust, particularly to recombination rate variation. However, all statistics show some sensitivity to the assumptions of the demographic model. Additionally, we show that nSL has at least as much power as other methods under a number of different selection scenarios, most notably in the cases of sweeps from standing variation and incomplete sweeps. This conclusion holds up under a variety of demographic models. In many aspects, our new method is similar to the iHS statistic; however, it is generally more robust and does not require a genetic map. To illustrate the utility of our new method, we apply it to HapMap3 data and show that in the Yoruban population, there is strong evidence of selection on genes relating to lipid metabolism. This observation could be related to the known differences in cholesterol levels, and lipid metabolism more generally, between African Americans and other populations. We propose that the underlying causes for the selection on these genes are pleiotropic effects relating to blood parasites rather than their role in lipid metabolism.

A scan for human-specific relaxation of negative selection reveals unexpected polymorphism in proteasome genes.

Environmental or genomic changes during evolution can relax negative selection pressure on specific loci, permitting high frequency polymorphisms at previously conserved sites. Here, we jointly analyze population genomic and comparative genomic data to search for functional processes showing relaxed negative selection specifically in the human lineage, whereas remaining evolutionarily conserved in other mammals. Consistent with previous studies, we find that olfactory receptor genes display such a signature of relaxation in humans. Intriguingly, proteasome genes also show a prominent signal of human-specific relaxation: multiple proteasome subunits, including four members of the catalytic core particle, contain high frequency nonsynonymous polymorphisms at sites conserved across mammals. Chimpanzee proteasome genes do not display a similar trend. Human proteasome genes also bear no evidence of recent positive or balancing selection. These results suggest human-specific relaxation of negative selection in proteasome subunits; the exact biological causes, however, remain unknown.

Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution.

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes.

Decay of linkage disequilibrium within genes across HGDP-CEPH human samples: most population isolates do not show increased LD.

BACKGROUND: It is well known that the pattern of linkage disequilibrium varies between human populations, with remarkable geographical stratification. Indirect association studies routinely exploit linkage disequilibrium around genes, particularly in isolated populations where it is assumed to be higher. Here, we explore both the amount and the decay of linkage disequilibrium with physical distance along 211 gene regions, most of them related to complex diseases, across 39 HGDP-CEPH population samples, focusing particularly on the populations defined as isolates. Within each gene region and population we use r2 between all possible single nucleotide polymorphism (SNP) pairs as a measure of linkage disequilibrium and focus on the proportion of SNP pairs with r2 greater than 0.8. RESULTS: Although the average r2 was found to be significantly different both between and within continental regions, a much higher proportion of r2 variance could be attributed to differences between continental regions (2.8% vs. 0.5%, respectively). Similarly, while the proportion of SNP pairs with r2 > 0.8 was significantly different across continents for all distance classes, it was generally much more homogenous within continents, except in the case of Africa and the Americas. The only isolated populations with consistently higher LD in all distance classes with respect to their continent are the Kalash (Central South Asia) and the Surui (America). Moreover, isolated populations showed only slightly higher proportions of SNP pairs with r2 > 0.8 per gene region than non-isolated populations in the same continent. Thus, the number of SNPs in isolated populations that need to be genotyped may be only slightly less than in non-isolates. CONCLUSION: The "isolated population" label by itself does not guarantee a greater genotyping efficiency in association studies, and properties other than increased linkage disequilibrium may make these populations interesting in genetic epidemiology.

A natural history of FUT2 polymorphism in humans.

Because pathogens are powerful selective agents, host-cell surface molecules used by pathogens as identification signals can reveal the signature of selection. Most of them are oligosaccharides, synthesized by glycosyltransferases. One known example is balancing selection shaping ABO evolution as a consequence of both, A and B antigens being recognized as receptors by some pathogens, and anti-A and/or anti-B natural antibodies produced by hosts conferring protection against the numerous infectious agents expressing A and B motifs. These antigens can also be found in tissues other than blood if there is activity of another enzyme, FUT2, a fucosyltransferase responsible for ABO biosynthesis in body fluids. Homozygotes for null variants at this locus present the nonsecretor phenotype (se), because they cannot express ABO antigens in secretions. Multiple independent mutations have been shown to be responsible for the nonsecretor phenotype, which is coexisting with the secretor phenotype in most populations. In this study, we have resequenced the coding region of FUT2 in 732 individuals from 39 worldwide human populations. We report a complex pattern of natural selection acting on the gene. Although frequencies of secretor and nonsecretor phenotypes are similar in different populations, the point mutations at the base of the phenotypes are different, with some variants showing a long history of balancing selection among Eurasian and African populations, and one recent variant showing a fast spread in East Asia, likely due to positive selection. Thus, a convergent phenotype composition has been achieved through different mutations with different evolutionary histories.

A variant in the gene FUT9 is associated with susceptibility to placental malaria infection.

Malaria in pregnancy forms a substantial part of the worldwide burden of malaria, with an estimated annual death toll of up to 200 000 infants, as well as increased maternal morbidity and mortality. Studies of genetic susceptibility to malaria have so far focused on infant malaria, with only a few studies investigating the genetic basis of placental malaria, focusing only on a limited number of candidate genes. The aim of this study therefore was to identify novel host genetic factors involved in placental malaria infection. To this end we carried out a nested case-control study on 180 Mozambican pregnant women with placental malaria infection, and 180 controls within an intervention trial of malaria prevention. We genotyped 880 SNPs in a set of 64 functionally related genes involved in glycosylation and innate immunity. A single nucleotide polymorphism (SNP) located in the gene FUT9, rs3811070, was significantly associated with placental malaria infection (odds ratio = 2.31, permutation P-value=0.028). Haplotypic analysis revealed a similarly strong association of a common haplotype of four SNPs including rs3811070. FUT9 codes for a fucosyl-transferase that is catalyzing the last step in the biosynthesis of the Lewis-x antigen, which forms part of the Lewis blood group-related antigens. These results therefore suggest an involvement of this antigen in the pathogenesis of placental malaria infection.

Human pseudogenes of the ABO family show a complex evolutionary dynamics and loss of function.

The GT6 glycosyltransferases gene family, that includes the ABO blood group, shows a complex evolution pattern, with multiple events of gain and loss in different mammal species. In humans the ABO gene is considered the sole functional member although the O allele is null and is fixed in certain populations. Here, we analyze the human GT6 pseudogene sequences (Forssman, IGB3, GGTA1, GT6m5, GT6m6, and GT6m7) from an evolutionary perspective, by the study of (i) their diversity levels in populations through the resequencing analysis of European and African individuals; (ii) the interpopulation differentiation, with genotyping data from a survey of populations covering most of human genetic diversity; and (iii) the interespecific divergence, by the comparison of the human and some other primate species sequences. Since pseudogenes are expected to evolve under neutrality, they should show an evolutionary pattern different to that of functional sequences, with higher levels of diversity as well as a ratio of nonsynonymous to synonymous changes close to 1. We describe some departures from these expectations, including selection for inactivation in IGB3, GGTA1, and the interesting case of FS (Forssman) with a probable shift of its initial function in the primate lineage, which put it apart from a pure neutral pseudogene. These results suggest that some of these GT6 human pseudogenes may still be functional and retain some valuable unknown function in humans, in some case even at the protein level. The evolutionary analysis of all members of the GT6 family in humans allows an insight into their functional history, a process likely due to the interaction of the host glycans that they synthesize with pathogens; the past process that can be unraveled through the footprints left by natural selection in the extant genome variation.

Balancing selection is the main force shaping the evolution of innate immunity genes.

The evolutionarily recent geographic expansion of humans, and the even more recent development of large, relatively dense human settlements, has exposed our species to new pathogenic environments. Potentially lethal pathogens are likely to have exerted important selective pressures on our genome, so immunity genes can be expected to show molecular signatures of the adaptation of human populations to these recent conditions. While genes related to the acquired immunity system have indeed been reported to show traces of local adaptation, little is known about the response of the innate immunity system. In this study, we analyze the variability patterns in different human populations of fifteen genes related to innate immunity. We have used both single nucleotide polymorphism and sequence data, and through the analysis of interpopulation differentiation, the linkage disequilibrium pattern, and intrapopulation diversity, we have discovered some signatures of positive and especially balancing selection in these genes, thus confirming the importance of the immune system genetic plasticity in the evolutionary adaptive process. Interestingly, the strongest evidence is found in three TLR genes and CD14. These innate immunity genes play a pivotal role, being involved in the primary recognition of pathogens. In general, more evidences of selection appear in the European populations, in some case possibly related to severe population specific pressures. However, we also describe evidence from African populations, which may reflect parallel or long-term selective forces acting in different geographic areas.

SNP analysis to results (SNPator): a web-based environment oriented to statistical genomics analyses upon SNP data.

UNLABELLED: Single nucleotide polymorphisms (SNPs) are the most widely used marker in studies to assess associations between genetic variants and complex traits or diseases. They are also becoming increasingly important in the study of the evolution and history of humans and other species. The analysis and processing of SNPs obtained thanks to high-throughput technologies imply the time consuming and costly use of different, complex and usually format-incompatible software. SNPator is a user-friendly web-based SNP data analysis suite that integrates, among many other algorithms, the most common steps of a SNP association study. It frees the user from the need to have large computer facilities and an in depth knowledge of genetic software installation and management. Genotype data is directly read from the output files of the usual genotyping platforms. Phenotypic data on the samples can also be easily uploaded. Many different quality control and analysis procedures can be performed either by using built-in SNPator algorithms or by calling standard genetic software. AVAILABILITY: Access is granted from the SNPator webpage http://www.snpator.org.

Is there selection for the pace of successive inactivation of the arpAT gene in primates?

Pseudogenes have classically been considered inactive sequences evolving under neutrality. In recent years, however, a growing body of evidence is favoring the appearance of hypotheses attributing a functional role to pseudogenes. One of these hypotheses is that the silencing of a gene could produce a loss of function that could have been favored by natural selection. Here, we analyzed the pace of pseudogenization of arpAT, an L-DOPA transporter related to the neurotransmitter function of this amino acid in the brain. While active in rodent, dog, and chicken, arpAT has been silenced during primate evolution. Given the high number of inactivating mutations described in humans, it is possible that there have been selective pressures favoring this silencing. Through analysis of orthologous sequences in several primate species, we show that the silencing of arpAT occurred approximately 77 million to 90 million years ago, and that the observed mutation pattern is likely a consequence of its antiquity.

Evolutionary analysis of genes of two pathways involved in placental malaria infection.

Placental malaria is a special form of malaria that causes up to 200,000 maternal and infant deaths every year. Previous studies show that two receptor molecules, hyaluronic acid and chondroitin sulphate A, are mediating the adhesion of parasite-infected erythrocytes in the placenta of patients, which is believed to be a key step in the pathogenesis of the disease. In this study, we aimed at identifying sites of malaria-induced adaptation by scanning for signatures of natural selection in 24 genes in the complete biosynthesis pathway of these two receptor molecules. We analyzed a total of 24 Mb of publicly available polymorphism data from the International HapMap project for three human populations with European, Asian and African ancestry, with the African population from a region of presently and historically high malaria prevalence. Using the methods based on allele frequency distributions, genetic differentiation between populations, and on long-range haplotype structure, we found only limited evidence for malaria-induced genetic adaptation in this set of genes in the African population; however, we identified one candidate gene with clear evidence of selection in the Asian population. Although historical exposure to malaria in this population cannot be ruled out, we speculate that it might be caused by other pathogens, as there is growing evidence that these molecules are important receptors in a variety of host-pathogen interactions. We propose to use the present methods in a systematic way to help identify candidate regions under positive selection as a consequence of malaria.