A composite of multiple signals distinguishes causal variants in regions of positive selection

Properties of different selection signature statistics and a new strategy for combining them

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.

A novel candidate region for genetic adaptation to high altitude in Andean populations

Humans living at high altitude (≥2,500 meters above sea level) have acquired unique abilities to survive the associated extreme environmental conditions, including hypoxia, cold temperature, limited food availability and high levels of free radicals and oxidants. Long-term inhabitants of the most elevated regions of the world have undergone extensive physiological and/or genetic changes, particularly in the regulation of respiration and circulation, when compared to lowland populations. Genome scans have identified candidate genes involved in altitude adaption in the Tibetan Plateau and the Ethiopian highlands, in contrast to populations from the Andes, which have not been as intensively investigated. In the present study, we focused on three indigenous populations from Bolivia: two groups of Andean natives, Aymara and Quechua, and the low-altitude control group of Guarani from the Gran Chaco lowlands. Using pooled samples, we identified a number of SNPs exhibiting large allele frequency differences over 900,000 genotyped SNPs. A region in chromosome 10 (within the cytogenetic bands q22.3 and q23.1) was significantly differentiated between highland and lowland groups. We resequenced ~1.5 Mb surrounding the candidate region and identified strong signals of positive selection in the highland populations. A composite of multiple signals like test localized the signal to FAM213A and a related enhancer; the product of this gene acts as an antioxidant to lower oxidative stress and may help to maintain bone mass. The results suggest that positive selection on the enhancer might increase the expression of this antioxidant, and thereby prevent oxidative damage. In addition, the most significant signal in a relative extended haplotype homozygosity analysis was localized to the SFTPD gene, which encodes a surfactant pulmonary-associated protein involved in normal respiration and innate host defense. Our study thus identifies two novel candidate genes and associated pathways that may be involved in high-altitude adaptation in Andean populations.

Differential Natural Selection of Human Zinc Transporter Genes between African and Non-African Populations

Zinc transporters play important roles in all eukaryotes by maintaining the rational zinc concentration in cells. However, the diversity of zinc transporter genes (ZTGs) remains poorly studied. Here, we investigated the genetic diversity of 24 human ZTGs based on the 1000 Genomes data. Some ZTGs show small population differences, such as SLC30A6 with a weighted-average FST (WA-FST = 0.015), while other ZTGs exhibit considerably large population differences, such as SLC30A9 (WA-FST = 0.284). Overall, ZTGs harbor many more highly population-differentiated variants compared with random genes. Intriguingly, we found that SLC30A9 was underlying natural selection in both East Asians (EAS) and Africans (AFR) but in different directions. Notably, a non-synonymous variant (rs1047626) in SLC30A9 is almost fixed with 96.4% A in EAS and 92% G in AFR, respectively. Consequently, there are two different functional haplotypes exhibiting dominant abundance in AFR and EAS, respectively. Furthermore, a strong correlation was observed between the haplotype frequencies of SLC30A9 and distributions of zinc contents in soils or crops. We speculate that the genetic differentiation of ZTGs could directly contribute to population heterogeneity in zinc transporting capabilities and local adaptations of human populations in regard to the local zinc state or diets, which have both evolutionary and medical implications.

Composite Selection Signals for Complex Traits Exemplified Through Bovine Stature Using Multibreed Cohorts of European and African Bos taurus

Understanding the evolution and molecular architecture of complex traits is important in domestic animals. Due to phenotypic selection, genomic regions develop unique patterns of genetic diversity called signatures of selection, which are challenging to detect, especially for complex polygenic traits. In this study, we applied the composite selection signals (CSS) method to investigate evidence of positive selection in a complex polygenic trait by examining stature in phenotypically diverse cattle comprising 47 European and 8 African Bos taurus breeds, utilizing a panel of 38,033 SNPs genotyped on 1106 animals. CSS were computed for phenotypic contrasts between multibreed cohorts of cattle by classifying the breeds according to their documented wither height to detect the candidate regions under selection. Using the CSS method, clusters of signatures of selection were detected at 26 regions (9 in European and 17 in African cohorts) on 13 bovine autosomes. Using comparative mapping information on human height, 30 candidate genes mapped at 12 selection regions (on 8 autosomes) could be linked to bovine stature diversity. Of these 12 candidate gene regions, three contained known genes (i.e., NCAPG-LCORL, FBP2-PTCH1, and PLAG1-CHCHD7) related to bovine stature, and nine were not previously described in cattle (five in European and four in African cohorts). Overall, this study demonstrates the utility of CSS coupled with strategies of combining multibreed datasets in the identification and discovery of genomic regions underlying complex traits. Characterization of multiple signatures of selection and their underlying candidate genes will elucidate the polygenic nature of stature across cattle breeds.

Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions

BACKGROUND

Genome signatures of artificial selection in U.S. Jersey cattle were identified by examining changes in haplotype homozygosity for a resource population of animals born between 1953 and 2007. Genetic merit of this population changed dramatically during this period for a number of traits, especially milk yield. The intense selection underlying these changes was achieved through extensive use of artificial insemination (AI), which also increased consanguinity of the population to a few superior Jersey bulls. As a result, allele frequencies are shifted for many contemporary animals, and in numerous cases to a homozygous state for specific genomic regions. The goal of this study was to identify those selection signatures that occurred after extensive use of AI since the 1960, using analyses of shared haplotype segments or Runs of Homozygosity. When combined with animal birth year information, signatures of selection associated with economically important traits were identified and compared to results from an extended haplotype homozygosity analysis.

RESULTS

Overall, our results reveal that more recent selection increased autozygosity across the entire genome, but some specific regions increased more than others. A genome-wide scan identified more than 15 regions with a substantial change in autozygosity. Haplotypes found to be associated with increased milk, fat and protein yield in U.S. Jersey cattle also consistently increased in frequency.

CONCLUSIONS

The analyses used in this study was able to detect directional selection over the last few decades when individual production records for Jersey animals were available.

Recent positive selection has acted on genes encoding proteins with more interactions within the whole human interactome

Genes vary in their likelihood to undergo adaptive evolution. The genomic factors that determine adaptability, however, remain poorly understood. Genes function in the context of molecular networks, with some occupying more important positions than others and thus being likely to be under stronger selective pressures. However, how positive selection distributes across the different parts of molecular networks is still not fully understood. Here, we inferred positive selection using comparative genomics and population genetics approaches through the comparison of 10 mammalian and 270 human genomes, respectively. In agreement with previous results, we found that genes with lower network centralities are more likely to evolve under positive selection (as inferred from divergence data). Surprisingly, polymorphism data yield results in the opposite direction than divergence data: Genes with higher centralities are more likely to have been targeted by recent positive selection during recent human evolution. Our results indicate that the relationship between centrality and the impact of adaptive evolution highly depends on the mode of positive selection and/or the evolutionary time-scale.

Inferring positive selection in humans from genomic data

Adaptation can be described as an evolutionary process that leads to an adjustment of the phenotypes of a population to their environment. In the classical view, new mutations can introduce novel phenotypic features into a population that leave footprints in the genome after fixation, such as selective sweeps. Alternatively, existing genetic variants may become beneficial after an environmental change and increase in frequency. Although they may not reach fixation, they may cause a shift of the optimum of a phenotypic trait controlled by multiple loci. With the availability of polymorphism data from various organisms, including humans and chimpanzees, it has become possible to detect molecular evidence of adaptation and to estimate the strength and target of positive selection. In this review, we discuss the two competing models of adaptation and suitable approaches for detecting the footprints of positive selection on the molecular level.

Genetic structure characterization of Chileans reflects historical immigration patterns

Identifying the ancestral components of genomes of admixed individuals helps uncovering the genetic basis of diseases and understanding the demographic history of populations. We estimate local ancestry on 313 Chileans and assess the contribution from three continental populations. The distribution of ancestry block-length suggests an average admixing time around 10 generations ago. Sex-chromosome analyses confirm imbalanced contribution of European men and Native-American women. Previously known genes under selection contain SNPs showing large difference in allele frequencies. Furthermore, we show that assessing ancestry is harder at SNPs with higher recombination rates and easier at SNPs with large difference in allele frequencies at the ancestral populations. Two observations, that African ancestry proportions systematically decrease from North to South, and that European ancestry proportions are highest in central regions, show that the genetic structure of Chileans is under the influence of a diffusion process leading to an ancestry gradient related to geography.

Chileans are genetically admixed. Here, the authors find that the average admixing time is around 10 generations ago and show the contribution of European men and Native-American women to the Chilean population.

A genome scan for selection signatures in pigs

Identifying signatures of selection can provide a straightforward insight into the mechanism of artificial selection and further uncover the causal genes related to the phenotypic variation. Based on Illumina Porcine60KSNP chip data, four complementary methods, Long-Range Haplotype (LRH), Tajima’s D, Cross Population Extend Haplotype Homozygosity Test (XPEHH) and F_ST, were implemented in this study to detect the selection signatures in the whole genome of one typical Chinese indigenous breed, Rongchang, one Chinese cultivated breed, Songliao, and two western breeds, Landrace and Yorkshire. False Discovery Rate (FDR) was implemented to control the false positive rates. In our study, a total of 159, 127, 179 and 159 candidate selection regions with average length of 0.80 Mb, 0.73 Mb, 0.78 Mb and 0.73 Mb were identified in Landrace, Rongchang, Songliao and Yorkshire, respectively, that span approximately 128.00 Mb, 92.38 Mb, 130.30 Mb and 115.40 Mb and account for approximately 3.74–5.33% of genome across all autosomes. The selection regions of 11.52 Mb shared by Landrace and Yorkshire were the longest when chosen pairs from the pool of the four breeds were examined. The overlaps between Yorkshire and Songliao, approximately 9.20 Mb, were greater than those of Yorkshire and Rongchang. Meanwhile, the overlaps between Landrace and Songliao were greater than those of Landrace and Rongchang but less than those of Songliao and Ronchang. Bioinformatics analysis showed that the genes/QTLs relevant to fertility, coat color, and ear morphology were found in candidate selection regions. Some genes, such as LEMD3, MC1R, KIT, TRHR etc. that were reported under selection, were confirmed in our study, and this analysis also demonstrated the diversity of breeds.

Modelling the effects of mass drug administration on the molecular epidemiology of schistosomes

As national governments scale up mass drug administration (MDA) programs aimed to combat neglected tropical diseases (NTDs), novel selection pressures on these parasites increase. To understand how parasite populations are affected by MDA and how to maximize the success of control programmes, it is imperative for epidemiological, molecular and mathematical modelling approaches to be combined. Modelling of parasite population genetic and genomic structure, particularly of the NTDs, has been limited through the availability of only a few molecular markers to date. The landscape of infectious disease research is being dramatically reshaped by next-generation sequencing technologies and our understanding of how repeated selective pressures are shaping parasite populations is radically altering. Genomics can provide high-resolution data on parasite population structure, and identify how loci may contribute to key phenotypes such as virulence and/or drug resistance. We discuss the incorporation of genetic and genomic data, focussing on the recently sequenced Schistosoma spp., into novel mathematical transmission models to inform our understanding of the impact of MDA and other control methods. We summarize what is known to date, the models that exist and how population genetics has given us an understanding of the effects of MDA on the parasites. We consider how genetic and genomic data have the potential to shape future research, highlighting key areas where data are lacking, and how future molecular epidemiology knowledge can aid understanding of transmission dynamics and the effects of MDA, ultimately informing public health policy makers of the best interventions for NTDs.

Soft shoulders ahead: spurious signatures of soft and partial selective sweeps result from linked hard sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of "soft shoulders" underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.

Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50–100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.

Genomic data as the "hitchhiker's guide" to cattle adaptation: tracking the milestones of past selection in the bovine genome

The bovine species have witnessed and played a major role in the drastic socio-economical changes that shaped our culture over the last 10,000 years. During this journey, cattle "hitchhiked" on human development and colonized the world, facing strong selective pressures such as dramatic environmental changes and disease challenge. Consequently, hundreds of specialized cattle breeds emerged and spread around the globe, making up a rich spectrum of genomic resources. Their DNA still carry the scars left from adapting to this wide range of conditions, and we are now empowered with data and analytical tools to track the milestones of past selection in their genomes. In this review paper, we provide a summary of the reconstructed demographic events that shaped cattle diversity, offer a critical synthesis of popular methodologies applied to the search for signatures of selection (SS) in genomic data, and give examples of recent SS studies in cattle. Then, we outline the potential and challenges of the application of SS analysis in cattle, and discuss the future directions in this field.

Genome-wide detection and characterization of positive selection in Korean Native Black Pig from Jeju Island

Background

In the 1980s, Korean native black pigs from Jeju Island (Jeju black pigs) served as representative sample of Korean native black pigs, and efforts were made to help the species rebound from the brink of extinction, which occurred as a result of the introduction of Western pig breeds. Geographical separation of Jeju Island from the Korean peninsula has allowed Jeju black pigs not only to acquire unique characteristics but also to retain merits of rare Korean native black pigs.

Results

To further analyze the Jeju black pig genome, we performed whole-genome re-sequencing (average read depth of 14×) of 8 Jeju black pig and 6 Korean pigs (which live on the Korean peninsula) to compare and identify putative signatures of positive selection in Jeju black pig, the true and pure Korean native black pigs. The candidate genes potentially under positive selection in Jeju black pig support previous reports of high marbling score, rare occurrence of pale, soft, exudative (PSE) meat, but low growth rate and carcass weight compared to Western breeds.

Conclusions

Several candidate genes potentially under positive selection were involved in fatty acid transport and may have contributed to the unique characteristics of meat quality in JBP. Jeju black pigs can offer a unique opportunity to investigate the true genetic resource of once endangered Korean native black pigs. Further genome-wide analyses of Jeju black pigs on a larger population scale are required in order to define a conservation strategy and improvement of native pig resources.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0160-1) contains supplementary material, which is available to authorized users.

An integrated approach to defining genetic and environmental determinants for major clinical outcomes involving vitamin D

There is substantial genetic and epidemiological evidence implicating vitamin D in the pathogenesis of many common diseases. A number of studies have sought to define an association for disease with sequence variation in the VDR gene, encoding the ligand-activated nuclear hormone receptor for vitamin D. The results of such studies have been difficult to replicate and are likely to need to account for specific environmental exposures. Here, we review recent work that has begun to study the interactions between VDR gene polymorphisms, vitamin D blood levels, and complex disease susceptibility, notably in the context of major clinical outcomes. We highlight the challenges moving forward in this area and its importance for effective clinical translation of current research.

Recent coselection in human populations revealed by protein-protein interaction network

Genome-wide scans for signals of natural selection in human populations have identified a large number of candidate loci that underlie local adaptations. This is surprising given the relatively short evolutionary time since the divergence of the human population. One hypothesis that has not been formally examined is whether and how the recent human evolution may have been shaped by coselection in the context of complex molecular interactome. In this study, genome-wide signals of selection were scanned in East Asians, Europeans, and Africans using 1000 Genome data, and subsequently mapped onto the protein-protein interaction (PPI) network. We found that the candidate genes of recent positive selection localized significantly closer to each other on the PPI network than expected, revealing substantial clustering of selected genes. Furthermore, gene pairs of shorter PPI network distances showed higher similarities of their recent evolutionary paths than those further apart. Last, subnetworks enriched with recent coselection signals were identified, which are substantially overrepresented in biological pathways related to signal transduction, neurogenesis, and immune function. These results provide the first genome-wide evidence for association of recent selection signals with the PPI network, shedding light on the potential mechanisms of recent coselection in the human genome.

A functional synonymous coding variant in the IL1RN gene is associated with survival in septic shock

RATIONALE

Death from infection is a highly heritable trait, yet there are few genetic variants with known mechanism influencing survival during septic shock.

OBJECTIVES

We hypothesized that a synonymous coding variant in the IL-1 receptor antagonist gene (IL1RN), rs315952, previously associated with reduced risk for acute respiratory distress syndrome, would be functional and associate with improved survival in septic shock.

METHODS

We used a human endotoxin (LPS) model of evoked inflammatory stress to measure plasma IL-1 receptor antagonist (IL1RA) following low-dose Food and Drug Administration-grade LPS injection (1 ng/kg) in 294 human volunteers. RNA sequencing of adipose tissue pre- and post-LPS was used to test for allelic imbalance at rs315952. In the Vasopressin and Septic Shock Trial cohort, we performed a genetic association study for survival, mortality, and organ failure-free days.

MEASUREMENTS AND MAIN RESULTS

Adipose tissue displayed significant allelic imbalance favoring the rs315952C allele in subjects of European ancestry. Consistent with this, carriers of rs315952C had slightly higher plasma IL1RA at baseline (0.039) and higher evoked IL1RA post-LPS (0.011). In the Vasopressin and Septic Shock Trial cohort, rs315952C associated with improved survival (P = 0.028), decreased adjusted 90-day mortality (P = 0.044), and faster resolution of shock (P = 0.029).

CONCLUSIONS

In European ancestry subjects, the IL1RN variant rs315952C is preferentially transcribed and associated with increased evoked plasma IL1RA and with improved survival from septic shock. It may be that genetically determined IL1RA levels influence survival from septic shock.

Genomic signatures reveal new evidences for selection of important traits in domestic cattle

We investigated diverse genomic selections using high-density single nucleotide polymorphism data of five distinct cattle breeds. Based on allele frequency differences, we detected hundreds of candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, and N'Dama. In addition to well-known genes such as KIT, MC1R, ASIP, GHR, LCORL, NCAPG, WIF1, and ABCA12, we found evidence for a variety of novel and less-known genes under selection in cattle, such as LAP3, SAR1B, LRIG3, FGF5, and NUDCD3. Selective sweeps near LAP3 were then validated by next-generation sequencing. Genome-wide association analysis involving 26,362 Holsteins confirmed that LAP3 and SAR1B were related to milk production traits, suggesting that our candidate regions were likely functional. In addition, haplotype network analyses further revealed distinct selective pressures and evolution patterns across these five cattle breeds. Our results provided a glimpse into diverse genomic selection during cattle domestication, breed formation, and recent genetic improvement. These findings will facilitate genome-assisted breeding to improve animal production and health.

Thinking too positive? Revisiting current methods of population genetic selection inference

In the age of next-generation sequencing, the availability of increasing amounts and improved quality of data at decreasing cost ought to allow for a better understanding of how natural selection is shaping the genome than ever before. However, alternative forces, such as demography and background selection (BGS), obscure the footprints of positive selection that we would like to identify. In this review, we illustrate recent developments in this area, and outline a roadmap for improved selection inference. We argue (i) that the development and obligatory use of advanced simulation tools is necessary for improved identification of selected loci, (ii) that genomic information from multiple time points will enhance the power of inference, and (iii) that results from experimental evolution should be utilized to better inform population genomic studies.

Genome-wide scan of 29,141 African Americans finds no evidence of directional selection since admixture

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study's conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas.

Integrating genomics into evolutionary medicine

The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles.

Searching for signatures of cold adaptations in modern and archaic humans: hints from the brown adipose tissue genes

Adaptation to low temperatures has been reasonably developed in the human species during the colonization of the Eurasian landmass subsequent to Out of Africa migrations of anatomically modern humans. In addition to morphological and cultural changes, also metabolic ones are supposed to have favored human isolation from cold and body heat production and this can be hypothesized also for most Neandertal and at least for some Denisovan populations, which lived in geographical areas that strongly experienced the last glacial period. Modulation of non-shivering thermogenesis, for which adipocytes belonging to the brown adipose tissue are the most specialized cells, might have driven these metabolic adaptations. To perform an exploratory analysis aimed at looking into this hypothesis, variation at 28 genes involved in such functional pathway was investigated in modern populations from different climate zones, as well as in Neandertal and Denisovan genomes. Patterns of variation at the LEPR gene, strongly related to increased heat dissipation by mitochondria, appeared to have been shaped by positive selection in modern East Asians, but not in Europeans. Moreover, a single potentially cold-adapted LEPR allele, different from the supposed adaptive one identified in Homo sapiens, was found also in Neandertal and Denisovan genomes. These findings suggest that independent mechanisms for cold adaptations might have been developed in different non-African human groups, as well as that the evolution of possible enhanced thermal efficiency in Neandertals and in some Denisovan populations has plausibly entailed significant changes also in other functional pathways than in the examined one.

A bioinformatics workflow for detecting signatures of selection in genomic data

The detection of "signatures of selection" is now possible on a genome-wide scale in many plant and animal species, and can be performed in a population-specific manner due to the wealth of per-population genome-wide genotype data that is available. With genomic regions that exhibit evidence of having been under selection shown to also be enriched for genes associated with biologically important traits, detection of evidence of selective pressure is emerging as an additional approach for identifying novel gene-trait associations. While high-density genotype data is now relatively easy to obtain, for many researchers it is not immediately obvious how to go about identifying signatures of selection in these data sets. Here we describe a basic workflow, constructed from open source tools, for detecting and examining evidence of selection in genomic data. Code to install and implement the pipeline components, and instructions to run a basic analysis using the workflow described here, can be downloaded from our public GitHub repository: http://www.github.com/smilefreak/selectionTools/

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.

Adaptations to local environments in modern human populations

After leaving sub-Saharan Africa around 50000-100000 years ago, anatomically modern humans have quickly occupied extremely diverse environments. Human populations were exposed to further environmental changes resulting from cultural innovations, such as the spread of farming, which gave rise to new selective pressures related to pathogen exposures and dietary shifts. In addition to changing the frequency of individual adaptive alleles, natural selection may also shape the overall genetic architecture of adaptive traits. Here, we review recent advances in understanding the genetic architecture of adaptive human phenotypes based on insights from the studies of lactase persistence, skin pigmentation and high-altitude adaptation. These adaptations evolved in parallel in multiple human populations, providing a chance to investigate independent realizations of the evolutionary process. We suggest that the outcome of adaptive evolution is often highly variable even under similar selective pressures. Finally, we highlight a growing need for detecting adaptations that did not follow the classical sweep model and for incorporating new sources of genetic evidence such as information from ancient DNA.

Signatures of selection in sheep bred for resistance or susceptibility to gastrointestinal nematodes

Background

Gastrointestinal nematodes are one of the most serious causes of disease in domestic ruminants worldwide. There is considerable variation in resistance to gastrointestinal nematodes within and between sheep breeds, which appears to be due to underlying genetic diversity. Through selection of resistant animals, rapid genetic progress has been demonstrated in both research and commercial flocks. Recent advances in genome sequencing and genomic technologies provide new opportunities to understand the ovine host response to gastrointestinal nematodes at the molecular level, and to identify polymorphisms conferring nematode resistance.

Results

Divergent lines of Romney and Perendale sheep, selectively bred for high and low faecal nematode egg count, were genotyped using the Illumina® Ovine SNP50 BeadChip. The resulting genome-wide SNP data were analysed for selective sweeps on loci associated with resistance or susceptibility to gastrointestinal nematode infection. Population differentiation using F_ST and Peddrift revealed sixteen regions, which included candidate genes involved in chitinase activity and the cytokine response. Two of the sixteen regions identified were contained within previously identified QTLs associated with nematode resistance.

Conclusions

In this study we identified fourteen novel regions associated with resistance or susceptibility to gastrointestinal nematodes. Results from this study support the hypothesis that host resistance to internal nematode parasites is likely to be controlled by a number of loci of moderate to small effects.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-637) contains supplementary material, which is available to authorized users.

Friendship and natural selection

More than any other species, humans form social ties to individuals who are neither kin nor mates, and these ties tend to be with similar people. Here, we show that this similarity extends to genotypes. Across the whole genome, friends' genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a "friendship score" that predicts the existence of friendship ties in a hold-out sample. A focused gene-set analysis indicates that some of the overall correlation in genotypes can be explained by specific systems; for example, an olfactory gene set is homophilic and an immune system gene set is heterophilic, suggesting that these systems may play a role in the formation or maintenance of friendship ties. Friends may be a kind of "functional kin." Finally, homophilic genotypes exhibit significantly higher measures of positive selection, suggesting that, on average, they may yield a synergistic fitness advantage that has been helping to drive recent human evolution.

Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences

BACKGROUND

Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes.

RESULTS

We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively.

CONCLUSIONS

We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.

The human condition-a molecular approach

Research into when and where modern humans originated and how they differ from, and interacted with, other now-extinct forms of human has so far been the realm of archaeologists and paleoanthropologists. However, over the past decade, molecular geneticists have begun to study genomes of extinct humans. Here, I discuss where we stand today with respect to understanding how modern humans came to differ from Neandertals and other human forms that existed until about 30,000 years ago.

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.

Influence of immune responses in gene/stem cell therapies for muscular dystrophies

Muscular dystrophies (MDs) are a heterogeneous group of diseases, caused by mutations in different components of sarcolemma, extracellular matrix, or enzymes. Inflammation and innate or adaptive immune response activation are prominent features of MDs. Various therapies under development are directed toward rescuing the dystrophic muscle damage using gene transfer or cell therapy. Here we discussed current knowledge about involvement of immune system responses to experimental therapies in MDs.

Deciphering the genetic blueprint behind Holstein milk proteins and production

Holstein is known to provide higher milk yields than most other cattle breeds, and the dominant position of Holstein today is the result of various selection pressures. Holstein cattle have undergone intensive selection for milk production in recent decades, which has left genome-wide footprints of domestication. To further characterize the bovine genome, we performed whole-genome resequencing analysis of 10 Holstein and 11 Hanwoo cattle to identify regions containing genes as outliers in Holstein, including CSN1S1, CSN2, CSN3, and KIT whose products are likely involved in the yield and proteins of milk and their distinctive black-and-white markings. In addition, genes indicative of positive selection were associated with cardiovascular disease, which is related to simultaneous propagation of genetic defects, also known as inbreeding depression in Holstein.

Heritability and genomics of gene expression in peripheral blood

We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood. The most highly heritable genes (∼777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function or ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic identity-by-descent sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which we further examined in a replication set of 1,895 unrelated subjects. A large number of non-redundant local eQTLs (6,756) met replication criteria, whereas a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide a new resource toward understanding the genetic control of transcription.

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.

Detecting natural selection in genomic data

The past fifty years have seen the development and application of numerous statistical methods to identify genomic regions that appear to be shaped by natural selection. These methods have been used to investigate the macro- and microevolution of a broad range of organisms, including humans. Here, we provide a comprehensive outline of these methods, explaining their conceptual motivations and statistical interpretations. We highlight areas of recent and future development in evolutionary genomics methods and discuss ongoing challenges for researchers employing such tests. In particular, we emphasize the importance of functional follow-up studies to characterize putative selected alleles and the use of selection scans as hypothesis-generating tools for investigating evolutionary histories.

The genomic signature of parallel adaptation from shared genetic variation

Parallel adaptation is common and may often occur from shared genetic variation, but the genomic consequences of this process remain poorly understood. We first use individual-based simulations to demonstrate that comparisons between populations adapted in parallel to similar environments from shared variation reveal a characteristic genomic signature around a selected locus: a low-divergence valley centred at the locus and flanked by twin peaks of high divergence. This signature is initiated by the hitchhiking of haplotype tracts differing between derived populations in the broader neighbourhood of the selected locus (driving the high-divergence twin peaks) and shared haplotype tracts in the tight neighbourhood of the locus (driving the low-divergence valley). This initial hitchhiking signature is reinforced over time because the selected locus acts as a barrier to gene flow from the source to the derived populations, thus promoting divergence by drift in its close neighbourhood. We next empirically confirm the peak-valley-peak signature by combining targeted and RAD sequence data at three candidate adaptation genes in multiple marine (source) and freshwater (derived) populations of threespine stickleback. Finally, we use a genome-wide screen for the peak-valley-peak signature to discover additional genome regions involved in parallel marine-freshwater divergence. Our findings offer a new explanation for heterogeneous genomic divergence and thus challenge the standard view that peaks in population divergence harbour divergently selected loci and that low-divergence regions result from balancing selection or localized introgression. We anticipate that genome scans for peak-valley-peak divergence signatures will promote the discovery of adaptation genes in other organisms.

An evolutionary analysis of antigen processing and presentation across different timescales reveals pervasive selection

The antigenic repertoire presented by MHC molecules is generated by the antigen processing and presentation (APP) pathway. We analyzed the evolutionary history of 45 genes involved in APP at the inter- and intra-species level. Results showed that 11 genes evolved adaptively in mammals. Several positively selected sites involve positions of fundamental importance to the protein function (e.g. the TAP1 peptide-binding domains, the sugar binding interface of langerin, and the CD1D trafficking signal region). In CYBB, all selected sites cluster in two loops protruding into the endosomal lumen; analysis of missense mutations responsible for chronic granulomatous disease (CGD) showed the action of different selective forces on the very same gene region, as most CGD substitutions involve aminoacid positions that are conserved in all mammals. As for ERAP2, different computational methods indicated that positive selection has driven the recurrent appearance of protein-destabilizing variants during mammalian evolution. Application of a population-genetics phylogenetics approach showed that purifying selection represented a major force acting on some APP components (e.g. immunoproteasome subunits and chaperones) and allowed identification of positive selection events in the human lineage.

We also investigated the evolutionary history of APP genes in human populations by developing a new approach that uses several different tests to identify the selection target, and that integrates low-coverage whole-genome sequencing data with Sanger sequencing. This analysis revealed that 9 APP genes underwent local adaptation in human populations. Most positive selection targets are located within noncoding regions with regulatory function in myeloid cells or act as expression quantitative trait loci. Conversely, balancing selection targeted nonsynonymous variants in TAP1 and CD207 (langerin). Finally, we suggest that selected variants in PSMB10 and CD207 contribute to human phenotypes. Thus, we used evolutionary information to generate experimentally-testable hypotheses and to provide a list of sites to prioritize in follow-up analyses.

Antigen-presenting cells digest intracellular and extracellular proteins and display the resulting antigenic repertoire on cell surface molecules for recognition by T cells. This process initiates cell-mediated immune responses and is essential to detect infections. The antigenic repertoire is generated by the antigen processing and presentation pathway. Because several pathogens evade immune recognition by hampering this process, genes involved in antigen processing and presentation may represent common natural selection targets. Thus, we analyzed the evolutionary history of these genes during mammalian evolution and in the more recent history of human populations. Evolutionary analyses in mammals indicated that positive selection targeted a very high proportion of genes (24%), and revealed that many selected sites affect positions of fundamental importance to the protein function. In humans, we found different signatures of natural selection acting both on regions that are expected to regulate gene expression levels or timing and on coding variants; two human selected polymorphisms may modulate the susceptibility to Crohn's disease and to HIV-1 infection. Therefore, we provide a comprehensive evolutionary analysis of antigen processing and we show that evolutionary studies can provide useful information concerning the location and nature of functional variants, ultimately helping to clarify phenotypic differences between and within species.

Composite selection signals can localize the trait specific genomic regions in multi-breed populations of cattle and sheep

Background

Discerning the traits evolving under neutral conditions from those traits evolving rapidly because of various selection pressures is a great challenge. We propose a new method, composite selection signals (CSS), which unifies the multiple pieces of selection evidence from the rank distribution of its diverse constituent tests. The extreme CSS scores capture highly differentiated loci and underlying common variants hauling excess haplotype homozygosity in the samples of a target population.

Results

The data on high-density genotypes were analyzed for evidence of an association with either polledness or double muscling in various cohorts of cattle and sheep. In cattle, extreme CSS scores were found in the candidate regions on autosome BTA-1 and BTA-2, flanking the POLL locus and MSTN gene, for polledness and double muscling, respectively. In sheep, the regions with extreme scores were localized on autosome OAR-2 harbouring the MSTN gene for double muscling and on OAR-10 harbouring the RXFP2 gene for polledness. In comparison to the constituent tests, there was a partial agreement between the signals at the four candidate loci; however, they consistently identified additional genomic regions harbouring no known genes. Persuasively, our list of all the additional significant CSS regions contains genes that have been successfully implicated to secondary phenotypic diversity among several subpopulations in our data. For example, the method identified a strong selection signature for stature in cattle capturing selective sweeps harbouring UQCC-GDF5 and PLAG1-CHCHD7 gene regions on BTA-13 and BTA-14, respectively. Both gene pairs have been previously associated with height in humans, while PLAG1-CHCHD7 has also been reported for stature in cattle. In the additional analysis, CSS identified significant regions harbouring multiple genes for various traits under selection in European cattle including polledness, adaptation, metabolism, growth rate, stature, immunity, reproduction traits and some other candidate genes for dairy and beef production.

Conclusions

CSS successfully localized the candidate regions in validation datasets as well as identified previously known and novel regions for various traits experiencing selection pressure. Together, the results demonstrate the utility of CSS by its improved power, reduced false positives and high-resolution of selection signals as compared to individual constituent tests.

Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle

BACKGROUND

Signatures of selection are regions in the genome that have been preferentially increased in frequency and fixed in a population because of their functional importance in specific processes. These regions can be detected because of their lower genetic variability and specific regional linkage disequilibrium (LD) patterns.

METHODS

By comparing the differences in regional LD variation between dairy and beef cattle types, and between indicine and taurine subspecies, we aim at finding signatures of selection for production and adaptation in cattle breeds. The VarLD method was applied to compare the LD variation in the autosomal genome between breeds, including Angus and Brown Swiss, representing taurine breeds, and Nelore and Gir, representing indicine breeds. Genomic regions containing the top 0.01 and 0.1 percentile of signals were characterized using the UMD3.1 Bos taurus genome assembly to identify genes in those regions and compared with previously reported selection signatures and regions with copy number variation.

RESULTS

For all comparisons, the top 0.01 and 0.1 percentile included 26 and 165 signals and 17 and 125 genes, respectively, including TECRL, BT.23182 or FPPS, CAST, MYOM1, UVRAG and DNAJA1.

CONCLUSIONS

The VarLD method is a powerful tool to identify differences in linkage disequilibrium between cattle populations and putative signatures of selection with potential adaptive and productive importance.

Extreme population differences in the human zinc transporter ZIP4 (SLC39A4) are explained by positive selection in Sub-Saharan Africa

Extreme differences in allele frequency between West Africans and Eurasians were observed for a leucine-to-valine substitution (Leu372Val) in the human intestinal zinc uptake transporter, ZIP4, yet no further evidence was found for a selective sweep around the ZIP4 gene (SLC39A4). By interrogating allele frequencies in more than 100 diverse human populations and resequencing Neanderthal DNA, we confirmed the ancestral state of this locus and found a strong geographical gradient for the derived allele (Val372), with near fixation in West Africa. In extensive coalescent simulations, we show that the extreme differences in allele frequency, yet absence of a classical sweep signature, can be explained by the effect of a local recombination hotspot, together with directional selection favoring the Val372 allele in Sub-Saharan Africans. The possible functional effect of the Leu372Val substitution, together with two pathological mutations at the same codon (Leu372Pro and Leu372Arg) that cause acrodermatitis enteropathica (a disease phenotype characterized by extreme zinc deficiency), was investigated by transient overexpression of human ZIP4 protein in HeLa cells. Both acrodermatitis mutations cause absence of the ZIP4 transporter cell surface expression and nearly absent zinc uptake, while the Val372 variant displayed significantly reduced surface protein expression, reduced basal levels of intracellular zinc, and reduced zinc uptake in comparison with the Leu372 variant. We speculate that reduced zinc uptake by the ZIP4-derived Val372 isoform may act by starving certain pathogens of zinc, and hence may have been advantageous in Sub-Saharan Africa. Moreover, these functional results may indicate differences in zinc homeostasis among modern human populations with possible relevance for disease risk.

Genome-wide scans to detect positive selection in Large White and Tongcheng pigs

Due to the direction, intensity, duration and consistency of genetic selection, especially recent artificial selection, the production performance of domestic pigs has been greatly changed. Therefore, we reasoned that there must be footprints or selection signatures that had been left during domestication. In this study, with porcine 60K BeadChip genotyping data from both commercial Large White and local Chinese Tongcheng pigs, we calculated the extended haplotype homozygosity values of the two breeds using the long-range haplotype method to detect selection signatures. We found 34 candidate regions, including 61 known genes, from Large White pigs and 25 regions comprising 57 known genes from Tongcheng pigs. Many selection signatures were found on SSC1, SSC4, SSC7 and SSC14 regions in both populations. According to quantitative trait loci and network pathway analyses, most of the regions and genes were linked to growth, reproduction and immune responses. In addition, the average genetic differentiation coefficient FST was 0.254, which means that there had already been a significant differentiation between the breeds. The findings from this study can contribute to further research on molecular mechanisms of pig evolution and domestication and also provide valuable references for improvement of their breeding and cultivation.

Revisiting the thrifty gene hypothesis via 65 loci associated with susceptibility to type 2 diabetes

We have investigated the evidence for positive selection in samples of African, European, and East Asian ancestry at 65 loci associated with susceptibility to type 2 diabetes (T2D) previously identified through genome-wide association studies. Selection early in human evolutionary history is predicted to lead to ancestral risk alleles shared between populations, whereas late selection would result in population-specific signals at derived risk alleles. By using a wide variety of tests based on the site frequency spectrum, haplotype structure, and population differentiation, we found no global signal of enrichment for positive selection when we considered all T2D risk loci collectively. However, in a locus-by-locus analysis, we found nominal evidence for positive selection at 14 of the loci. Selection favored the protective and risk alleles in similar proportions, rather than the risk alleles specifically as predicted by the thrifty gene hypothesis, and may not be related to influence on diabetes. Overall, we conclude that past positive selection has not been a powerful influence driving the prevalence of T2D risk alleles.

Natural selection in a bangladeshi population from the cholera-endemic ganges river delta

As an ancient disease with high fatality, cholera has likely exerted strong selective pressure on affected human populations. We performed a genome-wide study of natural selection in a population from the Ganges River Delta, the historic geographic epicenter of cholera. We identified 305 candidate selected regions using the composite of multiple signals (CMS) method. The regions were enriched for potassium channel genes involved in cyclic adenosine monophosphate-mediated chloride secretion and for components of the innate immune system involved in nuclear factor κB (NF-κB) signaling. We demonstrate that a number of these strongly selected genes are associated with cholera susceptibility in two separate cohorts. We further identify repeated examples of selection and association in an NF-κB/inflammasome-dependent pathway that is activated in vitro by Vibrio cholerae. Our findings shed light on the genetic basis of cholera resistance in a population from the Ganges River Delta and present a promising approach for identifying genetic factors influencing susceptibility to infectious diseases.

Genome-scale analysis of demographic history and adaptive selection

One of the main topics in population genetics is identification of adaptive selection among populations. For this purpose, population history should be correctly inferred to evaluate the effect of random drift and exclude it in selection identification. With the rapid progress in genomics in the past decade, vast genome-scale variations are available for population genetic analysis, which however requires more sophisticated models to infer species' demographic history and robust methods to detect local adaptation. Here we aim to review what have been achieved in the fields of demographic modeling and selection detection. We summarize their rationales, implementations, and some classical applications. We also propose that some widely-used methods can be improved in both theoretical and practical aspects in near future.