The impact of natural selection on health and disease: uses of the population genetics approach in humans

A general principle governing neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans

The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons-layer 2/3 intratelencephalic excitatory neurons-has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.

Bacterial Infection versus Viral Infection Preference of ABO Blood Group Phenotype Patients

Several studies have established an association between the blood group type and susceptibility to infections. This study aimed to evaluate a correlation between the blood group type and the susceptibility to infection. A total of 558 patients were enrolled in this study who attended at the Althawra Hospital, Ibb City, from March to August 2018. Blood samples were analyzed for complete blood count and blood group. We observed a high frequency of infections affecting the digestive system (26.4%), while the least affected system was the urogenital system 5.9%. Patients with A blood group exhibit an increased probability to be infected by viruses than they do for bacteria (odds ratio [OR] = 1.430; 95% confidence interval [CI] = 1.005 to 2.035; P = 0.05 and OR = 0.098; 95% CI = 0.064 to 0.148; P < 0.0001, respectively). It was observed that blood group A individuals were more susceptible to infection with hepatitis B virus than were the other groups (P = 0.041; OR = 1.704, 95% CI = 1.053-2.773). The liklihood of O blood group patients experiencing urogenital infections was less than that of non-O blood group patients one third (OR = 0.353, 95% CI = 0.158-0.789; P = 0.014). This study corroborates previous findings that demonstrated that certain blood groups are more prone to infection by one agent than are patients with other blood groups.

Disentangling archaic introgression and genomic signatures of selection at human immunity genes

Pathogens and infectious diseases have imposed exceptionally strong selective pressure on ancient and modern human genomes and contributed to the current variation in many genes. There is evidence that modern humans acquired immune variants through interbreeding with ancient hominins, but the impact of such variants on human traits is not fully understood. The main objectives of this research were to infer the genetic signatures of positive selection that may be involved in adaptation to infectious diseases and to investigate the function of Neanderthal alleles identified within a set of 50 Lithuanian genomes. Introgressed regions were identified using the machine learning tool ArchIE. Recent positive selection signatures were analysed using iHS. We detected high-scoring signals of positive selection at innate immunity genes (EMB, PARP8, HLAC, and CDSN) and evaluated their interactions with the structural proteins of pathogens. Interactions with human immunodeficiency virus (HIV) 1 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified. Overall, genomic regions introgressed from Neanderthals were shown to be enriched in genes related to immunity, keratinocyte differentiation, and sensory perception.

Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations

Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.

The Mystery of Cancer Resistance: A Revelation Within Nature

Cancer, a disease due to uncontrolled cell proliferation is as ancient as multicellular organisms. A 255-million-years-old fossilized forerunner mammal gorgonopsian is probably the oldest evidence of cancer, to date. Cancer seems to have evolved by adapting to the microenvironment occupied by immune sentinel, modulating the cellular behavior from cytotoxic to regulatory, acquiring resistance to chemotherapy and surviving hypoxia. The interaction of genes with environmental carcinogens is central to cancer onset, seen as a spectrum of cancer susceptibility among human population. Cancer occurs in life forms other than human also, although their exposure to environmental carcinogens can be different. Role of genetic etiology in cancer in multiple species can be interesting with regard to not only cancer susceptibility, but also genetic conservation and adaptation in speciation. The widely used model organisms for cancer research are mouse and rat which are short-lived and reproduce rapidly. Research in these cancer prone animal models has been valuable as these have led to cancer therapy. However, another rewarding area of cancer research can be the cancer-resistant animal species. The Peto's paradox and G-value paradox are evident when natural cancer resistance is observed in large mammals, like elephant and whale, small rodents viz. Naked Mole Rat and Blind Mole Rat, and Bat. The cancer resistance remains to be explored in other small or large and long-living animals like giraffe, camel, rhinoceros, water buffalo, Indian bison, Shire horse, polar bear, manatee, elephant seal, walrus, hippopotamus, turtle and tortoise, sloth, and squirrel. Indeed, understanding the molecular mechanisms of avoiding neoplastic transformation across various life forms can be potentially having translational value for human cancer management. Adapted and Modified from (Hanahan and Weinberg 2011).

Machine-Learning Prospects for Detecting Selection Signatures Using Population Genomics Data

Natural selection has been given a lot of attention because it relates to the adaptation of populations to their environments, both biotic and abiotic. An allele is selected when it is favored by natural selection. Consequently, the favored allele increases in frequency in the population and neighboring linked variation diminishes, causing so-called selective sweeps. A high-throughput genomic sequence allows one to disentangle the evolutionary forces at play in populations. With the development of high-throughput genome sequencing technologies, it has become easier to detect these selective sweeps/selection signatures. Various methods can be used to detect selective sweeps, from simple implementations using summary statistics to complex statistical approaches. One of the important problems of these statistical models is the potential to provide inaccurate results when their assumptions are violated. The use of machine learning (ML) in population genetics has been introduced as an alternative method of detecting selection by treating the problem of detecting selection signatures as a classification problem. Since the availability of population genomics data is increasing, researchers may incorporate ML into these statistical models to infer signatures of selection with higher predictive accuracy and better resolution. This article describes how ML can be used to aid in detecting and studying natural selection patterns using population genomic data.

Genetics of Normotension Preventing Hypertension Leads to a Novel Physiological Paradigm

Possessing blood pressure in normal ranges is considered healthy, and does not warrant medical attention for obvious clinical reasons. However, to realize normotension and then maintain it even when confronted with a hypertensive threat must have its biological 'shield of armour'. While sensitivity to hypertension has been widely recognized and studied, inherent mechanisms that enable a physiological resistance to hypertension to occur have received little attention. Recent advances in normotension genetics have produced unexpected insights. A hypertension 'suppressor' likely inhabits the normotensive genome of inbred Lewis rats. This suppressor behaves as a 'master' control capable of functionally abrogating the effects of hypertension-promoting alleles from multiple quantitative trait loci. This conceptual advancement lays the foundation for uncovering an anti-hypertension gene. Discovering its identity will assist our attempts at developing innovative diagnostic and therapeutic strategies for circumventing and treating hypertension. This new domain of suppressing hypertension goes beyond the conventional pharmacological treatments of hypertension before symptoms appear. For this purpose, a valid theoretical basis and framework is needed that can interpret the experimental data and produce testable predictions for authenticating, enriching or amending the normotension paradigm in the future.

Adaptive Evolution in TRIF Leads to Discordance between Human and Mouse Innate Immune Signaling

The TIR domain-containing adapter inducing IFN-β (TRIF) protein is an innate immune system protein that mediates the MyD88-independent toll-like receptor response pathway in mice and humans. Previously, we identified positive selection at seven distinct residues in mouse TRIF (mTRIF), as compared with human and other mammalian orthologs, thus predicting protein functional shift in mTRIF. We reconstructed TRIF for the most recent common ancestor of mouse and human, and mutated this at the seven sites to their extant mouse/human states. We overexpressed these TRIF mutants in immortalized human and mouse cell lines and monitored TRIF-dependent cytokine production and gene expression induction. We show that optimal TRIF function in human and mouse is dependent on the identity of the positively selected sites. These data provide us with molecular data relating observed differences in response between mouse and human MyD88-independent signaling in the innate immune system with protein functional change.

Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People

The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.

African Global Representation in Biomedical Sciences

African populations are diverse in their ethnicity, language, culture, and genetics. Although plagued by high disease burdens, until recently the continent has largely been excluded from biomedical studies. Along with limitations in research and clinical infrastructure, human capacity, and funding, this omission has resulted in an underrepresentation of African data and disadvantaged African scientists. This review interrogates the relative abundance of biomedical data from Africa, primarily in genomics and other omics. The visibility of African science through publications is also discussed. A challenge encountered in this review is the relative lack of annotation of data on their geographical or population origin, with African countries represented as a single group. In addition to the abovementioned limitations,the global representation of African data may also be attributed to the hesitation to deposit data in public repositories. Whatever the reason, the disparity should be addressed, as African data have enormous value for scientists in Africa and globally.

Biomimetics provides lessons from nature for contemporary ways to improve human health

Homo sapiens is currently living in serious disharmony with the rest of the natural world. For our species to survive, and for our well-being, we must gather knowledge from multiple perspectives and actively engage in studies of planetary health. The enormous diversity of species, one of the most striking aspects of life on our planet, provides a source of solutions that have been developed through evolution by natural selection by animals living in extreme environments. The food system is central to finding solutions; our current global eating patterns have a negative impact on human health, driven climate change and loss of biodiversity. We propose that the use of solutions derived from nature, an approach termed biomimetics, could mitigate the effects of a changing climate on planetary health as well as human health. For example, activation of the transcription factor Nrf2 may play a role in protecting animals living in extreme environments, or animals exposed to heat stress, pollution and pesticides. In order to meet these challenges, we call for the creation of novel interdisciplinary planetary health research teams.

The Genomic Architecture of Adaptation to Larval Malnutrition Points to a Trade-off with Adult Starvation Resistance in Drosophila

Periods of nutrient shortage impose strong selection on animal populations. Experimental studies of genetic adaptation to nutrient shortage largely focus on resistance to acute starvation at adult stage; it is not clear how conclusions drawn from these studies extrapolate to other forms of nutritional stress. We studied the genomic signature of adaptation to chronic juvenile malnutrition in six populations of Drosophila melanogaster evolved for 150 generations on an extremely nutrient-poor larval diet. Comparison with control populations evolved on standard food revealed repeatable genomic differentiation between the two set of population, involving >3,000 candidate SNPs forming >100 independently evolving clusters. The candidate genomic regions were enriched in genes implicated in hormone, carbohydrate, and lipid metabolism, including some with known effects on fitness-related life-history traits. Rather than being close to fixation, a substantial fraction of candidate SNPs segregated at intermediate allele frequencies in all malnutrition-adapted populations. This, together with patterns of among-population variation in allele frequencies and estimates of Tajima’s D, suggests that the poor diet results in balancing selection on some genomic regions. Our candidate genes for tolerance to larval malnutrition showed a high overlap with genes previously implicated in acute starvation resistance. However, adaptation to larval malnutrition in our study was associated with reduced tolerance to acute adult starvation. Thus, rather than reflecting synergy, the shared genomic architecture appears to mediate an evolutionary trade-off between tolerances to these two forms of nutritional stress.

Comparative analysis of Plasmodium falciparum dihydrofolate-reductase gene sequences from different regions of India

Molecular surveillance of the drug resistance genes in parasite can be used for monitoring/surveillance of drug resistance in endemic malaria areas. Here we report the prevalence of single nucleotide polymorphisms (SNPs) in dihydrofolate reductase (dhfr) gene in nucleotide sequence of Plasmodium falciparum from different regions in India. We found markedly prevalent mutants evident in P. falciparum infections N51I, C59R, 108N and I164L. Our results indicate that P. falciparum populations in the regions show an increase in the prevalence of polymorphisms, most likely reflecting different selective pressures found in humans and mosquitoes. Molecular surveillance can serve as a useful tool to monitor the prevalence/emergence of resistant genotypes within endemic populations and can serve for determining the efficacy of antimalarial drugs.

Antagonistic Pleiotropy in Human Disease

Between the 1930s and 1950s, scientists developed key principles of population genetics to try and explain the aging process. Almost a century later, these aging theories, including antagonistic pleiotropy and mutation accumulation, have been experimentally validated in animals. Although the theories have been much harder to test in humans despite research dating back to the 1970s, recent research is closing this evidence gap. Here we examine the strength of evidence for antagonistic pleiotropy in humans, one of the leading evolutionary explanations for the retention of genetic risk variation for non-communicable diseases. We discuss the analytical tools and types of data that are used to test for patterns of antagonistic pleiotropy and provide a primer of evolutionary theory on types of selection as a guide for understanding this mechanism and how it may manifest in other diseases. We find an abundance of non-experimental evidence for antagonistic pleiotropy in many diseases. In some cases, several studies have independently found corroborating evidence for this mechanism in the same or related sets of diseases including cancer and neurodegenerative diseases. Recent studies also suggest antagonistic pleiotropy may be involved in cardiovascular disease and diabetes. There are also compelling examples of disease risk variants that confer fitness benefits ranging from resistance to other diseases or survival in extreme environments. This provides increasingly strong support for the theory that antagonistic pleiotropic variants have enabled improved fitness but have been traded for higher burden of disease later in life. Future research in this field is required to better understand how this mechanism influences contemporary disease and possible consequences for their treatment.

ImaGene: a convolutional neural network to quantify natural selection from genomic data

BACKGROUND

The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determining such genetic bases is an evolutionary framework. As sites targeted by natural selection are likely to harbor important functionalities for the carrier, the identification of selection signatures in the genome has the potential to unveil the genetic mechanisms underpinning human phenotypes. Popular methods of detecting such signals rely on compressing genomic information into summary statistics, resulting in the loss of information. Furthermore, few methods are able to quantify the strength of selection. Here we explored the use of deep learning in evolutionary biology and implemented a program, called ImaGene, to apply convolutional neural networks on population genomic data for the detection and quantification of natural selection.

RESULTS

ImaGene enables genomic information from multiple individuals to be represented as abstract images. Each image is created by stacking aligned genomic data and encoding distinct alleles into separate colors. To detect and quantify signatures of positive selection, ImaGene implements a convolutional neural network which is trained using simulations. We show how the method implemented in ImaGene can be affected by data manipulation and learning strategies. In particular, we show how sorting images by row and column leads to accurate predictions. We also demonstrate how the misspecification of the correct demographic model for producing training data can influence the quantification of positive selection. We finally illustrate an approach to estimate the selection coefficient, a continuous variable, using multiclass classification techniques.

CONCLUSIONS

While the use of deep learning in evolutionary genomics is in its infancy, here we demonstrated its potential to detect informative patterns from large-scale genomic data. We implemented methods to process genomic data for deep learning in a user-friendly program called ImaGene. The joint inference of the evolutionary history of mutations and their functional impact will facilitate mapping studies and provide novel insights into the molecular mechanisms associated with human phenotypes.

Inflammaging: a new immune-metabolic viewpoint for age-related diseases

Ageing and age-related diseases share some basic mechanistic pillars that largely converge on inflammation. During ageing, chronic, sterile, low-grade inflammation - called inflammaging - develops, which contributes to the pathogenesis of age-related diseases. From an evolutionary perspective, a variety of stimuli sustain inflammaging, including pathogens (non-self), endogenous cell debris and misplaced molecules (self) and nutrients and gut microbiota (quasi-self). A limited number of receptors, whose degeneracy allows them to recognize many signals and to activate the innate immune responses, sense these stimuli. In this situation, metaflammation (the metabolic inflammation accompanying metabolic diseases) is thought to be the form of chronic inflammation that is driven by nutrient excess or overnutrition; metaflammation is characterized by the same mechanisms underpinning inflammaging. The gut microbiota has a central role in both metaflammation and inflammaging owing to its ability to release inflammatory products, contribute to circadian rhythms and crosstalk with other organs and systems. We argue that chronic diseases are not only the result of ageing and inflammaging; these diseases also accelerate the ageing process and can be considered a manifestation of accelerated ageing. Finally, we propose the use of new biomarkers (DNA methylation, glycomics, metabolomics and lipidomics) that are capable of assessing biological versus chronological age in metabolic diseases.

Genetic polymorphisms of antioxidant enzymes CAT and SOD affect the outcome of clinical, biochemical, and anthropometric variables in people with obesity under a dietary intervention

BACKGROUND

Genetic polymorphisms of antioxidant enzymes CAT, GPX, and SOD are involved in the etiology of obesity and its principal comorbidities. The aim of the present study was to analyze the effect of aforementioned SNPs over the output of several variables in people with obesity after a nutritional intervention. The study included 92 Mexican women, which received a dietary intervention by 3 months. Participants were genotyped and stratified into two groups: (1) carriers; mutated homozygous plus heterozygous (CR) and (2) homozygous wild type (WT). A comparison between CR and WT was done in clinical (CV), biochemical (BV), and anthropometric variables (AV), at the beginning and at the end of the intervention.

RESULTS

Participants (n = 92) showed statistically significant differences (p < 0.05) at the end of the nutritional intervention in several CV, BV, and AV. However, two kinds of responses were observed after genotyping participants: (A) CR and WT showed statistically significant differences (p < 0.05) in several CV, BV, and AV for the SNPs 599C>T GPX1 (rs1050450), - 251A>G SOD1 (rs2070424), and - 262C>T CAT (rs1001179). (B) Only CR showed statistically changes (p < 0.05) in several CV, BV, and AV for the SNPs - 21A>T CAT (rs7943316) and 47C>T SOD2 (rs4880). The dietary intervention effect was statistically significantly between the polymorphisms of 47C>T SOD2 and BMI, SBP, TBARS, total cholesterol, and C-LCL (p < 0.05) and between the polymorphisms of - 21A>T CAT (rs7943316) and SBP, DBP, total cholesterol, and atherogenic index (p < 0.05).

CONCLUSION

People with obesity display different response in several CV, BV, and AV after a nutritional intervention, depending on the antioxidant genetic background of SOD and CAT enzymes.

Pancreatic cancer biology and genetics from an evolutionary perspective

Cancer is an evolutionary disease, containing the hallmarks of an asexually reproducing unicellular organism subject to evolutionary paradigms. Pancreatic ductal adenocarcinoma (hereafter referred to as pancreatic cancer) is a particularly robust example of this phenomenon. Genomic features indicate that pancreatic cancer cells are selected for fitness advantages when encountering the geographic and resource-depleted constraints of the microenvironment. Phenotypic adaptations to these pressures help disseminated cells to survive in secondary sites, a major clinical problem for patients with this disease. In this Review we gather the wide-ranging aspects of pancreatic cancer research into a single concept rooted in Darwinian evolution, with the goal of identifying novel insights and opportunities for study.

The Impact of Evolutionary Driving Forces on Human Complex Diseases: A Population Genetics Approach

Investigating the molecular evolution of human genome has paved the way to understand genetic adaptation of humans to the environmental changes and corresponding complex diseases. In this review, we discussed the historical origin of genetic diversity among human populations, the evolutionary driving forces that can affect genetic diversity among populations, and the effects of human movement into new environments and gene flow on population genetic diversity. Furthermore, we presented the role of natural selection on genetic diversity and complex diseases. Then we reviewed the disadvantageous consequences of historical selection events in modern time and their relation to the development of complex diseases. In addition, we discussed the effect of consanguinity on the incidence of complex diseases in human populations. Finally, we presented the latest information about the role of ancient genes acquired from interbreeding with ancient hominids in the development of complex diseases.

267 Spanish Exomes Reveal Population-Specific Differences in Disease-Related Genetic Variation

Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalog of local variability motivated the whole-exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one-third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including ∼10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes, and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies to distinguish real disease associations from population-specific polymorphisms.

Variation in NAT2 acetylation phenotypes is associated with differences in food-producing subsistence modes and ecoregions in Africa

Background

Dietary changes associated to shifts in subsistence strategies during human evolution may have induced new selective pressures on phenotypes, as currently held for lactase persistence. Similar hypotheses exist for arylamine N-acetyltransferase 2 (NAT2) mediated acetylation capacity, a well-known pharmacogenetic trait with wide inter-individual variation explained by polymorphisms in the NAT2 gene. The environmental causative factor (if any) driving its evolution is as yet unknown, but significant differences in prevalence of acetylation phenotypes are found between hunter-gatherer and food-producing populations, both in sub-Saharan Africa and worldwide, and between agriculturalists and pastoralists in Central Asia. These two subsistence strategies also prevail among sympatric populations of the African Sahel, but knowledge on NAT2 variation among African pastoral nomads was up to now very scarce. Here we addressed the hypothesis of different selective pressures associated to the agriculturalist or pastoralist lifestyles having acted on the evolution of NAT2 by sequencing the gene in 287 individuals from five pastoralist and one agriculturalist Sahelian populations.

Results

We show that the significant NAT2 genetic structure of African populations is mainly due to frequency differences of three major haplotypes, two of which are categorized as decreased function alleles (NAT2*5B and NAT2*6A), particularly common in populations living in arid environments, and one fast allele (NAT2*12A), more frequently detected in populations living in tropical humid environments. This genetic structure does associate more strongly with a classification of populations according to ecoregions than to subsistence strategies, mainly because most Sahelian and East African populations display little to no genetic differentiation between them, although both regions hold nomadic or semi-nomadic pastoralist and sedentary agriculturalist communities. Furthermore, we found significantly higher predicted proportions of slow acetylators in pastoralists than in agriculturalists, but also among food-producing populations living in the Sahelian and dry savanna zones than in those living in humid environments, irrespective of their mode of subsistence.

Conclusion

Our results suggest a possible independent influence of both the dietary habits associated with subsistence modes and the chemical environment associated with climatic zones and biomes on the evolution of NAT2 diversity in sub-Saharan African populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0543-6) contains supplementary material, which is available to authorized users.

Population genetic differentiation of height and body mass index across Europe

Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10(-8); BMI, P < 5.95 × 10(-4)), and we find an among-population genetic correlation for tall and slender individuals (r = -0.80, 95% CI = -0.95, -0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).

Genome-based nutrition: An intervention strategy for the prevention and treatment of obesity and nonalcoholic steatohepatitis

Obesity and nonalcoholic steatohepatitis are increasing in westernized countries, regardless of their geographic location. In Latin America, most countries, including Mexico, have a heterogeneous admixture genome with Amerindian, European and African ancestries. However, certain high allelic frequencies of several nutrient-related polymorphisms may have been achieved by past gene-nutrient interactions. Such interactions may have promoted the positive selection of variants adapted to regional food sources. At present, the unbalanced diet composition of the Mexicans has led the country to a 70% prevalence rate of overweightness and obesity due to substantial changes in food habits, among other factors. International guidelines and intervention strategies may not be adequate for all populations worldwide because they do not consider disparities in genetic and environmental factors, and thus there is a need for differential prevention and management strategies. Here, we provide the rationale for an intervention strategy for the prevention and management of obesity-related diseases such as non-alcoholic steatohepatitis based on a regionalized genome-based diet. The components required to design such a diet should focus on the specific ancestry of each population around the world and the convenience of consuming traditional ethnic food.

Immunogenetic factors affecting susceptibility of humans and rodents to hantaviruses and the clinical course of hantaviral disease in humans

We reviewed the associations of immunity-related genes with susceptibility of humans and rodents to hantaviruses, and with severity of hantaviral diseases in humans. Several class I and class II HLA haplotypes were linked with severe or benign hantavirus infections, and these haplotypes varied among localities and hantaviruses. The polymorphism of other immunity-related genes including the C4A gene and a high-producing genotype of TNF gene associated with severe PUUV infection. Additional genes that may contribute to disease or to PUUV infection severity include non-carriage of the interleukin-1 receptor antagonist (IL-1RA) allele 2 and IL-1β (-511) allele 2, polymorphisms of plasminogen activator inhibitor (PAI-1) and platelet GP1a. In addition, immunogenetic studies have been conducted to identify mechanisms that could be linked with the persistence/clearance of hantaviruses in reservoirs. Persistence was associated during experimental infections with an upregulation of anti-inflammatory responses. Using natural rodent population samples, polymorphisms and/or expression levels of several genes have been analyzed. These genes were selected based on the literature of rodent or human/hantavirus interactions (some Mhc class II genes, Tnf promoter, and genes encoding the proteins TLR4, TLR7, Mx2 and β3 integrin). The comparison of genetic differentiation estimated between bank vole populations sampled over Europe, at neutral and candidate genes, has allowed to evidence signatures of selection for Tnf, Mx2 and the Drb Mhc class II genes. Altogether, these results corroborated the hypothesis of an evolution of tolerance strategies in rodents. We finally discuss the importance of these results from the medical and epidemiological perspectives.

Population Genomics of Human Adaptation

Recent advances in genotyping technologies have facilitated genome-wide scans for natural selection. Identification of targets of natural selection will shed light on processes of human adaptation and evolution and could be important for identifying variation that influences both normal human phenotypic variation as well as disease susceptibility. Here we focus on studies of natural selection in modern humans who originated ~200,000 years go in Africa and migrated across the globe ~50,000 - 100,000 years ago. Movement into new environments, as well as changes in culture and technology including plant and animal domestication, resulted in local adaptation to diverse environments. We summarize statistical approaches for detecting targets of natural selection and for distinguishing the effects of demographic history from natural selection. On a genome-wide scale, immune-related genes appear to be major targets of positive selection. Genes associated with reproduction and fertility also appear to be fast evolving. Additional examples of recent human adaptation include genes associated with lactase persistence, eccrine glands, and response to hypoxia. Lastly, we emphasize the need to supplement scans of selection with functional studies to demonstrate the physiologic impact of candidate loci.