Natural selection and infectious disease in human populations.
Ontology highlight
ABSTRACT:
SUBMITTER: Karlsson EK
PROVIDER: S-EPMC4912034 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:What evolutionary forces shape genes that contribute to the risk of human disease? Do similar selective pressures act on alleles that underlie simple versus complex disorders [1-3]? Answers to these questions will shed light onto the origin of human disorders (e.g., [4]) and help to predict the population frequencies of alleles that contribute to disease risk, with important implications for the efficient design of mapping studies [5-7]. As a first step toward addressing these questions, we created a hand-curated version of the Mendelian Inheritance in Man database (OMIM). We then examined selective pressures on Mendelian-disease genes, genes that contribute to complex-disease risk, and genes known to be essential in mouse by analyzing patterns of human polymorphism and of divergence between human and rhesus macaque. We found that Mendelian-disease genes appear to be under widespread purifying selection, especially when the disease mutations are dominant (rather than recessive). In contrast, the class of genes that influence complex-disease risk shows little signs of evolutionary conservation, possibly because this category includes targets of both purifying and positive selection.
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Project description: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.
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Project description:Bacteria produce a range of molecules that are secreted from the cell and can provide a benefit to the local population of cells. Laboratory experiments have suggested that these "public goods" molecules represent a form of cooperation, favored because they benefit closely related cells (kin selection). However, there is a relative lack of data demonstrating kin selection for cooperation in natural populations of bacteria. We used molecular population genetics to test for signatures of kin selection at the genomic level in natural populations of the opportunistic pathogen Pseudomonas aeruginosa We found consistent evidence from multiple traits that genes controlling putatively cooperative traits have higher polymorphism and greater divergence and are more likely to harbor deleterious mutations relative to genes controlling putatively private traits, which are expressed at similar rates. These patterns suggest that cooperative traits are controlled by kin selection, and we estimate that the relatedness for social interactions in P. aeruginosa is r = 0.84. More generally, our results demonstrate how molecular population genetics can be used to study the evolution of cooperation in natural populations.
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Project description:BackgroundAn increasing number of infectious disease models consider demographic change in the host population, but the demographic methods and assumptions vary considerably. We carry out a systematic review of the methods and assumptions used to incorporate dynamic populations in infectious disease models.MethodsWe systematically searched PubMed and Web of Science for articles on infectious disease transmission in dynamic host populations. We screened the articles and extracted data in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).ResultsWe identified 46 articles containing 53 infectious disease models with dynamic populations. Population dynamics were modelled explicitly in 71% of the disease transmission models using cohort-component-based models (CCBMs) or individual-based models (IBMs), while 29% used population prospects as an external input. Fertility and mortality were in most cases age- or age-sex-specific, but several models used crude fertility rates (40%). Households were incorporated in 15% of the models, which were IBMs except for one model using external population prospects. Finally, 17% of the infectious disease models included demographic sensitivity analyses.ConclusionsWe find that most studies model fertility, mortality and migration explicitly. Moreover, population-level modelling was more common than IBMs. Demographic characteristics beyond age and sex are cumbersome to implement in population-level models and were for that reason only incorporated in IBMs. Several IBMs included households and networks, but the granularity of the underlying demographic processes was often similar to that of CCBMs. We describe the implications of the most common assumptions and discuss possible extensions.
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Project description:The glycine amidinotransferase gene (GATM) plays a vital role in energy metabolism in muscle tissues and is associated with multiple clinically important phenotypes. However, the genetic diversity of the GATM gene remains poorly understood within and between human populations. Here we analyzed the 1,000 Genomes Project data through population genetics approaches and observed significant genetic diversity across the GATM gene among various continental human populations. We observed considerable variations in GATM allele frequencies and haplotype composition among different populations. Substantial genetic differences were observed between East Asian and European populations (FST = 0.56). In addition, the frequency of a distinct major GATM haplotype in these groups was congruent with population-wide diversity at this locus. Furthermore, we identified GATM as the top differentiated gene compared to the other statin drug response-associated genes. Composite multiple analyses identified signatures of positive selection at the GATM locus, which was estimated to have occurred around 850 generations ago in European populations. As GATM catalyzes the key step of creatine biosynthesis involved in energy metabolism, we speculate that the European prehistorical demographic transition from hunter-gatherer to farming cultures was the driving force of selection that fulfilled creatine-based metabolic requirement of the populations.
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Project description:Polymorphisms in the first intron of FTO have been robustly replicated for associations with obesity. In the Sorbs, a Slavic population resident in Germany, the strongest effect on body mass index (BMI) was found for a variant in the third intron of FTO (rs17818902). Since this may indicate population specific effects of FTO variants, we initiated studies testing FTO for signatures of selection in vertebrate species and human populations.First, we analyzed the coding region of 35 vertebrate FTO orthologs with Phylogenetic Analysis by Maximum Likelihood (PAML, ? = dN/dS) to screen for signatures of selection among species. Second, we investigated human population (Europeans/CEU, Yoruba/YRI, Chinese/CHB, Japanese/JPT, Sorbs) SNP data for footprints of selection using DnaSP version 4.5 and the Haplotter/PhaseII. Finally, using ConSite we compared transcription factor (TF) binding sites at sequences harbouring FTO SNPs in intron three.PAML analyses revealed strong conservation in coding region of FTO (?<1). Sliding-window results from population genetic analyses provided highly significant (p<0.001) signatures for balancing selection specifically in the third intron (e.g. Tajima's D in Sorbs = 2.77). We observed several alterations in TF binding sites, e.g. TCF3 binding site introduced by the rs17818902 minor allele.Population genetic analysis revealed signatures of balancing selection at the FTO locus with a prominent signal in intron three, a genomic region with strong association with BMI in the Sorbs. Our data support the hypothesis that genes associated with obesity may have been under evolutionary selective pressure.
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Project description:Population structure can provide novel insight into the human past, and recognizing and correcting for such stratification is a practical concern in gene mapping by many association methodologies. We investigate these patterns, primarily through principal component (PC) analysis of whole genome SNP polymorphism, in 2099 individuals from populations of Northern European origin (Ireland, United Kingdom, Netherlands, Denmark, Sweden, Finland, Australia, and HapMap European-American). The major trends (PC1 and PC2) demonstrate an ability to detect geographic substructure, even over a small area like the British Isles, and this information can then be applied to finely dissect the ancestry of the European-Australian and European-American samples. They simultaneously point to the importance of considering population stratification in what might be considered a small homogeneous region. There is evidence from F(ST)-based analysis of genic and nongenic SNPs that differential positive selection has operated across these populations despite their short divergence time and relatively similar geographic and environmental range. The pressure appears to have been focused on genes involved in immunity, perhaps reflecting response to infectious disease epidemic. Such an event may explain a striking selective sweep centered on the rs2508049-G allele, close to the HLA-G gene on chromosome 6. Evidence of the sweep extends over a 8-Mb/3.5-cM region. Overall, the results illustrate the power of dense genotype and sample data to explore regional population variation, the events that have crafted it, and their implications in both explaining disease prevalence and mapping these genes by association.
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Project description:Analyzing genetic variation of human populations for detecting loci that have been affected by positive natural selection is important for understanding adaptive history and phenotypic variation in humans. In this study, we analyzed recent positive selection in Northern Europe from genome-wide data sets of 250 000 and 500 000 single-nucleotide polymorphisms (SNPs) in a total of 999 individuals from Great Britain, Northern Germany, Eastern and Western Finland, and Sweden. Coalescent simulations were used for demonstrating that the integrated haplotype score (iHS) and long-range haplotype (LRH) statistics have sufficient power in genome-wide data sets of different sample sizes and SNP densities. Furthermore, the behavior of the F(ST) statistic in closely related populations was characterized by allele frequency simulations. In the analysis of the North European data set, 60 regions in the genome showed strong signs of recent positive selection. Out of these, 21 regions have not been discovered in previous scans, and many contain genes with interesting functions (eg, RAB38, INFG, NOS1AP, and APOE). In the putatively selected regions, we observed a statistically significant overrepresentation of genetic association with complex disease, which emphasizes the importance of the analysis of positive selection in understanding the evolution of human disease. Altogether, this study demonstrates the potential of genome-wide data sets to discover loci that lie behind evolutionary adaptation in different human populations.
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