61 research outputs found

    Evidence of Early-Stage Selection on EPAS1 and GPR126 Genes in Andean High Altitude Populations.

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    The aim of this study is to identify genetic variants that harbour signatures of recent positive selection and may facilitate physiological adaptations to hypobaric hypoxia. To achieve this, we conducted whole genome sequencing and lung function tests in 19 Argentinean highlanders (>3500 m) comparing them to 16 Native American lowlanders. We developed a new statistical procedure using a combination of population branch statistics (PBS) and number of segregating sites by length (nSL) to detect beneficial alleles that arose since the settlement of the Andes and are currently present in 15-50% of the population. We identified two missense variants as significant targets of selection. One of these variants, located within the GPR126 gene, has been previously associated with the forced expiratory volume/forced vital capacity ratio. The other novel missense variant mapped to the EPAS1 gene encoding the hypoxia inducible factor 2α. EPAS1 is known to be the major selection candidate gene in Tibetans. The derived allele of GPR126 is associated with lung function in our sample of highlanders (p < 0.05). These variants may contribute to the physiological adaptations to hypobaric hypoxia, possibly by altering lung function. The new statistical approach might be a useful tool to detect selected variants in population studies

    interPopula: a Python API to access the HapMap Project dataset

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    <p>Abstract</p> <p>Background</p> <p>The HapMap project is a publicly available catalogue of common genetic variants that occur in humans, currently including several million SNPs across 1115 individuals spanning 11 different populations. This important database does not provide any programmatic access to the dataset, furthermore no standard relational database interface is provided.</p> <p>Results</p> <p>interPopula is a Python API to access the HapMap dataset. interPopula provides integration facilities with both the Python ecology of software (e.g. Biopython and matplotlib) and other relevant human population datasets (e.g. Ensembl gene annotation and UCSC Known Genes). A set of guidelines and code examples to address possible inconsistencies across heterogeneous data sources is also provided.</p> <p>Conclusions</p> <p>interPopula is a straightforward and flexible Python API that facilitates the construction of scripts and applications that require access to the HapMap dataset.</p

    LOSITAN: A workbench to detect molecular adaptation based on a Fst-outlier method

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    <p>Abstract</p> <p>Background</p> <p>Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user.</p> <p>Results</p> <p>Here we present LOSITAN, a selection detection workbench based on a well evaluated <it>F</it><sub><it>st</it></sub>-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral <it>F</it><sub><it>st</it></sub>), provides data import and export functions, iterative contour smoothing and generation of graphics in a easy to use graphical user interface. LOSITAN is able to use modern multi-core processor architectures by locally parallelizing fdist, reducing computation time by half in current dual core machines and with almost linear performance gains in machines with more cores.</p> <p>Conclusion</p> <p>LOSITAN makes selection detection feasible to a much wider range of users, even for large population genomic datasets, by both providing an easy to use interface and essential functionality to complete the whole selection detection process.</p

    Plasmodium vivax Diversity and Population Structure across Four Continents

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    Plasmodium vivax is the geographically most widespread human malaria parasite. To analyze patterns of microsatellite diversity and population structure across countries of different transmission intensity, genotyping data from 11 microsatellite markers was either generated or compiled from 841 isolates from four continents collected in 1999–2008. Diversity was highest in South-East Asia (mean allelic richness 10.0–12.8), intermediate in the South Pacific (8.1–9.9) Madagascar and Sudan (7.9–8.4), and lowest in South America and Central Asia (5.5–7.2). A reduced panel of only 3 markers was sufficient to identify approx. 90% of all haplotypes in South Pacific, African and SE-Asian populations, but only 60–80% in Latin American populations, suggesting that typing of 2–6 markers, depending on the level of endemicity, is sufficient for epidemiological studies. Clustering analysis showed distinct clusters in Peru and Brazil, but little sub-structuring was observed within Africa, SE-Asia or the South Pacific. Isolates from Uzbekistan were exceptional, as a near-clonal parasite population was observed that was clearly separated from all other populations (FST>0.2). Outside Central Asia FST values were highest (0.11–0.16) between South American and all other populations, and lowest (0.04–0.07) between populations from South-East Asia and the South Pacific. These comparisons between P. vivax populations from four continents indicated that not only transmission intensity, but also geographical isolation affect diversity and population structure. However, the high effective population size results in slow changes of these parameters. This persistency must be taken into account when assessing the impact of control programs on the genetic structure of parasite populations

    Massive introgression drives species radiation at the range limit of Anopheles gambiae

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    Impacts of introgressive hybridisation may range from genomic erosion and species collapse to rapid adaptation and speciation but opportunities to study these dynamics are rare. We investigated the extent, causes and consequences of a hybrid zone between Anopheles coluzzii and Anopheles gambiae in Guinea-Bissau, where high hybridisation rates appear to be stable at least since the 1990s. Anopheles gambiae was genetically partitioned into inland and coastal subpopulations, separated by a central region dominated by A. coluzzii. Surprisingly, whole genome sequencing revealed that the coastal region harbours a hybrid form characterised by an A. gambiae-like sex chromosome and massive introgression of A. coluzzii autosomal alleles. Local selection on chromosomal inversions may play a role in this process, suggesting potential for spatiotemporal stability of the coastal hybrid form and providing resilience against introgression of medically-important loci and traits, found to be more prevalent in inland A. gambiae

    Positive selection of AS3MT to arsenic water in Andean populations.

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    Arsenic is a carcinogen associated with skin lesions and cardiovascular diseases. The Colla population from the Puna region in Northwest Argentinean is exposed to levels of arsenic in drinking water exceeding the recommended maximum by a factor of 20. Yet, they thrive in this challenging environment since thousands of years and therefore we hypothesize strong selection signatures in genes involved in arsenic metabolism. We analyzed genome-wide genotype data for 730,000 loci in 25 Collas, considering 24 individuals of the neighbouring CalchaquĂ­es and 24 WichĂ­ from the Gran Chaco region in the Argentine province of Salta as control groups. We identified a strong signal of positive selection in the main arsenic methyltransferase AS3MT gene, which has been previously associated with lower concentrations of the most toxic product of arsenic metabolism monomethylarsonic acid. This study confirms recent studies reporting selection signals in the AS3MT gene albeit using different samples, tests and control populations

    Local selection in the presence of high levels of gene flow: Evidence of heterogeneous insecticide selection pressure across Ugandan Culex quinquefasciatus populations

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    Background: Culex quinquefasciatus collected in Uganda, where no vector control interventions directly targeting this species have been conducted, was used as a model to determine if it is possible to detect heterogeneities in selection pressure driven by insecticide application targeting other insect species. Methodology/Principal findings: Population genetic structure was assessed through microsatellite analysis, and the impact of insecticide pressure by genotyping two target-site mutations, Vgsc-1014F of the voltage-gated sodium channel target of pyrethroid and DDT insecticides, and Ace1-119S of the acetylcholinesterase gene, target of carbamate and organophosphate insecticides. No significant differences in genetic diversity were observed among populations by microsatellite markers with HE ranging from 0.597 to 0.612 and low, but significant, genetic differentiation among populations (FST = 0.019, P = 0.001). By contrast, the insecticide-resistance markers display heterogeneous allelic distributions with significant differences detected between Central Ugandan (urban) populations relative to Eastern and Southwestern (rural) populations. In the central region, a frequency of 62% for Vgsc-1014F, and 32% for the Ace1-119S resistant allele were observed. Conversely, in both Eastern and Southwestern regions the Vgsc-1014F alleles were close to fixation, whilst Ace1-119S allele frequency was 12% (although frequencies may be underestimated due to copy number variation at both loci). Conclusions/Significance: Taken together, the microsatellite and both insecticide resistance target-site markers provide evidence that in the face of intense gene flow among populations, disjunction in resistance frequencies arise due to intense local selection pressures despite an absence of insecticidal control interventions targeting Culex

    Genomic analyses inform on migration events during the peopling of Eurasia

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    High-coverage whole-genome sequence studies have so far focused\ud on a limited number1 of geographically restricted populations2–5,\ud or been targeted at specific diseases, such as cancer6. Nevertheless,\ud the availability of high-resolution genomic data has led to the\ud development of new methodologies for inferring population\ud history7–9 and refuelled the debate on the mutation rate in humans10.\ud Here we present the Estonian Biocentre Human Genome Diversity\ud Panel (EGDP), a dataset of 483 high-coverage human genomes\ud from 148 populations worldwide, including 379 new genomes from\ud 125 populations, which we group into diversity and selection\ud sets. We analyse this dataset to refine estimates of continent-wide\ud patterns of heterozygosity, long- and short-distance gene flow, archaic\ud admixture, and changes in effective population size through time as\ud well as for signals of positive or balancing selection. We find a genetic\ud signature in present-day Papuans that suggests that at least 2% of\ud their genome originates from an early and largely extinct expansion\ud of anatomically modern humans (AMHs) out of Africa. Together\ud with evidence from the western Asian fossil record11, and admixture\ud between AMHs and Neanderthals predating the main Eurasian\ud expansion12, our results contribute to the mounting evidence for\ud the presence of AMHs out of Africa earlier than 75,000 years ago

    Genomic analyses inform on migration events during the peopling of Eurasia.

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    High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.Support was provided by: Estonian Research Infrastructure Roadmap grant no 3.2.0304.11-0312; Australian Research Council Discovery grants (DP110102635 and DP140101405) (D.M.L., M.W. and E.W.); Danish National Research Foundation; the Lundbeck Foundation and KU2016 (E.W.); ERC Starting Investigator grant (FP7 - 261213) (T.K.); Estonian Research Council grant PUT766 (G.C. and M.K.); EU European Regional Development Fund through the Centre of Excellence in Genomics to Estonian Biocentre (R.V.; M.Me. and A.Me.), and Centre of Excellence for Genomics and Translational Medicine Project No. 2014-2020.4.01.15-0012 to EGC of UT (A.Me.) and EBC (M.Me.); Estonian Institutional Research grant IUT24-1 (L.S., M.J., A.K., B.Y., K.T., C.B.M., Le.S., H.Sa., S.L., D.M.B., E.M., R.V., G.H., M.K., G.C., T.K. and M.Me.) and IUT20-60 (A.Me.); French Ministry of Foreign and European Affairs and French ANR grant number ANR-14-CE31-0013-01 (F.-X.R.); Gates Cambridge Trust Funding (E.J.); ICG SB RAS (No. VI.58.1.1) (D.V.L.); Leverhulme Programme grant no. RP2011-R-045 (A.B.M., P.G. and M.G.T.); Ministry of Education and Science of Russia; Project 6.656.2014/K (S.A.F.); NEFREX grant funded by the European Union (People Marie Curie Actions; International Research Staff Exchange Scheme; call FP7-PEOPLE-2012-IRSES-number 318979) (M.Me., G.H. and M.K.); NIH grants 5DP1ES022577 05, 1R01DK104339-01, and 1R01GM113657-01 (S.Tis.); Russian Foundation for Basic Research (grant N 14-06-00180a) (M.G.); Russian Foundation for Basic Research; grant 16-04-00890 (O.B. and E.B); Russian Science Foundation grant 14-14-00827 (O.B.); The Russian Foundation for Basic Research (14-04-00725-a), The Russian Humanitarian Scientific Foundation (13-11-02014) and the Program of the Basic Research of the RAS Presidium “Biological diversity” (E.K.K.); Wellcome Trust and Royal Society grant WT104125AIA & the Bristol Advanced Computing Research Centre (http://www.bris.ac.uk/acrc/) (D.J.L.); Wellcome Trust grant 098051 (Q.A.; C.T.-S. and Y.X.); Wellcome Trust Senior Research Fellowship grant 100719/Z/12/Z (M.G.T.); Young Explorers Grant from the National Geographic Society (8900-11) (C.A.E.); ERC Consolidator Grant 647787 ‘LocalAdaptatio’ (A.Ma.); Program of the RAS Presidium “Basic research for the development of the Russian Arctic” (B.M.); Russian Foundation for Basic Research grant 16-06-00303 (E.B.); a Rutherford Fellowship (RDF-10-MAU-001) from the Royal Society of New Zealand (M.P.C.)
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