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      The Andean Adaptive Toolkit to Counteract High Altitude Maladaptation: Genome-Wide and Phenotypic Analysis of the Collas

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          Abstract

          During their migrations out of Africa, humans successfully colonised and adapted to a wide range of habitats, including extreme high altitude environments, where reduced atmospheric oxygen (hypoxia) imposes a number of physiological challenges. This study evaluates genetic and phenotypic variation in the Colla population living in the Argentinean Andes above 3500 m and compares it to the nearby lowland Wichí group in an attempt to pinpoint evolutionary mechanisms underlying adaptation to high altitude hypoxia. We genotyped 730,525 SNPs in 25 individuals from each population. In genome-wide scans of extended haplotype homozygosity Collas showed the strongest signal around VEGFB, which plays an essential role in the ischemic heart, and ELTD1, another gene crucial for heart development and prevention of cardiac hypertrophy. Moreover, pathway enrichment analysis showed an overrepresentation of pathways associated with cardiac morphology. Taken together, these findings suggest that Colla highlanders may have evolved a toolkit of adaptative mechanisms resulting in cardiac reinforcement, most likely to counteract the adverse effects of the permanently increased haematocrit and associated shear forces that characterise the Andean response to hypoxia. Regulation of cerebral vascular flow also appears to be part of the adaptive response in Collas. These findings are not only relevant to understand the evolution of hypoxia protection in high altitude populations but may also suggest new avenues for medical research into conditions where hypoxia constitutes a detrimental factor.

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          DAVID: Database for Annotation, Visualization, and Integrated Discovery.

          Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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            Arlequin (version 3.0): An integrated software package for population genetics data analysis

            Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.
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              Ensembl 2012

              The Ensembl project (http://www.ensembl.org) provides genome resources for chordate genomes with a particular focus on human genome data as well as data for key model organisms such as mouse, rat and zebrafish. Five additional species were added in the last year including gibbon (Nomascus leucogenys) and Tasmanian devil (Sarcophilus harrisii) bringing the total number of supported species to 61 as of Ensembl release 64 (September 2011). Of these, 55 species appear on the main Ensembl website and six species are provided on the Ensembl preview site (Pre!Ensembl; http://pre.ensembl.org) with preliminary support. The past year has also seen improvements across the project.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                31 March 2014
                : 9
                : 3
                : e93314
                Affiliations
                [1 ]Division of Biological Anthropology, University of Cambridge, Cambridge, Cambridgeshire, United Kingdom
                [2 ]Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom
                [3 ]Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, United Kingdom
                [4 ]School of Chemistry, University of East Anglia, Norwich, Norfolk, United Kingdom
                Universitat Pompeu Fabra, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: CAE MM TK. Performed the experiments: CAE TA LP AC. Analyzed the data: CAE TA LP AC. Contributed reagents/materials/analysis tools: CAE TA LP AC MM TK. Wrote the paper: CAE TK MM. Critically revised the manuscript: TA LP AC. Collected the data in the field: CAE MM. Obtained ethical approval: TK MM.

                Article
                PONE-D-14-00926
                10.1371/journal.pone.0093314
                3970967
                24686296
                24a7801c-0eb1-4ba9-a50b-8c6822e99088
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 January 2014
                : 3 March 2014
                Page count
                Pages: 12
                Funding
                This work was supported by European Research Council Starting Investigator grant http://erc.europa.eu/starting-grants (FP7-261213, TK), a starting investigator grant from the University of East Anglia (RC-158, MM) and the Young Explorers Grant from the National Geographic Society http://www.nationalgeographic.co.uk/explorers/grants-programs/young-explorers/ (8900-11, CE). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome Scans
                Evolutionary Biology
                Evolutionary Processes
                Convergent Evolution
                Evolutionary Adaptation
                Natural Selection
                Population Genetics
                Genetic Polymorphism
                Haplotypes
                Evolutionary Genetics
                Genetics
                Heredity
                Genetic Linkage
                Genomics
                Human Genetics
                Mutation
                Phenotypes
                Population Biology

                Uncategorized
                Uncategorized

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