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  • 1
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    Great ape genetic diversity and population history (2013)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2013-07-05
    Description: Most great ape genetic variation remains uncharacterized; however, its study is critical for understanding population history, recombination, selection and susceptibility to disease. Here we sequence to high coverage a total of 79 wild- and captive-born individuals representing all six great ape species and seven subspecies and report 88.8 million single nucleotide polymorphisms. Our analysis provides support for genetically distinct populations within each species, signals of gene flow, and the split of common chimpanzees into two distinct groups: Nigeria-Cameroon/western and central/eastern populations. We find extensive inbreeding in almost all wild populations, with eastern gorillas being the most extreme. Inferred effective population sizes have varied radically over time in different lineages and this appears to have a profound effect on the genetic diversity at, or close to, genes in almost all species. We discover and assign 1,982 loss-of-function variants throughout the human and great ape lineages, determining that the rate of gene loss has not been different in the human branch compared to other internal branches in the great ape phylogeny. This comprehensive catalogue of great ape genome diversity provides a framework for understanding evolution and a resource for more effective management of wild and captive great ape populations.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3822165/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3822165/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Prado-Martinez, Javier -- Sudmant, Peter H -- Kidd, Jeffrey M -- Li, Heng -- Kelley, Joanna L -- Lorente-Galdos, Belen -- Veeramah, Krishna R -- Woerner, August E -- O'Connor, Timothy D -- Santpere, Gabriel -- Cagan, Alexander -- Theunert, Christoph -- Casals, Ferran -- Laayouni, Hafid -- Munch, Kasper -- Hobolth, Asger -- Halager, Anders E -- Malig, Maika -- Hernandez-Rodriguez, Jessica -- Hernando-Herraez, Irene -- Prufer, Kay -- Pybus, Marc -- Johnstone, Laurel -- Lachmann, Michael -- Alkan, Can -- Twigg, Dorina -- Petit, Natalia -- Baker, Carl -- Hormozdiari, Fereydoun -- Fernandez-Callejo, Marcos -- Dabad, Marc -- Wilson, Michael L -- Stevison, Laurie -- Camprubi, Cristina -- Carvalho, Tiago -- Ruiz-Herrera, Aurora -- Vives, Laura -- Mele, Marta -- Abello, Teresa -- Kondova, Ivanela -- Bontrop, Ronald E -- Pusey, Anne -- Lankester, Felix -- Kiyang, John A -- Bergl, Richard A -- Lonsdorf, Elizabeth -- Myers, Simon -- Ventura, Mario -- Gagneux, Pascal -- Comas, David -- Siegismund, Hans -- Blanc, Julie -- Agueda-Calpena, Lidia -- Gut, Marta -- Fulton, Lucinda -- Tishkoff, Sarah A -- Mullikin, James C -- Wilson, Richard K -- Gut, Ivo G -- Gonder, Mary Katherine -- Ryder, Oliver A -- Hahn, Beatrice H -- Navarro, Arcadi -- Akey, Joshua M -- Bertranpetit, Jaume -- Reich, David -- Mailund, Thomas -- Schierup, Mikkel H -- Hvilsom, Christina -- Andres, Aida M -- Wall, Jeffrey D -- Bustamante, Carlos D -- Hammer, Michael F -- Eichler, Evan E -- Marques-Bonet, Tomas -- 090532/Wellcome Trust/United Kingdom -- 260372/European Research Council/International -- DP1 ES022577/ES/NIEHS NIH HHS/ -- DP1ES022577-04/DP/NCCDPHP CDC HHS/ -- GM100233/GM/NIGMS NIH HHS/ -- HG002385/HG/NHGRI NIH HHS/ -- R01 GM095882/GM/NIGMS NIH HHS/ -- R01 GM100233/GM/NIGMS NIH HHS/ -- R01 HG002385/HG/NHGRI NIH HHS/ -- R01_HG005226/HG/NHGRI NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2013 Jul 25;499(7459):471-5. doi: 10.1038/nature12228. Epub 2013 Jul 3.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Institut de Biologia Evolutiva, CSIC-Universitat Pompeu Fabra, PRBB, Doctor Aiguader 88, Barcelona, Catalonia 08003, Spain.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23823723" target="_blank"〉PubMed〈/a〉
    Keywords: Africa ; Animals ; Animals, Wild/genetics ; Animals, Zoo/genetics ; Asia, Southeastern ; Evolution, Molecular ; Gene Flow/genetics ; *Genetic Variation ; Genetics, Population ; Genome/genetics ; Gorilla gorilla/classification/genetics ; Hominidae/classification/*genetics ; Humans ; Inbreeding ; Pan paniscus/classification/genetics ; Pan troglodytes/classification/genetics ; Phylogeny ; Polymorphism, Single Nucleotide/genetics ; Population Density
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 2
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    Convergent evolution in European and Rroma populations reveals pressure exerted by plague on Toll-like receptors (2014)
    National Academy of Sciences
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    Publication Date: 2014-02-03
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 3
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    VCF2Networks: applying genotype networks to single-nucleotide variants data (2015)
    Oxford University Press
    Details
    Publication Date: 2015-01-29
    Description: : A wealth of large-scale genome sequencing projects opens the doors to new approaches to study the relationship between genotype and phenotype. One such opportunity is the possibility to apply genotype networks analysis to population genetics data. Genotype networks are a representation of the set of genotypes associated with a single phenotype, and they allow one to estimate properties such as the robustness of the phenotype to mutations, and the ability of its associated genotypes to evolve new adaptations. So far, though, genotype networks analysis has rarely been applied to population genetics data. To help fill this gap, here we present VCF2Networks, a tool to determine and study genotype network structure from single-nucleotide variant data. Availability and implementation: VCF2Networks is available at https://bitbucket.org/dalloliogm/vcf2networks . Contact: giovanni.dallolio@kcl.ac.uk Supplementary information : Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 4
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    Recent Positive Selection Has Acted on Genes Encoding Proteins with More Interactions within the Whole Human Interactome (2015)
    Oxford University Press
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    Publication Date: 2015-04-22
    Description: 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.
    Electronic ISSN: 1759-6653
    Topics: Biology
    Published by Oxford University Press
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  • 5
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    Hierarchical boosting: a machine-learning framework to detect and classify hard selective sweeps in human populations (2015)
    Oxford University Press
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    Publication Date: 2015-12-10
    Description: Motivation: Detecting positive selection in genomic regions is a recurrent topic in natural population genetic studies. However, there is little consistency among the regions detected in several genome-wide scans using different tests and/or populations. Furthermore, few methods address the challenge of classifying selective events according to specific features such as age, intensity or state (completeness). Results: We have developed a machine-learning classification framework that exploits the combined ability of some selection tests to uncover different polymorphism features expected under the hard sweep model, while controlling for population-specific demography. As a result, we achieve high sensitivity toward hard selective sweeps while adding insights about their completeness (whether a selected variant is fixed or not) and age of onset. Our method also determines the relevance of the individual methods implemented so far to detect positive selection under specific selective scenarios. We calibrated and applied the method to three reference human populations from The 1000 Genome Project to generate a genome-wide classification map of hard selective sweeps. This study improves detection of selective sweep by overcoming the classical selection versus no-selection classification strategy, and offers an explanation to the lack of consistency observed among selection tests when applied to real data. Very few signals were observed in the African population studied, while our method presents higher sensitivity in this population demography. Availability and implementation: The genome-wide results for three human populations from The 1000 Genomes Project and an R-package implementing the ‘Hierarchical Boosting’ framework are available at http://hsb.upf.edu/ . Contact: jaume.bertranpetit@upf.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 6
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    Network-Level and Population Genetics Analysis of the Insulin/TOR Signal Transduction Pathway Across Human Populations (2012)
    Oxford University Press
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    Publication Date: 2012-05-01
    Description: Genes and proteins rarely act in isolation, but they rather operate as components of complex networks of interacting molecules. Therefore, for understanding their evolution, it may be helpful to take into account the interaction networks in which they participate. It has been shown that selective constraints acting on genes depend on the position that they occupy in the network. Less understood is how the impact of local adaptation at the intraspecific level is affected by the network structure. Here, we analyzed the patterns of molecular evolution of 67 genes involved in the insulin/target of rapamycin (TOR) signal transduction pathway. This well-characterized pathway plays a key role in fundamental processes such as energetic metabolism, growth, reproduction, and aging and is involved in metabolic disorders such as obesity, insulin resistance, and diabetes. For that purpose, we combined genotype data from worldwide human populations with current knowledge of the structure and function of the pathway. We identified the footprint of recent positive selection in nine of the studied genomic regions. Most of the adaptation signals were observed among Middle East and North African, European, and Central South Asian populations. We found that positive selection preferentially targets the most central elements in the pathway, in contrast to previous observations in the whole human interactome. This observation indicates that the impact of positive selection on genes involved in the insulin/TOR pathway is affected by the pathway structure.
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 7
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    Convergent evolution in Europe [Immunology] (2014)
    National Academy of Sciences
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    Publication Date: 2014-02-19
    Description: Recent historical periods in Europe have been characterized by severe epidemic events such as plague, smallpox, or influenza that shaped the immune system of modern populations. This study aims to identify signals of convergent evolution of the immune system, based on the peculiar demographic history in which two populations with...
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 8
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    Natural Selection in the Great Apes (2016)
    Oxford University Press
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    Publication Date: 2016-11-09
    Description: Natural selection is crucial for the adaptation of populations to their environments. Here, we present the first global study of natural selection in the Hominidae (humans and great apes) based on genome-wide information from population samples representing all extant species (including most subspecies). Combining several neutrality tests we create a multi-species map of signatures of natural selection covering all major types of natural selection. We find that the estimated efficiency of both purifying and positive selection varies between species and is significantly correlated with their long-term effective population size. Thus, even the modest differences in population size among the closely related Hominidae lineages have resulted in differences in their ability to remove deleterious alleles and to adapt to changing environments. Most signatures of balancing and positive selection are species-specific, with signatures of balancing selection more often being shared among species. We also identify loci with evidence of positive selection across several lineages. Notably, we detect signatures of positive selection in several genes related to brain function, anatomy, diet and immune processes. Our results contribute to a better understanding of human evolution by putting the evidence of natural selection in humans within its larger evolutionary context. The global map of natural selection in our closest living relatives is available as an interactive browser at http://tinyurl.com/nf8qmzh .
    Print ISSN: 0737-4038
    Electronic ISSN: 1537-1719
    Topics: Biology
    Published by Oxford University Press
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  • 9
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    1000 Genomes Selection Browser 1.0: a genome browser dedicated to signatures of natural selection in modern humans (2013)
    Oxford University Press
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    Publication Date: 2013-12-29
    Description: Searching for Darwinian selection in natural populations has been the focus of a multitude of studies over the last decades. Here we present the 1000 Genomes Selection Browser 1.0 ( http://hsb.upf.edu ) as a resource for signatures of recent natural selection in modern humans. We have implemented and applied a large number of neutrality tests as well as summary statistics informative for the action of selection such as Tajima’s D, CLR, Fay and Wu’s H, Fu and Li’s F* and D*, XPEHH, iHH, iHS, F ST , DAF and XPCLR among others to low coverage sequencing data from the 1000 genomes project (Phase 1; release April 2012). We have implemented a publicly available genome-wide browser to communicate the results from three different populations of West African, Northern European and East Asian ancestry (YRI, CEU, CHB). Information is provided in UCSC-style format to facilitate the integration with the rich UCSC browser tracks and an access page is provided with instructions and for convenient visualization. We believe that this expandable resource will facilitate the interpretation of signals of selection on different temporal, geographical and genomic scales.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 10
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    Worldwide genetic variation at the 3′ untranslated region of the HLA-G gene: balancing selection influencing genetic diversity (2013)
    Springer Nature
    Details
    Publication Date: 2013-12-19
    Print ISSN: 1466-4879
    Electronic ISSN: 1476-5470
    Topics: Biology , Medicine
    Published by Springer Nature
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