ALBERT

Description: There are two competing hypotheses for the origin of the Indo-European language family. The conventional view places the homeland in the Pontic steppes about 6000 years ago. An alternative hypothesis claims that the languages spread from Anatolia with the expansion of farming 8000 to 9500 years ago. We used Bayesian phylogeographic approaches, together with basic vocabulary data from 103 ancient and contemporary Indo-European languages, to explicitly model the expansion of the family and test these hypotheses. We found decisive support for an Anatolian origin over a steppe origin. Both the inferred timing and root location of the Indo-European language trees fit with an agricultural expansion from Anatolia beginning 8000 to 9500 years ago. These results highlight the critical role that phylogeographic inference can play in resolving debates about human prehistory.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112997/" 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/PMC4112997/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bouckaert, Remco -- Lemey, Philippe -- Dunn, Michael -- Greenhill, Simon J -- Alekseyenko, Alexander V -- Drummond, Alexei J -- Gray, Russell D -- Suchard, Marc A -- Atkinson, Quentin D -- 260864/European Research Council/International -- R01 GM086887/GM/NIGMS NIH HHS/ -- R01 HG006139/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2012 Aug 24;337(6097):957-60. doi: 10.1126/science.1219669.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Computer Science, University of Auckland, Auckland 1142, New Zealand.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22923579" target="_blank"〉PubMed〈/a〉

Description: The global epidemic of multidrug-resistant Salmonella Typhimurium DT104 provides an important example, both in terms of the agent and its resistance, of a widely disseminated zoonotic pathogen. Here, with an unprecedented national collection of isolates collected contemporaneously from humans and animals and including a sample of internationally derived isolates, we have used whole-genome sequencing to dissect the phylogenetic associations of the bacterium and its antimicrobial resistance genes through the course of an epidemic. Contrary to current tenets supporting a single homogeneous epidemic, we demonstrate that the bacterium and its resistance genes were largely maintained within animal and human populations separately and that there was limited transmission, in either direction. We also show considerable variation in the resistance profiles, in contrast to the largely stable bacterial core genome, which emphasizes the critical importance of integrated genotypic data sets in understanding the ecology of bacterial zoonoses and antimicrobial resistance.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4012302/" 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/PMC4012302/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Mather, A E -- Reid, S W J -- Maskell, D J -- Parkhill, J -- Fookes, M C -- Harris, S R -- Brown, D J -- Coia, J E -- Mulvey, M R -- Gilmour, M W -- Petrovska, L -- de Pinna, E -- Kuroda, M -- Akiba, M -- Izumiya, H -- Connor, T R -- Suchard, M A -- Lemey, P -- Mellor, D J -- Haydon, D T -- Thomson, N R -- 098051/Wellcome Trust/United Kingdom -- 260864/European Research Council/International -- AI107034/AI/NIAID NIH HHS/ -- HG006139/HG/NHGRI NIH HHS/ -- R01 AI107034/AI/NIAID NIH HHS/ -- R01 GM086887/GM/NIGMS NIH HHS/ -- R01 HG006139/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2013 Sep 27;341(6153):1514-7. doi: 10.1126/science.1240578. Epub 2013 Sep 12.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24030491" target="_blank"〉PubMed〈/a〉

Description: Understanding the spatiotemporal patterns of emergence and circulation of new human seasonal influenza virus variants is a key scientific and public health challenge. The global circulation patterns of influenza A/H3N2 viruses are well characterized, but the patterns of A/H1N1 and B viruses have remained largely unexplored. Here we show that the global circulation patterns of A/H1N1 (up to 2009), B/Victoria, and B/Yamagata viruses differ substantially from those of A/H3N2 viruses, on the basis of analyses of 9,604 haemagglutinin sequences of human seasonal influenza viruses from 2000 to 2012. Whereas genetic variants of A/H3N2 viruses did not persist locally between epidemics and were reseeded from East and Southeast Asia, genetic variants of A/H1N1 and B viruses persisted across several seasons and exhibited complex global dynamics with East and Southeast Asia playing a limited role in disseminating new variants. The less frequent global movement of influenza A/H1N1 and B viruses coincided with slower rates of antigenic evolution, lower ages of infection, and smaller, less frequent epidemics compared to A/H3N2 viruses. Detailed epidemic models support differences in age of infection, combined with the less frequent travel of children, as probable drivers of the differences in the patterns of global circulation, suggesting a complex interaction between virus evolution, epidemiology, and human behaviour.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4499780/" 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/PMC4499780/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bedford, Trevor -- Riley, Steven -- Barr, Ian G -- Broor, Shobha -- Chadha, Mandeep -- Cox, Nancy J -- Daniels, Rodney S -- Gunasekaran, C Palani -- Hurt, Aeron C -- Kelso, Anne -- Klimov, Alexander -- Lewis, Nicola S -- Li, Xiyan -- McCauley, John W -- Odagiri, Takato -- Potdar, Varsha -- Rambaut, Andrew -- Shu, Yuelong -- Skepner, Eugene -- Smith, Derek J -- Suchard, Marc A -- Tashiro, Masato -- Wang, Dayan -- Xu, Xiyan -- Lemey, Philippe -- Russell, Colin A -- 093488/Wellcome Trust/United Kingdom -- 093488/Z/10/Z/Wellcome Trust/United Kingdom -- 095831/Wellcome Trust/United Kingdom -- 260864/European Research Council/International -- MR/J008761/1/Medical Research Council/United Kingdom -- R01 AI 107034/AI/NIAID NIH HHS/ -- R01 AI107034/AI/NIAID NIH HHS/ -- R01 TW008246/TW/FIC NIH HHS/ -- R01 TW008246-01/TW/FIC NIH HHS/ -- U01 GM110721/GM/NIGMS NIH HHS/ -- U01 GM110721-01/GM/NIGMS NIH HHS/ -- U117512723/Medical Research Council/United Kingdom -- U54 GM111274/GM/NIGMS NIH HHS/ -- England -- Nature. 2015 Jul 9;523(7559):217-20. doi: 10.1038/nature14460. Epub 2015 Jun 8.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. ; 1] MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London SW7 2AZ, UK [2] Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA. ; World Health Organization (WHO) Collaborating Centre for Reference and Research on Influenza, Melbourne, Victoria 3000, Australia. ; SGT Medical College, Hospital and Research Institute, Village Budhera, District Gurgaon, Haryana 122505, India. ; National Institute of Virology, Pune 411001, India. ; WHO Collaborating Center for Reference and Research on Influenza, Centers for Disease Control and Prevention, Atlanta, Georgia 30329, USA. ; WHO Collaborating Center for Reference and Research on Influenza, Medical Research Council National Institute for Medical Research (NIMR), London NW7 1AA, UK. ; King Institute of Preventive Medicine and Research, Guindy, Chennai 600032, India. ; 1] World Health Organization (WHO) Collaborating Centre for Reference and Research on Influenza, Melbourne, Victoria 3000, Australia [2] Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria 3010, Australia. ; Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK. ; WHO Collaborating Center for Reference and Research on Influenza, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China. ; WHO Collaborating Center for Reference and Research on Influenza, National Institute of Infectious Diseases, Tokyo 208-0011, Japan. ; 1] Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA [2] Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK [3] Centre for Immunology, Infection and Evolution, University of Edinburgh, Edinburgh EH9 3FL, UK. ; 1] Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK [2] Department of Viroscience, Erasmus Medical Center, 3015 Rotterdam, The Netherlands. ; 1] Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, California 90095, USA [2] Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, California 90095, USA [3] Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, California 90095, USA. ; Department of Microbiology and Immunology, Rega Institute, KU Leuven - University of Leuven, 3000 Leuven, Belgium. ; Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26053121" target="_blank"〉PubMed〈/a〉

Description: Thirty years after the discovery of HIV-1, the early transmission, dissemination, and establishment of the virus in human populations remain unclear. Using statistical approaches applied to HIV-1 sequence data from central Africa, we show that from the 1920s Kinshasa (in what is now the Democratic Republic of Congo) was the focus of early transmission and the source of pre-1960 pandemic viruses elsewhere. Location and dating estimates were validated using the earliest HIV-1 archival sample, also from Kinshasa. The epidemic histories of HIV-1 group M and nonpandemic group O were similar until ~1960, after which group M underwent an epidemiological transition and outpaced regional population growth. Our results reconstruct the early dynamics of HIV-1 and emphasize the role of social changes and transport networks in the establishment of this virus in human populations.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254776/" 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/PMC4254776/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Faria, Nuno R -- Rambaut, Andrew -- Suchard, Marc A -- Baele, Guy -- Bedford, Trevor -- Ward, Melissa J -- Tatem, Andrew J -- Sousa, Joao D -- Arinaminpathy, Nimalan -- Pepin, Jacques -- Posada, David -- Peeters, Martine -- Pybus, Oliver G -- Lemey, Philippe -- 092807/Wellcome Trust/United Kingdom -- 095831/Wellcome Trust/United Kingdom -- MR/K010174/1/Medical Research Council/United Kingdom -- R01 AI050529/AI/NIAID NIH HHS/ -- R01 HG006139/HG/NHGRI NIH HHS/ -- R37 AI050529/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2014 Oct 3;346(6205):56-61. doi: 10.1126/science.1256739. Epub 2014 Oct 2.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK. KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Minderbroedersstraat 10, B-3000 Leuven, Belgium. ; Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Kings Buildings, West Mains Road, Edinburgh EH9 3JT, UK. Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA. Centre for Immunity, Infection and Evolution, University of Edinburgh, Kings Buildings, West Mains Road, Edinburgh EH9 3JT, UK. ; Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095-1766, USA. Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA 90095-1766, USA. ; KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Minderbroedersstraat 10, B-3000 Leuven, Belgium. ; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. ; Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Kings Buildings, West Mains Road, Edinburgh EH9 3JT, UK. ; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA. Department of Geography and Environment, University of Southampton, Highfield, Southampton, UK. ; KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Minderbroedersstraat 10, B-3000 Leuven, Belgium. Centro de Malaria e outras Doencas Tropicais and Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Rua da Junqueira 100, 1349-008 Lisbon, Portugal. ; Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK. ; Department of Microbiology and Infectious Diseases, Universite de Sherbrooke, CHUS, 3001, 12eme Avenue Nord, Sherbrooke, QC J1H 5N4, Canada. ; Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo 36310, Spain. ; Laboratoire Retrovirus, UMI233, Institut de Recherche pour le Developpement and University of Montpellier, 911 Avenue Agropolis, BP5045, 34032 Montpellier, France. ; Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK. philippe.lemey@rega.kuleuven.be oliver.pybus@zoo.ox.ac.uk. ; KU Leuven - University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Minderbroedersstraat 10, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be oliver.pybus@zoo.ox.ac.uk.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25278604" target="_blank"〉PubMed〈/a〉

Description: Model-based phylogenetic reconstructions increasingly consider spatial or phenotypic traits in conjunction with sequence data to study evolutionary processes. Alongside parameter estimation, visualization of ancestral reconstructions represents an integral part of these analyses. Here, we present a complete overhaul of the spatial phylogenetic reconstruction of evolutionary dynamics software, now called SpreaD3 to emphasize the use of data-driven documents, as an analysis and visualization package that primarily complements Bayesian inference in BEAST ( http://beast.bio.ed.ac.uk , last accessed 9 May 2016). The integration of JavaScript D3 libraries ( www.d3.org , last accessed 9 May 2016) offers novel interactive web-based visualization capacities that are not restricted to spatial traits and extend to any discrete or continuously valued trait for any organism of interest.

Description: Motivation: Statistical methods for comparing relative rates of synonymous and non - synonymous substitutions maintain a central role in detecting positive selection. To identify selection, researchers often estimate the ratio of these relative rates ( ) at individual alignment sites. Fitting a codon substitution model that captures heterogeneity in across sites provides a reliable way to perform such estimation, but it remains computationally prohibitive for massive datasets. By using crude estimates of the numbers of synonymous and non - synonymous substitutions at each site, counting approaches scale well to large datasets, but they fail to account for ancestral state reconstruction uncertainty and to provide site-specific estimates. Results: We propose a hybrid solution that borrows the computational strength of counting methods, but augments these methods with empirical Bayes modeling to produce a relatively fast and reliable method capable of estimating site-specific values in large datasets. Importantly, our hybrid approach, set in a Bayesian framework, integrates over the posterior distribution of phylogenies and ancestral reconstructions to quantify uncertainty about site-specific estimates. Simulations demonstrate that this method competes well with more - principled statistical procedures and , in some cases , even outperforms them. We illustrate the utility of our method using human immunodeficiency virus, feline panleukopenia and canine parvovirus evolution examples. Availability: Renaissance counting is implemented in the development branch of BEAST, freely available at http://code.google.com/p/beast-mcmc/ . The method will be made available in the next public release of the package, including support to set up analyses in BEAUti. Contact: philippe.lemey@rega.kuleuven.be or msuchard@ucla.edu Supplementary information: Supplementary data are available at Bioinformatics online.