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International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology
Infection, Genetics and Evolution 19 (2013) 335–336
Contents lists available at ScienceDirect
Infection, Genetics and Evolution journal homepage: www.elsevier.com/locate/meegid
Editorial
International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology
The 17th edition of the International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology was organized at the University of Belgrade, Faculty of Medicine, Belgrade, Serbia. Following a long tradition of past editions of the workshop, it provided both theoretical and practical training in phylogenetic inference and evolutionary hypothesis testing as applied in virology and molecular epidemiology. However, the format of the 2012 edition, which we outline below, was tailored to the current needs in the field of virology and epidemiology. Combating viral spread and their associated disease burden is a tremendous challenge requiring significant research efforts and decided public health measures. Viral sequence data has been recognized as a major asset in the characterization of pathogens that threaten public health. Understanding the processes that generate genetic diversity, such as natural selection, assists in the struggle against viral infections and contributes to our knowledge of past evolutionary and epidemiological events. Molecular epidemiology complements traditional epidemiological studies because they primarily focus on the etiological agent rather than the host. In particular, the historical information contained in viral gene sequences contributes to a better insight in emergence and early transmission dynamics, even before systematic epidemiological surveillance has been initiated, or it enables tracking its global trajectories once it has grown too large for individual cases to be examined. For many years, phylogenetic analysis has been the primary tool in molecular epidemiology. By reconstructing a phylogenetic tree, we are able to study the evolutionary history of the viral strains and assess epidemiological linkage amongst them. However, a full quantitative understanding of the processes that shape the epidemiology and evolution of RNA virus infections requires the integration of ecological, epidemiological and evolutionary dynamics (Holmes and Grenfell, 2009), a research direction that has been coined ‘phylodynamics’ (Grenfell et al., 2004) and that requires different analysis tools (Pybus and Rambaut, 2009). In addition to methodological advances, the field is also experiencing the impact of high-throughput DNA sequencing, which makes available pathogen genomic data in unprecedented quantities and with remarkable rapidity. The continuous development of new methodology, the mathematical and statistical nature of evolutionary inferences and the large quantities of sequence data challenge virologists who want to apply molecular tools in their research. This yearly workshop aims to address this by providing a thorough training in the theoretical background of molecular evolution and the application of the phylogenetic analysis and associated bioinformatic methods 1567-1348/$ - see front matter Ó 2013 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.meegid.2013.08.023
(http://www.rega.kuleuven.be/cev/workshop/). The programme was modified to include two parallel four-day modules: ‘Phylogenetic Inference’ and ‘Evolutionary Hypothesis Testing’. In addition, the participants were now able to complement these modules with a day on special interest topics (including next generation sequencing analysis, recombination and networks, ‘large data’ analysis, . . . ). The ‘Phylogenetic Inference’ module offered the theoretical background and hands-on experience in phylogenetic analysis for those who have little or no prior expertise in sequence analysis. ‘Evolutionary Hypothesis Testing’ was targeted to participants who are well familiar with alignments and phylogenetic trees, and wanted to extend their expertise to likelihood and Bayesian inference in phylogenetics, coalescent and phylogeographic analyses and molecular adaptation. Practical sessions in these modules involved software like, PHYLIP (Felsenstein, 1989), PAUP⁄ (Swofford, 1998), PHYML (Guindon et al., 2009), MEGA (Tamura et al., 2011), HYPHY (Kosakovsky Pond et al., 2005), TREE-PUZZLE (Schmidt et al., 2002), SplitsTree (Huson, 1998), BEAST (Drummond et al., 2012), MrBayes (Huelsenbeck and Ronquist, 2001), Simplot (Lole et al., 1999) and RDP3 (Martin et al., 2010). During the workshop, the sessions alternated between theoretical lectures and practical computer courses, and students were encouraged to work on their own data, with help of the lecturers. Interactions between participants as well as with the workshop lecturers, for example during the poster sessions where participants presented their own findings, stimulated discussions on the application of bioinformatics tools to specific viral problems. The phylogenetic and population genetic methods that are discussed during the workshop are summarized in the second edition of the Phylogenetic Handbook (http://www.kuleuven.ac.be/ aidslab/phylogenybook/index.htm). The studies reported in this special section have benefitted from the stimulating environment offered by the workshop, and reflect at least partly the progress participants have made with the computational analysis of their data. At the time of writing, the 18th edition of the workshop is about to take place in the University of Florida Conference Center in Gainesville, Florida, U.S.A. (http:// regaweb.med.kuleuven.be/veme-workshop/2013/) and we hope the workshop continues to serve the evolving needs in the field of virology and epidemiology. References Drummond, A.J., Suchard, M.A., Xie, D., Rambaut, A., 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973.
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Editorial / Infection, Genetics and Evolution 19 (2013) 335–336
Felsenstein, J., 1989. Phylogeny inference package (Version 3.2). Cladistics 5, 164– 166. Grenfell, B.T., Pybus, O.G., Gog, J.R., Wood, J.L., Daly, J.M., et al, 2004. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303, 327– 332. Guindon, S., Delsuc, F., Dufayard, J.F., Gascuel, O., 2009. Estimating maximum likelihood phylogenies with PhyML. Methods Mol. Biol. 537, 113–137. Holmes, E.C., Grenfell, B.T., 2009. Discovering the phylodynamics of RNA viruses. PLoS Comput. Biol. 5, e1000505. Huelsenbeck, J.P., Ronquist, F., 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17, 754–755. Huson, D.H., 1998. SplitsTree: analyzing and visualizing evolutionary data. Bioinformatics 14, 68–73. Kosakovsky Pond, S.L., Frost, S.D., Muse, S.V., 2005. HyPhy: hypothesis testing using phylogenies. Bioinformatics 21, 676–679. Lole, K.S., Bollinger, R.C., Paranjape, R.S., Gadkari, D., Kulkarni, S.S., et al, 1999. Fulllength human immunodeficiency virus type 1 genomes from subtype Cinfected seroconverters in India, with evidence of intersubtype recombination. J. Virol. 73, 152–160. Martin, D.P., Lemey, P., Lott, M., Moulton, V., Posada, D., et al, 2010. RDP3: a flexible and fast computer program for analyzing recombination. Bioinformatics 26, 2462–2463. Pybus, O.G., Rambaut, A., 2009. Evolutionary analysis of the dynamics of viral infectious disease. Nat. Rev. Genet. 10, 540–550.
Schmidt, H.A., Strimmer, K., Vingron, M., von Haeseler, A., 2002. TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics 18, 502–504. Swofford, D.L., 1998. PAUP⁄ 4.0 - Phylogenetic Analysis Using Parsimony (⁄and Other Methods), pp. Sinauer Assoc., Sunderland, MA. Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., et al, 2011. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 28, 2731–2739.
Philippe Lemey Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Minderbroedersstraat 10, 3000 Leuven, Belgium Maja Stanojevic University of Belgrade School of Medicine, Institute of Microbiology and Immunology, Dr Subotica 1, 11000 Belgrade, Serbia Anne-Mieke Vandamme Laboratory for Clinical and Epidemiological Virology, AIDS Reference Laboratory, Rega Institute & University Hospitals, KU Leuven, Minderbroedersstraat 10, 3000 Leuven, Belgium
Contents lists available at ScienceDirect
Infection, Genetics and Evolution journal homepage: www.elsevier.com/locate/meegid
Editorial
International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology
The 17th edition of the International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology was organized at the University of Belgrade, Faculty of Medicine, Belgrade, Serbia. Following a long tradition of past editions of the workshop, it provided both theoretical and practical training in phylogenetic inference and evolutionary hypothesis testing as applied in virology and molecular epidemiology. However, the format of the 2012 edition, which we outline below, was tailored to the current needs in the field of virology and epidemiology. Combating viral spread and their associated disease burden is a tremendous challenge requiring significant research efforts and decided public health measures. Viral sequence data has been recognized as a major asset in the characterization of pathogens that threaten public health. Understanding the processes that generate genetic diversity, such as natural selection, assists in the struggle against viral infections and contributes to our knowledge of past evolutionary and epidemiological events. Molecular epidemiology complements traditional epidemiological studies because they primarily focus on the etiological agent rather than the host. In particular, the historical information contained in viral gene sequences contributes to a better insight in emergence and early transmission dynamics, even before systematic epidemiological surveillance has been initiated, or it enables tracking its global trajectories once it has grown too large for individual cases to be examined. For many years, phylogenetic analysis has been the primary tool in molecular epidemiology. By reconstructing a phylogenetic tree, we are able to study the evolutionary history of the viral strains and assess epidemiological linkage amongst them. However, a full quantitative understanding of the processes that shape the epidemiology and evolution of RNA virus infections requires the integration of ecological, epidemiological and evolutionary dynamics (Holmes and Grenfell, 2009), a research direction that has been coined ‘phylodynamics’ (Grenfell et al., 2004) and that requires different analysis tools (Pybus and Rambaut, 2009). In addition to methodological advances, the field is also experiencing the impact of high-throughput DNA sequencing, which makes available pathogen genomic data in unprecedented quantities and with remarkable rapidity. The continuous development of new methodology, the mathematical and statistical nature of evolutionary inferences and the large quantities of sequence data challenge virologists who want to apply molecular tools in their research. This yearly workshop aims to address this by providing a thorough training in the theoretical background of molecular evolution and the application of the phylogenetic analysis and associated bioinformatic methods 1567-1348/$ - see front matter Ó 2013 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.meegid.2013.08.023
(http://www.rega.kuleuven.be/cev/workshop/). The programme was modified to include two parallel four-day modules: ‘Phylogenetic Inference’ and ‘Evolutionary Hypothesis Testing’. In addition, the participants were now able to complement these modules with a day on special interest topics (including next generation sequencing analysis, recombination and networks, ‘large data’ analysis, . . . ). The ‘Phylogenetic Inference’ module offered the theoretical background and hands-on experience in phylogenetic analysis for those who have little or no prior expertise in sequence analysis. ‘Evolutionary Hypothesis Testing’ was targeted to participants who are well familiar with alignments and phylogenetic trees, and wanted to extend their expertise to likelihood and Bayesian inference in phylogenetics, coalescent and phylogeographic analyses and molecular adaptation. Practical sessions in these modules involved software like, PHYLIP (Felsenstein, 1989), PAUP⁄ (Swofford, 1998), PHYML (Guindon et al., 2009), MEGA (Tamura et al., 2011), HYPHY (Kosakovsky Pond et al., 2005), TREE-PUZZLE (Schmidt et al., 2002), SplitsTree (Huson, 1998), BEAST (Drummond et al., 2012), MrBayes (Huelsenbeck and Ronquist, 2001), Simplot (Lole et al., 1999) and RDP3 (Martin et al., 2010). During the workshop, the sessions alternated between theoretical lectures and practical computer courses, and students were encouraged to work on their own data, with help of the lecturers. Interactions between participants as well as with the workshop lecturers, for example during the poster sessions where participants presented their own findings, stimulated discussions on the application of bioinformatics tools to specific viral problems. The phylogenetic and population genetic methods that are discussed during the workshop are summarized in the second edition of the Phylogenetic Handbook (http://www.kuleuven.ac.be/ aidslab/phylogenybook/index.htm). The studies reported in this special section have benefitted from the stimulating environment offered by the workshop, and reflect at least partly the progress participants have made with the computational analysis of their data. At the time of writing, the 18th edition of the workshop is about to take place in the University of Florida Conference Center in Gainesville, Florida, U.S.A. (http:// regaweb.med.kuleuven.be/veme-workshop/2013/) and we hope the workshop continues to serve the evolving needs in the field of virology and epidemiology. References Drummond, A.J., Suchard, M.A., Xie, D., Rambaut, A., 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973.
336
Editorial / Infection, Genetics and Evolution 19 (2013) 335–336
Felsenstein, J., 1989. Phylogeny inference package (Version 3.2). Cladistics 5, 164– 166. Grenfell, B.T., Pybus, O.G., Gog, J.R., Wood, J.L., Daly, J.M., et al, 2004. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303, 327– 332. Guindon, S., Delsuc, F., Dufayard, J.F., Gascuel, O., 2009. Estimating maximum likelihood phylogenies with PhyML. Methods Mol. Biol. 537, 113–137. Holmes, E.C., Grenfell, B.T., 2009. Discovering the phylodynamics of RNA viruses. PLoS Comput. Biol. 5, e1000505. Huelsenbeck, J.P., Ronquist, F., 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17, 754–755. Huson, D.H., 1998. SplitsTree: analyzing and visualizing evolutionary data. Bioinformatics 14, 68–73. Kosakovsky Pond, S.L., Frost, S.D., Muse, S.V., 2005. HyPhy: hypothesis testing using phylogenies. Bioinformatics 21, 676–679. Lole, K.S., Bollinger, R.C., Paranjape, R.S., Gadkari, D., Kulkarni, S.S., et al, 1999. Fulllength human immunodeficiency virus type 1 genomes from subtype Cinfected seroconverters in India, with evidence of intersubtype recombination. J. Virol. 73, 152–160. Martin, D.P., Lemey, P., Lott, M., Moulton, V., Posada, D., et al, 2010. RDP3: a flexible and fast computer program for analyzing recombination. Bioinformatics 26, 2462–2463. Pybus, O.G., Rambaut, A., 2009. Evolutionary analysis of the dynamics of viral infectious disease. Nat. Rev. Genet. 10, 540–550.
Schmidt, H.A., Strimmer, K., Vingron, M., von Haeseler, A., 2002. TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics 18, 502–504. Swofford, D.L., 1998. PAUP⁄ 4.0 - Phylogenetic Analysis Using Parsimony (⁄and Other Methods), pp. Sinauer Assoc., Sunderland, MA. Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., et al, 2011. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 28, 2731–2739.
Philippe Lemey Laboratory for Clinical and Epidemiological Virology, Rega Institute, KU Leuven, Minderbroedersstraat 10, 3000 Leuven, Belgium Maja Stanojevic University of Belgrade School of Medicine, Institute of Microbiology and Immunology, Dr Subotica 1, 11000 Belgrade, Serbia Anne-Mieke Vandamme Laboratory for Clinical and Epidemiological Virology, AIDS Reference Laboratory, Rega Institute & University Hospitals, KU Leuven, Minderbroedersstraat 10, 3000 Leuven, Belgium