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Proceedings of the Frontiers of Retrovirology Conference 2016

Retrovirology 2016年第1期13卷 1-40页

作者： Irena Zurnic Sylvia Hütter Nicole Stanke Tobias Kern Fabian Lindel Gesche Gerresheim Martin Hamann Erik Müllers Dirk Lindemann Ute Lehmann Juliane Reh Paul Lesbats Peter Cherepanov Melanie Mann Erik Serrao Alan Engelman Claire Da Silva Santos Kevin Tartour Andrea Cimarelli Rya Burdick Jianbo Chen Jaya Sastri Wei-Shau Hu Vinay Pathak Oliver T. Keppler Patrícia de Sousa-Pereira Hanna-Mari Baldauf Marcel Stern Karine Pradeau Sylvia Eiler Nicolas Levy Marc Ruff Sarah Lennon Sarah Cianferani Stéphane Emiliani Vincent Parissi Sylvie Rato Miguel Munoz Angela Ciuffi Antonio Rausell Amalio Telenti Alexander Zhyvoloup Ian Anderson Chen- Hsuin Lee Ariberto Fassati Anat Melamed Delphine Planas Petronela Ancuta Yuwei Zhang Huicheng Chen Annie Bernier Annie Gosselin Janos Kriston-Vizi Robin Ketteler Andy Merritt Charles Bangham Jocelyn Turpin Anthony Rodari Benoit Van Driessche Mathilde Galais Nadége Delacourt Sylvain Fauquenoy Caroline Vanhulle Anna Kula Carine Van Lint Ernst J. Wolvetang Arsène Burny Olivier Rohr Thijs van Montfort Renee van der Sluis Ben Berkhout Dave Speijer Gang Wang Na Zhao Atze T. Das Mirte Scherpenisse Bo Meng Andrzej Rutkowski Lars Dölken Andrew Lever Neil Berry Claire Ham Neil Almond Hoi Ping Mok Nicholas Norton Axel Fun Jack Hirst Mark Wills Chris Hellmund Harriet Groom Thomas Schuster Benedikt Asbach Ralf Wagner Christine Gross Martina Kalmer Andrea K. Thoma-Kress Norbert Donhauser Sebastian Millen Sandra M. Müller-Schmucker Veit Wiesmann Thomas Wittenberg Jan Gettemans Minghua Li Shan-Lu Liu Eric O. Freed Janis Müller Jan Münch Simone Joas Clement Wesley Gnanadurai Edina Lump Christina M. Stürzel Daniel Sauter Frank Kirchhoff Katharina Mack Kathrin Starz Christina Stürzel Xaver Sewald Nasim Motamedi Pradeep Uchil Ruoxi Pi Christin Herrmann Walther Mothes Mark Ladinsky Pamela Bjorkman Jagadish Beloor Priti Kumar Thomas Murooka Thorsten Mempel Michael Brehm Dale Greiner Erica Parrish Nicholas F. Parrish Beatrice H. Hahn Frederic Bibollet-Ruche Ulrike Sauermann Katharina Töpfer Tina Schultheiss Chris Molecular Virology and Gene Therapy Molecular Medicine Leuven Belgium Molecular Virology Technical University Dresden Dresden Germany Center for Regenerative Therapies Dresden Dresden Germany Potsdam University Potsdam Germany The Francis Crick Institute London Great Britain Institute of Clinical and Molecular Virology Friedrich-Alexander-Universität Erlangen-Nuremberg Erlangen Germany Dana Farber Cancer Institute Boston MA United States CIRI Lyon France National Cancer Institute Frederick MD United States Virology Max von Pettenkofer-Institut LMU Munich Munich Germany Institute of Medical Virology University of Frankfurt Frankfurt a. M. Germany German Center for Infection Research Munich Germany Institute of Medical Virology University Hospital Frankfurt Frankfurt a. M. Germany CIBIO/InBIO University of Porto Vairão Portugal Faculty of Sciences University of Porto Porto Portugal Virology Max von Pettenkofer Institute LMU Munich Germany Institute for Medical Virology Frankfurt a. M. Germany Integrative structural Biology IGBMC Illkirch France Institut Pluridisciplinaire Hubert Curien Strasbourg France Institut Cochin Paris France CNRS UMR5234 MFP Lab Bordeaux France Associated International Laboratory (LIA) Microbiology and Immunology CNRS/Université de Bordeaux/Heinrich Pette Institute-Leibniz Institute for Experimental Virology Bordeaux/Hamburg France Institute of Microbiology University Hospital Center and University of Lausanne Lausanne Switzerland Imagine Institute Paris Descartes University Paris France J. Craig Venter Institute La Jolla CA United States Infection University College London London Great Britain Medicine Imperial College London Great Britain Microbiology & Infection University of Montreal Montreal Great Britain CRCHUM Montreal Canada University College London LMCB London Great Britain MRC Technology Centre for Therapeutic Discovery London Great Britain Section of Virology Department of Medicine Imperial Co

Oral presentationsSession 1: Entry & uncoatingO1 Host cell polo-like kinases (PLKs) promote early prototype foamy virus (PFV) replicationIrena Zurnic, Sylvia Hütter, Ute Lehmann, Nicole Stanke, Juliane Re... 详细信息

Oral presentations

Session 1: Entry & uncoating

O1 Host cell polo-like kinases (PLKs) promote early prototype foamy virus (PFV) replication

Irena Zurnic, Sylvia Hütter, Ute Lehmann, Nicole Stanke, Juliane Reh, Tobias Kern, Fabian Lindel, Gesche Gerresheim, Martin Hamann, Erik Müllers, Paul Lesbats, Peter Cherepanov, Erik Serrao, Alan Engelman, Dirk Lindemann

O2 A novel entry/uncoating assay reveals the presence of at least two species of viral capsids during synchronized HIV-1 infection

Claire Da Silva Santos, Kevin Tartour, Andrea Cimarelli

O3 Dynamics of nuclear envelope association and nuclear import of HIV-1 complexes

Rya Burdick, Jianbo Chen, Jaya Sastri, Wei-Shau Hu, Vinay Pathak

O4 Human papillomavirus protein E4 potently enhances the susceptibility to HIV infection

Oliver T. Keppler

Session 2: Reverse transcription & integration

O5 Structure and function of HIV-1 integrase post translational modifications

Karine Pradeau, Sylvia Eiler, Nicolas Levy, Sarah Lennon, Sarah Cianferani, Stéphane Emiliani, Marc Ruff

O6 Regulation of retroviral integration by RNA polymerase II associated factors and chromatin structure

Vincent Parissi

Session 3: Transcription and latency

O7 A novel single-cell analysis pipeline to identify specific biomarkers of HIV permissiveness

Sylvie Rato, Antonio Rausell, Miguel Munoz, Amalio Telenti, Angela Ciuffi

O8 A capsid-dependent integration program linking T cell activation to HIV-1 gene expression

Alexander Zhyvoloup, Anat Melamed, Ian Anderson, Delphine Planas, Janos Kriston-Vizi, Robin Ketteler, Chen-Hsuin Lee, Andy Merritt, Petronela Ancuta, Charles Bangham, Ariberto Fassati

O9 Characterisation of new RNA polymerase III and RNA polymerase II transcriptional promoters in the Bovine Leukemia Virus genome

Anthony Rodari, Benoit Van Driessche, Mathilde Galais, Nadége Delacourt, Sylv

关键词： Human Immunodeficiency Virus Infection Simian Immunodeficiency Virus Feline Immunodeficiency Virus Bovine Leukemia Virus Prototype Foamy Virus

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Comparative Genomics of Human Adenovirus Types 7,14 and 55 Emergent and Re-emergent in China:New Epidemic Threats

Comparative Genomics of Human Adenovirus Types 7,14 and 55 E...

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第五届武汉现代病毒学国际研讨会

作者： Qiwei Zhang Donald Seto Suhui Zhao Bin Cao Changbing Wang Bing Zhu Yi Chen Changwen Ke Lirong Zou Jie Zhou Shuping Jing Zetao Cheng Chengsong Wan School of Public Health and Tropical Medicine Southern Medical University Bioinformatics and Computational Biology Program School of Systems BiologyGeorge Mason UniversityManassasVAUSA Department of Infectious Diseases and Clinical Microbiology Beijing Chao-Yang Hospital Central Laboratory Guangzhou Women and Children's Medical Center Guangdong Provincial Center for Diseases Control and Prevention

Human adenovirus types 7,14 and 55(HAdV-B7,-B14 and -B55) caused several acute respiratory disease(ARD) outbreaks in America,Europe and Asia recently,including in *** genome of HAdV-B14 firstly isolated in China by us in 2010,is highly similar with those causing ARD outbreaks in US during 2006-2009,with 15 mismatches,3 deletions, 7 insertions and 99.92%identity,all belonging to the same genotype HAdV-B14p1 by

关键词： Comparative Genomics of Human Adenovirus Types 7,14 and 55 Emergent and Re-emergent in China:New Epidemic Threats

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B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

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Genomics, Proteomics & bioinformatics 2012年第3期10卷 142-152页

作者： Fadi Towfic Shakti Gupta Vasant Honavar Shankar Subramaniam Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIA 50010USA Department of Bioengineering University of California at San DiegoLa JollaCA 92122USA

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Col- lectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG path- ways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches （e.g., gene coexpression network alignment algorithms） in elucidating biochemical pathways involved in complex signaling events in ceils.

关键词： Ligand recognition B-cells Gene coexpression network alignment

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Phytohormone signaling pathway analysis method for comparing hormone responses in plant-pest interactions

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BMC Research Notes 2012年第1期5卷 1-7页

作者： Studham, Matthew E. MacIntosh, Gustavo C. Bioinformatics and Computational Biology Program Iowa State University Ames IA 50011 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50011 United States

Background: Phytohormones mediate plant defense responses to pests and pathogens. In particular, the hormones jasmonic acid, ethylene, salicylic acid, and abscisic acid have been shown to dictate and fine-tune defense responses, and identification of the phytohormone components of a particular defense response is commonly used to characterize it. Identification of phytohormone regulation is particularly important in transcriptome analyses. Currently there is no computational tool to determine the relative activity of these hormones that can be applied to transcriptome analyses in soybean. Findings: We developed a pathway analysis method that provides a broad measure of the activation or suppression of individual phytohormone pathways based on changes in transcript expression of pathway-related genes. The magnitude and significance of these changes are used to determine a pathway score for a phytohormone for a given comparison in a microarray experiment. Scores for individual hormones can then be compared to determine the dominant phytohormone in a given defense response. To validate this method, it was applied to publicly available data from previous microarray experiments that studied the response of soybean plants to Asian soybean rust and soybean cyst nematode. The results of the analyses for these experiments agreed with our current understanding of the role of phytohormones in these defense responses. Conclusions: This method is useful in providing a broad measure of the relative induction and suppression of soybean phytohormones during a defense response. This method could be used as part of microarray studies that include individual transcript analysis, gene set analysis, and other methods for a comprehensive defense response characterization. © 2012 Studham and MacIntosh;licensee BioMed Central Ltd.

关键词： Salicylic Acid Jasmonic Acid Soybean Cyst Nematode Soybean Aphid Salicylic Acid Pathway

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

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Nature communications 2017年第1期8卷 1414页

作者： M Carola Zillikens Serkalem Demissie Yi-Hsiang Hsu Laura M Yerges-Armstrong Wen-Chi Chou Lisette Stolk Gregory Livshits Linda Broer Toby Johnson Daniel L Koller Zoltán Kutalik Jian'an Luan Ida Malkin Janina S Ried Albert V Smith Gudmar Thorleifsson Liesbeth Vandenput Jing Hua Zhao Weihua Zhang Ali Aghdassi Kristina Åkesson Najaf Amin Leslie J Baier Inês Barroso David A Bennett Lars Bertram Rainer Biffar Murielle Bochud Michael Boehnke Ingrid B Borecki Aron S Buchman Liisa Byberg Harry Campbell Natalia Campos Obanda Jane A Cauley Peggy M Cawthon Henna Cederberg Zhao Chen Nam H Cho Hyung Jin Choi Melina Claussnitzer Francis Collins Steven R Cummings Philip L De Jager Ilja Demuth Rosalie A M Dhonukshe-Rutten Luda Diatchenko Gudny Eiriksdottir Anke W Enneman Mike Erdos Johan G Eriksson Joel Eriksson Karol Estrada Daniel S Evans Mary F Feitosa Mao Fu Melissa Garcia Christian Gieger Thomas Girke Nicole L Glazer Harald Grallert Jagvir Grewal Bok-Ghee Han Robert L Hanson Caroline Hayward Albert Hofman Eric P Hoffman Georg Homuth Wen-Chi Hsueh Monica J Hubal Alan Hubbard Kim M Huffman Lise B Husted Thomas Illig Erik Ingelsson Till Ittermann John-Olov Jansson Joanne M Jordan Antti Jula Magnus Karlsson Kay-Tee Khaw Tuomas O Kilpeläinen Norman Klopp Jacqueline S L Kloth Heikki A Koistinen William E Kraus Stephen Kritchevsky Teemu Kuulasmaa Johanna Kuusisto Markku Laakso Jari Lahti Thomas Lang Bente L Langdahl Lenore J Launer Jong-Young Lee Markus M Lerch Joshua R Lewis Lars Lind Cecilia Lindgren Yongmei Liu Tian Liu Youfang Liu Östen Ljunggren Mattias Lorentzon Robert N Luben William Maixner Fiona E McGuigan Carolina Medina-Gomez Thomas Meitinger Håkan Melhus Dan Mellström Simon Melov Karl Michaëlsson Braxton D Mitchell Andrew P Morris Leif Mosekilde Anne Newman Carrie M Nielson Jeffrey R O'Connell Ben A Oostra Eric S Orwoll Aarno Palotie Stephen C J Parker Munro Peacock Markus Perola Annette Peters Ozren Polasek Richard L Prince Katri Räikkönen Stuart H Ralston Samuli Ripatti John A Robbins Jerome I Rotter Igor Rudan Veikko Department of Internal Medicine Erasmus MC Rotterdam 3000 The Netherlands. Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA) Leiden 2593 The Netherlands. Department of Biostatistics Boston University School of Public Health Boston MA 02118 USA. Hebrew SeniorLife Institute for Aging Research Roslindale MA 02131 USA. Harvard Medical School Boston MA 02115 USA. Molecular and Integrative Physiological Sciences Program Harvard School of Public Health Boston MA 02115 USA. Program in Personalized and Genomic Medicine and Department of Medicine Division of Endocrinology Diabetes and Nutrition University of Maryland School of Medicine Baltimore MD 21201 USA. Broad Institute Cambridge MA 02142 USA. Sackler Faculty of Medicine Department of Anatomy and Anthropology Tel Aviv University Tel Aviv 6997801 Israel. Department of Twin Research and Genetic Epidemiology King's College London St Thomas' Campus London WC2R 2LS UK. Department of Epidemiology Erasmus MC Rotterdam 3000 The Netherlands. Department of Medical Genetics University of Lausanne Lausanne 1011 Switzerland. Swiss Institute of Bioinformatics Lausanne 1015 Switzerland. Centre Hospitalier Universitaire (CHUV) University Institute for Social and Preventive Medicine Lausanne 1010 Switzerland. Department of Medical and Molecular Genetics Indiana University School of Medicine Indianapolis IN 46202 USA. MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge Biomedical Campus Cambridge CB2 OQQ UK. Institute of Epidemiology II Helmholtz Zentrum München - German Research Center for Environmental Health Neuherberg 85764 Germany. Icelandic Heart Association Kopavogur 201 Iceland. Faculty of Medicine University of Iceland Reykjavik 101 Iceland. deCODE Genetics Reykjavik 101 Iceland. Department of Internal Medicine Institute of Medicine Sahlgrenska Academy University of Gothenburg Gothenburg SE-405 30 Sweden. Dep

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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Invited: Reverse engineering whole-genome networks

Invited: Reverse engineering whole-genome networks

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IEEE International Conference on computational Advances in Bio and Medical Sciences (ICCABS)

作者： Srinivas Aluru Department of Electrical and Computer Engineering Bioinformatics and Computational Biology Program Iowa State University Ames IA USA

A research on the development of parallel methods to eliminate piecemeal approach on building whole-genome networks and facilitate genome-scale network inference, are discussed. A parallel mutual information based method is developed, which can scale up to an arbitrary number of genes and gene expression measurements on sufficiently large parallel computers and clusters. A novel technique to carry out permutation testing for assessing the statistical significance of predicted gene-gene interactions is used to construct a whole genome network of the model plant Arabidopsis thaliana in 9 minutes on a 1024 core cluster. The paper also studied the construction of the whole genome network using mutual information, sample small subgraphs from the network, and refine these local networks through parallel Bayesian inference; and heuristic algorithms for large scale Bayesian inference.

关键词： Bayesian methods bioinformatics Genomics Mutual information Gene expression Genetic communication

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A Comprehensive Survey of Human Proteome by Analyzing Large Scale Tandem Mass Spectrometry and RNA-sequencing Data

A Comprehensive Survey of Human Proteome by Analyzing Large ...

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第八届中国蛋白质组学大会

作者： Peng Li Jean Thierry-Mieg Baitang Ning James C Fuscoe Qi Lv Pengzhan Hu Ruichao Xue Christopher Mason Altuna Akalin Geng Chen Chen Zhao Weida Tong Huixiao Hong Lei Guo Hong Fang Tao Qing Ying Yu Wenzhong Xiao Danielle Thierry-Mieg Leming Shi Tieliu Shi Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China National Center for Biotechnology InformationNational Library of MedicineNIHBethesdaMD 20894USA National Center for Toxicological ResearchFood and Drug AdministrationJeffersonARUSA Department of PhysiologyBiophysicsand Systems BiologyTri-Institutional Program(CornellSloan-Ketteringand Rockefeller)on Medicine1305 York AveUSA Center for PharmacogenomicsSchool of PharmacyFudan UniversityShanghaiChina Massachusetts General HospitalHarvard Medical School51 Blossom StBostonMA 02114USA National Center for Toxicological ResearchFood and Drug AdministrationJeffersonARUSA Center for Pharmacogenomics School of PharmacyFudan UniversityShanghaiChina

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71 Genomic regions flanking E-box binding sites influence DNA binding specificity of bHLH transcription factors through DNA shape

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Journal of Biomolecular Structure and Dynamics 2013年第SUPP 1期31卷 45-46页

作者： Raluca Gordan[a][b][*] Ning Shen[c] Iris Dror[d] Tianyin Zhou[d] John Horton[b] Remo Rohs[d] & Martha L. Bulyk[e][f] [a] Departments of Biostatistics and Bioinformatics Computer Science and Molecular Genetics and Microbiology Duke University Durham NC USA [b] Institute for Genome Sciences and Policy Duke University Durham NC 27708 USA Phone: Phone: +1 (919) 667-8673 Fax: Phone: +1 (919) 667-8673 [c] Department of Pharmacology and Cancer Biology Duke University Durham NC 27708 USA [d] Molecular and Computational Biology Program Departments of Biological Sciences Chemistry and Physics and Astronomy University of Southern California 1050 Childs Way Los Angeles CA 90089 USA [e] Division of Genetics Departments of Medicine and Pathology Brigham and Women’s Hospital and Harvard Medical School Boston MA 02115 USA [f] Harvard-MIT Division of Health Sciences and Technology (HST) Harvard Medical School Boston MA 02115 USA

Transcriptional regulation of gene expression is enacted mainly through binding of transcription factors (TFs) to specific, short DNA sites in cis-regulatory regions of genes. Most TFs are members of protein families that share a common DNA-binding domain and thus recognize similar DNA-binding sequences. It is not well understood why paralogous TFs often bind different genomic target sitesin vivoto effect different regulatory programs, despite apparently recognizing the same sequence motifs. Here, we designed custom protein-binding microarrays (PBMs) to analyze the DNA-binding specificities of twoSaccharomyces cerevisiaebasic helix-loop-helix (bHLH) proteins, Tye7 and Cbf1, as a model system. Our data reveal that E-box DNA-binding sequences (CAnnTG), when tested in the context of their native genomic flanking sequences, are bound differently by Cbf1 and Tye7. computational models of the PBM data indicate that DNA sequence features located in the genomic sequences outside the E-box contribute to DNA-binding specificityin vitro. Our analyses suggest that these flanking regions affect DNA-binding specificity indirectly by influencing the three-dimensional structure of the E-box binding sites. Finally, we show that these subtle differences in intrinsic sequence preferences of Cbf1 and Tye7in vitrohelp to explain their differential DNA-binding preferencesin vivo. Our results provide further evidence that the local shape of DNA-binding sites may be an important feature in distinguishing the DNA-binding preferences among paralogous TFs and thus may play a widespread role in determining how transcriptional regulatory specificity within TF families is achieved.

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