9,514 results on '"Bioinformatics Institute"'
Search Results
2. Metabolic and Metagenomic Effects of Intestinal Microbiome Repopulation in Unexplained Atherosclerosis
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European Bioinformatics Institute
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- 2024
3. Correction: Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses.
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Wendi Bacon, Alexandra Holinski, Marina Pujol, Meredith Wilmott, Sarah L Morgan, and European Molecular Biology Laboratory—European Bioinformatics Institute Training Team
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Biology (General) ,QH301-705.5 - Abstract
[This corrects the article DOI: 10.1371/journal.pcbi.1010220.].
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- 2023
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4. Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses.
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Wendi Bacon, Alexandra Holinski, Marina Pujol, Meredith Wilmott, Sarah L Morgan, and European Molecular Biology Laboratory—European Bioinformatics Institute Training Team
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Biology (General) ,QH301-705.5 - Published
- 2022
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5. Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses
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Bacon, Wendi, Holinski, Alexandra, Pujol, Marina, Wilmott, Meredith, Morgan, Sarah L, and on behalf of the European Molecular Biology Laboratory—European Bioinformatics Institute Training Team
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Cellular and Molecular Neuroscience ,Computational Theory and Mathematics ,Ecology ,Modeling and Simulation ,Genetics ,Computational Biology ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics - Published
- 2022
6. A Provisional Regulatory Gene Network for Specification of Endomesoderm in the Sea Urchin Embryo
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Davidson, Eric H., Rast, Jonathan P., Oliveri, Paola, Ransick, Andrew, Calestani, Cristina, Yuh, Chiou-Hwa, Minokawa, Takuya, Amore, Gabriele, Hinman, Veronica, Arenas-Mena, César, Otim, Ochan, Brown, C.Titus, Livi, Carolina B., Lee, Pei Yun, Revilla, Roger, Schilstra, Maria J., Clarke, Peter J.C., Rust, Alistair G., Pan, Zhengjun, Arnone, Maria I., Rowen, Lee, Cameron, R.Andrew, McClay, David R., Hood, Leroy, and Bolouri, Hamid
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- 2002
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7. New Computational Approaches for Analysis of cis-Regulatory Networks
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Brown, C.Titus, Rust, Alistair G., Clarke, Peter J.C., Pan, Zhengjun, Schilstra, Maria J., De Buysscher, Tristan, Griffin, Gareth, Wold, Barbara J., Cameron, R.Andrew, Davidson, Eric H., and Bolouri, Hamid
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- 2002
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8. Cyrface - Bridging Cytoscape with R
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Emanuel Gonçalves The European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom and Julio Saez-Rodriguez The European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
- Abstract
Cyrface establishes an interface between R and Cytoscape by using different Java-R libraries, e.g. Rserve, RCaller. Cyrface can be used as a Cytoscape plug-in, e.g. to run R commands within Cytoscape, or used as a library to allow your plug-in to connect to R.
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- 2013
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9. 2012 Scientific Annual Report
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Virginia Bioinformatics Institute
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Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals ,LD5655.A7871 V57 - Published
- 2013
10. 2010 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2011
11. 2015 Open Access Week Keynote Address: Victoria Stodden
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McVoy, Elizabeth, Virginia Tech. University Libraries, Virginia Tech. Division of Computational Modeling and Data Analytics, Virginia Tech. Department of Computer Science, Virginia Tech. Department of Statistics, Virginia Tech. Laboratory for Interdisciplinary Statistical Analysis (LISA), Virginia Bioinformatics Institute, Stodden, Victoria, McVoy, Elizabeth, Virginia Tech. University Libraries, Virginia Tech. Division of Computational Modeling and Data Analytics, Virginia Tech. Department of Computer Science, Virginia Tech. Department of Statistics, Virginia Tech. Laboratory for Interdisciplinary Statistical Analysis (LISA), Virginia Bioinformatics Institute, and Stodden, Victoria
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Victoria Stodden gave the keynote address for Open Access Week 2015. "Scholarly communication in the era of big data and big computation" was sponsored by the University Libraries, Computational Modeling and Data Analytics, the Department of Computer Science, the Department of Statistics, the Laboratory for Interdisciplinary Statistical Analysis (LISA), and the Virginia Bioinformatics Institute. Victoria Stodden is an associate professor in the Graduate School of Library and Information Science at the University of Illinois at Urbana-Champaign. She completed both her PhD in statistics and her law degree at Stanford University. Her research centers on the multifaceted problem of enabling reproducibility in computational science. This includes studying adequacy and robustness in replicated results, designing and implementing validation systems, developing standards of openness for data and code sharing, and resolving legal and policy barriers to disseminating reproducible research.
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- 2015
12. 2009 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2010
13. 2009 Scientific Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2009
14. 2008 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2009
15. 2008 Scientific Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2008
16. 2007 Scientific Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2007
17. 2006 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2007
18. 2006 Scientific Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2006
19. 2005 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2006
20. 2005 Scientific Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2005
21. 2003 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute – Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2004
22. 2002 Annual Report
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Virginia Bioinformatics Institute
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LD5655.A7871 V565 ,Virginia Bioinformatics Institute -- Periodicals ,Bioinformatics -- Virginia -- Periodicals - Published
- 2002
23. Scientific Annual Report 2012
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2013
24. Impact the Future: Virginia Bioinformatics Institute 2010 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2011
25. 2010 Scientific Report: Virginia Bioinformatics Institute
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2010
26. The Virginia Bioinformatics Institute 2009 annual report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2010
27. Scientific Annual Report 2009
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2009
28. Networks: 2008 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2009
29. Scientific Annual Report 2008
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2008
30. Team Science: 2007 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2007
31. Pathogens: 2006 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2007
32. Scientific Annual Report 2007
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2007
33. Virginia Bioinformatics Institute at Virginia Tech: Scientific Annual Report 2006
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2006
34. Innovation, Connecting to the Future: 2005 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2006
35. Virginia Bioinformatics Institute 2004 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2005
36. Virginia Bioinformatics Institute at Virginia Tech: Scientific Annual Report 2005
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2005
37. Virginia Bioinformatics Institute 2003 Annual Report
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Virginia Bioinformatics Institute and Virginia Bioinformatics Institute
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- 2004
38. Metabolomics and modelling approaches for systems metabolic engineering
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Jasmeet Kaur Khanijou, Hanna Kulyk, Cécilia Bergès, Leng Wei Khoo, Pnelope Ng, Hock Chuan Yeo, Mohamed Helmy, Floriant Bellvert, Wee Chew, Kumar Selvarajoo, Singapore Institute of Food and Biotechnology Innovation [Singapore, Singapore] (SIFBI / A*STAR ), MetaToul FluxoMet (TBI-MetaToul), MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Bioinformatics Institute [Singapore], Agency for science, technology and research [Singapore] (A*STAR), Lakehead University, National University of Singapore (NUS), Nanyang Technological University [Singapour], School of Biological Sciences, Singapore Institute of Food and Biotechnology Innovation (SIFBI), A*STAR, Bioinformatics Institute (BII), A*STAR, National University of Singapore, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and KULYK, Hanna
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[SDV] Life Sciences [q-bio] ,Kinetic modelling ,Quantitative metabolomics ,Constraint-based modelling ,[SDV]Life Sciences [q-bio] ,Endocrinology, Diabetes and Metabolism ,Dynamic Metabolomics ,Machine learning ,Biomedical Engineering ,Biological sciences [Science] ,Dynamic metabolomics ,Spatial metabolomics ,Quantitative Metabolomics - Abstract
Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts. National Research Foundation (NRF) Published version This work was supported by the Intra-create Thematic Grant “Cities” (grant number: NRF2019-THE001-0007).
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- 2022
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39. A Family of Tree-Based Generators for Bubbles in Directed Graphs
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Leandro Lima, Giuseppe F. Italiano, Luca Pepè Sciarria, Marie-France Sagot, Blerina Sinaimeri, Vicente Acuña, Center for Mathematical Modelling - Centro de Modelamiento Matematico [Santiago] (CMM), Universidad de Chile = University of Chile [Santiago] (UCHILE)-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Libera Università Internazionale degli Studi Sociali Guido Carli [Roma] (LUISS), Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale (ERABLE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Università degli Studi di Roma Tor Vergata [Roma], Baobab, Département PEGASE [LBBE] (PEGASE), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Center for Mathematical Modeling (CMM), Universidad de Chile = University of Chile [Santiago] (UCHILE), European Bioinformatics Institute [Cambridge, UK], and University of Rome TorVergata
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Theoretical computer science ,General Computer Science ,Computer science ,0206 medical engineering ,Context (language use) ,0102 computer and information sciences ,02 engineering and technology ,01 natural sciences ,Bottleneck ,De Bruijn graph ,Article ,Theoretical Computer Science ,Set (abstract data type) ,Physics::Fluid Dynamics ,03 medical and health sciences ,symbols.namesake ,Bubble generator ,[INFO]Computer Science [cs] ,Tree based ,Representation (mathematics) ,030304 developmental biology ,De Bruijn sequence ,0303 health sciences ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,Directed graph ,Graph ,Computer Science Applications ,Computational Theory and Mathematics ,Bubble generator, directed graphs, alternative splicing ,010201 computation theory & mathematics ,symbols ,Geometry and Topology ,020602 bioinformatics ,Generator (mathematics) ,Directed graphs ,Alternative splicing - Abstract
International audience; Bubbles are pairs of internally vertex-disjoint (s, t)-paths in a directed graph. In de Bruijn graphs built from reads of RNA and DNA data, bubbles represent interesting biological events, such as alternative splicing (AS) and allelic differences (SNPs and indels). However, the set of all bubbles in a de Bruijn graph built from real data is usually too large to be efficiently enumerated and analysed in practice. In particular, despite significant research done in this area, listing bubbles still remains the main bottleneck for tools that detect AS events in a reference-free context. Recently, in [1] the concept of a bubble generator was introduced as a way for obtaining a compact representation of the bubble space of a graph. Although this bubble generator was quite effective in finding AS events, preliminary experiments showed that it is about 5 times slower than state-of-art methods. In this paper we propose a new family of bubble generators which improve substantially on previous work: bubble generators in this new family are about two orders of magnitude faster and are still able to achieve similar precision in identifying AS events. To highlight the practical value of our new bubble generators, we also report some experimental results on real datasets.
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- 2020
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40. Maternal Glycemic Dysregulation During Pregnancy and Neonatal Blood DNA Methylation: Meta-analyses of Epigenome-Wide Association Studies
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Elmar W. Tobi, Diana L. Juvinao-Quintero, Justiina Ronkainen, Raffael Ott, Rossella Alfano, Mickaël Canouil, Madelon L. Geurtsen, Amna Khamis, Leanne K. Küpers, Ives Y. Lim, Patrice Perron, Giancarlo Pesce, Johanna Tuhkanen, Anne P. Starling, Toby Andrew, Elisabeth Binder, Robert Caiazzo, Jerry K.Y. Chan, Romy Gaillard, Peter D. Gluckman, Elina Keikkala, Neerja Karnani, Sanna Mustaniemi, Tim S. Nawrot, François Pattou, Michelle Plusquin, Violeta Raverdy, Kok Hian Tan, Evangelia Tzala, Katri Raikkonen, Christiane Winkler, Anette-G. Ziegler, Isabella Annesi-Maesano, Luigi Bouchard, Yap Seng Chong, Dana Dabelea, Janine F. Felix, Barbara Heude, Vincent W.V. Jaddoe, Jari Lahti, Brigitte Reimann, Marja Vääräsmäki, Amélie Bonnefond, Philippe Froguel, Sandra Hummel, Eero Kajantie, Marjo-Riita Jarvelin, Regine P.M. Steegers-Theunissen, Caitlin G. Howe, Marie-France Hivert, Sylvain Sebert, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Harvard Pilgrim Health Care Institute, University of Oulu, Helmholtz Zentrum München = German Research Center for Environmental Health, Klinikums rechts der Isar, Hasselt University (UHasselt), Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), The Generation R Study Group, Imperial College London, Bioinformatics Institute (A*STAR), Singapore Institute for Clinical Sciences [Singapour] (SICS), Agency for science, technology and research [Singapore] (A*STAR), Université de Sherbrooke (UdeS), Centre Hospitalier Universitaire de Sherbrooke, Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Epidemiology of Allergic and Respiratory Diseases Department [iPlesp] (EPAR), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), TKK Helsinki University of Technology (TKK), Colorado School of Public Health [Aurora, CO, USA] (CSPH), University of Colorado Anschutz [Aurora], Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, Emory University School of Medicine, Emory University [Atlanta, GA], Recherche translationnelle sur le diabète - U 1190 (RTD), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), KK Women's and Children's Hospital [Singapore], Duke-NUS Medical School [Singapore], Liggins Institute, University of Auckland [Auckland], Finnish Institute for Health and Welfare [Helsinki, Finland] (FIHW), Oulu University Hospital [Oulu], Bioinformatics Institute [Singapore], Yong Loo Lin School of Medicine [Singapore], Faculty of Medecine [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Institut Desbrest de santé publique (IDESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Université du Québec à Chicoutimi (UQAC), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Norwegian University of Life Sciences (NMBU), Brunel University London [Uxbridge], Geisel School of Medicine at Dartmouth, Harvard Medical School [Boston] (HMS), Massachusetts General Hospital [Boston], Salvy-Córdoba, Nathalie, Obstetrics & Gynecology, Pediatrics, Binder, Elisabeth, Küpers, Leanne K., Geurtsen, Madelon L., Raikkonen, Katri, Tuhkanen, Johanna, Felix, Janine F., ALFANO, Rossella, Winkler, Christiane, Ott, Raffael, Dabelea, Dana, Khamis, Amna, Bouchard, Luigi, Bonnefond, Amélie, Canouil, Mickaël, Karnani, Neerja, Hummel, Sandra, Tobi, Elmar W, Sebert, Sylvain, Jarvelin, Marjo-Riita, Keikkala, Elina, Heude, Barbara, Pesce, Giancarlo, Steegers-Theunissen, Regine P.M., Lim, Ives Y., REIMANN, Brigitte, Caiazzo, Robert, Hian Tan, Kok, Chan, Jerry K.Y., Ronkainen, Justiina, Ziegler, Anette-G., NAWROT, Tim, Froguel, Philippe, Gluckman, Peter D., Raverdy, Violeta, Starling, Anne P., Howe, Caitlin G., Lahti, Jari, Mustaniemi, Sanna, Hivert, Marie-France, Seng Chong, Yap, Jaddoe, Vincent W.V., Perron, Patrice, Pattou, François, Annesi-Maesano, Isabella, Juvinao-Quintero, Diana L., Gaillard, Romy, Vääräsmäki, Marja, Plusquin, Michelle, Andrew, Toby, Kajantie, Eero, and Tzala, Evangelia
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Endocrinology, Diabetes and Metabolism ,MESH: Epigenome ,[SDV.MHEP.GEO]Life Sciences [q-bio]/Human health and pathology/Gynecology and obstetrics ,Epigenesis, Genetic ,Endocrinology & Metabolism ,Epigenome ,MESH: DNA Methylation ,MESH: Pregnancy ,[SDV.MHEP.PED] Life Sciences [q-bio]/Human health and pathology/Pediatrics ,SDG 3 - Good Health and Well-being ,HYPERGLYCEMIA ,Pregnancy ,Internal Medicine ,Humans ,MESH: Fetal Blood ,MESH: Epigenesis, Genetic ,Advanced and Specialized Nursing ,MESH: Diabetes, Gestational ,[SDV.MHEP.EM] Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism ,[SDV.MHEP.PED]Life Sciences [q-bio]/Human health and pathology/Pediatrics ,Science & Technology ,MESH: Humans ,MESH: Infant, Newborn ,Infant, Newborn ,DNA Methylation ,[SDV.MHEP.EM]Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism ,Fetal Blood ,Diabetes, Gestational ,[SDV.MHEP.GEO] Life Sciences [q-bio]/Human health and pathology/Gynecology and obstetrics ,Diabetes Mellitus, Type 2 ,Female ,Life Sciences & Biomedicine ,MESH: Female ,MESH: Diabetes Mellitus, Type 2 - Abstract
OBJECTIVE Maternal glycemic dysregulation during pregnancy increases the risk of adverse health outcomes in her offspring; a risk thought to be linearly related to maternal hyperglycemia. It is hypothesized that changes in offspring DNA methylation (DNAm) underline these associations. RESEARCH DESIGN AND METHODS To address this hypothesis, we conducted fixed-effect meta-analyses of epigenome-wide association study (EWAS) results from eight birth cohorts investigating relationships between cord blood DNAm and fetal exposure to maternal glucose (Nmax= 3,503), insulin (Nmax= 2,062), and the area under the curve of glucose (AUCgluc) following oral glucose tolerance tests (OGTT, Nmax= 1,505). We performed look-up analyses for identified CpG dinucleotides (CpGs) in independent observational cohorts to examine associations between DNAm and cardiometabolic traits as well as tissue-specific gene expression. RESULTS Greater maternal AUCgluc was associated with lower cord blood DNAm at neighboring CpGs cg26974062 (β= -0.013 [SE=2.1x10-3], PFDR= 5.1x10-3) and cg02988288 (β= -0.013 [SE=2.3x10-3], PFDR =0.031) in TXNIP. These associations were attenuated in women with GDM. Lower blood DNAm at these two CpGs near TXNIP was associated with multiple metabolic traits later in life, including type 2 diabetes. TXNIP DNAm in liver biopsies was associated with hepatic expression of TXNIP. We observed little evidence of associations between either maternal glucose or insulin and cord blood DNAm. CONCLUSION Maternal hyperglycemia, as reflected by AUCgluc, was associated with lower cord blood DNAm at TXNIP. Associations between DNAm at these CpGs and metabolic traits in subsequent look-up analyses suggest that these may be candidate loci to investigate in future causal and mediation analyses.
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- 2022
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41. Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment
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Xiaoqin Zou, Théo Mauri, Hang Shi, Shaowen Zhu, Justas Dapkūnas, Yuanfei Sun, Didier Barradas-Bautista, Raphael A. G. Chaleil, Ragul Gowthaman, Sohee Kwon, Xianjin Xu, Zuzana Jandova, Genki Terashi, Ryota Ashizawa, Petras J. Kundrotas, Shuang Zhang, Tunde Aderinwale, Jian Liu, Sandor Vajda, Paul A. Bates, Jianlin Cheng, Daisuke Kihara, Luis A. Rodríguez-Lumbreras, Carlos A. Del Carpio Muñoz, Liming Qiu, Guillaume Brysbaert, Jorge Roel-Touris, Česlovas Venclovas, Tereza Clarence, Rui Yin, Amar Singh, Patryk A. Wesołowski, Rafał Ślusarz, Adam Liwo, Guangbo Yang, Agnieszka S. Karczyńska, Yoshiki Harada, Sergei Kotelnikov, Yuya Hanazono, Charlotte W. van Noort, Marc F. Lensink, Jonghun Won, Adam K. Sieradzan, Israel Desta, Xufeng Lu, Charles Christoffer, Anna Antoniak, Taeyong Park, Sheng-You Huang, Tsukasa Nakamura, Brian G. Pierce, Usman Ghani, Yang Shen, Luigi Cavallo, Chaok Seok, Hao Li, Nurul Nadzirin, Ghazaleh Taherzadeh, Jacob Verburgt, Rodrigo V. Honorato, Artur Giełdoń, Jeffrey J. Gray, Dima Kozakov, Ming Liu, Shan Chang, Eiichiro Ichiishi, Manon Réau, Rui Duan, Francesco Ambrosetti, Johnathan D. Guest, Juan Fernández-Recio, Alexandre M. J. J. Bonvin, Ilya A. Vakser, Farhan Quadir, Yumeng Yan, Ren Kong, Sameer Velankar, Sergei Grudinin, Mateusz Kogut, Mikhail Ignatov, Yasuomi Kiyota, Hyeonuk Woo, Shoshana J. Wodak, Ameya Harmalkar, Shinpei Kobayashi, Panagiotis I. Koukos, Zhen Cao, Kliment Olechnovič, Cezary Czaplewski, Xiao Wang, Agnieszka G. Lipska, Kathryn A. Porter, Peicong Lin, Emilia A. Lubecka, Nasser Hashemi, Bin Liu, Mayuko Takeda-Shitaka, Karolina Zięba, Dzmitry Padhorny, Zhuyezi Sun, Daipayan Sarkar, Romina Oliva, Andrey Alekseenko, Siri Camee van Keulen, Mireia Rosell, Raj S. Roy, Brian Jiménez-García, Jinsol Yang, Martyna Maszota-Zieleniak, Cancer Research UK, Department of Energy and Climate Change (UK), European Commission, Institut National de Recherche en Informatique et en Automatique (France), Medical Research Council (UK), Japan Society for the Promotion of Science, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), National Institute of General Medical Sciences (US), National Institutes of Health (US), National Natural Science Foundation of China, National Science Foundation (US), Unité de Glycobiologie Structurale et Fonctionnelle (UGSF), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Biomolecular Modelling Laboratory [London], The Francis Crick Institute [London], Jiangsu University of Technology [Changzhou], Department of Electrical Engineering and Computer Science [Columbia] (EECS), University of Missouri [Columbia] (Mizzou), University of Missouri System-University of Missouri System, Institute for Data Science and Informatics [Columbia], University of Gdańsk (UG), Faculty of Electronics, Telecommunications and Informatics [GUT Gdańsk] (ETI), Gdańsk University of Technology (GUT), Medical University of Gdańsk, Graduate School of Medical Sciences [Nagoya], Nagoya City University [Nagoya, Japan], International University of Health and Welfare Hospital (IUHW Hospital), Department of Chemical and Biomolecular Engineering [Baltimore], Johns Hopkins University (JHU), Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], Stony Brook University [SUNY] (SBU), State University of New York (SUNY), Innopolis University, Boston University [Boston] (BU), Russian Academy of Sciences [Moscow] (RAS), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Universidad de La Rioja (UR), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Données, Apprentissage et Optimisation (DAO), Laboratoire Jean Kuntzmann (LJK), Université Grenoble Alpes (UGA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Huazhong University of Science and Technology [Wuhan] (HUST), Indiana University - Purdue University Indianapolis (IUPUI), Indiana University System, Graduate School of Information Sciences [Sendaï], Tohoku University [Sendai], National Institutes for Quantum and Radiological Science and Technology (QST), University of Maryland [Baltimore], King Abdullah University of Science and Technology (KAUST), University of Naples Federico II, Texas A&M University [Galveston], Seoul National University [Seoul] (SNU), Kitasato University, University of Kansas [Lawrence] (KU), Vilnius University [Vilnius], University of Missouri System, VIB-VUB Center for Structural Biology [Bruxelles], VIB [Belgium], Sub NMR Spectroscopy, Sub Overig UiLOTS, Sub Mathematics Education, NMR Spectroscopy, Université de Lille, CNRS, Unité de Glycobiologie Structurale et Fonctionnelle (UGSF) - UMR 8576, European Bioinformatics Institute [Hinxton] [EMBL-EBI], Department of Electrical Engineering and Computer Science [Columbia] [EECS], Faculty of Chemistry [Univ Gdańsk], Faculty of Electronics, Telecommunications and Informatics [GUT Gdańsk] [ETI], International University of Health and Welfare Hospital [IUHW Hospital], Johns Hopkins University [JHU], Stony Brook University [SUNY] [SBU], Department of Biomedical Engineering [Boston], Instituto de Ciencias de la Vid y el Vino [ICVV], Huazhong University of Science and Technology [Wuhan] [HUST], Indiana University - Purdue University Indianapolis [IUPUI], National Institutes for Quantum and Radiological Science and Technology [QST], King Abdullah University of Science and Technology [KAUST], Università degli Studi di Napoli 'Parthenope' = University of Naples [PARTHENOPE], Seoul National University [Seoul] [SNU], University of Kansas [Lawrence] [KU], University of Missouri [Columbia] [Mizzou], Unité de Glycobiologie Structurale et Fonctionnelle - UMR 8576 (UGSF), Université de Lille-Centre National de la Recherche Scientifique (CNRS), University of Naples Federico II = Università degli studi di Napoli Federico II, European Project: 675728,H2020,H2020-EINFRA-2015-1,BioExcel(2015), European Project: 823830,H2020-EU.1.4.1.3. Development, deployment and operation of ICT-based e-infrastructures, H2020-EU.1.4. EXCELLENT SCIENCE - Research Infrastructures ,BioExcel-2(2019), European Project: 777536,H2020-EU.1.4.1.3. Development, deployment and operation of ICT-based e-infrastructures, and H2020-EU.1.4. EXCELLENT SCIENCE - Research Infrastructures,EOSC-hub(2018)
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Models, Molecular ,blind prediction ,CAPRI ,CASP ,docking ,oligomeric state ,protein assemblies ,protein complexes ,protein docking ,protein–protein interaction ,template-based modeling ,Computer science ,[SDV]Life Sciences [q-bio] ,Machine learning ,computer.software_genre ,Biochemistry ,Article ,protein-protein interaction ,03 medical and health sciences ,Sequence Analysis, Protein ,Structural Biology ,Server ,Protein Interaction Domains and Motifs ,Molecular Biology ,ComputingMilieux_MISCELLANEOUS ,030304 developmental biology ,0303 health sciences ,Binding Sites ,business.industry ,030302 biochemistry & molecular biology ,Computational Biology ,Proteins ,3. Good health ,Molecular Docking Simulation ,Artificial intelligence ,business ,computer ,Software - Abstract
We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands., Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC001003
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- 2021
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42. Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships
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Sánchez-Valle, Jon, Tejero-Cicuéndez, Héctor, Fernández, José María, Juan, David, Urda-García, Beatriz, Capella-Gutiérrez, Salvador, Al-Shahrour, Fátima, Tabarés-Seisdedos, Rafael, Baudot, Anaïs, Pancaldi, Vera, Valencia, Alfonso, Ministerio de Economía y Competitividad (España), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Instituto de Salud Carlos III, European Commission, Aix-Marseille Université, Instituto Nacional de Bioinformática (España), Generalitat Valenciana, Barcelona Supercomputing Center, Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Spanish National Cancer Research Center (CNIO), Spanish National Bioinformatics Institute [Madrid, Espagne], Institute of Evolutionary Biology [Barcelone, Espagne], Universitat de València (UV), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Mathématiques de Marseille (I2M), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherches en Cancérologie de Toulouse (CRCT), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT), Institució Catalana de Recerca i Estudis Avançats (ICREA), This work was supported by a Ph.D. Fellowship (BES-2016-077403) and funded by the Spanish Ministry of Economics and Competitiveness (BFU2015-71241-R, RTI2018-096653-B-I00). The Coordination Node led by A.V. at the Barcelona Supercomputing Center (BSC) is a member of the Spanish National Bioinformatics Institute (INB), ISCIII-Bioinformatics platform and is supported by grant PT17/0009/0001 of the Acción Estratégica en Salud 2013-2016 of the Programa Estatal de Investigación Orientada a los Retos de la Sociedad, funded by the Instituto de Salud Carlos III (ISCIII) and European Regional Development Fund (ERDF). V.P. is supported by INSERM, the Fondation Toulouse Cancer Santé and Pierre Fabre Research Institute as part of the Chair of Bioinformatics in Oncology of the CRCT. A.B. has received funding from the Excellence Initiative of Aix-Marseille University—A*Midex, a French 'Investissements d’Avenir' program. D.J. was supported by Juan de la Cierva fellowship (FJCI-2016-29558) from the Ministerio de Ciencia, Innovación y Universidades. H.T. and F.A.-S. were supported by the Instituto de Salud Carlos III (ISCIII), Spanish National Bioinformatics Institute (INB) Grant (PT17/0009/0011—ISCIII-SGEFI/ERDF) and Marie-Curie Career Integration Grant (CIG334361). J.M.F. and S.C.-G. were supported by the Instituto de Salud Carlos III (ISCIII), Spanish National Bioinformatics Institute (INB) Grant (PT17/0009/0001— ISCIII-SGEFI/ERDF). R.T.-S. was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIIIFEDER., ANR-11-IDEX-0001,Amidex,INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE(2011), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées, Bodescot, Myriam, and INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE - - Amidex2011 - ANR-11-IDEX-0001 - IDEX - VALID
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Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC] ,Disease PERCEPTION portal ,Science ,Datasets as Topic ,Diseases ,Comorbidity ,Protein−protein interaction ,Article ,Genètica molecular ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Genetics ,Humans ,Genetic Predisposition to Disease ,Biomedical research ,Molecular genetics ,lcsh:Science ,Cancer ,Gene Expression Profiling ,Healthcare ,Computational Biology ,Computational biology and bioinformatics ,Phenotypes ,Gene expression profiles ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,Molecular similarity ,Case-Control Studies ,Malalties ,[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,lcsh:Q ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Enginyeria biomèdica ,Gene expression ,Biomedical engineering ,Medical care ,Biomarkers - Abstract
Comorbidity is a medical condition attracting increasing attention in healthcare and biomedical research. Little is known about the involvement of potential molecular factors leading to the emergence of a specific disease in patients affected by other conditions. We present here a disease interaction network inferred from similarities between patients’ molecular profiles, which significantly recapitulates epidemiologically documented comorbidities. Furthermore, we identify disease patient-subgroups that present different molecular similarities with other diseases, some of them opposing the general tendencies observed at the disease level. Analyzing the generated patient-subgroup network, we identify genes involved in such relations, together with drugs whose effects are potentially associated with the observed comorbidities. All the obtained associations are available at the disease PERCEPTION portal (http://disease-perception.bsc.es)., This work was supported by a Ph.D. Fellowship (BES-2016-077403) and funded by the Spanish Ministry of Economics and Competitiveness (BFU2015-71241-R, RTI2018-096653-B-I00). The Coordination Node led by A.V. at the Barcelona Supercomputing Center (BSC) is a member of the Spanish National Bioinformatics Institute (INB), ISCIII-Bioinformatics platform and is supported by grant PT17/0009/0001 of the Acción Estratégica en Salud 2013-2016 of the Programa Estatal de Investigación Orientada a los Retos de la Sociedad, funded by the Instituto de Salud Carlos III (ISCIII) and European Regional Development Fund (ERDF). V.P. is supported by INSERM, the Fondation Toulouse Cancer Santé and Pierre Fabre Research Institute as part of the Chair of Bioinformatics in Oncology of the CRCT. A.B. has received funding from the Excellence Initiative of Aix-Marseille University—A*Midex, a French “Investissements d’Avenir” program. D.J. was supported by Juan de la Cierva fellowship (FJCI-2016-29558) from the Ministerio de Ciencia, Innovación y Universidades. H.T. and F.A.-S. were supported by the Instituto de Salud Carlos III (ISCIII), Spanish National Bioinformatic
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- 2020
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43. Development and application of a transcriptional sensor for detection of heterologous acrylic acid production in E. coli
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Sharon Chee, Siau Jia Wei, Jeremie Poschmann, Farid J. Ghadessy, Sarada Raghavan, Chandra S. Verma, Niranjan Nagarajan, Juntao Li, Le Bihan, Sylvie, p53 Laboratory Technology Development Group (A*STAR), Genome Institute of Singapore (GIS), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Department of Computational and Systems Biology [Singapore], Bioinformatics Institute (A*STAR), National University of Singapore (NUS), Nanyang Technological University [Singapour], Agency for Science, Technology and Research (Singapore)., School of Biological Sciences, and Bioinformatics Institute, A*STAR
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[SDV]Life Sciences [q-bio] ,Mutant ,lcsh:QR1-502 ,Heterologous ,Bioengineering ,Biosensing Techniques ,medicine.disease_cause ,Applied Microbiology and Biotechnology ,Fluorescence ,lcsh:Microbiology ,Amidase ,Green fluorescent protein ,chemistry.chemical_compound ,In vivo ,E. Coli ,Escherichia coli ,medicine ,Promoter Regions, Genetic ,Acrylic acid ,chemistry.chemical_classification ,Acrylamide ,Acrylic Acid ,Chemistry ,Research ,Biological sciences [Science] ,[SDV] Life Sciences [q-bio] ,Enzyme ,Acrylates ,Metabolic Engineering ,Biochemistry ,Biotechnology - Abstract
Background Acrylic acid (AA) is a widely used commodity chemical derived from non-renewable fossil fuel sources. Alternative microbial-based production methodologies are being developed with the aim of providing “green” acrylic acid. These initiatives will benefit from component sensing tools that facilitate rapid and easy detection of in vivo AA production. Results We developed a novel transcriptional sensor facilitating in vivo detection of acrylic acid (AA). RNAseq analysis of Escherichia coli exposed to sub-lethal doses of acrylic acid identified a selectively responsive promoter (PyhcN) that was cloned upstream of the eGFP gene. In the presence of AA, eGFP expression in E. coli cells harbouring the sensing construct was readily observable by fluorescence read-out. Low concentrations of AA (500 μM) could be detected whilst the closely related lactic and 3-hydroxy propionic acids failed to activate the sensor. We further used the developed AA-biosensor for in vivo FACS-based screening and identification of amidase mutants with improved catalytic properties for deamination of acrylamide to acrylic acid. Conclusions The transcriptional AA sensor developed in this study will benefit strain, enzyme and pathway engineering initiatives targeting the efficient formation of bio-acrylic acid. Electronic supplementary material The online version of this article (10.1186/s12934-019-1185-y) contains supplementary material, which is available to authorized users.
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- 2019
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44. Identification of genes required for eye development by high-throughput screening of mouse knockouts
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Bret A. Moore1, Brian C. Leonard2, Lionel Sebbag1, Sydney G. Edwards1, Ann Cooper1, Denise M. Imai3, 4, Luis Santos4, Christopher Reilly3, Stephen M. Griffey3, Lynette Bower5, David Clary5, 6, Michel J. Roux 7, 8, 9, Hamid Meziane7, Ewan Straiton Jeremy Mason Yann Herault Ann M. Flenniken12, Lauryl M.J. Nutter12, Zorana Berberovic12, Celeste Owen12, Susan Newbigging12, Hibret Adissu12, Mohammed Eskandarian12, Chih-Wei Hsu15, Sowmya Kalaga15, Uchechukwu Udensi15, Chinwe Asomugha15, Ritu Bohat16, Juan J. Gallegos16, John R. Seavitt16, Jason D. Heaney16, Arthur L. Beaudet16, Mary E. Dickinson15, Monica J. Justice12, Vivek Philip17, Vivek Kumar 17, Karen L. Svenson17, Robert E. Braun17, Sara Wells4, Heather Cater4, Michelle Stewart4, Sharon Clementson-Mobbs4, Russell Joynson4, Xiang Gao18, Tomohiro Suzuki19, Shigeharu Wakana 19, Damian Smedley20, J. K Seong21, Glauco Tocchini-Valentini22, Mark Moore23, Colin Fletcher24, Natasha Karp25, Ramiro Ramirez-Solis25, Jacqueline K. White17, Martin Hrabe de Angelis 26, Wolfgang Wurst26, Sara M. Thomasy2, Paul Flicek 6, Helen Parkinson6, Steve D.M. Brown4, Terrence F. Meehan6, Patsy M. Nishina17, Stephen A. Murray17, Mark P. Krebs17, Ann-Marie Mallon4, K.C.Kent Lloyd 5, Christopher J. Murphy2, Ala Moshiri27, Institut de génétique et biologie moléculaire et cellulaire (IGBMC), Université Louis Pasteur - Strasbourg I-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Department of Molecular and Human Genetics, Baylor College of Medicine (BCM), Baylor University-Baylor University, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Medical Research Counc, Department of Surgery, Second Hospital of HeBei Medical University, European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Cell Biology and Neurobiology Institute, Consiglio Nazionale delle Ricerche [Roma] (CNR), The Wellcome Trust Sanger Institute [Cambridge], GSF research center, Institute of Experimental Genetis, Biochemistry, and European Bioinformatics Institute
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0301 basic medicine ,genetic structures ,Ocular Pathology ,[SDV]Life Sciences [q-bio] ,Medicine (miscellaneous) ,Computational biology ,Disease ,Biology ,Eye ,General Biochemistry, Genetics and Molecular Biology ,DNA sequencing ,Article ,03 medical and health sciences ,0302 clinical medicine ,Genetics ,2.1 Biological and endogenous factors ,Aetiology ,lcsh:QH301-705.5 ,Gene ,development ,Eye Disease and Disorders of Vision ,Gene knockout ,ComputingMilieux_MISCELLANEOUS ,mouse mutants ,Human Genome ,Phenotype ,eye ,eye diseases ,Forward genetics ,030104 developmental biology ,lcsh:Biology (General) ,sense organs ,International Mouse Phenotyping Consortium ,General Agricultural and Biological Sciences ,030217 neurology & neurosurgery ,Genetic screen ,Biotechnology - Abstract
Despite advances in next generation sequencing technologies, determining the genetic basis of ocular disease remains a major challenge due to the limited access and prohibitive cost of human forward genetics. Thus, less than 4,000 genes currently have available phenotype information for any organ system. Here we report the ophthalmic findings from the International Mouse Phenotyping Consortium, a large-scale functional genetic screen with the goal of generating and phenotyping a null mutant for every mouse gene. Of 4364 genes evaluated, 347 were identified to influence ocular phenotypes, 75% of which are entirely novel in ocular pathology. This discovery greatly increases the current number of genes known to contribute to ophthalmic disease, and it is likely that many of the genes will subsequently prove to be important in human ocular development and disease., Bret Moore et al. from the International Mouse Phenotyping Consortium report the identification of 347 mouse genes that influence ocular phenotypes when knocked out. 75% of the identified genes have not previously been associated with any ocular pathology.
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- 2018
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45. Gearing up to handle the mosaic nature of life in the quest for orthologs
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Forslund, Kristoffer, Pereira, Cécile, Capella-Gutiérrez, Salvador, da Silva, Alan Sousa, Altenhoff, Adrian, Huerta-Cepas, Jaime, Muffato, Matthieu, Patricio, Mateus, Vandepoele, Klaas, Ebersberger, Ingo, Blake, Judith, Fernández Breis, Jesualdo Tomás, Boeckmann, Brigitte, Gabaldon, Toni, Sonnhammer, Erik, Dessimoz, Christophe, Lewis, Suzanna, Bello, Carla, Briois, Sébastien, Chalstrey, Edward, Chiba, Hirokazu, Conchillo-Solé, Oscar, Daubin, Vincent, DeLuca, Todd, Dufayard, Jean-François, Durand, Dannie, Fernández-Breis, Jesualdo Tomás, Glover, Natasha, Hauser, Alexander, Heller, Davide, Kaduk, Mateus, Koch, Jan, Koonin, Eugene, Kriventseva, Evgenia, Kuraku, Shigehiro, Lecompte, Odile, Lespinet, Olivier, Levy, Jeremy, Liebeskind, Benjamin, Linard, Benjamin, Marcet-Houben, Marc, Kauffmann, Martin, McWhite, Claire, Mekhedov, Sergei, Moretti, Sebastien, Müller, Steven, Nadia, El-Mabrouk, Notredame, Cedric, Penel, Simon, Pilizota, Ivana, Redestig, Henning, Robinson-Rechavi, Marc, Schreiber, Fabian, Sjölander, Kimmen, Škunca, Nives, Steinegger, Martin, Szklarczyk, Damian, Thomas, Paul, Thuer, Ernst, Train, Clément, Uchiyama, Ikuo, Wittwer, Lucas, Xenarios, Ioannis, Yates, Bethan, Zdobnov, Evgeny, Waterhouse, Robert, European Molecular Biology Laboratory [Heidelberg] (EMBL), University of Florida [Gainesville], Institut de Biologie Intégrative de la Cellule (I2BC), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Bioinformatique (LRI) (BioInfo - LRI), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Universitat Pompeu Fabra [Barcelona], Swiss Institute of Bioinformatics (SIB), Centre for Genomic Regulation (CRG), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, VIB Department of Plant Systems Biology, Ghent University [Belgium] (UGENT), Senckenberg Climate and Research, Applied Bioinformatics, University of Southern California (USC), Department of Computer Science, Laboratoire de Biologie Cellulaire et Moléculaire du Contrôle de la Prolifération (LBCMCP), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Bioinformatique, phylogénie et génomique évolutive (BPGE), Département PEGASE [LBBE] (PEGASE), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Harvard Medical School [Boston] (HMS), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Universidad de Murcia, National Center for Biotechnology Information (NCBI), University of Geneva Medical School, Genome Resource and Analysis Unit (GRAS), RIKEN Center for Developmental Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Méthodes et Algorithmes pour la Bioinformatique (MAB), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Swiss Institute of Bioinformatics, Comparative Bioinformatics, Department of Ecology and Evolution, Université de Lausanne (UNIL), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Universität Zürich [Zürich] (UZH), Defence Science and Technology Laboratory (Dstl), Ministry of Defence (UK) (MOD), Swiss Institute of Bioinformatics [Genève] (SIB), Medical School, Université de Genève (UNIGE), University of Florida [Gainesville] (UF), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Universitat Pompeu Fabra [Barcelona] (UPF), Swiss Institute of Bioinformatics [Lausanne] (SIB), Center for Plant Systems Biology (PSB Center), Vlaams Instituut voor Biotechnologie [Ghent, Belgique] (VIB), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Department of Ecology and Evolution [Lausanne], Universität Zürich [Zürich] = University of Zurich (UZH), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Université de Lausanne = University of Lausanne (UNIL), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Genève = University of Geneva (UNIGE), European Molecular Biology Laboratory [Heidelberg] ( EMBL ), University of Florida [Gainesville] ( UF ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Sud - Paris 11 ( UP11 ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Bioinformatique (LRI) ( BioInfo - LRI ), Laboratoire de Recherche en Informatique ( LRI ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ), Centre for Genomic Regulation ( CRG ), European Bioinformatics Institute [Hinxton] ( EMBL-EBI ), European Molecular Biology Laboratory [Hinxton], Ghent University [Belgium] ( UGENT ), Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Southern California ( USC ), Swiss Federal Institute of Technology in Zürich ( ETH Zürich ), LBCMCP, Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Biométrie et Biologie Evolutive ( LBBE ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ), Harvard Medical School [Boston] ( HMS ), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales ( UMR AGAP ), Institut national de la recherche agronomique [Montpellier] ( INRA Montpellier ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), National Center for Biotechnology Information ( NCBI ), Genome Resource and Analysis Unit ( GRAS ), Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Méthodes et Algorithmes pour la Bioinformatique ( MAB ), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier ( LIRMM ), Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Université de Lausanne ( UNIL ), University of California [Berkeley], Universität Zürich [Zürich] ( UZH ), Defence Science and Technology Laboratory ( Dstl ), Ministry of Defence (UK) ( MOD ), Swiss Institute of Bioinformatics [Genève] ( SIB ), Université de Genève ( UNIGE ), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Saclay, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
- Subjects
[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM] ,[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience; The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches. Central to the QfO effort is proper benchmarking of methods and services, as well as design of standardized datasets and standardized formats to allow sharing and comparison of results. Simultaneously, analysis pipelines have been improved, evaluated and adapted to handle large datasets. All this would not have occurred without the long-term collaboration of Consortium members. Meeting regularly to review and coordinate complementary activities from a broad spectrum of innovative researchers clearly benefits the community. Highlights of the meeting include addressing sources of and legitimacy of disagreements between orthology calls, the context dependency of orthology definitions, special challenges encountered when analyzing very anciently rooted orthologies, orthology in the light of whole-genome duplications, and the concept of orthologous versus paralogous relationships at different levels, including domain-level orthology. Furthermore, particular needs for different applications (e.g. plant genomics, ancient gene families and others) and the infrastructure for making orthol-ogy inferences available (e.g. interfaces with model organism databases) were discussed, with several ongoing efforts that are expected to be reported on during the upcoming 2017 QfO meeting.
- Published
- 2018
- Full Text
- View/download PDF
46. Computational pan-genomics : Status, promises and challenges
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Lodewyk F. A. Wessels, Jan O. Korbel, Jasmijn A. Baaijens, Francesca Chiaromonte, Gunnar W. Klau, Kai Ye, Alexander Schönhuth, Francesca D. Ciccarelli, Tobias Marschall, Robin Cijvat, Matthias Schlesner, Adam M. Novak, Eleazar Eskin, Ashley D. Sanders, Sven Rahmann, Carl Shneider, Wigard P. Kloosterman, Knut Reinert, Eric-Wubbo Lameijer, Sandra Smit, Benedict Paten, Mohammed El-Kebir, Valentina Boeva, Evan E. Eichler, Cornelia M. van Duijn, Can Alkan, Jeroen de Ridder, Benjamin Langmead, Dick de Ridder, Jiayin Wang, David Porubsky, Fabio Vandin, Erwin Datema, Ben Raphael, Paul Kersey, Nadia Pisanti, Corinna Ernst, Klaasjan G. Ouwens, Y. Zhang, Thomas Abeel, Erik Garrison, Veli Mäkinen, Paul I.W. de Bakker, Victor Guryev, Siavash Sheikhizadeh, Manja Marz, Marcel Martin, Ole Schulz-Trieglaff, Pieter B. Neerincx, Rayan Chikhi, Eric Rivals, John C. Mu, Raoul J. P. Bonnal, Bas E. Dutilh, Paul Medvedev, Louis Dijkstra, Pierre Peterlongo, Ali Ghaffaari, Daniel Valenzuela, Epidemiology, Gastroenterology & Hepatology, Erasmus MC other, Alkan, Can, Saarland University [Saarbrücken], Max Planck Institute for Informatics [Saarbrücken], Karlsruhe Institute of Technology (KIT), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Delft Bioinformatics Lab [Delft], Delft University of Technology (TU Delft), Computational Science Lab [Amsterdam], University of Amsterdam [Amsterdam] (UvA), Theoretical Biology & Bioinformatics [Utrecht], University Medical Center [Utrecht], Universidade Federal do Rio de Janeiro (UFRJ), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Section genetics [Utrecht], Center for Molecular medicine [Utrecht], University Medical Center [Utrecht]-University Medical Center [Utrecht], Helsinki Institute for Information Technology, Department of Computer Science [Helsinki], Falculty of Science [Helsinki], University of Helsinki-University of Helsinki, Howard Hughes Medical Institute [Santa Cruz] (HHMI), Center for Biomolecular Science & Engineering, European Research Institute for the Biology of Ageing [Groningen] (ERIBA), University Medical Center Groningen [Groningen] (UMCG), Institut de Biologie Computationnelle (IBC), Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Méthodes et Algorithmes pour la Bioinformatique (MAB), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Engineering (Bilkent-CS), Bilkent, Life Sciences [Amsterdam] (MAC4), Centrum Wiskunde & Informatica (CWI), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), PSL Research University (PSL), Centre de Bioinformatique (CBIO), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Cancer et génôme: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, MINES ParisTech - École nationale supérieure des mines de Paris-Institut Curie-Institut National de la Santé et de la Recherche Médicale (INSERM), Integrative Biology Program [Milano], Istituto Nazionale Genetica Molecolare [Milano] (INGM), Department of Statistics [Pennsylvania], Pennsylvania State University (Penn State), Penn State System-Penn State System, Bioinformatics and Sequence Analysis (BONSAI), Université de Lille, Sciences et Technologies-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Ecole Centrale de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Ecole Centrale de Lille-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Monet DB Solutions [Amsterdam], KeyGene [Wageningen], Department of Epidemiology [Rotterdam], Erasmus University Medical Center [Rotterdam] (Erasmus MC), Howard Hughes Medical Institute [Berkeley], University of California [Berkeley], University of California-University of California, Genome Informatics [Duisburg], Universität Duisburg-Essen [Essen], Departement of human genetics [Los Angeles], Computer Science Department [Los Angeles] (UCLA), University of California [Los Angeles] (UCLA), University of California-University of California-University of California [Los Angeles] (UCLA), The Wellcome Trust Sanger Institute [Cambridge], Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale (ERABLE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Universiteit Leiden [Leiden], Department of Computer Science [Baltimore], Johns Hopkins University (JHU), Centre de Physique des Particules de Marseille (CPPM), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Aix Marseille Université (AMU), University of Pennsylvania [Philadelphia], China Agricultural University (CAU), University of Groningen [Groningen], Department of Biological Psychology [Amsterdam], Vrije Universiteit Amsterdam [Amsterdam] (VU), Scalable, Optimized and Parallel Algorithms for Genomics (GenScale), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Dipartimento di Informatica [Pisa] (DI), University of Pisa - Università di Pisa, Faculty of Computer Science [Dortmund], Technische Universität Dortmund [Dortmund] (TU), Service de Pneumologie A [Paris], AP-HP - Hôpital Bichat - Claude Bernard [Paris], Department of Mathematics and Computer Science (Freie Universität Berlin), Freie Universität Berlin, Wageningen University and Research Centre [Wageningen] (WUR), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Division of Theoretical Bioinformatics [Heidelberg], German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Illumina Cambridge, Illumina, Terry Fox Laboratory, BC Cancer Agency (BCCRC)-British Columbia Cancer Agency Research Centre, Bioinformatics Group [Wageningen], Leiden Observatory [Leiden], Regeneron Pharmaceuticals [Tarrytown], Shaanxi University of Science and Technology, Netherlands Cancer Institute (NKI), Antoni van Leeuwenhoek Hospital, Universita degli Studi di Padova, The Netherlands Organization for Scientific Research (NWO) Vidi (639.072.309 to A.S., 864.14.004 to B.E.D.), CAPES/BRASIL (to B.E.D.), the Academy of Finland (284598 [CoECGR] to V.M. and D.V.), the Russian Scientific Foundation (14–11–00826 to L.D.), Institut de Biologie Computationnelle (ANR-11-BINF- 0002 to E.R.), and the French Colib’read project (ANR–12– BS02–0008 to E.R.). NSFC 31671372 (to K. Y.), the Dutch Graduate School for Experimental Plant Sciences (054EPS15 to S.S.), the EMGO Institute for Health and Care Research (EMGO+) to K.O., the National Human Genome Research Institute (1U54HG007990 [BD2K] to B.P. and A.M.N., 5U41HG007234 [GENCODE] to B.P.), the W. M. Keck Foundation (DT06172015 to B.P. and A.M.N.), the Simons Foundation (SFLIFE# 351901 to B.P. and A.M.N.), the ARCS Foundation (2014–15 ARCS fellowship to A.M.N.), Edward Schulak (Edward Schulak Fellowship in Genomics to A.M.N.), ANR-11-BINF-0002,IBC,Institut de Biologie Computationnelle de Montpellier(2011), ANR-12-BS02-0008,Colib'read,Méthodes d'extraction d'information biologique dans les données HTS non assemblées(2012), Karlsruhe Institute of Technology ( KIT ), Broad Institute of MIT and Harvard ( BROAD INSTITUTE ), Harvard Medical School [Boston] ( HMS ) -Massachusetts General Hospital [Boston] ( MGH ) -Massachusetts Institute of Technology ( MIT ), Delft University of Technology ( TU Delft ), University of Amsterdam [Amsterdam] ( UvA ), Universidade Federal do Rio de Janeiro ( UFRJ ), European Bioinformatics Institute [Hinxton] ( EMBL-EBI ), European Molecular Biology Laboratory [Hinxton], Department of Computer Science, Howard Hughes Medical Institute [Santa Cruz] ( HHMI ), European Research Institute for the Biology of Ageing [Groningen] ( ERIBA ), University Medical Center Groningen [Groningen] ( UMCG ), Institut de Biologie Computationnelle ( IBC ), Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -Institut National de la Recherche Agronomique ( INRA ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Méthodes et Algorithmes pour la Bioinformatique ( MAB ), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier ( LIRMM ), Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Computer Engineering ( Bilkent-CS ), Life Sciences [Amsterdam] ( MAC4 ), Centrum Wiskunde & Informatica ( CWI ), Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), PSL Research University ( PSL ), Centre de Bioinformatique ( CBIO ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), MINES ParisTech - École nationale supérieure des mines de Paris-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -INSTITUT CURIE, Istituto Nazionale Genetica Molecolare [Milano] ( INGM ), PennState University [Pennsylvania] ( PSU ), Bioinformatics and Sequence Analysis ( BONSAI ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 ( CRIStAL ), Ecole Centrale de Lille-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut Mines-Télécom [Paris]-Université de Lille-Centre National de la Recherche Scientifique ( CNRS ) -Ecole Centrale de Lille-Institut Mines-Télécom [Paris]-Université de Lille-Centre National de la Recherche Scientifique ( CNRS ) -Centre National de la Recherche Scientifique ( CNRS ), Centre National de la Recherche Scientifique ( CNRS ), Erasmus University Medical Center [Rotterdam], Computer Science Department [Los Angeles] ( UCLA ), University of California at Los Angeles [Los Angeles] ( UCLA ) -University of California at Los Angeles [Los Angeles] ( UCLA ), Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale ( ERABLE ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Johns Hopkins University ( JHU ), Centre de Physique des Particules de Marseille ( CPPM ), Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Aix Marseille Université ( AMU ), China Agricultural University ( CAU ), Vrije Universiteit Amsterdam [Amsterdam] ( VU ), Scalable, Optimized and Parallel Algorithms for Genomics ( GenScale ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -GESTION DES DONNÉES ET DE LA CONNAISSANCE ( IRISA_D7 ), Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ) -Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ), Dipartimento di Informatica [Pisa] ( DI ), University of Pisa [Pisa], Technische Universität Dortmund [Dortmund] ( TU ), Department of Mathematics and Computer Science ( Freie Universität Berlin ), Freie Universität Berlin [Berlin], Wageningen University and Research Centre [Wageningen] ( WUR ), K.U.Leuven, German Cancer Research Center [Heidelberg] ( DKFZ ), Helmholtz-Gemeinschaft-Helmholtz-Gemeinschaft, BC Cancer Agency ( BCCRC ) -British Columbia Cancer Agency Research Centre, Netherlands Cancer Institute ( NKI ), ANR-11-BINF-0002,IBC,Institut de Biologie Computationnelle de Montpellier ( 2011 ), ANR-12-BS02-0008,Colib'read,Méthodes d'extraction d'information biologique dans les données HTS non assemblées ( 2012 ), Helsinki Institute for Information Technology (HIIT), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Aalto University, Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of California [Santa Cruz] (UC Santa Cruz), University of California (UC), Bilkent University [Ankara], Université Paris sciences et lettres (PSL), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Statistics [PennState], Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), University of Washington [Seattle], Howard Hughes Medical Institute (HHMI), Universität Duisburg-Essen = University of Duisburg-Essen [Essen], University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), Universiteit Leiden, Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Department of Mathematics and Computer Science, Wageningen University and Research [Wageningen] (WUR), Università degli Studi di Padova = University of Padua (Unipd), ANR-11-BINF-0002,IBC,Institut de biologie Computationnelle(2011), Aalto University-University of Helsinki, University of California [Santa Cruz] (UCSC), University of California, Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), MINES ParisTech - École nationale supérieure des mines de Paris, Centre National de la Recherche Scientifique (CNRS)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Inria Lille - Nord Europe, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), and Groningen Research Institute for Asthma and COPD (GRIAC)
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0301 basic medicine ,Data structures ,Computer science ,Medizin ,02 engineering and technology ,computer.software_genre ,Genome ,Computational and Statistical Genetics ,data structures ,haplotypes ,pan-genome ,read mapping ,sequence graph ,Tumours of the digestive tract Radboud Institute for Molecular Life Sciences [Radboudumc 14] ,0303 health sciences ,education.field_of_study ,Point (typography) ,Genomics ,Papers ,Data mining ,Sequence graph ,Computational problem ,Construct (philosophy) ,Algorithms ,Human ,Information Systems ,Bioinformatics ,0206 medical engineering ,Population ,Pan-genome ,03 medical and health sciences ,[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM] ,Bioinformatica ,Humans ,Haplotypes ,Read mapping ,Computational Biology ,Genome, Human ,Software ,Molecular Biology ,education ,Representation (mathematics) ,030304 developmental biology ,Computational genomics ,Data structure ,Data science ,Human genetics ,030104 developmental biology ,Paradigm shift ,ddc:004 ,[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ,EPS ,computer ,020602 bioinformatics - Abstract
Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case ofHomo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic datasets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension ofcomputational pan-genomics, a new sub-area of research in computational biology. In this paper, we generalize existing definitions and understand apan-genomeas any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies, and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains.
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- 2018
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47. The International Mouse Phenotyping Consortium (IMPC): a functional catalogue of the mammalian genome that informs conservation · the IMPC consortium
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Muñoz-Fuentes, Violeta, Cacheiro, Pilar, Meehan, Terrence, Aguilar-Pimentel, Juan Antonio, Brown, Steve, Flenniken, Ann, Flicek, Paul, Galli, Antonella, Mashhadi, Hamed Haseli, Hrabě De Angelis, Martin, Kim, Jong Kyoung, Lloyd, K C Kent, McKerlie, Colin, Morgan, Hugh, Murray, Stephen, Nutter, Lauryl, Reilly, Patrick, Seavitt, John, Seong, Je Kyung, Simon, Michelle, Wardle-Jones, Hannah, Mallon, Ann-Marie, Smedley, Damian, Parkinson, Helen, Queen Mary University of London (QMUL), German Research Center for Environmental Health - Helmholtz Center München (GmbH), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, The Wellcome Trust Sanger Institute [Cambridge], Institute for Experimental Genetics, GSF - National Research Center for Environment and Health, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Medical Research Counc, and European Bioinformatics Institute
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Wolf ,Mouse ,Knockout ,Cheetah ,Essential genes ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,Endangered species ,Loss-of-function ,Polar bear ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,Panda ,Phenotype ,IMPC ,Non-model species - Abstract
International audience; The International Mouse Phenotyping Consortium (IMPC) is building a catalogue of mammalian gene function by producing and phenotyping a knockout mouse line for every protein-coding gene. To date, the IMPC has generated and characterised 5186 mutant lines. One-third of the lines have been found to be non-viable and over 300 new mouse models of human disease have been identified thus far. While current bioinformatics efforts are focused on translating results to better understand human disease processes, IMPC data also aids understanding genetic function and processes in other species. Here we show, using gorilla genomic data, how genes essential to development in mice can be used to help assess the potentially deleterious impact of gene variants in other species. This type of analyses could be used to select optimal breeders in endangered species to maintain or increase fitness and avoid variants associated to impaired-health phenotypes or loss-of-function mutations in genes of critical importance. We also show, using selected examples from various mammal species, how IMPC data can aid in the identification of candidate genes for studying a condition of interest, deliver information about the mechanisms involved, or support predictions for the function of genes that may play a role in adaptation. With genotyping costs decreasing and the continued improvements of bioinformatics tools, the analyses we demonstrate can be routinely applied.
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- 2018
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48. Prediction of homo- and hetero-protein complexes by protein docking and template-based modeling: a CASP-CAPRI experiment
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Eichiro Ichiishi, Dmitri Beglov, Bernard Maigret, Gyu Rie Lee, Artem B. Mamonov, Shoshana J. Wodak, Jonathan C. Fuller, Dima Kozakov, Jong Young Joung, Petr Popov, Xiaofeng Yu, Keehyoung Joo, João P. G. L. M. Rodrigues, Anna Vangone, Koen M. Visscher, Xiaoqin Zou, Paul A. Bates, Andriy Kryshtafovych, Shourya S. Roy Burman, Daisuke Kihara, Romina Oliva, Efrat Ben-Zeev, Jeffrey J. Gray, Yang Shen, Li C. Xue, Sameer Velankar, Emilie Neveu, Shruthi Viswanath, Dina Schneidman-Duhovny, Juan Esquivel-Rodríguez, Mieczyslaw Torchala, Amit Roy, Alexandre M. J. J. Bonvin, David R. Hall, Tanggis Bohnuud, Xusi Han, David W. Ritchie, Ron Elber, Daisuke Kuroda, Zhiwei Ma, Joan Segura, Carlos A. Del Carpio, Nicholas A. Marze, Jong Yun Kim, Andrej Sali, Petras J. Kundrotas, Ezgi Karaca, Neil J. Bruce, Chaok Seok, Panagiotis L. Kastritis, Shen You Huang, Ilya A. Vakser, Lim Heo, Sanbo Qin, Raphael A. G. Chaleil, Adrien S. J. Melquiond, Miguel Romero-Durana, Anisah W. Ghoorah, Surendra S. Negi, Andrey Tovchigrechko, Françoise Ochsenbein, Narcis Fernandez-Fuentes, Liming Qiu, Miriam Eisenstein, Mehdi Nellen, Marie-Dominique Devignes, Lenna X. Peterson, Jinchao Yu, Minkyung Baek, Brian G. Pierce, Hasup Lee, Toshiyuki Oda, Rebecca C. Wade, Raphael Guerois, Juan Fernández-Recio, Iain H. Moal, Edrisse Chermak, Sergei Grudinin, Sangwoo Park, Ivan Anishchenko, Chengfei Yan, Thom Vreven, Kentaro Tomii, Bing Xia, Hyung Rae Kim, Chiara Pallara, Jooyoung Lee, Kazunori D. Yamada, Xianjin Xu, Kenichiro Imai, Zhiping Weng, Luigi Cavallo, Tyler M. Borrman, Jianlin Cheng, Marc F. Lensink, Huan-Xiang Zhou, Jilong Li, Gydo C. P. van Zundert, Brian Jiménez-García, Tsukasa Nakamura, Scott E. Mottarella, Sandor Vajda, Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq] ( IRI ), Université de Lille, Sciences et Technologies-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), European Molecular Biology Laboratory, European Bioinformatics Institute, Genome Center [UC Davis], University of California at Davis, Research Support Computing [Columbia], University of Missouri-Columbia, Bioinformatics Consortium and Department of Computer Science [Columbia], Department of Bioengineering and Therapeutic Sciences, University of California [San Francisco] ( UCSF ), Department of Pharmaceutical Chemistry, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, University of California [San Francisco] ( UCSF ) -California Institute for Quantitative Biosciences, GN7 of the National Institute for Bioinformatics (INB) and Biocomputing Unit, Centro Nacional de Biotecnología (CSIC), Institute of Biological, Environmental and Rural Sciences ( IBERS ), Institute for Computational Engineering and Sciences [Austin] ( ICES ), University of Texas at Austin [Austin], Department of Computer Science, Department of Chemistry, Algorithms for Modeling and Simulation of Nanosystems ( NANO-D ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Laboratoire Jean Kuntzmann ( LJK ), Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Institut National Polytechnique de Grenoble ( INPG ), Moscow Institute of Physics and Technology [Moscow] ( MIPT ), Seoul National University [Seoul], Florida State University [Tallahassee] ( FSU ), Computational Algorithms for Protein Structures and Interactions ( CAPSID ), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Department of Complex Systems, Artificial Intelligence & Robotics ( LORIA - AIS ), Laboratoire Lorrain de Recherche en Informatique et ses Applications ( LORIA ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Laboratoire Lorrain de Recherche en Informatique et ses Applications ( LORIA ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), University of Mauritius, Biomolecular Modelling Laboratory, The Francis Crick Institute, Lincoln's Inn Fields Laboratory, G-INCPM, Weizmann Institute of Science, Chemical Research Support [Rehovot], Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch ( UTMB ), Program in Bioinformatics and Integrative Biology [Worcester], University of Massachusetts Medical School [Worcester] ( UMASS ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Sud - Paris 11 ( UP11 ), Bijvoet Center for Biomolecular Research [Utrecht], Utrecht University [Utrecht], Dalton Cardiovascular Research Center [Columbia], Department of Computer Science [Columbia], Informatics Intitute, Department of Biochemistry, University of Missouri, UNIVERSITY OF MISSOURI, Toyota Technological Institute at Chicago [Chicago] ( TTIC ), Department of Biological Sciences, Purdue University, Purdue University [West Lafayette], Department of Computer Science [Purdue], Bioinformatics and Computational Biosciences Branch, Rocky Mountain Laboratories, Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies, Center for Molecular Biology ( ZMBH ), Universität Heidelberg [Heidelberg], Interdisciplinary Center for Scientific Computing ( IWR ), Department of Molecular Biosciences [Lawrence], University of Kansas [Lawrence] ( KU ), Computational Biology Research Center ( CBRC ), National Institute of Advanced Industrial Science and Technology ( AIST ), Graduate School of Frontier Sciences, The University of Tokyo, Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center - Centro Nacional de Supercomputacion ( BSC - CNS ), Center for In-Silico Protein Science, Korea Institute for Advanced Study ( KIAS ), Center for Advanced Computation, Department of Biomedical Engineering [Boston], Boston University [Boston] ( BU ), Institute of Biological Diversity, International Pacific Institute of Indiana, Drosophila Genetic Resource Center, Kyoto Institute of Technology, International University of Health and Welfare Hospital ( IUHW Hospital ), International University of Health and Welfare Hospital, Department of Chemical and Biomolecular Engineering [Baltimore], Johns Hopkins University ( JHU ), Program in Molecular Biophysics [Baltimore], King Abdullah University of Science and Technology ( KAUST ), University of Naples, J Craig Venter Institute, Structural Biology Research Center, VIB, 1050 Brussels, Belgium, Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq] (IRI), Université de Lille, Sciences et Technologies-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), University of Missouri [Columbia] (Mizzou), University of Missouri System, University of California [San Francisco] (UC San Francisco), Centro Nacional de Biotecnología [Madrid] (CNB-CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Institute of Biological, Environmental and Rural Sciences (IBERS), Institute for Computational Engineering and Sciences [Austin] (ICES), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Moscow Institute of Physics and Technology [Moscow] (MIPT), Seoul National University [Seoul] (SNU), Florida State University [Tallahassee] (FSU), Computational Algorithms for Protein Structures and Interactions (CAPSID), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Biomolecular Modelling Laboratory [London], The Francis Crick Institute [London], Weizmann Institute of Science [Rehovot, Israël], The University of Texas Medical Branch (UTMB), University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS)-University of Massachusetts System (UMASS), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Assemblage moléculaire et intégrité du génome (AMIG), Département Biochimie, Biophysique et Biologie Structurale (B3S), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of Missouri System-University of Missouri System, Toyota Technological Institute at Chicago [Chicago] (TTIC), Department of Biological Sciences [Lafayette IN], Heidelberg Institute for Theoretical Studies (HITS ), Center for Molecular Biology (ZMBH), Universität Heidelberg [Heidelberg] = Heidelberg University, Interdisciplinary Center for Scientific Computing (IWR), University of Kansas [Lawrence] (KU), Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), The University of Tokyo (UTokyo), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Korea Institute for Advanced Study (KIAS), Boston University [Boston] (BU), International University of Health and Welfare Hospital (IUHW Hospital), Johns Hopkins University (JHU), King Abdullah University of Science and Technology (KAUST), University of Naples Federico II = Università degli studi di Napoli Federico II, J. Craig Venter Institute, VIB-VUB Center for Structural Biology [Bruxelles], VIB [Belgium], Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Droit et Santé-Université de Lille, Sciences et Technologies, University of California-University of California, University of California [San Francisco] (UCSF), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), University of Naples Federico II, Barcelona Supercomputing Center, NMR Spectroscopy, and Sub NMR Spectroscopy
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0301 basic medicine ,Protein Conformation, alpha-Helical ,Protein Folding ,Computer science ,International Cooperation ,Amino Acid Motifs ,Oligomer state ,Homoprotein ,DATA-BANK ,computer.software_genre ,Molecular Docking Simulation ,Biochemistry ,CAPRI Round 30 ,DESIGN ,Structural Biology ,ALIGN ,Blind prediction ,AFFINITY ,Protein interaction ,Enginyeria biomèdica [Àrees temàtiques de la UPC] ,ZDOCK ,Oligomer State ,computer.file_format ,Articles ,Protein structure prediction ,Proteïnes--Investigació ,3. Good health ,WEB SERVER ,CASP ,Thermodynamics ,Data mining ,CAPRI ,Protein docking ,Molecular Biology ,Algorithms ,INTERFACES ,Protein Binding ,[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation ,Bioinformatics ,STRUCTURAL BIOLOGY ,Computational biology ,Molecular Dynamics Simulation ,Article ,03 medical and health sciences ,[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM] ,Heteroprotein ,Humans ,Protein binding ,Macromolecular docking ,Protein Interaction Domains and Motifs ,Homology modeling ,ALGORITHM ,Protein-protein docking ,Internet ,Binding Sites ,Models, Statistical ,030102 biochemistry & molecular biology ,Bacteria ,Sequence Homology, Amino Acid ,Computational Biology ,Proteins ,Protein Data Bank ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,Protein Structure, Tertiary ,030104 developmental biology ,Structural biology ,Docking (molecular) ,Protein structure ,Protein Conformation, beta-Strand ,Protein Multimerization ,oligomer state ,blind prediction ,protein interaction ,protein docking ,[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ,computer ,Software - Abstract
We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. We are most grateful to the PDBe at the European Bioinformatics Institute in Hinxton, UK, for hosting the CAPRI website. Our deepest thanks go to all the structural biologists and to the following structural genomics initiatives: Northeast Structural Genomics Consortium, Joint Center for Structural Genomics, NatPro PSI:Biology, New York Structural Genomics Research Center, Midwest Center for Structural Genomics, Structural Genomics Consortium, for contributing the targets for this joint CASP-CAPRI experiment. MFL acknowledges support from the FRABio FR3688 Research Federation “Structural & Functional Biochemistry of Biomolecular Assemblies.”
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- 2016
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49. Genome sequence of Aedes aegypti, a major arbovirus vector
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Sergio Verjovski-Almeida, James E. Galagan, Ryan C. Kennedy, Zhiyong Xi, Jason R. Miller, Eric Eisenstadt, Kyanne R. Reidenbach, Robert V. Bruggner, Yu-Hui Rogers, Hadi Quesneville, Doreen Werner, Owen White, Alexander S. Raikhel, Mario Stanke, J. Spencer Johnston, Diane D. Lovin, Evgenia V. Kriventseva, Ian T. Paulsen, Kathryn S. Campbell, Norman H. Lee, Ewan Birney, Karyn Megy, Hean Koo, David Kulp, Shelby L. Bidwell, Jingsong Zhu, Philip Montgomery, Paolo Amedeo, Yongmei Zhao, Chinnappa D. Kodira, Javier Costas, Michael C. Schatz, Steven P. Sinkins, Claire M. Fraser-Liggett, Martin Shumway, Kurt LaButti, Akio Mori, Brendan J. Loftus, Manfred Grabherr, Eric O. Stinson, Frank H. Collins, Zhijian Jake Tu, Monique R. Coy, Matt Crawford, Janice P. Vanzee, William M. Gelbart, Joshua Orvis, Peter Arensburger, Chunhong Mao, Evgeny M. Zdobnov, Saul A. Kravitz, Suely Lopes Gomes, David DeCaprio, David G. Hogenkamp, Daniel Lawson, Dennis L. Knudson, David W. Severson, George Dimopoulos, Marcelo B. Soares, Sinéad B. O'Leary, Peter W. Atkinson, David M. Jaffe, Becky deBruyn, Martin Hammond, Ana L. T. O. Nascimento, Jim Biedler, Stefan Wyder, Jose M. C. Tubio, Bruce W. Birren, Catherine A. Hill, Chad Nusbaum, Eduardo Lee, Song Li, Susan E. Brown, Jennifer R. Wortman, James R. Hogan, Hamza El-Dorry, Qi Zhao, Linda Hannick, Carlos Frederico Martins Menck, Vishvanath Nene, Jonathan Crabtree, Steven L. Salzberg, Michael H. Holmes, Maria de Fatima Bonaldo, Quinghu Ren, Mihaela Pertea, Charles Roth, Evan Mauceli, Karin Eiglmeier, Horacio Naveira, Brian J. Haas, Qiandong Zeng, Neil F. Lobo, Jennifer R. Schneider, The Institute for Genomic Research, The Institute for Genomic Research, Rockville, European Bioinformatics Institute [Hinxton] ( EMBL-EBI ), European Molecular Biology Laboratory [Hinxton], Broad Institute of MIT and Harvard ( BROAD INSTITUTE ), Broad Institute of MIT and Harvard, Virginia Polytechnic Institute and State University [Blacksburg], University College Dublin [Dublin] ( UCD ), Bloomberg School of Public Health, Johns Hopkins University ( JHU ) -Bloomberg School of Public Health, University of Geneva Medical School, Swiss Institute of Bioinformatics-University of Geneva Medical School, University of Notre Dame ( UND ), Harvard University [Cambridge], College of Agricultural Sciences Colorado State University, Colorado State University [Fort Collins] ( CSU ) -College of Agricultural Sciences, Northwestern University [Evanston], University of California [Riverside] ( UCR ), Department of Atmospheric, Oceanic and Planetary Physics [Oxford] ( AOPP ), University of Oxford [Oxford], Purdue University [West Lafayette], Centro Nacional de Genotipado Fundación Pública Galega de Medicina Xenómica Hospital Clínico Universitario de Santiago, Centro Nacional de Genotipado-Fundación Pública Galega de Medicina Xenómica-Hospital Clínico Universitario de Santiago, Institut Pasteur [Paris], Universidade de Sao Paulo Instituto de Quimica, Universidade de São Paulo ( USP ) -Instituto de Quimica, Texas A&M University [College Station], Joint Technology Center, University of Massachusetts [Amherst] ( UMass Amherst ), Universidade de Sao Paulo, Institute of Biomedical Sciences, Universidade de São Paulo ( USP ) -Institute of Biomedical Sciences, Instituto Butantan [São Paulo], Universidade da Coruña, University of Maryland [College Park], Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), University of California [Santa Cruz] ( UCSC ), Complexo Hospitalario Universitario de Santiago, Universität Göttingen, Georg-August-Universität Göttingen, George Washington University Medical Center, George Washington University ( GW ), The Institute for Genomic Research (TIGR), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], University College Dublin [Dublin] (UCD), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne (UNIL)-Université de Lausanne (UNIL)-University of Geneva Medical School, University of Notre Dame [Indiana] (UND), Colorado State University [Fort Collins] (CSU)-College of Agricultural Sciences, University of California [Riverside] (UCR), University of California, Department of Atmospheric, Oceanic and Planetary Physics [Oxford] (AOPP), Universidade de São Paulo (USP)-Instituto de Quimica, University of Massachusetts [Amherst] (UMass Amherst), University of Massachusetts System (UMASS), Universidade de São Paulo (USP)-Institute of Biomedical Sciences (ICB/USP), Universidade de São Paulo (USP), University of Maryland System, Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), University of California [Santa Cruz] (UCSC), Georg-August-University [Göttingen], The George Washington University (GW), George Washington University (GW), Université de Lausanne = University of Lausanne (UNIL)-Université de Lausanne = University of Lausanne (UNIL)-University of Geneva Medical School, Harvard University, University of California [Riverside] (UC Riverside), University of California (UC), University of Oxford, Institut Pasteur [Paris] (IP), Universidade de São Paulo = University of São Paulo (USP)-Instituto de Quimica, Universidade de São Paulo = University of São Paulo (USP)-Institute of Biomedical Sciences (ICB/USP), Universidade de São Paulo = University of São Paulo (USP), University of California [Santa Cruz] (UC Santa Cruz), Georg-August-University = Georg-August-Universität Göttingen, Zdobnov, Evgeny, and Wyder, Stefan
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0106 biological sciences ,Male ,Transcription, Genetic ,Genome, Insect ,transposons ,receptors ,Genes, Insect ,Aedes/ genetics/metabolism ,MESH: Genes, Insect ,Yellow Fever/prevention & control/transmission ,MESH: Base Sequence ,01 natural sciences ,Dengue/prevention & control/transmission ,MESH: Protein Structure, Tertiary ,MESH: Arboviruses ,MESH : Insect Vectors ,MESH: Insect Proteins ,MESH : Anopheles gambiae ,MESH: Animals ,MESH : Arboviruses ,insects ,MESH: Yellow Fever ,superfamily ,ddc:616 ,0303 health sciences ,Anopheles ,MESH : Genes, Insect ,3. Good health ,yellow-fever mosquito ,anopheles-gambiae ,drosophila-melanogaster ,expression ,evolution ,organization ,Drosophila melanogaster ,MESH: DNA Transposable Elements ,[ SDV.BBM.GTP ] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Multigene Family ,Public Health ,MESH : Protein Structure, Tertiary ,MESH: Sex Characteristics ,Molecular Sequence Data ,MESH : Multigene Family ,MESH: Sex Determination (Genetics) ,MESH : Sex Determination (Genetics) ,Arbovirus ,Article ,03 medical and health sciences ,Species Specificity ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,MESH: Anopheles gambiae ,Yellow Fever ,MESH: Species Specificity ,Humans ,MESH: Humans ,MESH: Molecular Sequence Data ,fungi ,MESH : Humans ,MESH : Sex Characteristics ,Membrane Transport Proteins ,Sex Determination Processes ,medicine.disease ,Insect Vectors ,Protein Structure, Tertiary ,Sex Determination (Genetics) ,MESH: Multigene Family ,MESH: Female ,MESH : Sequence Analysis, DNA ,MESH: Sequence Analysis, DNA ,Drosophila melanogaster/genetics ,MESH : Molecular Sequence Data ,Odorant binding ,Insect Proteins/genetics ,Anopheles gambiae ,MESH: Dengue ,Genome ,MESH: Membrane Transport Proteins ,Dengue ,MESH : Membrane Transport Proteins ,Aedes ,Insect Vectors/ genetics/metabolism ,MESH : Drosophila melanogaster ,MESH : Female ,Membrane Transport Proteins/genetics ,Genetics ,MESH : Insect Proteins ,Sex Characteristics ,Multidisciplinary ,MESH: Synteny ,MESH: Aedes ,MESH : Genome, Insect ,MESH : DNA Transposable Elements ,Insect Proteins ,Female ,Orthologous Gene ,MESH : Male ,MESH : Dengue ,Aedes aegypti ,MESH: Insect Vectors ,Biology ,010603 evolutionary biology ,Synteny ,MESH: Drosophila melanogaster ,Protein Structure, Tertiary/genetics ,MESH : Yellow Fever ,parasitic diseases ,medicine ,MESH : Species Specificity ,Animals ,030304 developmental biology ,MESH : Aedes ,Base Sequence ,MESH: Genome, Insect ,MESH: Transcription, Genetic ,MESH : Synteny ,MESH : Transcription, Genetic ,Sequence Analysis, DNA ,biology.organism_classification ,MESH: Male ,DNA Transposable Elements ,MESH : Base Sequence ,MESH : Animals ,Arboviruses ,Anopheles gambiae/genetics/metabolism - Abstract
We present a draft sequence of the genome of Aedes aegypti , the primary vector for yellow fever and dengue fever, which at ∼1376 million base pairs is about 5 times the size of the genome of the malaria vector Anopheles gambiae . Nearly 50% of the Ae. aegypti genome consists of transposable elements. These contribute to a factor of ∼4 to 6 increase in average gene length and in sizes of intergenic regions relative to An. gambiae and Drosophila melanogaster . Nonetheless, chromosomal synteny is generally maintained among all three insects, although conservation of orthologous gene order is higher (by a factor of ∼2) between the mosquito species than between either of them and the fruit fly. An increase in genes encoding odorant binding, cytochrome P450, and cuticle domains relative to An. gambiae suggests that members of these protein families underpin some of the biological differences between the two mosquito species.
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- 2016
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50. GO-FAANG meeting: a Gathering On Functional Annotation of Animal Genomes
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Tuggle, Christopher, Giuffra, Elisabetta, White, Stephen, Clarke, Laura, Zhou, Huaijun, Ross, Pablo, Finno, Carrie, Acloque, H., Reecy, James, Archibald, Alan, Bellone ¶ ¶, Rebecca, Boichard, Michèle, Chamberlain, Amanda, Cheng, Hans, Crooijmans, Richard, Delany, Mary, Finno, Carrie J., Groenen, Martien, Hayes, Ben, Lunney, Joan, Petersen, Jessica, Plastow, Graham, Schmidt, Carl, Song, Jiuzhou, Watson, Mick, Iowa State University (ISU), Génétique Animale et Biologie Intégrative (GABI), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, USDA-ARS : Agricultural Research Service, Center for Reproductive Biology, Washington State University (WSU), Department of Veterinary Microbiology and Pathology, European Molecular Biology Laboratory, European Bioinformatics Institute, Department of Animal Science, University of California, Department of Population Health and Reproduction, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Department of Population Health and Reproduction, School of Veterinary Medicine, Department of Economic Development, Jobs, Transport and Resources (DEDJTR), Avian Disease and Oncology Laboratory, 4279 E Mount Hope Road, Animal Breeding and Genomics Centre, Wageningen University and Research [Wageningen] (WUR), Centre for Nutrition and Food Sciences - Queensland Alliance for Agriculture and Food Innovation, University of Southern Queensland (USQ), Animal Parasitic Diseases Laboratory [Beltsville, USA], United States Department of Agriculture (USDA)-USDA Agricultural Research Service [Beltsville, Maryland], USDA-ARS : Agricultural Research Service-USDA-ARS : Agricultural Research Service, Department of Agricultural, Food & Nutritional Science, University of Alberta, Department of Animal & Food Sciences, University of Delaware [Newark], Department of Animal and Avian Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, National Science Foundation (NSF) NSF-IOS-1548275, United States Department of Agriculture (USDA) USDA-NIFA-AFRI, 2015-68004-24104, Illumina, Inc, Iowa State University, USDA-NRSP-8 Bioinformatics, United States Department of Agriculture (USDA) 2016-67015-24579, Genome Canada, Affymetrix, Inc, Geneseek, Inc, Biotechnology and Biological Sciences Research Council including Institute Strategic Programme and National Capability Grants (BBSRC) BBS/E/D/20310000 BB/J004243/1, INRA through the SelGen metaprogramme (Fr-AgENCODE project), Biotechnology and Biological Sciences Research Council (BBSRC) : BBS/E/D/20211551, BBS/E/D/20211550, BBS/E/D/20310000, BB/M01844X/1., United States Department of Agriculture (USDA), European Molecular Biology Laboratory European Bioinformatics Institute, University of California [Davis] (UC Davis), Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT], Roslin Institute, Wageningen University and Research Centre (WUR), University of Queensland [Brisbane], Dept Anim & Food Sci, and University of Maryland System
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data coordination centre (DCC) ,Dairy & Animal Science ,[SDV]Life Sciences [q-bio] ,International Cooperation ,data sharing ,[SDV.SA.ZOO]Life Sciences [q-bio]/Agricultural sciences/Zootechny ,dna ,Animal Breeding and Genomics ,metanalysis ,genomic ,Genetics ,Animals ,[INFO]Computer Science [cs] ,Fokkerij en Genomica ,Veterinary Sciences ,Domestic ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,regulatory variation ,Genome ,Genomics ,Articles ,Congresses as Topic ,Reference Standards ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal genetics ,reveal principle ,data coordination centre ,Animals, Domestic ,District of Columbia ,WIAS ,chromatin ,Original Article ,Zoology - Abstract
International audience; The Functional Annotation of Animal Genomes (FAANG) Consortium recently held a Gathering On FAANG (GO-FAANG) Workshop in Washington, DC on October 7-8, 2015. This consortium is a grass-roots organization formed to advance the annotation of newly assembled genomes of domesticated and non-model organisms (www.faang.org). The workshop gathered together from around the world a group of 100+ genome scientists, administrators, representatives of funding agencies and commodity groups to discuss the latest advancements of the consortium, new perspectives, next steps and implementation plans. The workshop was streamed live and recorded, and all talks, along with speaker slide presentations, are available at www.faang.org. In this report, we describe the major activities and outcomes of this meeting. We also provide updates on ongoing efforts to implement discussions and decisions taken at GO-FAANG to guide future FAANG activities. In summary, reference datasets are being established under pilot projects; plans for tissue sets, morphological classification and methods of sample collection for different tissues were organized; and core assays and data and meta-data analysis standards were established.
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- 2016
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