Identification of genetic elements in metabolism by high-throughput mouse phenotyping

The genetic basis of metabolic diseases is incompletely understood. Here, by high-throughput phenotyping of 2,016 knockout mouse strains, Rozman and colleagues identify candidate metabolic genes, many of which are associated with unexplored regulatory gene networks and metabolic traits in human GWAS...

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Autores principales:	Jan Rozman, Birgit Rathkolb, Manuela A. Oestereicher, Christine Schütt, Aakash Chavan Ravindranath, Stefanie Leuchtenberger, Sapna Sharma, Martin Kistler, Monja Willershäuser, Robert Brommage, Terrence F. Meehan, Jeremy Mason, Hamed Haselimashhadi, IMPC Consortium, Tertius Hough, Ann-Marie Mallon, Sara Wells, Luis Santos, Christopher J. Lelliott, Jacqueline K. White, Tania Sorg, Marie-France Champy, Lynette R. Bower, Corey L. Reynolds, Ann M. Flenniken, Stephen A. Murray, Lauryl M. J. Nutter, Karen L. Svenson, David West, Glauco P. Tocchini-Valentini, Arthur L. Beaudet, Fatima Bosch, Robert B. Braun, Michael S. Dobbie, Xiang Gao, Yann Herault, Ala Moshiri, Bret A. Moore, K. C. Kent Lloyd, Colin McKerlie, Hiroshi Masuya, Nobuhiko Tanaka, Paul Flicek, Helen E. Parkinson, Radislav Sedlacek, Je Kyung Seong, Chi-Kuang Leo Wang, Mark Moore, Steve D. Brown, Matthias H. Tschöp, Wolfgang Wurst, Martin Klingenspor, Eckhard Wolf, Johannes Beckers, Fausto Machicao, Andreas Peter, Harald Staiger, Hans-Ulrich Häring, Harald Grallert, Monica Campillos, Holger Maier, Helmut Fuchs, Valerie Gailus-Durner, Thomas Werner, Martin Hrabe de Angelis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/7b0bd2741d2c4a34a03d78a177e5cce3
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spelling	oai:doaj.org-article:7b0bd2741d2c4a34a03d78a177e5cce32021-12-02T14:39:26ZIdentification of genetic elements in metabolism by high-throughput mouse phenotyping10.1038/s41467-017-01995-22041-1723https://doaj.org/article/7b0bd2741d2c4a34a03d78a177e5cce32018-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-01995-2https://doaj.org/toc/2041-1723The genetic basis of metabolic diseases is incompletely understood. Here, by high-throughput phenotyping of 2,016 knockout mouse strains, Rozman and colleagues identify candidate metabolic genes, many of which are associated with unexplored regulatory gene networks and metabolic traits in human GWAS.Jan RozmanBirgit RathkolbManuela A. OestereicherChristine SchüttAakash Chavan RavindranathStefanie LeuchtenbergerSapna SharmaMartin KistlerMonja WillershäuserRobert BrommageTerrence F. MeehanJeremy MasonHamed HaselimashhadiIMPC ConsortiumTertius HoughAnn-Marie MallonSara WellsLuis SantosChristopher J. LelliottJacqueline K. WhiteTania SorgMarie-France ChampyLynette R. BowerCorey L. ReynoldsAnn M. FlennikenStephen A. MurrayLauryl M. J. NutterKaren L. SvensonDavid WestGlauco P. Tocchini-ValentiniArthur L. BeaudetFatima BoschRobert B. BraunMichael S. DobbieXiang GaoYann HeraultAla MoshiriBret A. MooreK. C. Kent LloydColin McKerlieHiroshi MasuyaNobuhiko TanakaPaul FlicekHelen E. ParkinsonRadislav SedlacekJe Kyung SeongChi-Kuang Leo WangMark MooreSteve D. BrownMatthias H. TschöpWolfgang WurstMartin KlingensporEckhard WolfJohannes BeckersFausto MachicaoAndreas PeterHarald StaigerHans-Ulrich HäringHarald GrallertMonica CampillosHolger MaierHelmut FuchsValerie Gailus-DurnerThomas WernerMartin Hrabe de AngelisNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-16 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jan Rozman Birgit Rathkolb Manuela A. Oestereicher Christine Schütt Aakash Chavan Ravindranath Stefanie Leuchtenberger Sapna Sharma Martin Kistler Monja Willershäuser Robert Brommage Terrence F. Meehan Jeremy Mason Hamed Haselimashhadi IMPC Consortium Tertius Hough Ann-Marie Mallon Sara Wells Luis Santos Christopher J. Lelliott Jacqueline K. White Tania Sorg Marie-France Champy Lynette R. Bower Corey L. Reynolds Ann M. Flenniken Stephen A. Murray Lauryl M. J. Nutter Karen L. Svenson David West Glauco P. Tocchini-Valentini Arthur L. Beaudet Fatima Bosch Robert B. Braun Michael S. Dobbie Xiang Gao Yann Herault Ala Moshiri Bret A. Moore K. C. Kent Lloyd Colin McKerlie Hiroshi Masuya Nobuhiko Tanaka Paul Flicek Helen E. Parkinson Radislav Sedlacek Je Kyung Seong Chi-Kuang Leo Wang Mark Moore Steve D. Brown Matthias H. Tschöp Wolfgang Wurst Martin Klingenspor Eckhard Wolf Johannes Beckers Fausto Machicao Andreas Peter Harald Staiger Hans-Ulrich Häring Harald Grallert Monica Campillos Holger Maier Helmut Fuchs Valerie Gailus-Durner Thomas Werner Martin Hrabe de Angelis Identification of genetic elements in metabolism by high-throughput mouse phenotyping
description	The genetic basis of metabolic diseases is incompletely understood. Here, by high-throughput phenotyping of 2,016 knockout mouse strains, Rozman and colleagues identify candidate metabolic genes, many of which are associated with unexplored regulatory gene networks and metabolic traits in human GWAS.
format	article
author	Jan Rozman Birgit Rathkolb Manuela A. Oestereicher Christine Schütt Aakash Chavan Ravindranath Stefanie Leuchtenberger Sapna Sharma Martin Kistler Monja Willershäuser Robert Brommage Terrence F. Meehan Jeremy Mason Hamed Haselimashhadi IMPC Consortium Tertius Hough Ann-Marie Mallon Sara Wells Luis Santos Christopher J. Lelliott Jacqueline K. White Tania Sorg Marie-France Champy Lynette R. Bower Corey L. Reynolds Ann M. Flenniken Stephen A. Murray Lauryl M. J. Nutter Karen L. Svenson David West Glauco P. Tocchini-Valentini Arthur L. Beaudet Fatima Bosch Robert B. Braun Michael S. Dobbie Xiang Gao Yann Herault Ala Moshiri Bret A. Moore K. C. Kent Lloyd Colin McKerlie Hiroshi Masuya Nobuhiko Tanaka Paul Flicek Helen E. Parkinson Radislav Sedlacek Je Kyung Seong Chi-Kuang Leo Wang Mark Moore Steve D. Brown Matthias H. Tschöp Wolfgang Wurst Martin Klingenspor Eckhard Wolf Johannes Beckers Fausto Machicao Andreas Peter Harald Staiger Hans-Ulrich Häring Harald Grallert Monica Campillos Holger Maier Helmut Fuchs Valerie Gailus-Durner Thomas Werner Martin Hrabe de Angelis
author_facet	Jan Rozman Birgit Rathkolb Manuela A. Oestereicher Christine Schütt Aakash Chavan Ravindranath Stefanie Leuchtenberger Sapna Sharma Martin Kistler Monja Willershäuser Robert Brommage Terrence F. Meehan Jeremy Mason Hamed Haselimashhadi IMPC Consortium Tertius Hough Ann-Marie Mallon Sara Wells Luis Santos Christopher J. Lelliott Jacqueline K. White Tania Sorg Marie-France Champy Lynette R. Bower Corey L. Reynolds Ann M. Flenniken Stephen A. Murray Lauryl M. J. Nutter Karen L. Svenson David West Glauco P. Tocchini-Valentini Arthur L. Beaudet Fatima Bosch Robert B. Braun Michael S. Dobbie Xiang Gao Yann Herault Ala Moshiri Bret A. Moore K. C. Kent Lloyd Colin McKerlie Hiroshi Masuya Nobuhiko Tanaka Paul Flicek Helen E. Parkinson Radislav Sedlacek Je Kyung Seong Chi-Kuang Leo Wang Mark Moore Steve D. Brown Matthias H. Tschöp Wolfgang Wurst Martin Klingenspor Eckhard Wolf Johannes Beckers Fausto Machicao Andreas Peter Harald Staiger Hans-Ulrich Häring Harald Grallert Monica Campillos Holger Maier Helmut Fuchs Valerie Gailus-Durner Thomas Werner Martin Hrabe de Angelis
author_sort	Jan Rozman
title	Identification of genetic elements in metabolism by high-throughput mouse phenotyping
title_short	Identification of genetic elements in metabolism by high-throughput mouse phenotyping
title_full	Identification of genetic elements in metabolism by high-throughput mouse phenotyping
title_fullStr	Identification of genetic elements in metabolism by high-throughput mouse phenotyping
title_full_unstemmed	Identification of genetic elements in metabolism by high-throughput mouse phenotyping
title_sort	identification of genetic elements in metabolism by high-throughput mouse phenotyping
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/7b0bd2741d2c4a34a03d78a177e5cce3
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Identification of genetic elements in metabolism by high-throughput mouse phenotyping

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