Nature Communications (Jan 2018)

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

  • 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

DOI
https://doi.org/10.1038/s41467-017-01995-2
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 16

Abstract

Read online

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.