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Improving laboratory animal genetic reporting: LAG-R guidelines

Author

Listed:
  • Lydia Teboul

    (Harwell Campus)

  • James Amos-Landgraf

    (University of Missouri School of Medicine
    University of Missouri College of Veterinary Medicine
    University of Missouri)

  • Fernando J. Benavides

    (The University of Texas MD Anderson Cancer Center)

  • Marie-Christine Birling

    (Illkirch-Grafenstaden)

  • Steve D. M. Brown

    (Illkirch-Grafenstaden)

  • Elizabeth Bryda

    (University of Missouri)

  • Rosie Bunton-Stasyshyn

    (Harwell Campus)

  • Hsian-Jean Chin

    (NARLabs)

  • Martina Crispo

    (Institut Pasteur de Montevideo, Mataojo 2020)

  • Fabien Delerue

    (The University of Texas MD Anderson Cancer Center)

  • Michael Dobbie

    (Australian National University)

  • Craig L. Franklin

    (University of Missouri)

  • Ernst-Martin Fuchtbauer

    (University of Aarhus)

  • Xiang Gao

    (Nanjing University)

  • Christelle Golzio

    (IGBMC UMR 7104- UMR-S 1258)

  • Rebecca Haffner

    (Weizmann Institute of Science)

  • Yann Hérault

    (Illkirch-Grafenstaden
    IGBMC UMR 7104- UMR-S 1258)

  • Martin Hrabe de Angelis

    (Ingolstaedter Landstraße 1
    Alte Akademie 8
    Ingolstaedter Landstraße 1)

  • Kevin C. Kent Lloyd

    (University of California Davis)

  • Terry R. Magnuson

    (The University of North Carolina at Chapel Hill)

  • Lluis Montoliu

    (National Centre for Biotechnology (CNB-CSIC)
    Centre for Biomedical Network Research on Rare Diseases (CIBERER-ISCIII))

  • Stephen A. Murray

    (The Jackson Laboratory)

  • Ki-Hoan Nam

    (Korea Research Institute of Bioscience and Biotechnology (KRIBB))

  • Lauryl M. J. Nutter

    (The Hospital for Sick Children and The Centre for Phenogenomics)

  • Eric Pailhoux

    (BREED)

  • Fernando Pardo Manuel de Villena

    (University of North Carolina
    University of North Carolina)

  • Kevin Peterson

    (The Jackson Laboratory)

  • Laura Reinholdt

    (The Jackson Laboratory)

  • Radislav Sedlacek

    (Institute of Molecular Genetics of the Czech Academy of Sciences)

  • Je Kyung Seong

    (Seoul National University, and Korea Mouse Phenotyping Center)

  • Toshihiko Shiroishi

    (RIKEN BioResource Research Center (BRC))

  • Cynthia Smith

    (Jackson Laboratory)

  • Toru Takeo

    (Kumamoto University)

  • Louise Tinsley

    (Harwell Campus)

  • Jean-Luc Vilotte

    (GABI)

  • Søren Warming

    (a member of the Roche group)

  • Sara Wells

    (Harwell Campus
    Francis Crick Institute)

  • C. Bruce Whitelaw

    (University of Edinburgh)

  • Atsushi Yoshiki

    (RIKEN BioResource Research Center)

  • Guillaume Pavlovic

    (Illkirch-Grafenstaden)

Abstract

The biomedical research community addresses reproducibility challenges in animal studies through standardized nomenclature, improved experimental design, transparent reporting, data sharing, and centralized repositories. The ARRIVE guidelines outline documentation standards for laboratory animals in experiments, but genetic information is often incomplete. To remedy this, we propose the Laboratory Animal Genetic Reporting (LAG-R) framework. LAG-R aims to document animals’ genetic makeup in scientific publications, providing essential details for replication and appropriate model use. While verifying complete genetic compositions may be impractical, better reporting and validation efforts enhance reliability of research. LAG-R standardization will bolster reproducibility, peer review, and overall scientific rigor.

Suggested Citation

  • Lydia Teboul & James Amos-Landgraf & Fernando J. Benavides & Marie-Christine Birling & Steve D. M. Brown & Elizabeth Bryda & Rosie Bunton-Stasyshyn & Hsian-Jean Chin & Martina Crispo & Fabien Delerue , 2024. "Improving laboratory animal genetic reporting: LAG-R guidelines," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49439-y
    DOI: 10.1038/s41467-024-49439-y
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    References listed on IDEAS

    as
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