Disease Models & Mechanisms (May 2014)

Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen

  • Hibret A. Adissu,
  • Jeanne Estabel,
  • David Sunter,
  • Elizabeth Tuck,
  • Yvette Hooks,
  • Damian M. Carragher,
  • Kay Clarke,
  • Natasha A. Karp,
  • Sanger Mouse Genetics Project,
  • Susan Newbigging,
  • Nora Jones,
  • Lily Morikawa,
  • Jacqueline K. White,
  • Colin McKerlie

DOI
https://doi.org/10.1242/dmm.015263
Journal volume & issue
Vol. 7, no. 5
pp. 515 – 524

Abstract

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The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice.

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