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Power matters in closing the phenotyping gap.
Naturwissenschaften 94, 401-406 (2007)
Much of our understanding of physiology and metabolism is derived from investigating mouse mutants and transgenic mice, and open-access platforms for standardized mouse phenotyping such as the German Mouse Clinic (GMC) are currently viewed as one powerful tool for identifying novel gene-function relationships. Phenotyping or phenotypic screening involves the comparison of wild-type control mice with their mutant or transgenic littermates. In our study, we explored the extent to which standardized phenotyping will succeed in detecting biologically relevant phenotypic differences in mice generated and provided by different collaborators. We analyzed quantitative metabolic data (body mass, energy intake, and energy metabolized) collected at the GMC under the current workflow, and used them for statistical power considerations. Our results demonstrate that there is substantial variability in these parameters among lines of wild-type C57BL/6 (B6) mice from different sources. Given this variable background noise in mice that serve as controls, subtle phenotypes in mutant or transgenic littermates may be overlooked. Furthermore, a phenotype observed in one cohort of a mutant line may not be reproducible (to the same extent) in mice coming from a different environment or supplier. In the light of these constraints, we encourage researchers to incorporate information on intrastrain variability into future study planning, or to perform advanced hierarchical analyses. Both will ultimately improve the detectability of novel phenotypes by phenotypic screening.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Phenotyping; Mouse mutants; Statistical power
ISSN (print) / ISBN
0028-1042
e-ISSN
1432-1904
Zeitschrift
Naturwissenschaften, Die
Quellenangaben
Band: 94,
Heft: 5,
Seiten: 401-406
Verlag
Springer
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Experimental Genetics (IEG)