Abstract
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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Austin CP, Battey JF, Bradley A, Bucan M, Capecchi M, Collins FS, Dove WF, Duyk G, Dymecki S, Eppig JT, Grieder FB, Heintz N, Hicks G, Insel TR, Joyner A, Koller BH, Lloyd KC, Magnuson T, Moore MW, Nagy A, Pollock JD, Roses AD, Sands AT, Seed B, Skarnes WC, Snoddy J, Soriano P, Stewart DJ, Stewart F, Stillman B, Varmus H, Varticovski L, Verma IM, Vogt TF, von Melchner H, Witkowski J, Woychik RP, Wurst W, Yancopoulos GD, Young SG, Zambrowicz B (2004) The knockout mouse project. Nat Genet 36:921–924
Brown SD, Peters J (1996) Combining mutagenesis and genomics in the mouse-closing the phenotype gap. Trends Genet 12:433–435
Brown SD, Chambon P, Hrabe de Angelis M (2005) EMPReSS: standardized phenotype screens for functional annotation of the mouse genome. Nat Genet 37:1155
Bultman SJ, Michaud EJ, Woychik RP (1992) Molecular characterization of the mouse agouti locus. Cell 71:1195–1204
Cohen J (1969) Statistical power analysis for the behavioral sciences, 1st edn. Lawrence Erlbaum, Hillsdale (2nd edn 1988)
Crabbe JC, Wahlsten D, Dudek BC (1999) Genetics of mouse behavior: interactions with laboratory environment. Science 284:1670–1672
Drozdz A, Weiner J (1975) Some bioenergetic parameters of wild ruminants. Pol Ecol Stud 1:85–101
Gailus-Durner V, Fuchs H, Becker L, Bolle I, Brielmeier M, Calzada-Wack J, Elvert R, Ehrhardt N, Dalke C, Franz TJ, Grundner-Culemann E, Hammelbacher S, Holter SM, Holzlwimmer G, Horsch M, Javaheri A, Kalaydjiev SV, Klempt M, Kling E, Kunder S, Lengger C, Lisse T, Mijalski T, Naton B, Pedersen V, Prehn C, Przemeck G, Racz I, Reinhard C, Reitmeir P, Schneider I, Schrewe A, Steinkamp R, Zybill C, Adamski J, Beckers J, Behrendt H, Favor J, Graw J, Heldmaier G, Hofler H, Ivandic B, Katus H, Kirchhof P, Klingenspor M, Klopstock T, Lengeling A, Muller W, Ohl F, Ollert M, Quintanilla-Martinez L, Schmidt J, Schulz H, Wolf E, Wurst W, Zimmer A, Busch DH, Hrabe de Angelis M (2005) Introducing the German Mouse Clinic: open access platform for standardized phenotyping. Nat Methods 2:403–404
Hintz JL (2000) PASS 2000 user’s guide. NCSS Statistical Software, Kaysville
Howard BR (2002) Control of variability. ILAR J 43:194–201
Hrabé de Angelis M, Flaswinkel H, Fuchs H, Rathkolb B, Soewarto D, Marschall S, Heffner S, Pargent W, Wuensch K, Jung M, Reis A, Richter T, Alessandrini F, Jakob T, Fuchs E, Kolb H, Kremmer E, Schaeble K, Rollinski B, Roscher A, Peters C, Meitinger T, Strom T, Steckler T, Holsboer F, Klopstock T, Gekeler F, Schindewolf C, Jung T, Avraham K, Behrendt H, Ring J, Zimmer A, Schughart K, Pfeffer K, Wolf E, Balling R (2000) Genome-wide, large-scale production of mutant mice by ENU mutagenesis. Nat Genet 25:444–447
Julious SA (2004) Sample sizes for clinical trials with normal data. Stat Med 23:1921–1986
Shih WJ, Ohman-Strickland PA, Lin Y (2004) Analysis of pilot and early phase studies with small sample sizes. Stat Med 23:1827–1842
Silver LM (1995) Mouse genetics. concepts and applications, 1st edn. Oxford University Press, Oxford
Tartaglia LA, Dembski M, Weng X, Deng N, Culpepper J, Devos R, Richards GJ, Campfield LA, Clark FT, Deeds J (1995) Identification and expression cloning of a leptin receptor, OB-R. Cell 83:1263–1271
Turek FW, Joshu C, Kohsaka A, Lin E, Ivanova G, McDearmon E, Laposky A, Losee-Olson S, Easton A, Jensen DR, Eckel RH, Takahashi JS, Bass J (2005) Obesity and metabolic syndrome in circadian Clock mutant mice. Science 308:1043–1045
Verbeke G, Molenberghs G (2001) Linear mixed models for longitudinal data. Springer, Berlin Heidelberg New York
Wallenius V, Wallenius K, Ahren B, Rudling M, Carlsten H, Dickson SL, Ohlsson C, Jansson JO (2002) Interleukin-6-deficient mice develop mature-onset obesity. Nat Med 8:75–79
Zhang Y, Scarpace PJ (2006) The role of leptin in leptin resistance and obesity. Physiol Behav 88:249–256
Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM (1994) Positional cloning of the mouse obese gene and its human homologue. Nature 372:425–432
Acknowledgements
This work was supported by NGFN2 grants #01GS0483 (Obesity and related disorders), #01GR0437 (SMP Tiermodelle), and #01GR0460 (SMP GEM). All animal experiments were approved by the German animal welfare authorities.
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Carola W. Meyer and Ralf Elvert contributed equally to this work.
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Meyer, C.W., Elvert, R., Scherag, A. et al. Power matters in closing the phenotyping gap. Naturwissenschaften 94, 401–406 (2007). https://doi.org/10.1007/s00114-006-0203-1
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DOI: https://doi.org/10.1007/s00114-006-0203-1