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Mammalian Genome

, Volume 26, Issue 7–8, pp 348–354 | Cite as

Within-strain variation in behavior differs consistently between common inbred strains of mice

  • Maarten LoosEmail author
  • Bastijn Koopmans
  • Emmeke Aarts
  • Gregoire Maroteaux
  • Sophie van der Sluis
  • Neuro-BSIK Mouse Phenomics Consortium
  • Matthijs Verhage
  • August B. Smit
Article

Abstract

Genetic and environmental factors interact throughout life and give rise to individual differences, i.e., individuality. The diversifying effect of environmental factors is counteracted by genetic mechanisms to yield persistence of specific features (robustness). Here, we compared robustness between cohorts of isogenic mice of eight different commonly used strains by analyzing to what extent environmental variation contributed to individuality in each of the eight genotypes, using a previously published dataset. Behavior was assessed in the home-cage, providing control over environmental factors, to reveal within-strain variability in numerous spontaneous behaviors. Indeed, despite standardization and in line with previous studies, substantial variability among mice of the same inbred strain was observed. Strikingly, across a multidimensional set of 115 behavioral parameters, several strains consistently ranked high in within-strain variability (DBA/2J, 129S1/Sv A/J and NOD/LtJ), whereas other strains ranked low (C57BL/6J and BALB/c). Strain rankings of within-strain variability in behavior were confirmed in an independent, previously published behavioral dataset using conventional behavioral tests administered to different mice from the same breeding colonies. Together, these show that genetically inbred mouse strains consistently differ in phenotypic robustness against environmental variation, suggesting that genetic factors contribute to variation in robustness.

Keywords

Inbred Strain Strain Difference Behavioral Phenotype Video Tracking Average Variability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We thank Rolinka van der Loo for operating the PhenoTyper systems and Ruud Wijnands for assistance, Noldus Information Technology for supplying software free of charge and hardware at cost price, and Ben Loke, Cecilia Herrera, Raymond de Heer, and Willem van der Veer for development of hardware, software, and test scripts. This work was supported by Agentschap NL (NeuroBSIK Mouse Phenomics Consortium, BSIK03053), the Netherlands Organization for Scientific Research (NWO/MaGW: VIDI-452-12-014 to S.v.d.S). The authors declare no conflict of interest. M.L. and B.K. are full time employees of Sylics (Synaptologics BV), a private, VU University spin-off company that offers mouse phenotyping services using AHCODA™. A.B.S. and M.V. participate in a holding that owns Sylics shares and have received consulting fees from Sylics.

Supplementary material

335_2015_9578_MOESM1_ESM.pdf (91 kb)
Supplementary material 1 (PDF 91 kb)
335_2015_9578_MOESM2_ESM.pdf (187 kb)
Supplementary material 2 (PDF 186 kb)

References

  1. Ayroles JF, Buchanan SM, O’Leary C et al (2015) Behavioral idiosyncrasy reveals genetic control of phenotypic variability. Proc Natl Acad Sci 112:201503830. doi: 10.1073/pnas.1503830112 CrossRefGoogle Scholar
  2. Bendesky A, Bargmann CI (2011) Genetic contributions to behavioural diversity at the gene-environment interface. Nat Rev Genet 12:809–820. doi: 10.1038/nrg3065 PubMedGoogle Scholar
  3. Carlier M, Roubertoux P, Cohen-Salmon C (1982) Differences in patterns of pup care in Mus musculus domesticus l-Comparisons between eleven inbred strains. Behav Neural Biol 35:205–210CrossRefPubMedGoogle Scholar
  4. Crabbe JC, Wahlsten D, Dudek BC (1999) Genetics of mouse behavior: interactions with laboratory environment. Science 284:1670–1672CrossRefPubMedGoogle Scholar
  5. Debat V, David P (2001) Mapping phenotypes: canalization, plasticity and developmental stability. Trends Ecol Evol 16:555–561. doi: 10.1016/S0169-5347(01)02266-2 CrossRefGoogle Scholar
  6. Egan CM, Sridhar S, Wigler M, Hall IM (2007) Recurrent DNA copy number variation in the laboratory mouse. Nat Genet 39:1384–1389. doi: 10.1038/ng.2007.19 CrossRefPubMedGoogle Scholar
  7. Fraser HB, Schadt EE (2010) The quantitative genetics of phenotypic robustness. PLoS ONE 5:e8635. doi: 10.1371/journal.pone.0008635 PubMedCentralCrossRefPubMedGoogle Scholar
  8. Freund J, Brandmaier AM, Lewejohann L et al (2013) Emergence of individuality in genetically identical mice. Science 340:756–759. doi: 10.1126/science.1235294 CrossRefPubMedGoogle Scholar
  9. Gärtner K (1990) A third component causing random variability beside environment and genotype. A reason for the limited success of a 30 year long effort to standardize laboratory animals? Lab Anim 24:71–77CrossRefPubMedGoogle Scholar
  10. Hegmann JP, Possidente B (1981) Estimating genetic correlations from inbred strains. Behav Genet 11:103–114CrossRefPubMedGoogle Scholar
  11. Hen I, Sakov A, Kafkafi N et al (2004) The dynamics of spatial behavior: how can robust smoothing techniques help? J Neurosci Methods 133:161–172. doi: 10.1016/j.jneumeth.2003.10.013 CrossRefPubMedGoogle Scholar
  12. Kaiser HF (1960) The application of electronic computers to factor analysis. Educ Psychol Meas 20:141–151CrossRefGoogle Scholar
  13. Kaminsky ZA, Tang T, Wang S-C et al (2009) DNA methylation profiles in monozygotic and dizygotic twins. Nat Genet 41:240–245. doi: 10.1038/ng.286 CrossRefPubMedGoogle Scholar
  14. Lathe R (2004) The individuality of mice. Genes Brain Behav 3:317–327. doi: 10.1111/j.1601-183X.2004.00083.x CrossRefPubMedGoogle Scholar
  15. Loos M, van der Sluis S, Bochdanovits Z et al (2009) Activity and impulsive action are controlled by different genetic and environmental factors. Genes Brain Behav 8:817–828. doi: 10.1111/j.1601-183X.2009.00528.x CrossRefPubMedGoogle Scholar
  16. Loos M, Koopmans B, Aarts E et al (2014) Sheltering behavior and locomotor activity in 11 genetically diverse common inbred mouse strains using home-cage monitoring. PLoS ONE 9:e108563. doi: 10.1371/journal.pone.0108563 PubMedCentralCrossRefPubMedGoogle Scholar
  17. Lynch KE, Kemp DJ (2013) Nature-via-nurture and unravelling causality in evolutionary genetics. Trends Ecol Evol. doi: 10.1016/j.tree.2013.10.005 PubMedGoogle Scholar
  18. Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sinauer Associates, SunderlandGoogle Scholar
  19. Maroteaux G, Loos M, van der Sluis S et al (2012) High-throughput phenotyping of avoidance learning in mice discriminates different genotypes and identifies a novel gene. Genes Brain Behav 11:772–784. doi: 10.1111/j.1601-183X.2012.00820.x PubMedCentralCrossRefPubMedGoogle Scholar
  20. Molenaar PC, Boomsma DI, Dolan CV (1993) A third source of developmental differences. Behav Genet 23:519–524CrossRefPubMedGoogle Scholar
  21. Pujadas E, Feinberg AP (2012) Regulated noise in the epigenetic landscape of development and disease. Cell 148:1123–1131. doi: 10.1016/j.cell.2012.02.045 PubMedCentralCrossRefPubMedGoogle Scholar
  22. Queitsch C, Sangster TA, Lindquist S (2002) Hsp90 as a capacitor of phenotypic variation. Nature 417:618–624. doi: 10.1038/nature749 CrossRefPubMedGoogle Scholar
  23. Queitsch C, Carlson KD, Girirajan S (2012) Lessons from model organisms: phenotypic robustness and missing heritability in complex disease. PLoS Genet 8:e1003041. doi: 10.1371/journal.pgen.1003041 PubMedCentralCrossRefPubMedGoogle Scholar
  24. Rutherford SL, Lindquist S (1998) Hsp90 as a capacitor for morphological evolution. Nature 396:336–342. doi: 10.1038/24550 CrossRefPubMedGoogle Scholar
  25. Sangster TA, Salathia N, Undurraga S et al (2008) HSP90 affects the expression of genetic variation and developmental stability in quantitative traits. Proc Natl Acad Sci U S A 105:2963–2968. doi: 10.1073/pnas.0712200105 PubMedCentralCrossRefPubMedGoogle Scholar
  26. Taft RA, Davisson M, Wiles MV (2006) Know thy mouse. Trends Genet 22:649–653. doi: 10.1016/j.tig.2006.09.010 CrossRefPubMedGoogle Scholar
  27. Van Dongen J, Slagboom PE, Draisma HHM et al (2012) The continuing value of twin studies in the omics era. Nat Rev Genet 13:640–653. doi: 10.1038/nrg3243 CrossRefPubMedGoogle Scholar
  28. Watkins-Chow DE, Pavan WJ (2008) Genomic copy number and expression variation within the C57BL/6J inbred mouse strain. Genome Res 18:60–66. doi: 10.1101/gr.6927808 PubMedCentralCrossRefPubMedGoogle Scholar
  29. Whitelaw NC, Chong S, Morgan DK et al (2010a) Reduced levels of two modifiers of epigenetic gene silencing, Dnmt3a and Trim28, cause increased phenotypic noise. Genome Biol 11:R111. doi: 10.1186/gb-2010-11-11-r111 PubMedCentralCrossRefPubMedGoogle Scholar
  30. Whitelaw NC, Chong S, Whitelaw E (2010b) Tuning into noise: epigenetics and intangible variation. Dev Cell 19:649–650. doi: 10.1016/j.devcel.2010.11.001 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Maarten Loos
    • 1
    • 2
    Email author
  • Bastijn Koopmans
    • 1
  • Emmeke Aarts
    • 3
  • Gregoire Maroteaux
    • 3
  • Sophie van der Sluis
    • 4
  • Neuro-BSIK Mouse Phenomics Consortium
  • Matthijs Verhage
    • 3
  • August B. Smit
    • 2
  1. 1.Sylics (Synaptologics BV)AmsterdamThe Netherlands
  2. 2.Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research (CNCR), Neuroscience Campus AmsterdamVU University AmsterdamAmsterdamThe Netherlands
  3. 3.Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Neuroscience Campus AmsterdamVU University AmsterdamAmsterdamThe Netherlands
  4. 4.Department of Clinical Genetics, Section Complex Trait Genetics, VU Medical CenterVU UniversityAmsterdamThe Netherlands

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