Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Applying mouse complex-trait resources to behavioural genetics


Studies of the genetic basis of behaviour in mice are at a turning point. Soon, new resources will enable the behavioural function of all genes to be tested and the networks of genes, messenger RNAs and proteins involved in a particular behaviour to be identified. Using these resources, scientists will be able to analyse mouse behaviour at an unprecedented level of detail. Interpreting the new data, however, will require a shift in focus from gene-based approaches to network-based approaches.

Your institute does not have access to this article

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Genetic dissection of behaviour.


  1. Silva, A. J., Paylor, R., Wehner, J. M. & Tonegawa, S. Impaired spatial learning in α-calcium–calmodulin kinase II mutant mice. Science 257, 206–211 (1992).

    ADS  CAS  Article  Google Scholar 

  2. Grant, S. G. N. et al. Impaired long-term potentiation, spatial learning and hippocampal development in Fyn mutant mice. Science 258, 1903–1910 (1992).

    ADS  CAS  Article  Google Scholar 

  3. Flint, J. et al. A simple genetic basis for a complex psychological trait in laboratory mice. Science 269, 1432–1435 (1995).

    ADS  CAS  Article  Google Scholar 

  4. Long, A. D., Mullaney, S. L., Mackay, T. F. C. & Langley, C. H. Genetic interactions between naturally occurring alleles at quantitative trait loci and mutant alleles at candidate loci affecting bristle number in Drosophila melanogaster. Genetics 144, 1497–1510 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Yalcin, B. et al. Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nature Genet. 36, 1197–1202 (2004). This was the first report of using quantitative complementation to identify the effect of a quantitative trait locus gene on behaviour.

    CAS  Article  Google Scholar 

  6. Silva, A. J. et al. Mutant mice and neuroscience: recommendations concerning genetic background. Neuron 19, 755–759 (1997).

    Article  Google Scholar 

  7. Amieux, P. S. et al. Increased basal cAMP-dependent protein kinase activity inhibits the formation of mesoderm-derived structures in the developing mouse embryo. J. Biol. Chem. 277, 27294–27304 (2002).

    CAS  Article  Google Scholar 

  8. Huang, Y. Y. et al. A genetic test of the effects of mutations in PKA on mossy fiber LTP and its relation to spatial and contextual learning. Cell 83, 1211–1222 (1995).

    CAS  Article  Google Scholar 

  9. Talbot, C. J. et al. High-resolution mapping of quantitative trait loci in outbred mice. Nature Genet. 21, 305–308 (1999).

    CAS  Article  Google Scholar 

  10. Shimomura, K. et al. Genome-wide epistatic interaction analysis reveals complex genetic determinants of circadian behavior in mice. Genome Res. 11, 959–980 (2001).

    CAS  Article  Google Scholar 

  11. Tully, T. et al. A return to genetic dissection of memory in Drosophila. Cold Spring Harb. Symp. Quant. Biol. 61, 207–218 (1996).

    CAS  Article  Google Scholar 

  12. Nadeau, J. H. & Frankel, W. N. The roads from phenotypic variation to gene discovery: mutagenesis versus QTLs. Nature Genet. 25, 381–384 (2000).

    CAS  Article  Google Scholar 

  13. Vitaterna, M. H. et al. Mutagenesis and mapping of a mouse gene, Clock, essential for circadian behaviour. Science 264, 719–725 (1994).

    ADS  CAS  Article  Google Scholar 

  14. Grupe, A. et al. In silico mapping of complex disease-related traits in mice. Science 292, 1915–1918 (2001).

    ADS  CAS  Article  Google Scholar 

  15. Wade, C. M. et al. The mosaic structure of variation in the laboratory mouse genome. Nature 420, 574–578 (2002).

    ADS  CAS  Article  Google Scholar 

  16. Payseur, B. A. & Place, M. Prospects for association mapping in classical inbred mouse strains. Genetics 175, 1999–2008 (2007).

    CAS  Article  Google Scholar 

  17. Schadt, E. E. et al. An integrative genomics approach to infer causal associations between gene expression and disease. Nature Genet. 37, 710–717 (2005). This paper introduced a method to investigate causal relationships between sequence variants, gene expression and phenotypes.

    CAS  Article  Google Scholar 

  18. Mehrabian, M. et al. Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits. Nature Genet. 37, 1224–1233 (2005).

    CAS  Article  Google Scholar 

  19. Chen, Y. et al. Variations in DNA elucidate molecular networks that cause disease. Nature 452, 429–435 (2008).

    ADS  CAS  Article  Google Scholar 

  20. Hovatta, I. et al. Glyoxalase 1 and glutathione reductase 1 regulate anxiety in mice. Nature 438, 662–666 (2005).

    ADS  CAS  Article  Google Scholar 

  21. Flint, J., Valdar, W., Shifman, S. & Mott, R. Strategies for mapping and cloning quantitative trait genes in rodents. Nature Rev. Genet. 6, 271–286 (2005).

    CAS  Article  Google Scholar 

  22. Valdar, W. et al. Genome-wide genetic association of complex traits in heterogeneous stock mice. Nature Genet. 38, 879–887 (2006). This study shows that high-resolution genome-wide association mapping of behaviour, and other traits, is possible in outbred mice.

    CAS  Article  Google Scholar 

  23. Kishimoto, T. et al. Deletion of Crhr2 reveals an anxiolytic role for corticotropin-releasing hormone receptor-2. Nature Genet. 24, 415–419 (2000).

    CAS  Article  Google Scholar 

  24. Keays, D. A. et al. Mutations in α-tubulin cause abnormal neuronal migration in mice and lissencephaly in humans. Cell 128, 45–57 (2007).

    CAS  Article  Google Scholar 

  25. Collins, F. S., Rossant, J. & Wurst, W. A mouse for all reasons. Cell 128, 9–13 (2007).

    CAS  Article  Google Scholar 

  26. Ding, S. et al. Efficient transposition of the piggyBac (PB) transposon in mammalian cells and mice. Cell 122, 473–483 (2005).

    CAS  Article  Google Scholar 

  27. Sanes, J. R. & Lichtman, J. W. Can molecules explain long-term potentiation? Nature Neurosci. 2, 597–604 (1999).

    CAS  Article  Google Scholar 

  28. Tong, A. H. et al. Global mapping of the yeast genetic interaction network. Science 303, 808–813 (2004).

    ADS  CAS  Article  Google Scholar 

  29. Wuchty, S., Oltvai, Z. N. & Barabasi, A. L. Evolutionary conservation of motif constituents in the yeast protein interaction network. Nature Genet. 35, 176–179 (2003).

    CAS  Article  Google Scholar 

  30. Keller, M. P. et al. A gene expression network model of type 2 diabetes links cell cycle regulation in islets with diabetes susceptibility. Genome Res. 18, 706–716 (2008).

    CAS  Article  Google Scholar 

  31. Choudhary, J. & Grant, S. G. Proteomics in postgenomic neuroscience: the end of the beginning. Nature Neurosci. 7, 440–445 (2004).

    CAS  Article  Google Scholar 

  32. Churchill, G. A. et al. The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nature Genet. 36, 1133–1137 (2004).

    CAS  Article  Google Scholar 

  33. Valdar, W., Flint, J. & Mott, R. Simulating the collaborative cross: power of quantitative trait loci detection and mapping resolution in large sets of recombinant inbred strains of mice. Genetics 172, 1783–1797 (2006).

    CAS  Article  Google Scholar 

  34. Laurie, C. C. et al. Linkage disequilibrium in wild mice. PLoS Genet. 3, e144 (2007).

    Article  Google Scholar 

  35. Zeggini, E. et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature Genet. 40, 638–645 (2008).

    CAS  Article  Google Scholar 

Download references


We thank the Wellcome Trust for support and are grateful to S.McCormick for comments on the manuscript.

Author information

Authors and Affiliations


Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reprints and permissions information is available at

Correspondence should be addressed to J.F. (

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Flint, J., Mott, R. Applying mouse complex-trait resources to behavioural genetics. Nature 456, 724–727 (2008).

Download citation

  • Published:

  • Issue Date:

  • DOI:

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing