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.

Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function


Patterns of gene expression in the central nervous system are highly variable and heritable. This genetic variation among normal individuals leads to considerable structural, functional and behavioral differences. We devised a general approach to dissect genetic networks systematically across biological scale, from base pairs to behavior, using a reference population of recombinant inbred strains. We profiled gene expression using Affymetrix oligonucleotide arrays in the BXD recombinant inbred strains, for which we have extensive SNP and haplotype data. We integrated a complementary database comprising 25 years of legacy phenotypic data on these strains. Covariance among gene expression and pharmacological and behavioral traits is often highly significant, corroborates known functional relations and is often generated by common quantitative trait loci. We found that a small number of major-effect quantitative trait loci jointly modulated large sets of transcripts and classical neural phenotypes in patterns specific to each tissue. We developed new analytic and graph theoretical approaches to study shared genetic modulation of networks of traits using gene sets involved in neural synapse function as an example. We built these tools into an open web resource called WebQTL that can be used to test a broad array of hypotheses.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Genome-wide interval mapping for several transcripts from WebQTL, including the cis-regulatory QTL for Kcnj9 (98322_at), Per3 (102242_at) and Grin2b (101312_at) and trans-regulatory QTLs for Pitpnb (102696_s_at) and Neurod2 (98808_at).
Figure 2: Physical map of chromosome 16 showing cis-regulatory locus for expression of a pyridoxil-dependent decarboxylase (160163_at).
Figure 3: Transcriptome maps for 12,422 transcripts.
Figure 4: Frequency of transcript abundances with LRS peaks mapping to 5-Mb QTL location bins identify approximately seven key trans-regulatory QTLs.
Figure 5: Genetic correlation of Drd2 expression with several behavioral phenotypes in WebQTL's BXD Published Phenotypes database.
Figure 6: Cluster map showing the polygenic and pleiotropic regulation of the synaptic vesicle cycling mechanisms.


  1. 1

    Cowles, C.R., Hirschorn, J.N., Altshuler, D. & Lander, E.S. Detection of regulatory variation in mouse genes. Nat. Genet. 32, 432–437 (2002).

    CAS  Article  Google Scholar 

  2. 2

    Jansen, R. & Nap, J.P. Genetical genomics: the added value from segregation. Trends Genet. 17, 388–391 (2001).

    CAS  Article  Google Scholar 

  3. 3

    Brem, R., Yvert, G., Clinton, R. & Kruglyak, L. Genetic dissection of transcriptional regulation in budding yeast. Science 296, 725–755 (2002).

    Article  Google Scholar 

  4. 4

    Bading, H., Ginty, D.D. & Greenberg, M.E. Regulation of gene expression in hippocampal neurons by distinct calcium signaling pathways. Science 260, 181–186 (1993).

    CAS  Article  Google Scholar 

  5. 5

    Paigen, K. & Eppig, J. A mouse phenome project. Mamm. Genome 111, 715–717 (2000).

    Article  Google Scholar 

  6. 6

    Threadgill, D.W., Hunter, K.W. & Williams, R.W. Genetic dissection of complex and quantitative traits: from fantasy to reality via a community effort. Mamm. Genome 13, 175–178 (2002).

    CAS  Article  Google Scholar 

  7. 7

    Peirce, J.L. et al. A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet. 5, 7 (2004).

    Article  Google Scholar 

  8. 8

    Li, X. et al. High-resolution genetic mapping of the saccharin preference locus (Sac) and the putative sweet taste receptor (T1R1) gene (Gpr70) to mouse distal Chromosome 4. Mamm. Genome 12, 13–16 (2001).

    CAS  Article  Google Scholar 

  9. 9

    Mogil, J.S. et al. The melanocortin-1 receptor gene mediates female-specific mechanisms of analgesia in mice and humans. Proc. Natl. Acad. Sci. USA 100, 4867–4872 (2003).

    CAS  Article  Google Scholar 

  10. 10

    Shirley, R.L. et al. Mpdz is a quantitative trait gene for drug withdrawal seizures. Nat. Neurosci. 7, 699–700 (2004).

    CAS  Article  Google Scholar 

  11. 11

    Taylor, B.A. et al. Genotyping new BXD recombinant inbred mouse strains and comparison of BXD and consensus maps. Mamm. Genome 10, 335–348 (1999).

    CAS  Article  Google Scholar 

  12. 12

    Flint, J. Analysis of quantitative trait loci that influence animal behavior. J. Neurobiol. 54, 46–77 (2003).

    CAS  Article  Google Scholar 

  13. 13

    Schadt, E.E. et al. Genetics of gene expression surveyed in maize, mouse and man. Nature 422, 297–302 (2003).

    CAS  Article  Google Scholar 

  14. 14

    Bystrykh, L. et al. Uncovering regulatory pathways that affect hematopoietic stem cell function using 'genetical genomics'. Nat. Genet. advance online publication, 13 February 2005 (10.1038/ng1497).

  15. 15

    Belknap, J.K. Effect of within-strain sample size on QTL detection and mapping using recombinant inbred mouse strains. Behav. Genet. 28, 29–38 (1998).

    CAS  Article  Google Scholar 

  16. 16

    Wang, J., Williams, R.W. & Manly, K.F. WebQTL: Web-based complex trait analysis. Neuroinformatics 1, 299–308 (2003).

    Article  Google Scholar 

  17. 17

    Rikke, B.A. & Johnson, T.E. Towards the cloning of genes underlying murine QTLs. Mamm. Genome 9, 963–968 (1998).

    CAS  Article  Google Scholar 

  18. 18

    Visscher, P.M. Speed congenics: accelerated genome recovery using genetic markers. Genet. Res. 74, 81–85 (1999).

    CAS  Article  Google Scholar 

  19. 19

    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

    Google Scholar 

  20. 20

    Manly, K.F., Nettleton, D. & Hwang, J.T. Genomics, prior probability, and statistical tests of multiple hypotheses. Genome Res. 14, 997–1001 (2004).

    CAS  Article  Google Scholar 

  21. 21

    Storey, J.D., Taylor, J.E. & Siegmund, D. Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: a unified approach. J. R. Stat. Soc. B 66, 187–205 (2004).

    Article  Google Scholar 

  22. 22

    Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).

    CAS  Article  Google Scholar 

  23. 23

    Zhang, B., Schmoyer, D., Kirov, S. & Snoddy, J. GOTree Machine (GOTM): a web-based platform for interpreting interesting sets of genes using Gene Ontology hierarchies. BMC Bioinformatics 5, 16 (2004).

    Article  Google Scholar 

  24. 24

    Chesler, E.J., Lu, L., Wang, J., Williams, R.W. & Manly, K.F. WebQTL: rapid exploratory analysis of gene expression and genetic networks for brain and behavior. Nat. Neurosci. 7, 485–486 (2004).

    CAS  Article  Google Scholar 

  25. 25

    Chesler, E.J. et al. Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes. Neuroinformatics 1, 343–357 (2003).

    Article  Google Scholar 

  26. 26

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

    CAS  Article  Google Scholar 

  27. 27

    Lu, L., Airey, D.C. & Williams, R.W. Complex trait analysis of the hippocampus: mapping and biometric analysis of two novel gene loci with specific effects on hippocampal structure in mice. J. Neurosci. 21, 3503–3514 (2001).

    CAS  Article  Google Scholar 

  28. 28

    Peirce, J.L., Chesler, E.J., Williams, R.W. & Lu, L. Genetic architecture of the mouse hippocampus: identification of gene loci with selective regional effects. Genes Brain Behav. 2, 238–252 (2003).

    CAS  Article  Google Scholar 

  29. 29

    Jones, B.C. et al. Quantitative genetic analysis of ventral midbrain and liver iron in BXD recombinant inbred mice. Nutr. Neurosci. 6, 369–377 (2003).

    CAS  Article  Google Scholar 

  30. 30

    Cunningham, C.L. Localization of genes influencing ethanol-induced conditioned place preference and locomotor activity in BXD recombinant inbred mice. Psychopharmacology 120, 28–24 (1995).

    CAS  Article  Google Scholar 

  31. 31

    Risinger, F.O. & Cunningham, C.L. Ethanol-induced conditioned taste aversion in BXD recombinant inbred mice. Alcohol. Clin. Exp. Res. 22, 1234–1244 (1998).

    CAS  Article  Google Scholar 

  32. 32

    Crabbe, J.C., Kosobud, A., Young, E.R. & Janowsky, J.S. Polygenic and single-gene determination of responses to ethanol in BXD/Ty recombinant inbred mouse strains. Neurobehav. Toxicol. Teratol. 5, 181–187 (1983).

    CAS  PubMed  Google Scholar 

  33. 33

    Phillips, T.J., Crabbe, J.C., Metten, P. & Belknap, J.K. Localization of genes affecting alcohol drinking in mice. Alcohol. Clin. Exp. Res. 18, 931–941 (1994).

    CAS  Article  Google Scholar 

  34. 34

    Phillips, T.J., Huson, M., Gwiazdon, C., Burkhart-Kasch, S. & Shen, E.H. Effects of acute and repeated ethanol exposures on the locomotor activity of BXD recombinant inbred mice. Alcohol. Clin. Exp. Res. 19, 269–278 (1995).

    CAS  Article  Google Scholar 

  35. 35

    Hitzemann, R. et al. Dopamine D2 receptor binding, Drd2 expression and the number of dopamine neurons in the BXD recombinant inbred series: genetic relationships to alcohol and other drug associated phenotypes. Alcohol. Clin. Exp. Res. 27, 1–11 (2003).

    CAS  Article  Google Scholar 

  36. 36

    Storey, J.D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA 100, 9440–9445 (2003).

    CAS  Article  Google Scholar 

  37. 37

    Blichenberg, A. et al. Identification of a cis-acting dendritic targeting element in MAP2 mRNAs. J. Neurosci. 19, 8818–8829 (1999).

    CAS  Article  Google Scholar 

  38. 38

    Jeong, H., Tombor, B., Albert, R., Oltvai, Z.N. & Barabási, A.-L. The large scale organization of metabolic networks. Nature 407, 651–653 (2000).

    CAS  Article  Google Scholar 

  39. 39

    Baldwin, N.E. et al. Computational, integrative and comparative methods for the elucidation of genetic co-expression networks. J. Biomed. Biotechnol. (in the press).

  40. 40

    Bartoli, M. et al. Down-regulation of striatin, a neuronal calmodulin-binding protein, impairs rat locomotor activity. J. Neurobiol. 40, 234–243 (1999).

    CAS  Article  Google Scholar 

  41. 41

    Becamel, C. et al. Synaptic multiprotein complexes associated with 5-HT(2C) receptors: a proteomic approach. EMBO J. 21, 2332–2342 (2002).

    CAS  Article  Google Scholar 

  42. 42

    Klose, J. et al. Genetic analysis of the mouse brain proteome. Nat. Genet. 30, 385–393 (2002).

    CAS  Article  Google Scholar 

  43. 43

    Chesler, E.J. & Williams, R.W. Brain gene expression: genomics and genetics. Int. Rev. Neurobiol. 60, 59–95 (2004).

    CAS  Article  Google Scholar 

  44. 44

    Yalcin, B. et al. Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nat. Genet. 36, 1197–1202 (2004).

    CAS  Article  Google Scholar 

  45. 45

    Williams, R.W., Gu, J., Qi, S. & Lu, L. The genetic structure of recombinant inbred mice: high-resolution consensus maps for complex trait analysis. Genome Biol. 2, RESEARCH0046 (2002).

    Google Scholar 

  46. 46

    Irizarry, R.A. et al. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31, e15 (2003).

    Article  Google Scholar 

  47. 47

    Churchill, G.A. & Doerge, R.W. Empirical threshold values for quantitative trait mapping. Genetics 138, 963–971 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Visscher, P.M., Thomopson, R. & Haley, C.S. Confidence intervals in QTL mapping by bootstrapping. Genetics 143, 1013–1020 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Hutson, A.D. Bootstrap smoothing strategies based on uniform spacings with practical applications. Technical Report. (Division of Biostatistics, University at Buffalo, Buffalo, New York, 2002).

  50. 50

    Broman, K., Wu, H., Sen, S. & Churchill, G.A. R/qtl: QTL mapping in experimental crosses. Bioinformatics, 19, 889–890 (2003).

    CAS  Article  Google Scholar 

Download references


We thank T. Sutter and the Feinstone Center for array support, J. Hogenesch and R. Edwards for helping to map probe sets using BLAT and J. Crabbe and J. Belknap for assistance in updating and compiling the many traits they have contributed to the Published Phenotypes database. Most arrays were processed at Genome Explorations Inc. by D. Patel. The authors acknowledge support of a Human Brain Project funded by the National Institute of Mental Health, the National Institute of Drug Abuse and the National Science Foundation, and an Integrative Neuroscience Initiative on Alcoholism grant from the National Institute of Alcohol Abuse and Addiction. Array costs were covered by the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. Additional support was provided by the National Institute of Aging, the National Science Foundation, Veterans Affairs and the Office of Naval Research.

Author information



Corresponding author

Correspondence to Robert W Williams.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Genetic variation and fold range of strain means for transcript abundance. (DOC 241 kb)

Supplementary Table 2

Locations of best cis- and trans-QTLs based on genetic variance >30% and FDR (q-value) < 25%. (DOC 244 kb)

Supplementary Table 3

Location and SNP density by location in the major trans-QTL bands. (DOC 44 kb)

Supplementary Table 4

Tissue specificity and number of single nucleotide polymorphisms (SNPs) by location in cis-QTLs. (DOC 209 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Chesler, E., Lu, L., Shou, S. et al. Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function. Nat Genet 37, 233–242 (2005).

Download citation

Further reading


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