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.

Genetics of gene expression surveyed in maize, mouse and man


Treating messenger RNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been pursued in gene-specific ways. Transcript abundances often serve as a surrogate for classical quantitative traits in that the levels of expression are significantly correlated with the classical traits across members of a segregating population. The correlation structure between transcript abundances and classical traits has been used to identify susceptibility loci for complex diseases such as diabetes1 and allergic asthma2. One study recently completed the first comprehensive dissection of transcriptional regulation in budding yeast3, giving a detailed glimpse of a genome-wide survey of the genetics of gene expression. Unlike classical quantitative traits, which often represent gross clinical measurements that may be far removed from the biological processes giving rise to them, the genetic linkages associated with transcript abundance affords a closer look at cellular biochemical processes. Here we describe comprehensive genetic screens of mouse, plant and human transcriptomes by considering gene expression values as quantitative traits. We identify a gene expression pattern strongly associated with obesity in a murine cross, and observe two distinct obesity subtypes. Furthermore, we find that these obesity subtypes are under the control of different loci.

This is a preview of subscription content, access via your institution

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: Murine gene expression quantitative trait loci (eQTL) distributions and the molecular basis for fat pad mass (FPM) in a murine F2 cross.
Figure 2: Cis-acting eQTL identified for several DNA polymorphisms known to induce transcription polymorphisms.
Figure 3: Clinical QTL (cQTL) for obesity-related traits localize together with eQTL.
Figure 4: Genes with no overall correlation with respect to expression demonstrate interesting patterns of genetic interaction.


  1. Eaves, I. A. et al. Combining mouse congenic strains and microarray gene expression analyses to study a complex trait: the NOD model of type 1 diabetes. Genome Res. 12, 232–243 (2002)

    CAS  Article  Google Scholar 

  2. Karp, C. L. et al. Identification of complement factor 5 as a susceptibility locus for experimental allergic asthma. Nature Immunol. 1, 221–226 (2000)

    CAS  Article  Google Scholar 

  3. Brem, R. B., Yvert, G., Clinton, R. & Kruglyak, L. Genetic dissection of transcriptional regulation in budding yeast. Science 296, 752–755 (2002)

    ADS  CAS  Article  Google Scholar 

  4. Claudio, L., Lee, T., Wolff, M. S. & Wetmur, J. G. A murine model of genetic susceptibility to lead bioaccumulation. Fundam. Appl. Toxicol. 35, 84–90 (1997)

    CAS  Article  Google Scholar 

  5. Huang, Y. H., Chen, Y. T., Lai, J. J., Yang, S. T. & Yang, U. C. PALS db: Putative Alternative Splicing database. Nucleic Acids Res. 30, 186–190 (2002)

    CAS  Article  Google Scholar 

  6. Yan, L., Otterness, D. M., Kozak, C. A. & Weinshilboum, R. M. Mouse nicotinamide N-methyltransferase gene: molecular cloning, structural characterization, and chromosomal localization. DNA Cell Biol. 17, 659–667 (1998)

    CAS  Article  Google Scholar 

  7. Hughes, T. R. et al. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nature Biotechnol. 19, 342–347 (2001)

    CAS  Article  Google Scholar 

  8. Drake, T. A. et al. Genetic loci determining bone density in mice with diet-induced atherosclerosis. Physiol. Genomics 5, 205–215 (2001)

    CAS  Article  Google Scholar 

  9. Timm, D. E., Baker, L. J., Mueller, H., Zidek, L. & Novotny, M. V. Structural basis of pheromone binding to mouse major urinary protein (MUP-I). Protein Sci. 10, 997–1004 (2001)

    CAS  Article  Google Scholar 

  10. Metcalf, D. et al. Gigantism in mice lacking suppressor of cytokine signalling-2. Nature 405, 1069–1073 (2000)

    ADS  CAS  Article  Google Scholar 

  11. Swift, L. L., Valyi-Nagy, K., Rowland, C. & Harris, C. Assembly of very low density lipoproteins in mouse liver: evidence of heterogeneity of particle density in the Golgi apparatus. J. Lipid Res. 42, 218–224 (2001)

    CAS  PubMed  Google Scholar 

  12. Borecki, I. G., Rice, T., Perusse, L., Bouchard, C. & Rao, D. C. An exploratory investigation of genetic linkage with body composition and fatness phenotypes: the Quebec Family Study. Obesity Res. 2, 213–219 (1994)

    CAS  Article  Google Scholar 

  13. Lembertas, A. V. et al. Identification of an obesity quantitative trait locus on mouse chromosome 2 and evidence of linkage to body fat and insulin on the human homologous region 20q. J. Clin. Invest. 100, 1240–1247 (1997)

    CAS  Article  Google Scholar 

  14. Damerval, C., Maurice, A., Josse, J. M. & de Vienne, D. Quantitative trait loci underlying gene product variation: a novel perspective for analyzing regulation of genome expression. Genetics 137, 289–301 (1994)

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Causse, M. et al. Genetic dissection of the relationship between carbon metabolism and early growth in maize, with emphasis on key-enzyme loci. Mol. Breed. 1, 259–272 (1995)

    CAS  Article  Google Scholar 

  16. Byrne, P. F. et al. Quantitative trait loci and metabolic pathways: genetic control of the concentration of maysin, a corn earworm resistance factor, in maize silks. Proc. Natl Acad. Sci. USA 93, 8820–8825 (1996)

    ADS  CAS  Article  Google Scholar 

  17. Dausset, J. et al. Centre d'Etude du Polymorphisme Humain (CEPH): collaborative genetic mapping of the human genome. Genomics 6, 575–577 (1990)

    CAS  Article  Google Scholar 

  18. van't Veer, L. J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536 (2002)

    CAS  Article  Google Scholar 

  19. Tosatio, G. Generation of Epstein-Barr Virus (EBV)-immortalized B cell lines. Curr. Protoc. Immunol. 1, 7.22.1–7.22.3 (1991)

    Article  Google Scholar 

  20. Troyer, A. F. Background of US hybrid corn. Crop Sci. 39, 601–626 (1999)

    Article  Google Scholar 

  21. Hughes, T. R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109–126 (2000)

    CAS  Article  Google Scholar 

  22. Amos, C. I. Robust variance-components approach for assessing genetic linkage in pedigrees. Am. J. Hum. Genet. 54, 535–543 (1994)

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Lincoln, S. E., Daly, M. J. & Lander, E. S. MAPMAKER/QTL User's Manual (Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, 1993)

    Google Scholar 

  24. Basten, C. A., Weir, B. S. & Zeng, Z. B. QTL Cartographer User's Manual (Department of Statistics, North Carolina State University, Raleigh, 1999)

    Google Scholar 

  25. Fisch, R. D., Ragot, M. & Gay, G. A generalization of the mixture model in the mapping of quantitative trait loci for progeny from a biparental cross of inbred lines. Genetics 143, 571–577 (1996)

    CAS  PubMed  PubMed Central  Google Scholar 

Download references


Rosetta Inpharmatics is a wholly owned subsidiary of Merck & Co., Inc.

Author information

Authors and Affiliations


Corresponding authors

Correspondence to Eric E. Schadt or Stephen H. Friend.

Ethics declarations

Competing interests

Stephen Friend is a Senior Vice President of Merck Research Laboratories.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI:

This article is cited by


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