Combining Mouse Congenic Strains and Microarray Gene Expression Analyses to Study a Complex Trait: The NOD Model of Type 1 Diabetes

  1. Iain A. Eaves1,
  2. Linda S. Wicker2,5,
  3. Ghassan Ghandour3,
  4. Paul A. Lyons1,
  5. Laurence B. Peterson4,
  6. John A. Todd1,6, and
  7. Richard J. Glynne3
  1. 1Juvenile Diabetes Research Foundation/ Wellcome Trust (JDRF/WT) Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/Medical Research Council (MRC) Building, Addenbrooke's Hospital, Cambridge, CB2 2XY, UK; 2Department of Immunology and Rheumatology, Merck Research Laboratories, Rahway, New Jersey 07065, USA; 3Eos Biotechnology, Inc., South San Francisco, California 94080, USA; 4Department of Pharmacology, Merck Research Laboratories, Rahway, New Jersey 07065, USA

Abstract

Combining congenic mapping with microarray expression profiling offers an opportunity to establish functional links between genotype and phenotype for complex traits such as type 1 diabetes (T1D). We used high-density oligonucleotide arrays to measure the relative expression levels of >39,000 genes and ESTs in the NOD mouse (a murine model of T1D and other autoimmune conditions), four NOD-derived diabetes-resistant congenic strains, and two nondiabetic control strains. We developed a simple, yet general, method for measuring differential expression that provides an objective assessment of significance and used it to identify >400 gene expression differences and eight new candidates for the Idd9.1 locus. We also discovered a potential early biomarker for autoimmune hemolytic anemia that is based on different levels of erythrocyte-specific transcripts in the spleen. Overall, however, our results suggest that the dramatic disease protection conferred by six Idd loci (Idd3,Idd5.1, Idd5.2, Idd9.1, Idd9.2, andIdd9.3) cannot be rationalized in terms of global effects on the noninduced immune system. They also illustrate the degree to which regulatory systems appear to be robust to genetic variation. These observations have important implications for the design of future microarray-based studies in T1D and, more generally, for studies that aim to combine genome-wide expression profiling and congenic mapping.

[The supplemental research data accompanying this article are available through the authors' web site (http://www-gene.cimr.cam.ac.uk/todd/), and the array data have been submitted to the GEO data repository (http://www.ncbi.nlm.nih.gov/geo/) under accession no. GSE11]

Footnotes

  • 5 Present address: JDRF/WT Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrooke's Hospital, Cambridge, CB2 2XY, UK

  • 6 Corresponding author.

  • E-MAIL john.todd{at}cimr.cam.ac.uk; FAX 44-1223-762102.

  • Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.214102. Article published online before print in January 2002.

    • Received September 6, 2001.
    • Accepted November 15, 2001.
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