Identification of Candidate Disease Genes by EST Alignments, Synteny, and Expression and Verification of Ensembl Genes on Rat Chromosome 1q43-54

  1. Ursula Vitt1,3,
  2. Darryl Gietzen1,
  3. Kristian Stevens1,
  4. Jim Wingrove1,
  5. Shanya Becha1,
  6. Sean Bulloch1,
  7. John Burrill1,
  8. Narinder Chawla1,
  9. Jennifer Chien1,
  10. Matthew Crawford1,
  11. Craig Ison1,
  12. Liam Kearney1,
  13. Mary Kwong1,
  14. Joe Park1,
  15. Jennifer Policky1,
  16. Mark Weiler1,
  17. Renee White1,
  18. Yuming Xu1,
  19. Sue Daniels1,
  20. Howard Jacob2,
  21. Michael I. Jensen-Seaman2,
  22. Jozef Lazar2,
  23. Laura Stuve1, and
  24. Jeanette Schmidt1
  1. 1 Incyte Corporation, Palo Alto, California 94304, USA
  2. 2 Human and Molecular Genetics Center and Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconain 53226, USA

Abstract

We aligned Incyte ESTs and publicly available sequences to the rat genome and analyzed rat chromosome 1q43-54, a region in which several quantitative trait loci (QTLs) have been identified, including renal disease, diabetes, hypertension, body weight, and encephalomyelitis. Within this region, which contains 255 Ensembl gene predictions, the aligned sequences clustered into 568 Incyte genes and gene fragments. Of the Incyte genes, 261 (46%) overlapped 184 (72%) of the Ensembl gene predictions, whereas 307 were unique to Incyte. The rat-to-human syntenic map displays rearrangement of this region on rat chr. 1 onto human chromosomes 9 and 10. The mapping of corresponding human disease phenotypes to either one of these chromosomes has allowed us to focus in on genes associated with disease phenotypes. As an example, we have used the syntenic information for the rat Rf-1 disease region and the orthologous human ESRD disease region to reduce the size of the original rat QTL to only 11.5 Mb. Using the syntenic information in combination with expression data from ESTs and microarrays, we have selected a set of 66 candidate disease genes for Rf-1. The combination of the results from these different analyses represents a powerful approach for narrowing the number of genes that could play a role in the development of complex diseases.

Footnotes

  • [Supplemental material is available online at www.genome.org.]

  • Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.1932304.

  • 3 Corresponding author. E-MAIL uvitt{at}incyte.com; FAX (650) 845-5495.

    • Accepted December 2, 2003.
    • Received November 4, 2003.
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