TY  - JOUR
A1  - Vitt, Ursula
A1  - Gietzen, Darryl
A1  - Stevens, Kristian
A1  - Wingrove, Jim
A1  - Becha, Shanya
A1  - Bulloch, Sean
A1  - Burrill, John
A1  - Chawla, Narinder
A1  - Chien, Jennifer
A1  - Crawford, Matthew
A1  - Ison, Craig
A1  - Kearney, Liam
A1  - Kwong, Mary
A1  - Park, Joe
A1  - Policky, Jennifer
A1  - Weiler, Mark
A1  - White, Renee
A1  - Xu, Yuming
A1  - Daniels, Sue
A1  - Jacob, Howard
A1  - Jensen-Seaman, Michael I.
A1  - Lazar, Jozef
A1  - Stuve, Laura
A1  - Schmidt, Jeanette
T1  - Identification of Candidate Disease Genes by EST Alignments, Synteny, and Expression and Verification of Ensembl Genes on Rat Chromosome 1q43-54
Y1  - 2004/04/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 640 
EP  - 650 
DO  - 10.1101/gr.1932304 
VL  - 14 
IS  - 4 
UR  - http://genome.cshlp.org/content/14/4/640.abstract 
N2  - 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. 
ER  -