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Submitted to Genetic Analysis Workshop 15, 2006 Joint study of genetic regulators for Expression Traits Related to Breast Cancer ∗

By Tian Zheng, Shuang Wang, Lei Cong, Yuejing Ding, Iuliana Ionita-laza and Shaw-hwa Lo

Abstract

Gene expression analyses have been powerful tools in the study and diagnosis of breast cancer. Recently, genome scans are used to study the genetics of gene expressions. In this article, we carry out a detailed study of 18 expression traits that are related to breast cancer to identify possible shared common transcription factor loci and inter-regulation patterns. Background Breast cancer [MIM 114480] is a common human disorder that is known to be genetically heterogeneous. The population prevalence for women in US is estimated to be about 12.5 % (Nathanson and Weber 2002). It has been shown that gene expressions possess discriminating powers for the diagnosis of breast cancer (van ’t Veer et al. 2002). On the other hand, the search for genetic regulators of such expression traits in humans has been underway through linkage/disequilibrium scans (Cheung et al. 2003; Morley et al. 2004; Cheung et al. 2005). It is thus instructive, for understanding the complex etiology of breast cancer, to identify jointly the genetic regulators of the expression traits that are related to previously identified breast cancer susceptibility genes. In this article, treating the expression levels of these genes as hereditable quantitative traits, we use multi-locus association genome scan, combined with traditional linkage scan, to study the joint regulation patterns of these breast cancer susceptibility genes. Materials and Methods Using the Affymetrix Human Focus Arrays, expression levels of 8500 transcripts were measured on 194 individuals in 14 CEPH families (Morley et al. 2004). 3554 transcripts were identified to have shown greater between-subject variation than within-subject variation and were used for linkage analysis in Morley et al. (2004). For the linkage analysis, genotypes of these CEPH individuals on 2882 SNPs across the genome were obtained from The SNP Consortiu

Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.178.5587
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