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This article is part of the supplement: Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci

Open Access Proceedings

Joint study of genetic regulators for expression traits related to breast cancer

Tian Zheng1*, Shuang Wang2, Lei Cong1, Yuejing Ding1, Iuliana Ionita-Laza3 and Shaw-Hwa Lo1

Author Affiliations

1 Department of Statistics, Columbia University, New York, New York 10027, USA

2 Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York 10032, USA

3 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA

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BMC Proceedings 2007, 1(Suppl 1):S10  doi:

Published: 18 December 2007

Abstract

Background

The mRNA expression levels of genes have been shown to have discriminating power for the classification of breast cancer. Studying the heritability of gene expression levels on breast cancer related transcripts can lead to the identification of shared common regulators and inter-regulation patterns, which would be important for dissecting the etiology of breast cancer.

Results

We applied multilocus association genome-wide scans to 18 breast cancer related transcripts and combined the results with traditional linkage scans. Regulatory hotspots for these transcripts were identified and some inter-regulation patterns were observed. We also derived evidence on interacting genetic regulatory loci shared by a number of these transcripts.

Conclusion

In this paper, by restricting to a set of related genes, we were able to employ a more detailed multilocus approach that evaluates both marginal and interaction association signals at each single-nucleotide polymorphism. Interesting inter-regulation patterns and significant overlaps of genetic regulators between transcripts were observed. Interaction association results returned more expression quantitative trait locus hotspots that are significant.