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Nucleic Acids Research 2004 32(22):6627-6635; doi:10.1093/nar/gkh1005
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Published online 17 December 2004

Nucleic Acids Research, Vol. 32 No. 22 © Oxford University Press 2004; all rights reserved

Identifying estrogen receptor {alpha} target genes using integrated computational genomics and chromatin immunoprecipitation microarray

Victor X. Jin, Yu-Wei Leu, Sandya Liyanarachchi, Hao Sun, Meiyun Fan1, Kenneth P. Nephew1, Tim H.-M. Huang and Ramana V. Davuluri*

Human Cancer Genetics Program, Department of Molecular Virology, Immunology, and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA and 1 Medical Sciences Program, Indiana University School of Medicine, Bloomington, IN 47405, USA

* To whom correspondence should be addressed. Tel: +1 614 688 3088; Fax: +1 614 688 4006; Email: davuluri-1{at}medctr.osu.edu
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors

Received September 24, 2004; Revised November 8, 2004; Accepted November 29, 2004

The estrogen receptor {alpha} (ER{alpha}) regulates gene expression by either direct binding to estrogen response elements or indirect tethering to other transcription factors on promoter targets. To identify these promoter sequences, we conducted a genome-wide screening with a novel microarray technique called ChIP-on-chip. A set of 70 candidate ER{alpha} loci were identified and the corresponding promoter sequences were analyzed by statistical pattern recognition and comparative genomics approaches. We found mouse counterparts for 63 of these loci and classified 42 (67%) as direct ER{alpha} targets using classification and regression tree (CART) statistical model, which involves position weight matrix and human-mouse sequence similarity scores as model parameters. The remaining genes were considered to be indirect targets. To validate this computational prediction, we conducted an additional ChIP-on-chip assay that identified acetylated chromatin components in active ER{alpha} promoters. Of the 27 loci upregulated in an ER{alpha}-positive breast cancer cell line, 20 having mouse counterparts were correctly predicted by CART. This integrated approach, therefore, sets a paradigm in which the iterative process of model refinement and experimental verification will continue until an accurate prediction of promoter target sequences is derived.


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