Identifying estrogen receptor α target genes using integrated computational genomics and chromatin immunoprecipitation microarray

Victor X. Jin, Yu Wei Leu, Sandya Liyanarachchi, Hao Sun, Meiyun Fan, Kenneth P. Nephew, Tim H.M. Huang, Ramana V. Davuluri

Research output: Contribution to journalArticlepeer-review

63 Scopus citations

Abstract

The estrogen receptor α (ERα) 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 ERα 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 ERα 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 ERα promoters. Of the 27 loci upregulated in an ERα-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.

Original languageEnglish (US)
Pages (from-to)6627-6635
Number of pages9
JournalNucleic acids research
Volume32
Issue number22
DOIs
StatePublished - 2004

ASJC Scopus subject areas

  • Genetics

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