Affiliations: Division of Metabolic Disease, Center for Biomedical
Science, National Institute of Health, Nokbun-dong 5, Eunpyung-gu, Seoul
122-701, South Korea | Department of Microbiology, College of Medicine, The
Catholic University of Korea, Seoul, South Korea
Abstract: To understand the transcriptional regulatory network in eukaryotic
cells, it is essential to identify functional cis-regulatory sequences
that interact with trans-acting factors. A number of algorithms have been
developed to predict common cis-regulatory elements for co-regulated
genes with similar expression patterns. However, previous methods usually deal
with disjoint gene groups partitioned or clustered by arbitrary cutoffs, which
might cause information losses. To preclude the defining step of gene set, we
adopted enrichment analysis and termed the method binding site enrichment
analysis (BSEA). BSEA was first applied for publicly available ChIP-on-chip
data of c-MYC, MAX and E2F transcription factors, identifying significant
enrichment for signatures of corresponding factors and potential co-activators.
Using time-scaled expression profiling of 3T3-L1 adipogenesis, we observed
enrichment for signatures of known adipogenic factors such as
C/EBPα, C/EBPβ and
PPARγ, temporally coincident with previous reports.
BSEA was also applied to tissue-specific expression profiles of human and
mouse, identifying well-known tissue-specific transcription factors such as
HNF-4 in liver and MEF-2 in heart along with other putative tissue-specific
regulators. With extended versatility coping with various kinds of microarray
dataset, BSEA can identify key regulators for global microarray data in which
transcriptional regulation plays a major role. As a generalized method, BSEA
would help to elucidate the transcriptional regulatory networks, the primary
challenges in functional genomics.
