Differential motif enrichment analysis of paired ChIP-seq experiments
doi: 10.1186/1471-2164-15-752
Tom Lesluyes, James Johnson, Philip Machanick and Timothy L Bailey
Background
Motif enrichment analysis of transcription factor ChIP-seq data can help
identify transcription factors that cooperate or compete. Previously, little
attention has been given to comparative motif enrichment analysis of pairs of
ChIP-seq experiments, where the binding of the same transcription factor is
assayed under different conditions. Such comparative analysis could potentially
identify the distinct regulatory partners/competitors of the assayed
transcription factor under different conditions or at different stages of
development.
Results
We describe a new methodology for identifying sequence motifs that are
differentially enriched in one set of DNA or RNA sequences relative to another
set, and apply it to paired ChIP-seq experiments. We show that, using paired
ChIP-seq data for a single transcription factor, differential motif enrichment
analysis identifies all the known key transcription factors involved in the
transformation of non-cancerous immortalized breast cells (MCF10A-ER-Src cells)
into cancer stem cells whereas non-differential motif enrichment analysis does
not. We also show that differential motif enrichment analysis identifies
regulatory motifs that are significantly enriched at constrained locations
within the bound promoters, and that these motifs are not identified by
non-differential motif enrichment analysis. Our methodology differs from other
approaches in that it leverages both comparative enrichment and positional
enrichment of motifs in ChIP-seq peak regions or in the promoters of genes bound
by the transcription factor.
Conclusions
We show that differential motif enrichment analysis of paired ChIP-seq
experiments offers biological insights not available from non-differential
analysis. In contrast to previous approaches, our method detects motifs that are
enriched in a constrained region in one set of sequences, but not enriched in
the same region in the comparative set. We have enhanced the web-based CentriMo
algorithm to allow it to perform the constrained differential motif enrichment
analysis described in this paper, and CentriMo’s on-line interface
(http://meme.ebi.edu.au)
provides dozens of databases of DNA- and RNA-binding
motifs from a full range of organisms. All data and output files presented here
are available at
http://research.imb.uq.edu.au/t.bailey/supplementary_data/Lesluyes2014.
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