De novo motif identification improves the accuracy of predicting transcription factor binding sites in ChIP-Seq data analysis

De novo motif identification improves the accuracy of predicting transcription factor binding sites in ChIP-Seq data analysis
Valentina Boeva1,2,3,4, Didier Surdez1,2, Noëlle Guillon1,2, Franck Tirode1,2, Anthony P. Fejes5, Olivier Delattre1,2 and Emmanuel Barillot1,3,4,*

1Institut Curie, 26 rue d’Ulm, 2INSERM, U830, Genetics and Biology of Cancer, 3INSERM, U900, Bioinformatics, Biostatistics, Epidemiology and Computational Systems Biology of Cancer, Paris, F-75248, 4Mines ParisTech, Fontainebleau, F-77300, France and 5Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, V5Z 4S6, Canada

*To whom correspondence should be addressed. Tel: ; Fax: +33 1 56 24 69 11; Email: micsa@curie.fr

Received November 10, 2009. Revised February 23, 2010. Accepted March 15, 2010.

Dramatic progress in the development of next-generation sequencing technologies has enabled accurate genome-wide characterization of the binding sites of DNA-associated proteins. This technique, baptized as ChIP-Seq, uses a combination of chromatin immunoprecipitation and massively parallel DNA sequencing. Other published tools that predict binding sites from ChIP-Seq data use only positional information of mapped reads. In contrast, our algorithm MICSA (Motif Identification for ChIP-Seq Analysis) combines this source of positional information with information on motif occurrences to better predict binding sites of transcription factors (TFs). We proved the greater accuracy of MICSA with respect to several other tools by running them on datasets for the TFs NRSF, GABP, STAT1 and CTCF. We also applied MICSA on a dataset for the oncogenic TF EWS-FLI1. We discovered >2000 binding sites and two functionally different binding motifs. We observed that EWS-FLI1 can activate gene transcription when (i) its binding site is located in close proximity to the gene transcription start site (up to ~150 kb), and (ii) it contains a microsatellite sequence. Furthermore, we observed that sites without microsatellites can also induce regulation of gene expression—positively as often as negatively—and at much larger distances (up to ~1 Mb).