Workshop 6: ChIP-Seq

Detecting Transcription Factor Binding Sites with ChIP-Seq Data and Predicting Damaging Cis-Regulatory Variations



Date: Sunday, 9 September 2012
Time: 9am - 5pm
Registration: Congress Center Basel, Messeplatz 21
Venue: Room "Helvetia 2", Swissotel Le Plaza, Messeplatz 25





Workshop overview

The workshop covers genome re-sequencing data analysis for the prediction of variations within cis-regulatory sequences, called cis-regulatory variations (CRVs). Despite improvement of identification methods for functional variations within protein encoding exons, the prediction of CRVs remains an unmet challenge. With full-genome sequences becoming widely accessible for medical genetics research, the need to identify in silico causal regulatory variations is imperative.


Transcription factors (TFs) and their specific binding sites act to modulate the rate of gene transcription. Delineating specific positions at which TFs bind to DNA is of high importance in deciphering gene regulation at the transcriptional level. The accurate prediction of TFBSs is an enduring challenge, suffering from a high rate of false predictions. The ChIP-Seq procedure has proven capacity to define regions bound by a TF. The ongoing availability of data sets coming from the ChIP-Seq procedure allows researchers to develop new approaches to predict the specific locations of TFBSs with greater confidence than was previously possible. The global relationship between TFBS recognition and nucleotide variations remains largely unidentified both experimentally and in silico. The convergence of high-throughput technologies for sequencing individual full-genomes and rapid advances in genome annotation are driving a neo-revolution in human genetics. Recent studies have shown causal CRVs responsible for striking phenotypes and extensive genetic variations within human TFBSs correlated with differences in gene expression. Combining the application of models and procedures for predicting TFBSs at genome-scale with data arising from full-genome re-sequencing will permit researchers to identify phenotype-conferring CRVs.


The workshop responds to the high demand from researchers to combine results from transcription factor ChIP-Seq data with pedigree-based genome sequencing studies. It will be highly relevant to researchers from multiple domains of computational biology, including those interested in genome sequence data, gene expression, cis-regulatory sequence analysis and motif models for pattern discrimination. We aim to gain new insights for the development of methods that empower scientists to (i) improve models for the detection of transcription factor binding sites using ChIP-Seq data and (ii) use derived models to predict CRVs.


Preliminary schedule


Data/databases available to study gene regulation and analysis of regulatory elements
9.00 Dr. W. Wasserman Introduction
9.05 Mr. J.  Lim ChIP-seq data, PAZAR, JASPAR databases
9.50 Dr. U. Ohler From ChIP-seq to CLIP-seq and DNase-seq: computational tools for high-resolution binding and chromatin assays
10.30 Coffee break

TFBS predictions
11.00 Dr. A. Mathelier A new tool to predict TFBSs using ChIP-seq data
11.45 Dr. J. van Helden RSAT peak-moitfs: fast extraction of transcription binding motifs from full-size ChIP-seq datasets
12.30 Lunch

Detection of causal variations within exomes and full-genomes sequencing data
13.30 Dr. Y. Moreau

Predicting causal variations and copy number variations in the context of disease

14.15 Dr. S. Aerts Prediction of cancer-specific gene regulatory networks for the identification of coding and non-coding cancer drivers
15.00 Coffee break

Discussion and conclusion
15.30 Dr. B. Lenhard

Overlapping grammars on vertebrate promoters

16.15 Dr.W.Wasserman Panel discussion
16.50 Conclusion
17:00 End of Workshop




Wyeth W. Wasserman, Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia
Virginie Bernard, ICGex, NGS plateform, Curie Institute
Jonathan Lim, Centre for Molecular Medicine and Therapeutics, University of British Columbia
Anthony Mathelier, Centre for Molecular Medicine and Therapeutics, University of British Columbia