Identifying Transcription Factor Binding Sites from ChIP-seq Data

Reetu TutejaScience Analyst, CyVerse

Learning objectives

Understand the nature of ChIP-seq data

Efficiently manage and analyze ChIP-seq data: from reads to peaks

How to do quality assessment using R ChIPQC package

Using CyVerse Discovery Environment apps to do ChIP-seq analysis

What is ChIP-seq?

How do cells know what to do?

Image source: cK12.org

Transcriptional regulation

Wasserman et al, Nature Reviews 2004

Transcription factors are proteins that can activate or repress the expression of target genes through the binding on DNA cis-regulatory elements

Chromatin accessibility and histonemodification also regulate geneexpression

Key steps in ChIP assay

ChIP DNA Input DNA

Chipseq workflow: from reads to peaks

Did my ChIP-seq worked?-- Cross-Correlation score-- FRiP score

• MACS2 (Model-based analysis of ChIP-seq)

1. Pre-alignment processing • Removal of adapter sequences• Remove low-quality • Discard short-reads

2. Alignment Use any standard short-read alignment program

3. Peak Calling MACS2 (Model-based analysis of ChIP-seq)

4. Post-alignment processing

Tutorial Link: https://cyverse-chipseq-tutorial.readthedocs-hosted.com/en/latest/index.html

Downstream analyses

Park et al, Nature Reviews 2009

ChIP signal

Jothi et al (2008) Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data

ChIP signal vs artifact signal

Landt et al (2012) ChIP-seq guidelines and practices for the ENCODE and modENCODE consortia

Plus strandMinus strand

Cross-correlation score

Successful vs failed ChIP

Strand shift (bp) Strand shift (bp) Strand shift (bp)

CyVerse is supported by the National Science Foundation under Grants No. DBI-0735191, DBI-1265383 and DBI-1743442.