Background

Chromatin modification has been implicated in the molecular mechanisms of drug addiction and may hold the key to understanding multiple aspects of addictive behaviors (Robison and Nestler, 2011). Chromatin Immuno-Precipitation (ChIP) followed by massively parallel sequencing (ChIP-seq) is the current state of the art technology to profile the chromatin landscape. The typical procedure of ChIP-seq involves: 1) using the antibody against a protein of interest to pull down the binding DNA, which has been fixed to the protein and broken into smaller fragments, 2) the immunoprecipitated DNA is then purified and constructed into a library for high throughput sequencing of short reads (usually 50-100 bp) from the ends of insert DNA fragments, 3) the short reads are aligned to the genome and put through data analysis. Compared with its predecessor – ChIP-chip, ChIP-seq has unparalleled advantages such as unbiased coverage of the entire genome, single base resolution, and significantly improved signal-to-noise ratio (Park, 2009). It has proven to be an invaluable tool to understand numerous types of chromatin modifications.

Brief overview of ChIP-seq experiment: Please see original research articles for greater experimental details (Renthal et al., 2009; Lee et al., 2006). Briefly, adult mice received a standard regimen of repeated cocaine (7 daily IP injections of cocaine [20 mg/kg] or saline) and were used 24 h after the last injection (Robison and Nestler, 2011). The nucleus accumbens, a major brain reward region, was obtained by punch dissection and used for ChIP-seq. Chromatin IP was performed as described previously (Renthal et al., 2009; Lee et al. 2006; http://jura.wi.mit.edu/young_public/hES_PRC/ChIP.html) with minor modifications, using two antibodies, anti-H3K4me3 (tri-methylation of Lys4 in histone H4) (Abcam #ab8580) and anti-H3K9me3 (Abcam #ab8898). Sequencing libraries for each experimental condition were generated in triplicate, and were then sequenced on an Illumina sequencer.

Bioinformatic analysis: The sequencing data generated from libraries under treatment and corresponding control conditions will be used to identify the specific genomic regions that have undergone chromatin changes. We can then associate these regions with biological functions and select the regions of interest for further study. The basic procedure for this kind of bioinformatic analysis can be laid out as a pipeline of eight steps (Figure 1):
1. Perform quality control analyses on the sequencing data files;
2. Align the sequences to the genome;
3. Remove PCR duplicates;
4. Perform cross-correlation quality analysis;
5. Generate coverage files to be loaded into a genome browser;
6. Generate global coverage plots;
7. Perform peak detection and annotation;
8. Perform differential analysis and functional association.

This protocol shall explain each of these steps in more detail, including some of the principles and rationale underlying the bioinformatics analyses, and provide the necessary commands for execution in a Unix-like command-line environment.


Figure 1. Flowchart of the ChIP-seq analysis pipeline