ChIP-Seq

ChIP-Seq provides genome-wide profiling of DNA targets for histone modification, transcription factors, and other DNA-associated proteins. It combines the selectivity of chromatin immunoprecipitation (ChIP) for recovering specific protein-DNA complexes with the power of NGS for high-throughput sequencing of the recovered DNA. Additionally, because the protein-DNA complexes are recovered from living cells, binding sites can be compared in different cell types or tissues, or under different conditions.

In ChIP-Seq, enriched DNA regions (protein binding sites) are detected as peaks above background reads, and bioinformatics analyses of these regions can reveal binding motifs. Applications include studies on gene regulation, transcription complex assembly, histone modification, developmental mechanisms, and disease processes. At Novogene, we can provide you with high quality sequencing and comprehensive bioinformatics analysis for your ChIP-Seq project.

Novogene also provides sequencing service and bioinformatics analysis on other kinds of IP-sequencing. Please contact us for more information.

The Novogene Advantage

• Cost-effective: Rapid and efficient genome-wide profiling of multiple samples, using only 1/100 of the amount of DNA required for ChIP-chip.
• Comprehensive analysis: Expert bioinformatics analyses utilizing widely accepted MACS2 software and latest programs for motif prediction, peak annotation, functional analysis, and data visualization.
• Professional bioinformatics: All PhD team for Chip-Seq data analysis.

Project Workflow

Sequencing Strategy

• 100~350 bp insert DNA library (depending on peak distribution)
• HiSeq platform, single-end 50 bp

Sample Requirements

• DNA amount ≥ 50 ng, main peak of 100-500 bp
• DNA concentration: ≥ 20 ng/μl
• DNA volume: ≥ 10 μl
• Purity: No degradation, no DNA contamination

Turnaround Time

• 35 working days from verification of sample quality without data analysis

Recommended Sequencing Depth

• ≥ 20 M reads

Analysis Pipeline

Table. Representative samples showing data quality of Novogene’s ChIP-seq service.

Sample	Raw Reads	Low Quality	Degeneratives	Empty	Too Short	Trimmed	Untrimmed	Clean Reads	Clean Rate (%)
Sample 1	21618631	43220	768	2079	1420	703080	20868064	21571144	99.78
Input Control	30300790	21692	1038	3255	888	869766	29404161	30273927	99.91

Quality control result of the project: including raw reads, trimmed reads and the raw-to-clean rate.



Figure. Strand cross-correlation evaluation curve

The x-axis represents the distance (nt) between forward strand and reverse strand and the y-axis represents the Pearson Correlation Coefficient.



Figure. Peak width distribution

The x-axis represents the peak width and y-axis represents the peak count.



Figure. Motif prediction results

The base calls as predicted by motif search software. The base calls on the right were the reverse-complementary strands.

Project Example

The following study utilized Novogene's expertise in ChIP-sequencing.

A Natural Allele of a Transcription Factor in Rice Confers Broad-Spectrum Blast Resistance
Cell, 170.1 (2017)

Rice is an extremely important crop, feeding much of the world’s population. However, it is susceptible to rice blast, a destructive disease caused by the fungus M. oryzae, which results in low yield and low grain quality in rice. It has been a challenge to identify broad-spectrum, durable genes that confer resistance in plants, and the few discovered are limited in application due to their linkage to negative agricultural traits. In this Cell paper, researchers performed a genome-wide association study to compare Digu, a rice variety with durable resistance to a broad range of M. oryzae races, to other rice accessions and identified the allele bsr-d1, encoding a C2H2-type transcription factor, as a contributor to Digu’s natural resistance. The bsr-d1 allele causes a single-nucleotide polymorphism in the promoter of the gene, which decreases gene expression through MYB transcription factor-mediated repression. BSR-D1 was determined to target peroxidase genes using Novogene’s ChIP-sequencing. Regulation of these H2O2-degradation enzymes is controlled by both BRS-D1 and MYBS1, and the inhibition of H2O2-degradation caused by the bsr-d1 allele results in increased blast resistance. This study illustrates the potential of the brs-d1 allele as a possible strategy for increasing disease resistance in rice and highlights the utility of ChIP-seq as a technique for identifying protein targets.




Figure. A model for bsr-d1-mediated disease resistance