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ChIP-Seq Service ChIP-seq profiles DNA targets of histone modifications, transcription factors and other DNA-associated proteins on a genome-wide scale. It combines the immunospecificity of chromatin immunoprecipitation (ChIP) for recovering specific protein-DNA complexes with the power of NGS for high-throughput sequencing of the DNA. Additionally, because the protein-DNA complexes are recovered from living cells, binding sites can be compared in different cell types, tissues or under different conditions. In ChIP-seq, enriched DNA regions (protein binding sites) are detected as peaks above background reads. Thebioinformatics analyses of these regions can reveal the specific binding motifs of the certain protein. Applications include studies on gene regulation, transcription complex assembly, histone modification, developmental mechanisms and disease processes. Novogene can provide 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 analysisand data visualization.
  • Professional bioinformatics:A bioinformatics analysis team composed of Ph.D. scientists entirely for Chip-Seq data analysis.

Project Workflow

ChIP-Seq Service

Sequencing Strategy

  • 200-400 bp insert DNA library (depending on peak distribution)
  • NovaSeq 6000 platform, paired-end 150 bp

Sample Requirements

  • DNA amount:≥ 50 ng, main peak of 100-500 bp
  • DNA volume: ≥ 10 μl
  • Purity: OD260/280 = 1.8–2.0 without degradation, no protein or RNA contamination

Turnaround Time

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

Recommended Sequencing Depth

  • ≥ 20 M reads

Project Workflow

ChIP-Seq Service
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. Strand cross-correlation evaluation curve 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. Chip Seq Peaks Figure. Peak width distribution The x-axis represents the peak width and y-axis represents the peak count. Motif prediction results 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