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Product Brief

ChIP-Seq is an epigenetic research technique combining Chromatin Immunoprecipitation (ChIP) with the two generation sequencing, which can efficiently detect the interaction between DNA and protein in the genome wide range, and is usually used for transcription factor binding sites or histone specific modification sites.

ChIP-seq Assay Kit for Histone Methylation (Laboratorytalk, 2016)

Our advantages

One Customized analysis strategy: customized selection algorithm based on different sequencing and sequencing objectives. Peak Calling algorithm and annotation database area information;

Two Strong self research ability: self published development Peak Calling algorithm (Wang et al., BMC Bioinformatics, 2010) and location annotation system and a series of downstream analysis tools;

Three Comprehensive database integration: constantly updating genome database and integrating multi database and multi version to get accurate results. Peak positioning information and annotations;

Four Powerful joint analysis ability of omics: will ChIP-Seq is combined with methylation sequencing, transcriptome sequencing and genome sequencing technology to further expand single protein binding data.


Sample requirements

Note: early immunoprecipitation ( ChIP) the experiment needs customers to complete independently, and strong ice provides sequencing and data analysis services.

ChIP DNA sample requirements:

The total volume of 1. DNA is more than 20ng, the concentration is more than 1ng/ 1ng/ L (Qubit detection), the volume requirement is 20-100 L.

2. OD260/280 is between 1.8-2.0.

3. Agilent 2200 quality inspection qualified, DNA sample main peak range is 100-500bp;

Four Electrophoretic detection was not obvious. The genome of RNA is clear and complete without degradation.

Five Please mark the sample number clearly when sending the sample. Parafilm membrane seal;

6. avoid repeated freezing and thawing during preservation.

7. dry ice transportation for sample delivery.



Experiment flow


One Cell cross-linking fixation Formaldehyde treatment cells connect the target protein with chromatin.

2. DNA ultrasound interrupted: interrupting genomic DNA to 100-500bp;

3. co immunoprecipitation: an antibody specific to the target protein was added to form an immunoprecipitation complex.

4. recovery of DNA fragments: de crosslinking and purification of DNA;

Five Library Construction: The library was amplified by PCR.

Six Machine sequencing: strong ice recommended Hiseq or NovaSeq sequencing platform, data volume 6Gb.



Data analysis process

Result example

1. Quality control of raw data
Fastp software was used to filtrate the low quality sequence, undetected sequence and serial sequence of the original data. The GC ratio, base mass, length distribution, joint retention and Duplication ratio were analyzed before and after filtration. Figure 1 shows the results of raw data quality control.

Base quality results map

Note: the abscissa of the left picture represents the base site, and the ordinate represents the base mass. The different color curves represent different bases in each. The mass values on the read; the right cross coordinates represent the base sites, and the ordinates represent the ratio of the base content. The different color curves represent the bases of different loci.



2. DNA genome alignment (DNA Mapping)
The Bowtie2 algorithm is used to compare the filtered data to the genome and get the BAM files for genome comparison. Based on the BAM file, the information ratio is obtained, and the genomic comparison rate and the distribution of reads on the chromosome are obtained.

DNA mapping result graph

Note: left picture is Reads The comparison on the genome; the right picture is The distribution of reads on chromosomes. The gray column represents the ratio of the base number on each chromosome to the genome, and the green column is compared to the chromosome. The base number of reads accounts for the proportion of genome.



3, Peak Calling and Peak notes (Peak Annotation)
The MACS2 algorithm was used to detect the peak peak of BAM files after DNA Mapping, and the enriched region of ChIP transcription factor binding or histone modification was obtained, that is, peak region. The Chipseeker algorithm was used to annotate peak, and the corresponding genes and the gene structure of peak were obtained, including promoters, exons, Chi Ko and intergenic regions. In addition, we can also use deeptools software to map the coverage of the sequence in the target area, and get the distribution of reads in peak region or gene structure.

The quantity of peak and its distribution in gene structure

Twohig JP et al., Nat Immunol, 2019

Note: left picture is different grouping. The proportion of peak in the genome structure, the right picture is the total number of different groups of peak.



4. Motif analysis (Motif Analysis)
HOMER/MEME algorithm and JAPSAR database are used to carry out motif analysis of peak region and get potential motif feature sequences.

Specific transcription factor binding Enrichment of motifs

Twohig JP et al., Nat Immunol, 2019

Note: MEME and STAMP/Jaspar software jointly predict binding Motif for STAT1 and STAT3.



5. Functional analysis (GO Analysis) signal pathway analysis (Pathway Analysis)
NCBI/UNIPROT/SWISSPROT/AMIGO and other GO databases and KEGG databases were used to perform functional analysis and signal pathway analysis of Peak Annotation related genes. GO entries and Pathway entries were significantly enriched by these gene groups.

GO analysis results

Zhang QT et al., Theranostics. 2019

Note: the left picture is significantly enriched by down-regulation genes. GO entry (Top 10 The right picture is significantly enriched by the up-regulated gene. GO entry (Top 10).



Advanced data analysis
1, IGV screenshots
The igvtools algorithm is used to transform the BAM file after genome alignment into TDF format. The peak distribution near the target gene is visualized by IGV software.

ISL1 target gene place Peak distribution

Zhang QT et al., Theranostics. 2019

Note: the graph shows. ISL1 Near target gene H3K4me1 , H3K27ac and ISL1 Of Peak distribution, the arrow represents the peak of the combination.



2. Gene-Act-Network Analysis
Taking the significant GO Analysis and significant Pathway Analysis and histone related phenotype genes as the research objectives, we used KEGG database annotation to draw Gene-Act-Network.

Intergenic interaction network

Gao et al., Cancer. 2015

Note: Profile1 , 2, 4 gene interaction network map.



Examples of literature

[1] Twohig JP, Cardus Figueras A, Andrews R, et al. Activation, et, al., Cardus, JP, Cardus, and Figueras.


[2] Mirtschink P, Bischof C, Pham MD, et al. Inhibition of, the alpha alpha, P, Bischof, 2019


[3] Han X, Huang H, Gao P, et al. E-protein regulatory network links TCR signaling to effector Treg cell differentiation. cell 2019 Feb 15. pii: 201800494. (IF=9.504)


[4] Zhang QT, Zhang QQ, Jiang X, et al. Collaborative ISL1/GATA3, al., MYCN.Theranostics 2019. 9 (4): 986 - 1000. (IF=8.537)


[5] Ranjit M, Hirano M, Aoki K, et al. Aberrant Active Aberrant, 2019, 26; 26 (9):


[6] Gao Y, et al. Single Cas9 nickase induced generation of generation 2017, 1, 18 (1): (13.)



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