Interplay between DNA and its interacting proteins
ChIP-Seq is used primarily to determine how proteins interact with DNA to regulate gene expression with the intent to elucidate the complex circuitry of genetic regulatory networks, genetic pathways and epigenetic mechanisms in living cells. The approach enables thorough examination of the genome-wide distribution of chromatin-binding proteins and histone modifications in any genome with a known sequence, giving insights into gene regulation events that play a role in various diseases and biological pathways, such as development and cancer progression.
LIbrary preparation and sequencing
Our workflow starts from immunoprecipitated (IP) DNA samples. The material generated by IP is often in extremely low amounts, however we'll give it a chance and try to produce a library. ChIP-seq experiment usually includes matched controls (input, IgG or untagged strain) used for background subtraction, i.e. more accurate peak identification. IPs and controls are always processed in parallel. The sequencing is performed on Hiseq2500 in 50 bp single-read or 125 bp paired-end mode, and on NextSeq 500 in a 75 bp single-read mode.
Bioinformatics analysis
Our analysis enables discovery of novel transcription factor binding sites, identification of genes regulated by known transcription factors and co-regulators, direct comparison of regulatory events in different cell states (i.e. normal v. disease) and investigation of drug effects and other stimuli on regulatory pathways.
Standard bioinformatics analysis:
- Base calling and demultiplexing
- Trimming - removing low quality bases and adapters
- Reads alignment on reference genome and selection of uniquely mapping read
- Quality control - contaminants assessment by using proprietary script and examination on how well the signal in the ChIP-seq sample can be differentiated from the background distribution of reads in the control sample (bamFingerprinting)
- Peak detection
- Peak annotation – identification of potential association of ChIP regions with functionally important genomic regions. Analysis provides statistics on ChIP enrichment at important genome features such as specific chromosome, promoters, gene bodies, or exons, and infers genes most likely to be regulated by a binding factor. Provided only for human samples aligned on human hg19, mouse mm9, fly dm3 and worm ce6 reference.
Advanced bioinformatics analysis:
-
Identification of sites that are differentially bound between two sample groups, including overlapping and merging peak sets, counting sequencing reads overlapping intervals in peak sets, and identifying statistically significantly differentially bound sites based on evidence of binding affinity (measured by differences in read densities).
We provide full support on study design to ensure correct sequencing and bioinformatics strategies are used to meet your project goals. Our expert will consult with you about your specific requirements.