What is Chromatin Immunoprecipitation Sequencing (ChIP-Seq)?

Epigenetic markers, such as DNA and histone modifications, are crucial for transcriptional regulation. These chromatin states differ during development and in different tissues and disease conditions.

Thus, mapping the protein-DNA interactions and epigenetic markers is required to understand transcriptional regulation.

ChIP-seq is a high throughput technique using next-generation sequencing (NGS) to identify transcription factor (TF) binding sites and chromatin modifications for determining gene regulatory networks in various biological processes.

​​​​​​​Image Credit: CI Photos/Shutterstock.com​​​​​​​Image Credit: CI Photos/Shutterstock.com

Foundations of ChIP-seq

Principle

ChIP-seq encompasses the precise enrichment of DNA fragments bound by the target protein (TF or histones) using ChIP, followed by DNA purification, and library construction.

High-throughput sequencing of the enriched fragments is performed, and the resulting sequence tags are mapped to the genome. This provides information on the DNA fragments interacting with the target protein across the genome.1

Method

The ChIP-seq process involves the following steps:

  1. Crosslinking: The protein-DNA interactions are stabilized using a crosslinking agent, such as formaldehyde.
  2. Chromatin fragmentation: Chromatin is extracted from the fixed cells and sheared into approximately 150–300 bp fragments using sonication/enzymatic digestion. An aliquot of fragmented chromatin is used as input control for quality control assessment and enrichment comparisons.
  3. Immunoprecipitation: The sheared chromatin is incubated with an antibody specific to the target protein. The magnetic bead coupled antibody pulls down the protein-DNA complexes. H3K4me3 and IgG antibodies are used as positive and negative controls, respectively.
  4. DNA purification: Crosslinking is reversed using heat treatment. The ChIP and input DNA samples are purified and the desired level of fragmentation is confirmed using agarose gel electrophoresis.
  5. Library preparation: The ChIP and input DNA are subjected to library preparation. All fragments are converted to 5′-phosphorylated blunt-ended DNA through end-repair. Then, an “A” base is added to the 3′ end using dATP. This is followed by adapter ligation, amplification, and purification. qPCR is performed to ensure the library is enriched with specific target sites.
  6. Sequencing: High throughput sequencing platforms are used to sequence the prepared library generating several DNA sequence reads that are subsequently aligned to the reference genome. A genome-wide map is produced followed by data analysis using bioinformatics software to determine the binding sites of the target protein.2

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Applications of ChIP-Seq

Gene Regulation

ChIP has been used to identify the precise binding sites of TFs and the role of these factors in activating genes downstream and governing extensive regulatory networks.

Robertson et al mapped STAT1 targets in unstimulated or interferon γ-stimulated HeLa S3 cells. ChIP-seq accurately identified STAT1 binding sites, demonstrating its robustness and comprehensiveness.3

The global binding sites of androgen receptor (AR) and corepressors such as histone deacetylase 1 (HDAC1), HDAC2, and HDAC3 were extensively mapped in prostate cancer cells.

These corepressors suppressed AR-induced gene expression, influencing epithelial differentiation and metastasis inhibition. This underscores the crucial role of ChIP-seq in revealing transcriptional networks for targeted therapies in prostate cancer eradication.4

The impact of SUMOylation of the glucocorticoid receptor (GR) on endogenous GR target genes and chromatin binding patterns was explored in wild-type or SUMOylation-defective GR HEK293 cells. SUMOylation selectively modulated GR chromatin occupancy at loci linked to cellular growth, influencing differential gene expression between cell lines.5

Thus, ChIP-seq, coupled with site-specific mutations or post-translational modifications of TFs can determine fundamental mechanisms of differential gene regulation.

Epigenetics

Epigenetic modifications of histones via acetylation or methylation can alter gene accessibility by promoting or suppressing gene expression. ChIP-seq has been employed to determine their genome-wide location and distribution.

Neutrophil dysfunction observed in individuals infected with HIV demonstrated increased H3K4me3 levels and transcription dysfunction in the circulating neutrophils of these individuals.

This dysregulation coincided with reduced responsiveness of neutrophils to lipopolysaccharides, impaired synthesis of chemokines/cytokines/growth factors, and increased apoptosis, with ChIP revealing notable abnormalities in exons, introns, and promoter-transcription start site regions (TSS). 6

ChIP-seq demonstrated chromatin remodeling of genes associated with cardiac function is responsible for cardiac hypertrophy. Antibodies to histone marks associated with active and repressed regions and transcribed genes were used for ChIP-seq.

The findings revealed that all the histone marks analyzed had been redistributed to TSS (±4 kb).7

Thus, ChIP-seq can determine crucial epigenetic regulation and dysregulation mechanisms in healthy and disease conditions.

Advantages and Limitations

Compared with ChIP-chip, ChIP-seq offers several advantages:

  • Genome-wide profiling, which is important for analyzing repetitive regions of the genome
  • Single nucleotide level resolution
  • Reduced background noise
  • Amount of ChIP DNA required is low (10-50 pg)
  • Vast dynamic range
  • Multiplexing is possible
  • Approximately 104-105 cells are required for ChIP-seq compared with 107 for ChIP-chip.
  • Reduced number of amplification rounds decreases PCR bias artifacts.1

Limitations

  • ChIP is expensive, but researchers have reduced the cost by creating their own protocols for constructing libraries.
  • Lack of easy access to platforms, which has improved due to institutional support.
  • Time-consuming process requiring 20-40 million reads/library to obtain an adequate signal.
  • Crosslinking agents should be optimized for every cell type and target; therefore, the type, concentration, and incubation time must be appropriately selected. Inadequate crosslinking can enhance sensitivity to the shearing process, whereas excessive crosslinking can cause ineffective chromatin shearing.
  • High-quality antibodies are crucial to reduce nonspecific binding to off-target proteins and recover a substantial amount of the target. Antibody validation is crucial, although a time-consuming process.
  • Sequencing errors occur at the end of each read, which can be mitigated via improvements in alignment algorithms and computational analysis.
  • GC bias may be present in fragment selection during library preparation and amplification before sequencing.1

Challenges

Nonuniform chromatin fragmentation can produce an uneven distribution of sequence tags across the genome. Thus, repetitive sequences may appear enriched. To overcome this issue, it is necessary to compare the peak identified in the ChIP-seq profile with the corresponding loci in the input sample to ascertain its significance.

Large amounts of data are produced via NGS, and data management is a significant issue. Large file sizes do not permit the deposition of NGS data. Thus, Sequence Read Archive has been developed wherein the metadata describing the experimental details can be deposited.

As many reads are produced, traditional alignment algorithms are time-consuming. Currently, Eland, Bowtie, and MAQ are commonly used aligners. No aligner is adequate for all applications, and the choice of aligner is based on a balance between speed, accuracy, flexibility, and memory.

As the amount of starting material for ChIP-seq is high, improvements are underway to use low input starting material so that the assay can be used for rare cell or tissue types. 1

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Recent Advances

Microfluidic System

Traditional ChIP-seq focuses on averaged features across multiple cells. Internal heterogeneity can be addressed within tissues using single-cell ChIP-seq. The Drop-ChIP method for chromatin labeling and sequencing uses droplet-based microfluidics. Despite its low sequencing depth, it can accurately classify cell types and subpopulations in embryonic stem cells, demonstrating its potential to uncover cellular heterogeneity in chromatin signatures.8

Tagmentation

The application of tagmentation-based library preparation with Tn5 transposase is extensively performed in ChIP-seq. For single-cell itChIP-seq, tagmentation is utilized for labeling and preparing libraries before the standard ChIP experiment. As this method resembles the established ChIP-seq technique, it is easier to use than single-cell Drop-ChIP.8

ChIP-free Techniques

Cleavage Under Targets and Release Using Nuclease (CUT&RUN) technology involves the semi-quantitative detection of protein-DNA interactions in situ at ~20 bp resolution. The cells are immobilized on lectin-coated magnetic beads and incubated with specific antibodies and protein A-MNase. The cleavage reaction is initiated with Ca2+ to release the target protein-DNA complexes for sequencing.

Cleavage Under Targets and Tagmentation (CUT&Tag) technology utilizes Tn5 tagmentation rather than MNase digestion. Simplifying the library construction steps permits single-cell experiments to investigate histone modifications.

As these methods possess the disadvantages of antibody-based techniques, novel antibody- and enrichment-free approaches should be developed for quantitative mapping of histone modifications at single base resolution.8

Data Interpretation

Robust data interpretation requires advanced bioinformatic tools and algorithms. Improving peak calling algorithms, reducing background noise, and integrating ChIP-seq data with other omics data is crucial for obtaining reliable and accurate results.9

Unsupervised machine-learning techniques have been used to develop integrative methods for segmenting, classifying, and annotating whole-genome sequences. These methods parallelly analyze all ChIP sample data and do not rely on individual peak calling and comparison methods.

For example, the hiHMM method simultaneously identifies chromatin state maps across multiple genomes and cell types. Markov random field model and EM algorithm are joint analysis tools used for TFs.8

Future Potential

Functional Genomics

ChIP-seq has been integrated with functional genomic assays to create gene regulation models. The combination of ChIP-seq and RNA-seq has enabled the assessment of the influence of TF binding or histone modifications on the expression of neighboring genes.9

ChIA-PET and Hi-C have been employed to determine long-range chromatin interactions.

To efficiently capture long-range interactions, novel methods combining HiC and ChIA-PET have been developed, namely PLAC-seq and HiCHIP. ChIP-seq has been integrated with DNase-/ATAC-/FAIRE-seq to determine chromatin accessibility.10

Precision Medicine

Examining the 3D genome structure provides clues into gene interactions and gene expression regulation.

The technologies developed to study the 3D genome structure include Hi-C (overall genome structure mapping), ChIP-seq (specific genome sites for protein-DNA interactions), and ICL-seq (specific genome sites involved in gene expression). The potential applications of combining these technologies are as follows:

  • Identifying genetic mutations associated with specific diseases to develop customized personalized treatments
  • Identifying genetic variants to determine a patient’s response to a particular drug for suitable drug selection
  • Identifying individuals at risk for developing certain diseases to develop preventive measures
  • Identifying new drug targets to develop novel and effective drugs with minimum side effects1!

Conclusion

ChIP is a powerful tool to determine specific protein binding sites on the genome and to provide insights into their regulatory functions and mechanisms.

ChIP-seq is also used to identify epigenetic marks, such as histone modifications, which influence chromatin structure and gene expression. This offers novel targets for developing therapeutic strategies against various diseases.

The challenges of ChIP-seq can be overcome by improving the experimental methods and data analysis tools and integration with other technologies. Future work should focus on antibody validation, using fewer cells, single-cell ChIP, robust data management and analysis tools.

References

  1. Park PJ. ChIP–seq: advantages and challenges of a maturing technology. Nature Reviews Genetics. 2009 Oct;10(10):669-80. https://www.nature.com/articles/nrg2641
  2. O’Geen H, Echipare L, Farnham PJ. Using ChIP-seq technology to generate high-resolution profiles of histone modifications. Epigenetics Protocols. 2011:265-86. https://pubmed.ncbi.nlm.nih.gov/21913086/
  3. Robertson G, Hirst M, Bainbridge M, Bilenky M, Zhao Y, Zeng T, Euskirchen G, Bernier B, Varhol R, Delaney A, Thiessen N. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nature Methods. 2007 Aug;4(8):651-7. https://profiles.wustl.edu/en/publications/genome-wide-profiles-of-stat1-dna-association-using-chromatin-imm
  4. Chng KR, Chang CW, Tan SK, Yang C, Hong SZ, Sng NY, Cheung E. A transcriptional repressor co‐regulatory network governing androgen response in prostate cancers. The EMBO Journal. 2012 Jun 13;31(12):2810-23. https://www.embopress.org/doi/10.1038/emboj.2012.112
  5. Paakinaho V, Kaikkonen S, Makkonen H, Benes V, Palvimo JJ. SUMOylation regulates the chromatin occupancy and anti-proliferative gene programs of glucocorticoid receptor. Nucleic Acids Research. 2014 Feb 1;42(3):1575-92. https://academic.oup.com/nar/article/49/4/1951/6125668
  6. Piatek P, Tarkowski M, Namiecinska M, Riva A, Wieczorek M, Michlewska S, Dulska J, Domowicz M, Kulińska-Michalska M, Lewkowicz N, Lewkowicz P. H3K4me3 histone ChIP-Seq analysis reveals molecular mechanisms responsible for neutrophil dysfunction in HIV-infected individuals. Frontiers in Immunology. 2021 Jul 15;12:682094. https://pubmed.ncbi.nlm.nih.gov/34335583/
  7. Papait, R., Cattaneo, P., Kunderfranco, P., Greco, C., Carullo, P., Guffanti, A., Viganò, V., Stirparo, G.G., Latronico, M.V., Hasenfuss, G. and Chen, J., 2013. Genome-wide analysis of histone marks identifying an epigenetic signature of promoters and enhancers underlying cardiac hypertrophy. Proceedings of the National Academy of Sciences, 110(50), pp.20164-20169. https://europepmc.org/article/pmc/3864351
  8. Nakato R, Sakata T. Methods for ChIP-seq analysis: A practical workflow and advanced applications. Methods. 2021 Mar 1;187:44-53. https://pubmed.ncbi.nlm.nih.gov/32240773/
  9. Dacey D (2023). The use of ChIP-seq in drug discovery. [Online] Dovetail Biopartners. Available at: https://dovetailbiopartners.com/2023/09/26/the-use-of-chip-seq-in-drug-discovery/ (Accessed on 4 July 2024).
  10. Jiang S, Mortazavi A. Integrating ChIP-seq with other functional genomics data. Briefings in Functional Genomics. 2018 Mar;17(2):104-15. https://academic.oup.com/bfg/article/17/2/104/4944665
  11. Kandavel PK (2023) 3D genomics: the future of precision medicine [Online]. Available at: https://www.linkedin.com/pulse/3d-genomics-future-precision-medicine-palani-kannan-kandavel-phd (Accessed on 4 July 2024).

Further Reading 

Last Updated: Jul 9, 2024

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