ChIP sequencing

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ChIP-sequencing, also known as ChIP-seq, is a method used to analyze protein interactions with DNA. ChIP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. It can be used to map global binding sites precisely for any protein of interest. Previously, ChIP-on-chip was the most common technique utilized to study these protein–DNA relations.

Contents

Uses

ChIP-seq is primarily used to determine how transcription factors and other chromatin-associated proteins influence phenotype-affecting mechanisms. Determining how proteins interact with DNA to regulate gene expression is essential for fully understanding many biological processes and disease states. This epigenetic information is complementary to genotype and expression analysis. ChIP-seq technology is currently seen primarily as an alternative to ChIP-chip which requires a hybridization array. This introduces some bias, as an array is restricted to a fixed number of probes. Sequencing, by contrast, is thought to have less bias, although the sequencing bias of different sequencing technologies is not yet fully understood. [1]

Specific DNA sites in direct physical interaction with transcription factors and other proteins can be isolated by chromatin immunoprecipitation. ChIP produces a library of target DNA sites bound to a protein of interest. Massively parallel sequence analyses are used in conjunction with whole-genome sequence databases to analyze the interaction pattern of any protein with DNA, [2] or the pattern of any epigenetic chromatin modifications. This can be applied to the set of ChIP-able proteins and modifications, such as transcription factors, polymerases and transcriptional machinery, structural proteins, protein modifications, and DNA modifications. [3] As an alternative to the dependence on specific antibodies, different methods have been developed to find the superset of all nucleosome-depleted or nucleosome-disrupted active regulatory regions in the genome, like DNase-Seq [4] and FAIRE-Seq. [5] [6]

Workflow of ChIP-sequencing

ChIP-sequencing workflow Chromatin immunoprecipitation sequencing.svg
ChIP-sequencing workflow

ChIP

ChIP is a powerful method to selectively enrich for DNA sequences bound by a particular protein in living cells. However, the widespread use of this method has been limited by the lack of a sufficiently robust method to identify all of the enriched DNA sequences. The ChIP wet lab protocol contains ChIP and hybridization. There are essentially five parts to the ChIP protocol [7] that aid in better understanding the overall process of ChIP. In order to carry out the ChIP, the first step is cross-linking [8] using formaldehyde and large batches of the DNA in order to obtain a useful amount. The cross-links are made between the protein and DNA, but also between RNA and other proteins. The second step is the process of chromatin fragmentation which breaks up the chromatin in order to get high quality DNA pieces for ChIP analysis in the end. These fragments should be cut to become under 500 base pairs [9] each to have the best outcome for genome mapping. The third step is called chromatin immunoprecipitation, [7] which is what ChIP is short for. The ChIP process enhances specific crosslinked DNA-protein complexes using an antibody against the protein of interest followed by incubation and centrifugation to obtain the immunoprecipitation. The immunoprecipitation step also allows for the removal of non-specific binding sites. The fourth step is DNA recovery and purification, [7] taking place by the reversed effect on the cross-link between DNA and protein to separate them and cleaning DNA with an extraction. The fifth and final step is the analyzation step of the ChIP protocol by the process of qPCR, ChIP-on-chip (hybrid array) or ChIP sequencing. Oligonucleotide adaptors are then added to the small stretches of DNA that were bound to the protein of interest to enable massively parallel sequencing. Through the analysis, the sequences can then be identified and interpreted by the gene or region to where the protein was bound. [7]

Sequencing

After size selection, all the resulting ChIP-DNA fragments are sequenced simultaneously using a genome sequencer. A single sequencing run can scan for genome-wide associations with high resolution, meaning that features can be located precisely on the chromosomes. ChIP-chip, by contrast, requires large sets of tiling arrays for lower resolution. [10]

There are many new sequencing methods used in this sequencing step. Some technologies that analyze the sequences can use cluster amplification of adapter-ligated ChIP DNA fragments on a solid flow cell substrate to create clusters of approximately 1000 clonal copies each. The resulting high density array of template clusters on the flow cell surface is sequenced by a genome analyzing program. Each template cluster undergoes sequencing-by-synthesis in parallel using novel fluorescently labelled reversible terminator nucleotides. Templates are sequenced base-by-base during each read. Then, the data collection and analysis software aligns sample sequences to a known genomic sequence to identify the ChIP-DNA fragments.[ citation needed ]

Quality control

ChIP-seq offers us a fast analysis, however, a quality control must be performed to make sure that the results obtained are reliable:

Sensitivity

Sensitivity of this technology depends on the depth of the sequencing run (i.e. the number of mapped sequence tags), the size of the genome and the distribution of the target factor. The sequencing depth is directly correlated with cost. If abundant binders in large genomes have to be mapped with high sensitivity, costs are high as an enormously high number of sequence tags will be required. This is in contrast to ChIP-chip in which the costs are not correlated with sensitivity. [12] [13]

Unlike microarray-based ChIP methods, the precision of the ChIP-seq assay is not limited by the spacing of predetermined probes. By integrating a large number of short reads, highly precise binding site localization is obtained. Compared to ChIP-chip, ChIP-seq data can be used to locate the binding site within few tens of base pairs of the actual protein binding site. Tag densities at the binding sites are a good indicator of protein–DNA binding affinity, [14] which makes it easier to quantify and compare binding affinities of a protein to different DNA sites. [15]

Current research

STAT1 DNA association: ChIP-seq was used to study STAT1 targets in HeLa S3 cells which are clones of the HeLa line that are used for analysis of cell populations. [16] The performance of ChIP-seq was then compared to the alternative protein–DNA interaction methods of ChIP-PCR and ChIP-chip. [17]

Nucleosome Architecture of Promoters: Using ChIP-seq, it was determined that Yeast genes seem to have a minimal nucleosome-free promoter region of 150bp in which RNA polymerase can initiate transcription. [18]

Transcription factor conservation: ChIP-seq was used to compare conservation of TFs in the forebrain and heart tissue in embryonic mice. The authors identified and validated the heart functionality of transcription enhancers, and determined that transcription enhancers for the heart are less conserved than those for the forebrain during the same developmental stage. [19]

Genome-wide ChIP-seq: ChIP-sequencing was completed on the worm C. elegans to explore genome-wide binding sites of 22 transcription factors. Up to 20% of the annotated candidate genes were assigned to transcription factors. Several transcription factors were assigned to non-coding RNA regions and may be subject to developmental or environmental variables. The functions of some of the transcription factors were also identified. Some of the transcription factors regulate genes that control other transcription factors. These genes are not regulated by other factors. Most transcription factors serve as both targets and regulators of other factors, demonstrating a network of regulation. [20]

Inferring regulatory network: ChIP-seq signal of Histone modification were shown to be more correlated with transcription factor motifs at promoters in comparison to RNA level. [21] Hence author proposed that using histone modification ChIP-seq would provide more reliable inference of gene-regulatory networks in comparison to other methods based on expression.

ChIP-seq offers an alternative to ChIP-chip. STAT1 experimental ChIP-seq data have a high degree of similarity to results obtained by ChIP-chip for the same type of experiment, with greater than 64% of peaks in shared genomic regions. Because the data are sequence reads, ChIP-seq offers a rapid analysis pipeline as long as a high-quality genome sequence is available for read mapping and the genome doesn't have repetitive content that confuses the mapping process. ChIP-seq also has the potential to detect mutations in binding-site sequences, which may directly support any observed changes in protein binding and gene regulation.

Computational analysis

As with many high-throughput sequencing approaches, ChIP-seq generates extremely large data sets, for which appropriate computational analysis methods are required. To predict DNA-binding sites from ChIP-seq read count data, peak calling methods have been developed. One of the most popular methods[ citation needed ] is MACS which empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. [22] MACS is optimized for higher resolution peaks, while another popular algorithm, SICER is programmed to call for broader peaks, spanning over kilobases to megabases in order to search for broader chromatin domains. SICER is more useful for histone marks spanning gene bodies. A mathematical more rigorous method BCP (Bayesian Change Point) can be used for both sharp and broad peaks with faster computational speed, [23] see benchmark comparison of ChIP-seq peak-calling tools by Thomas et al. (2017). [24]

Another relevant computational problem is differential peak calling, which identifies significant differences in two ChIP-seq signals from distinct biological conditions. Differential peak callers segment two ChIP-seq signals and identify differential peaks using Hidden Markov Models. Examples for two-stage differential peak callers are ChIPDiff [25] and ODIN. [26]

To reduce spurious sites from ChIP-seq, multiple experimental controls can be used to detect binding sites from an IP experiment. Bay2Ctrls adopts a Bayesian model to integrate the DNA input control for the IP, the mock IP and its corresponding DNA input control to predict binding sites from the IP. [27] This approach is particularly effective for complex samples such as whole model organisms. In addition, the analysis indicates that for complex samples mock IP controls substantially outperform DNA input controls probably due to the active genomes of the samples. [27]

See also

Similar methods

Related Research Articles

<span class="mw-page-title-main">ChIP-on-chip</span> Molecular biology method

ChIP-on-chip is a technology that combines chromatin immunoprecipitation ('ChIP') with DNA microarray ("chip"). Like regular ChIP, ChIP-on-chip is used to investigate interactions between proteins and DNA in vivo. Specifically, it allows the identification of the cistrome, the sum of binding sites, for DNA-binding proteins on a genome-wide basis. Whole-genome analysis can be performed to determine the locations of binding sites for almost any protein of interest. As the name of the technique suggests, such proteins are generally those operating in the context of chromatin. The most prominent representatives of this class are transcription factors, replication-related proteins, like origin recognition complex protein (ORC), histones, their variants, and histone modifications.

<span class="mw-page-title-main">ABI Solid Sequencing</span>

SOLiD (Sequencing by Oligonucleotide Ligation and Detection) is a next-generation DNA sequencing technology developed by Life Technologies and has been commercially available since 2006. This next generation technology generates 108 - 109 small sequence reads at one time. It uses 2 base encoding to decode the raw data generated by the sequencing platform into sequence data.

DNA adenine methyltransferase identification, often abbreviated DamID, is a molecular biology protocol used to map the binding sites of DNA- and chromatin-binding proteins in eukaryotes. DamID identifies binding sites by expressing the proposed DNA-binding protein as a fusion protein with DNA methyltransferase. Binding of the protein of interest to DNA localizes the methyltransferase in the region of the binding site. Adenine methylation does not occur naturally in eukaryotes and therefore adenine methylation in any region can be concluded to have been caused by the fusion protein, implying the region is located near a binding site. DamID is an alternate method to ChIP-on-chip or ChIP-seq.

<span class="mw-page-title-main">Tiling array</span>

Tiling arrays are a subtype of microarray chips. Like traditional microarrays, they function by hybridizing labeled DNA or RNA target molecules to probes fixed onto a solid surface.

<span class="mw-page-title-main">RNA immunoprecipitation chip</span>

RIP-chip is a molecular biology technique which combines RNA immunoprecipitation with a microarray. The purpose of this technique is to identify which RNA sequences interact with a particular RNA binding protein of interest in vivo. It can also be used to determine relative levels of gene expression, to identify subsets of RNAs which may be co-regulated, or to identify RNAs that may have related functions. This technique provides insight into the post-transcriptional gene regulation which occurs between RNA and RNA binding proteins.

Epigenomics is the study of the complete set of epigenetic modifications on the genetic material of a cell, known as the epigenome. The field is analogous to genomics and proteomics, which are the study of the genome and proteome of a cell. Epigenetic modifications are reversible modifications on a cell's DNA or histones that affect gene expression without altering the DNA sequence. Epigenomic maintenance is a continuous process and plays an important role in stability of eukaryotic genomes by taking part in crucial biological mechanisms like DNA repair. Plant flavones are said to be inhibiting epigenomic marks that cause cancers. Two of the most characterized epigenetic modifications are DNA methylation and histone modification. Epigenetic modifications play an important role in gene expression and regulation, and are involved in numerous cellular processes such as in differentiation/development and tumorigenesis. The study of epigenetics on a global level has been made possible only recently through the adaptation of genomic high-throughput assays.

Paired-end tags (PET) are the short sequences at the 5’ and 3' ends of a DNA fragment which are unique enough that they (theoretically) exist together only once in a genome, therefore making the sequence of the DNA in between them available upon search or upon further sequencing. Paired-end tags (PET) exist in PET libraries with the intervening DNA absent, that is, a PET "represents" a larger fragment of genomic or cDNA by consisting of a short 5' linker sequence, a short 5' sequence tag, a short 3' sequence tag, and a short 3' linker sequence. It was shown conceptually that 13 base pairs are sufficient to map tags uniquely. However, longer sequences are more practical for mapping reads uniquely. The endonucleases used to produce PETs give longer tags but sequences of 50–100 base pairs would be optimal for both mapping and cost efficiency. After extracting the PETs from many DNA fragments, they are linked (concatenated) together for efficient sequencing. On average, 20–30 tags could be sequenced with the Sanger method, which has a longer read length. Since the tag sequences are short, individual PETs are well suited for next-generation sequencing that has short read lengths and higher throughput. The main advantages of PET sequencing are its reduced cost by sequencing only short fragments, detection of structural variants in the genome, and increased specificity when aligning back to the genome compared to single tags, which involves only one end of the DNA fragment.

Chromatin Interaction Analysis by Paired-End Tag Sequencing is a technique that incorporates chromatin immunoprecipitation (ChIP)-based enrichment, chromatin proximity ligation, Paired-End Tags, and High-throughput sequencing to determine de novo long-range chromatin interactions genome-wide.

<span class="mw-page-title-main">Chromatin immunoprecipitation</span> Genomic technique

Chromatin immunoprecipitation (ChIP) is a type of immunoprecipitation experimental technique used to investigate the interaction between proteins and DNA in the cell. It aims to determine whether specific proteins are associated with specific genomic regions, such as transcription factors on promoters or other DNA binding sites, and possibly define cistromes. ChIP also aims to determine the specific location in the genome that various histone modifications are associated with, indicating the target of the histone modifiers. ChIP is crucial for the advancements in the field of epigenomics and learning more about epigenetic phenomena.

Peak calling is a computational method used to identify areas in a genome that have been enriched with aligned reads as a consequence of performing a ChIP-sequencing or MeDIP-seq experiment. These areas are those where a protein interacts with DNA. When the protein is a transcription factor, the enriched area is its transcription factor binding site (TFBS). Popular software programs include MACS. Wilbanks and colleagues is a survey of the ChIP-seq peak callers, and Bailey et al. is a description of practical guidelines for peak calling in ChIP-seq data.

<span class="mw-page-title-main">ChIP-exo</span>

ChIP-exo is a chromatin immunoprecipitation based method for mapping the locations at which a protein of interest binds to the genome. It is a modification of the ChIP-seq protocol, improving the resolution of binding sites from hundreds of base pairs to almost one base pair. It employs the use of exonucleases to degrade strands of the protein-bound DNA in the 5'-3' direction to within a small number of nucleotides of the protein binding site. The nucleotides of the exonuclease-treated ends are determined using some combination of DNA sequencing, microarrays, and PCR. These sequences are then mapped to the genome to identify the locations on the genome at which the protein binds.

<span class="mw-page-title-main">STARR-seq</span>

STARR-seq is a method to assay enhancer activity for millions of candidates from arbitrary sources of DNA. It is used to identify the sequences that act as transcriptional enhancers in a direct, quantitative, and genome-wide manner.

ATAC-seq is a technique used in molecular biology to assess genome-wide chromatin accessibility. In 2013, the technique was first described as an alternative advanced method for MNase-seq, FAIRE-Seq and DNase-Seq. ATAC-seq is a faster analysis of the epigenome than DNase-seq or MNase-seq.

Transcription factors are proteins that bind genomic regulatory sites. Identification of genomic regulatory elements is essential for understanding the dynamics of developmental, physiological and pathological processes. Recent advances in chromatin immunoprecipitation followed by sequencing (ChIP-seq) have provided powerful ways to identify genome-wide profiling of DNA-binding proteins and histone modifications. The application of ChIP-seq methods has reliably discovered transcription factor binding sites and histone modification sites.

Selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq) is a technique developed for the rapid identification of DNA binding specificities and affinities of full length monomeric and dimeric transcription factors in a fast and semi-high-throughput fashion.

CUT&RUN sequencing, also known as cleavage under targets and release using nuclease, is a method used to analyze protein interactions with DNA. CUT&RUN sequencing combines antibody-targeted controlled cleavage by micrococcal nuclease with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. It can be used to map global DNA binding sites precisely for any protein of interest. Currently, ChIP-Seq is the most common technique utilized to study protein–DNA relations, however, it suffers from a number of practical and economical limitations that CUT&RUN sequencing does not.

CUT&Tag-sequencing, also known as cleavage under targets and tagmentation, is a method used to analyze protein interactions with DNA. CUT&Tag-sequencing combines antibody-targeted controlled cleavage by a protein A-Tn5 fusion with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. It can be used to map global DNA binding sites precisely for any protein of interest. Currently, ChIP-Seq is the most common technique utilized to study protein–DNA relations, however, it suffers from a number of practical and economical limitations that CUT&RUN and CUT&Tag sequencing do not. CUT&Tag sequencing is an improvement over CUT&RUN because it does not require cells to be lysed or chromatin to be fractionated. CUT&RUN is not suitable for single-cell platforms so CUT&Tag is advantageous for these.

ChIL sequencing (ChIL-seq), also known as Chromatin Integration Labeling sequencing, is a method used to analyze protein interactions with DNA. ChIL-sequencing combines antibody-targeted controlled cleavage by Tn5 transposase with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. It can be used to map global DNA binding sites precisely for any protein of interest. Currently, ChIP-Seq is the most common technique utilized to study protein–DNA relations, however, it suffers from a number of practical and economical limitations that ChIL-Sequencing does not. ChIL-Seq is a precise technique that reduces sample loss could be applied to single-cells.

<span class="mw-page-title-main">MNase-seq</span> Sk kasid Youtuber

MNase-seq, short for micrococcal nuclease digestion with deep sequencing, is a molecular biological technique that was first pioneered in 2006 to measure nucleosome occupancy in the C. elegans genome, and was subsequently applied to the human genome in 2008. Though, the term ‘MNase-seq’ had not been coined until a year later, in 2009. Briefly, this technique relies on the use of the non-specific endo-exonuclease micrococcal nuclease, an enzyme derived from the bacteria Staphylococcus aureus, to bind and cleave protein-unbound regions of DNA on chromatin. DNA bound to histones or other chromatin-bound proteins may remain undigested. The uncut DNA is then purified from the proteins and sequenced through one or more of the various Next-Generation sequencing methods.

<span class="mw-page-title-main">PLAC-Seq</span> Proximity ligation assisted chip-seq technology

Proximity ligation-assisted chromatin immunoprecipitation sequencing (PLAC-seq) is a chromatin conformation capture(3C)-based technique to detect and quantify genomic chromatin structure from a protein-centric approach. PLAC-seq combines in situ Hi-C and chromatin immunoprecipitation (ChIP), which allows for the identification of long-range chromatin interactions at a high resolution with low sequencing costs. Mapping long-range 3-dimensional(3D) chromatin interactions is important in identifying transcription enhancers and non-coding variants that can be linked to human diseases.

References

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  1. ↑ Chèneby J, Gheorghe M, Artufel M, Mathelier A, Ballester B (January 2018). "ReMap 2018: an updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments". Nucleic Acids Research. 46 (D1): D267–D275. doi:10.1093/nar/gkx1092. PMC   5753247 . PMID   29126285.
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