ChIA-PET

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Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET or ChIA-PETS) 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. [1]

Contents

Genes can be regulated by regions far from the promoter such as regulatory elements, insulators and boundary elements, and transcription-factor binding sites (TFBS). Uncovering the interplay between regulatory regions and gene coding regions is essential for understanding the mechanisms governing gene regulation in health and disease (Maston et al., 2006). ChIA-PET can be used to identify unique, functional chromatin interactions between distal and proximal regulatory transcription-factor binding sites and the promoters of the genes they interact with.

ChIA-PET can also be used to unravel the mechanisms of genome control during processes such as cell differentiation, proliferation, and development. By creating ChIA-PET interactome maps for DNA-binding regulatory proteins and promoter regions, we can better identify unique targets for therapeutic intervention (Fullwood & Yijun, 2009).

Methodology

The ChIA-PET method combines ChIP-based methods, [2] and Chromosome conformation capture (3C) based methods, [3] to extend the capabilities of both approaches. ChIP-Sequencing (ChIP-Seq) is a popular method used to identify TFBS while 3C has been used to identify long-range chromatin interactions. Independently, both suffer from limitations in identifying de-novo long-range interactions genome wide. While ChIP-Seq is able to identify TFBS genome-wide, [4] [5] it provides only linear information of protein binding sites along the chromosomes (but not interactions between them), and can suffer from high genomic background noise (false positives). While 3C is capable of analyzing non-linear, long-range chromatin interactions, it cannot be used genome wide and, like ChIP-Seq, also suffers from high levels of background noise. Since the noise increases in relation to the distance between interacting regions (max 100kb), laborious and tedious controls are required for accurate characterization of chromatin interactions. [6] Unlike 3C which is a locus-specific interaction profiling method, alternative methods such as Hi-C have been established to profile interactions genome wide. [7] Despite whole genome profiling methods for both TFBS and long range interactions, combining approaches with the ChIA-PET method allows for identification of genomic areas in which the protein of interest is bound as well as the genomic region which it interacts with. [8] [9]

The ChIA-PET method successfully resolves the issues of non-specific interaction noise found in ChIP-Seq by sonicating the ChIP fragments in order to separate random attachments from specific interaction complexes. The next step, which is referred to as enrichment, reduces complexity for genome-wide analysis and adds specificity to chromatin interactions bound by pre-determined TFs (transcription factors). The ability of 3C approaches to identify long-range interactions is based on the theory of proximity ligation. In regards to DNA inter-ligation, fragments that are tethered by common protein complexes have greater kinetic advantages under dilute conditions, than those freely diffusing in solution or anchored in different complexes. ChIA-PET takes advantage of this concept by incorporating linker sequences onto the free ends of the DNA fragments tethered to the protein complexes. In order to build connectivity of the fragments tethered by regulatory complexes, the linker sequences are ligated during nuclear proximity ligation. Therefore, the products of linker-connected ligation can be analyzed by ultra-high-throughput PET sequencing and mapped to the reference genome. Since ChIA-PET is not dependent on specific sites for detection as 3C and 4C are, it allows unbiased, genome-wide de-novo detection of chromatin interactions. [8] Compared to Hi-C, the use of an antibody pulldown limits the number of sequenced fragments to chromatin interactions bound by the protein of interest which also can ease the data analysis.

Workflow

Wet-lab portion of the workflow:

Figure 1. Biotinylated universal linkers with Mme1 restriction endonuclease sites are introduced. ChIPPET3.JPG
Figure 1. Biotinylated universal linkers with Mme1 restriction endonuclease sites are introduced.
Figure 2. Biotinylated universal linkers are ligated to the free DNA ends. ChIPPET4.JPG
Figure 2. Biotinylated universal linkers are ligated to the free DNA ends.
Figure 3. Ligation of linkers during proximity ligation. ChIPPET5.JPG
Figure 3. Ligation of linkers during proximity ligation.
Figure 4. Pull down of biotinylated linkers by streptavidin-beads, and amplification of DNA tags. ChIPPET7.JPG
Figure 4. Pull down of biotinylated linkers by streptavidin-beads, and amplification of DNA tags.
Figure 5. Conformations of universal linkers. ChIPPET6.JPG
Figure 5. Conformations of universal linkers.

Dry-lab portion of the workflow:

PET extraction, mapping, and statistical analyses

The PET tags are extracted and mapped to the reference human genome in silico.

Identification of ChIP enriched peaks (binding sites)

Self-ligated PET are used for identifying ChIP enriched sites because they provide the most reliable mapping (20 + 20 bit/s) to the reference genome.

ChIP enrichment peak-finding algorithm

A called peak is considered a binding site if there are multiple overlapping self-ligated PETs. The false discovery rate (FDR) is determined using statistical simulations to estimate the random background of PET-derived virtual DNA overlaps, and the estimated background noise.

Filtering of repetitive DNA (affects non-specific binding)

Satellite regions and binding sites present in regions with severe structural variations are removed.

ChIP enrichment count

The numbers of self-ligation and inter-ligation PETs (within + 250 bp window) are reported at each site. The total number of self-ligated and inter-ligated PETs at a specific site is called the ChIP enrichment count.

Figure 6. PET Classification: Uniquely aligned PET sequences can be classified by whether they are derived from one DNA fragment or two DNA fragments.

Figure 6. Intra and inter-ligated PETs are clustered around TFBS when mapped to the reference human genome. ChIPPET8.JPG
Figure 6. Intra and inter-ligated PETs are clustered around TFBS when mapped to the reference human genome.

If the two tags of a PET are mapped on the same chromosome with the genomic span in the range of ChIP DNA fragments (less than 3 Kb), with expected self-ligation orientation and on the same strand, they are considered to be derived from a self-ligation of a single ChIP DNA fragment, and considered a self-ligation PET.

If a PET does not fit into these criteria, then the PET most likely resulted from a ligation product between two DNA fragments and referred to as an inter-ligation PET. The two tags of an inter-ligation PETs do not have fixed tag orientations, might not be found on the same strands, might have any genomic span, and might not map to the same chromosome.

If the two tags of an inter-ligation PET are mapped in the same chromosome but with a span > 3 Kb in any orientation, then these PETs are called intrachromosomal inter-ligation PETs.

PETs which are mapped to different chromosomes are called interchromosomal inter-ligation PETs.

Figure 7. Proposed mechanism showing how distal regulatory elements can initiate long-range chromatin interactions involving promoter regions of target genes.

Figure 7. Proposed DNA looping mechanism between distal regulatory proteins and the promoter region ChIPPET9.JPG
Figure 7. Proposed DNA looping mechanism between distal regulatory proteins and the promoter region

The interactions form DNA loop structures with multiple TFBS at the anchoring center. Small loops might package genes near the anchoring center in a tight sub-compartment, which could increase the local concentration of regulatory proteins for enhanced transcriptional activation. This mechanism might also enhance transcription efficiency, allowing RNA pol II to cycle the tight circular gene templates. The large interaction loops are more likely to link together distant genes at either end of the loop residing near anchor sites for coordinated regulation, or could separate genes in long loops to prevent their activation. Adapted from Fullwood et al. (2009).

Strengths and weaknesses

Advantages of the ChIA-PET method

Weaknesses

History

Fullwood et al. (2009), used ChIA-PET to detect and map the chromatin interaction network mediated by estrogen receptor alpha (ER-alpha) in human cancer cells. The resulting global chromatin interactome map revealed that remote ER-alpha-binding sites were also anchored to gene promoters through long-range chromatin interactions suggesting that ER-alpha functions by extensive chromatin looping in order to bring genes together for coordinated transcriptional regulation.

Analysis and software

Software typically used in a ChIA-PET experiment
SoftwareDescription
C3PETA software suite for processing ChIA-PET data. Uses a non-parametric Bayesian approach to predict chromatin interacting protein complexes.
ChIA-PET ToolA software suite for processing ChIA-PET data.
ChIA-PET2A software suite for processing ChIA-PET data. Supports data from a variety of protocols and provides quality control of data analysis.
ChIA-SigA software suite for processing ChIA-PET data using the NCHG model. ChIA-Sig web site
ELANDMaps ChIP enriched DNA fragments to the reference human genome.
MangoA software suite for processing ChIA-PET data. Completes all required steps of processing ChIA-PET datasets and provides statistical confidence estimates for interactions.
Monte Carlo SimulationUsed to estimate the false discovery rates. [11]
GenomicInteractionsAn R package for processing ChIA-PET or Hi-C data.
GIVEA programming library for creating a custom genome browser compatible with ChIA-PET or Hi-C data.
RepeatMaskerIn-silico masking of repetitive elements.

Alternatives

Chromatin immunoprecipitation (ChIP):

Chromosome conformation techniques Chromosome conformation techniques.jpg
Chromosome conformation techniques

The original ChIP method is an antibody-based technology that identify and bind proteins selectively in order to offer information regarding chromatin states and gene transcription.

Genome Architecture Mapping (GAM):

This technique eliminates a number of drawbacks associated with 3C-based techniques by collecting three-dimensional proximities between any number of genomic loci. [12]

Split-Pool Recognition of Interactions by Tag Extension (SPRITE)

SPRITE is a technique for mapping higher-order interactions in the nucleus across the genome. This approach detects interactions that occur over greater spatial distances and it allows for genome-wide detection of numerous RNA and DNA interactions that occur at the same time. [13]

ChIA-Drop

ChIA-Drop is a straightforward method for analyzing multiplex chromatin interactions using droplet-based and barcode-linked sequencing at single-molecule accuracy. Previous pairwise population-level approaches such as Hi-C and ChIA-PET are distinct from this technology. [14] [15]

Related Research Articles

Chromatin is a complex of DNA and protein found in eukaryotic cells. The primary function is to package long DNA molecules into more compact, denser structures. This prevents the strands from becoming tangled and also plays important roles in reinforcing the DNA during cell division, preventing DNA damage, and regulating gene expression and DNA replication. During mitosis and meiosis, chromatin facilitates proper segregation of the chromosomes in anaphase; the characteristic shapes of chromosomes visible during this stage are the result of DNA being coiled into highly condensed chromatin.

<span class="mw-page-title-main">DNA-binding protein</span> Proteins that bind with DNA, such as transcription factors, polymerases, nucleases and histones

DNA-binding proteins are proteins that have DNA-binding domains and thus have a specific or general affinity for single- or double-stranded DNA. Sequence-specific DNA-binding proteins generally interact with the major groove of B-DNA, because it exposes more functional groups that identify a base pair.

DNA footprinting is a method of investigating the sequence specificity of DNA-binding proteins in vitro. This technique can be used to study protein-DNA interactions both outside and within cells.

<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">Chromosome conformation capture</span>

Chromosome conformation capture techniques are a set of molecular biology methods used to analyze the spatial organization of chromatin in a cell. These methods quantify the number of interactions between genomic loci that are nearby in 3-D space, but may be separated by many nucleotides in the linear genome. Such interactions may result from biological functions, such as promoter-enhancer interactions, or from random polymer looping, where undirected physical motion of chromatin causes loci to collide. Interaction frequencies may be analyzed directly, or they may be converted to distances and used to reconstruct 3-D structures.

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.

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.

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.

<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.

<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.

<span class="mw-page-title-main">Nuclear organization</span> Spatial distribution of chromatin within a cell nucleus

Nuclear organization refers to the spatial distribution of chromatin within a cell nucleus. There are many different levels and scales of nuclear organisation. Chromatin is a higher order structure of DNA.

<span class="mw-page-title-main">Single cell epigenomics</span> Study of epigenomics in individual cells by single cell sequencing

Single cell epigenomics is the study of epigenomics in individual cells by single cell sequencing. Since 2013, methods have been created including whole-genome single-cell bisulfite sequencing to measure DNA methylation, whole-genome ChIP-sequencing to measure histone modifications, whole-genome ATAC-seq to measure chromatin accessibility and chromosome conformation capture.

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">Hi-C (genomic analysis technique)</span> Genomic analysis technique

Hi-C is a high-throughput genomic and epigenomic technique first described in 2009 by Lieberman-Aiden et al. to capture chromatin conformation. In general, Hi-C is considered as a derivative of a series of chromosome conformation capture technologies, including but not limited to 3C, 4C, and 5C. Hi-C comprehensively detects genome-wide chromatin interactions in the cell nucleus by combining 3C and next-generation sequencing (NGS) approaches and has been considered as a qualitative leap in C-technology development and the beginning of 3D genomics.

<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.

Pore-C is an emerging genomic technique which utilizes chromatin conformation capture (3C) and Oxford Nanopore Technologies' (ONT) long-read sequencing to characterize three-dimensional (3D) chromatin structure. To characterize concatemers, the originators of Pore-C developed an algorithm to identify alignments that are assigned to a restriction fragment; concatemers with greater than two associated fragments are deemed high order. Pore-C attempts to improve on previous 3C technologies, such as Hi-C and SPRITE, by not requiring DNA amplification prior to sequencing. This technology was developed as a simpler and more easily scalable method of capturing higher-order chromatin structure and mapping regions of chromatin contact. In addition, Pore-C can be used to visualize epigenomic interactions due to the capability of ONT long-read sequencing to detect DNA methylation. Applications of this technology include analysis of combinatorial chromatin interactions, the generation of de novo chromosome scale assemblies, visualization of regions associated with multi-locus histone bodies, and detection and resolution of structural variants.

References

  1. ↑ Fullwood, Melissa J.; Ruan, Yijun (2009-05-01). "ChIP-based methods for the identification of long-range chromatin interactions". Journal of Cellular Biochemistry. 107 (1): 30–39. doi:10.1002/jcb.22116. ISSN   1097-4644. PMC   2748757 . PMID   19247990.
  2. ↑ Kuo, Min-Hao; Allis, C.David (November 1999). "In Vivo Cross-Linking and Immunoprecipitation for Studying Dynamic Protein:DNA Associations in a Chromatin Environment". Methods. 19 (3): 425–433. doi:10.1006/meth.1999.0879. PMID   10579938.
  3. ↑ Dekker, Job; Rippe, Karsten; Dekker, Martijn; Kleckner, Nancy (2002-02-15). "Capturing Chromosome Conformation". Science. 295 (5558): 1306–1311. Bibcode:2002Sci...295.1306D. doi:10.1126/science.1067799. ISSN   0036-8075. PMID   11847345. S2CID   3561891.
  4. ↑ Barski, Artem; Cuddapah, Suresh; Cui, Kairong; Roh, Tae-Young; Schones, Dustin E.; Wang, Zhibin; Wei, Gang; Chepelev, Iouri; Zhao, Keji (May 2007). "High-Resolution Profiling of Histone Methylations in the Human Genome". Cell. 129 (4): 823–837. doi: 10.1016/j.cell.2007.05.009 . PMID   17512414. S2CID   6326093.
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  7. ↑ Lieberman-Aiden, Erez; van Berkum, Nynke L.; Williams, Louise; Imakaev, Maxim; Ragoczy, Tobias; Telling, Agnes; Amit, Ido; Lajoie, Bryan R.; Sabo, Peter J.; Dorschner, Michael O.; Sandstrom, Richard (2009-10-09). "Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome". Science. 326 (5950): 289–293. Bibcode:2009Sci...326..289L. doi:10.1126/science.1181369. ISSN   0036-8075. PMC   2858594 . PMID   19815776.
  8. 1 2 Fullwood, Melissa J.; Liu, Mei Hui; Pan, You Fu; Liu, Jun; Xu, Han; Mohamed, Yusoff Bin; Orlov, Yuriy L.; Velkov, Stoyan; Ho, Andrea; Mei, Poh Huay; Chew, Elaine G. Y. (November 2009). "An oestrogen-receptor-α-bound human chromatin interactome". Nature. 462 (7269): 58–64. Bibcode:2009Natur.462...58F. doi:10.1038/nature08497. ISSN   0028-0836. PMC   2774924 . PMID   19890323.
  9. ↑ Li, Guoliang; Ruan, Xiaoan; Auerbach, Raymond K.; Sandhu, Kuljeet Singh; Zheng, Meizhen; Wang, Ping; Poh, Huay Mei; Goh, Yufen; Lim, Joanne; Zhang, Jingyao; Sim, Hui Shan (2012-01-20). "Extensive Promoter-Centered Chromatin Interactions Provide a Topological Basis for Transcription Regulation". Cell. 148 (1): 84–98. doi:10.1016/j.cell.2011.12.014. ISSN   0092-8674. PMC   3339270 . PMID   22265404.
  10. ↑ Downes, Damien J.; Beagrie, Robert A.; Gosden, Matthew E.; Telenius, Jelena; Carpenter, Stephanie J.; Nussbaum, Lea; De Ornellas, Sara; Sergeant, Martin; Eijsbouts, Chris Q.; Schwessinger, Ron; Kerry, Jon (2021-01-22). "High-resolution targeted 3C interrogation of cis-regulatory element organization at genome-wide scale". Nature Communications. 12 (1): 531. Bibcode:2021NatCo..12..531D. doi:10.1038/s41467-020-20809-6. ISSN   2041-1723. PMC   7822813 . PMID   33483495.
  11. ↑ Monte Carlo method
  12. ↑ Beagrie, Robert A.; Scialdone, Antonio; Schueler, Markus; Kraemer, Dorothee C. A.; Chotalia, Mita; Xie, Sheila Q.; Barbieri, Mariano; de Santiago, Inês; Lavitas, Liron-Mark; Branco, Miguel R.; Fraser, James (March 2017). "Complex multi-enhancer contacts captured by genome architecture mapping". Nature. 543 (7646): 519–524. Bibcode:2017Natur.543..519B. doi:10.1038/nature21411. ISSN   1476-4687. PMC   5366070 . PMID   28273065.
  13. ↑ Quinodoz, Sofia A.; Ollikainen, Noah; Tabak, Barbara; Palla, Ali; Schmidt, Jan Marten; Detmar, Elizabeth; Lai, Mason M.; Shishkin, Alexander A.; Bhat, Prashant; Takei, Yodai; Trinh, Vickie (2018-07-26). "Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus". Cell. 174 (3): 744–757.e24. doi:10.1016/j.cell.2018.05.024. ISSN   0092-8674. PMC   6548320 . PMID   29887377. S2CID   47013513.
  14. ↑ Zheng, Meizhen; Tian, Simon Zhongyuan; Capurso, Daniel; Kim, Minji; Maurya, Rahul; Lee, Byoungkoo; Piecuch, Emaly; Gong, Liang; Zhu, Jacqueline Jufen; Li, Zhihui; Wong, Chee Hong (February 2019). "Multiplex chromatin interactions with single-molecule precision". Nature. 566 (7745): 558–562. Bibcode:2019Natur.566..558Z. doi:10.1038/s41586-019-0949-1. ISSN   1476-4687. PMC   7001875 . PMID   30778195.
  15. ↑ Koch, Linda (April 2019). "Getting the drop on chromatin interaction". Nature Reviews Genetics. 20 (4): 192–193. doi:10.1038/s41576-019-0103-9. ISSN   1471-0064. PMID   30783222. S2CID   67752274.
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