Guideline for Evaluating Chromosomal Looping using enChIP
Product Name
enChIP Kit
pAM_gRNA Vector
pAM_dCas9 Vector
FuGENE® HD Transfection Reagent

Format16 rxns
10 µg
10 µg
0.2 mlCatalog No.
53125
53121
53122
32042

The following guideline is designed for use with Active Motif’s enChIP Kit (Catalog No. 53125) and Active Motif’s deactivated Cas9 (dCas9)
expression construct pAM_dCas9 Vector (Catalog No. 53122) for identification of cis- and trans-chromosomal interactions. The pAM_gRNAVector (Catalog No. 53121) may be used for cloning the 20 bp target sequence, or researchers may utilize their own gRNA constructs. The
target sequence must be expressed in combination with the AM-tagged dCas9 protein. Please refer to the vector data sheets and theenChIP Kit manual for detailed instructions on cloning and expression.

Introduction
Engineered DNA-binding molecule-mediated chromatin immunoprecipitation (enChIP) was first described in 2013 by Toshitsugu Fujita
and Hodaka Fujii1, 2. enChIP was designed to purify specific genomic regions using the CRISPR/Cas9 system. A 20 bp target sequence iscloned into a single guide RNA vector expressing a fusion of the crRNA-tracrRNA sequence (5´side to identify the DNA target sequence
and a 3´duplex RNA structure to bind Cas9). When the gRNA is expressed in combination with a tagged deactivated Streptococcus pyogenes Cas9 (dCas9) protein, specific genomic regions can be immunoprecipitated using an antibody directed against the tag. By using acatalytically inactive form of Cas9 endonuclease, double-stranded breaks are not introduced and DNA, RNA and proteins associated withthe target sequence can be recovered1-6. With Active Motif’s enChIP Kit, simply clone your 20 nucleotide target sequence into Active
Motif’s gRNA or dCas9 expression vectors. Following transfection and expression of the gRNA and AM-tagged dCas9, cells are formaldehyde fixed, lysed and the chromatin is fragmented by sonication. An antibody directed against the AM-tag is used to enrich for genomic
sequences bound by the gRNA/dCas9 complex. Following immunoprecipitation, DNA can be analyzed by qPCR or NGS to identify theenriched genomic regions.
Chromosomal looping is an epigenetic mechanism by which two (or more) genomic loci are brought into close proximity by DNA binding
proteins and their cofactors for the purpose of long-range gene regulation. Looping events play a role in bringing distal regulatory elements such as enhancers into functional proximity of their target promoters, or to separate active regions of the genome from repressedregions via CTCF-mediated insulator elements7. Current methods to identify such looping events, namely chromatin conformation
capture (3C) and its derivatives (4C, 5C, Hi-C)8, have shaped the way we understand 3D organization of the nucleus, and how it regulates
global gene expression.
The Fujii lab recently described a procedure for using enChIP to identify genomic regions interacting with the 5´HS5 locus in K562
chronic myelogenous leukemia cells6. Here we describe a parallel approach for using enChIP for the de novo identification of cis- andtrans-chromosomal looping events with a single genomic locus.

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Experimental Set-up
In order to confidently use enChIP to determine genomic regions interacting with a locus of interest, a minimum of two specific gRNAs
must be designed against the target locus, with each gRNA being used independently in its own transfection. Additionally, a no gRNA
control experiment should be performed to identify genomic regions that interact with dCas9 non-specifically. Detailed instructions fordesigning and cloning gRNAs into Active Motif’s expression vectors can be found in the enChIP manual at www.activemotif.com/enchip.
In designing gRNAs, take caution not to target genomic loci containing a conserved transcription factor binding site since that region may
be blocked by DNA binding protein preventing gRNA binding and/or because blocking a protein binding site may prevent binding of that
protein to biologically functional locus, which may result in functional dysregulation of cellular biology. It is also recommended to avoid
designing gRNAs downstream of a transcription start site (TSS) as this may interfere with expression of that gene via a mechanism known as
CRISPRi9.

Figure 1:  UCSC genome browser snapshot showing a CTCF peak in HEK293T cells.
The black and green bar at the bottom of the image represents a CTCF peak called by the ENCODE consortium, with the green segment
representing the genomic region containing the consensus DNA motif recognized by CTCF. Immediately below the peak, four blackboxes represent the locations of four gRNAs (gRNA1-4) targeting a 200 bp region surrounding the CTCF binding site on chromosome 19.
To prevent interference of CTCF binding, all four gRNAs were designed not to overlap with the CTCF recognition motif or TSS.

To ensure that the experiment is designed to functionally characterize chromosomal looping of a single locus, design the two or moregRNA sequences within a relatively short genomic interval. It is recommended that gRNA target sites bind within the average fragment
size of the chromatin, or within approximately 500-1,000 bp of each other. Each gRNA will represent a unique sequence targeting the same
genomic interval. Each gRNA sequence is then independently cloned and expressed according to the recommendations provided in theenChIP Kit manual. Figure 1, shown above, displays the locations of four gRNAs designed to target a 200 bp region surrounding a CTCF binding site on chromosome 19 (5,804,115–5,804,209) in HEK293T cells.

Chromosomal Looping Experimental Design• Design 2 or more gRNAs (within 0.5-1 kb of each other) targeting different
20 bp sequences of the same genomic locus• Avoid sequences containing conserved transcription factor binding sites• Avoid sequences downstream of a transcriptional start site• Include a no gRNA negative control to identify and eliminate non-specific dCas9
protein binding during data analysis• Following data analysis, design the reciprocal experiment to verify each potential
chromosomal looping site

Data Analysis – Distinction Between Chromosomal Looping and Off-target Binding
After aligning raw sequencing reads to the appropriate genome, we recommend calling peaks using MACS2 (https://github.com/taoliu/MACS/) on each individual enChIP experiment using the no gRNA negative control reaction as the control or ‘input’ to remove any peaks
that represent non-specific interactions of the dCas9 protein alone.
macs2 callpeak –t enChIP_experiment.bam –c enChIP_No_gRNA_Control.bam –g (genomesize of ‘hs’) ––outdir enChIP/MACS/ –n enChIP_experiment_name –p 1e-7
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Peaks called on each experiment represent regions of the genome that interact with the dCas9/gRNA complex. Expected peak numbers
range from several dozen to a couple of thousand peaks per experiment. In addition to the targeted genomic locus the peaks represent
potential chromosomal interactions and off-target gRNA binding sites that are enriched relative to the no gRNA control. To distinguishbetween looping and off-target peaks, we take advantage of having targeted the locus of interest with multiple independent gRNAs. EachgRNA has a unique DNA binding context, so it is expected that any differences between experiments targeting the same genomic locus
represent off-target binding, and that any peaks common between experiments represent potential cis- and trans-interacting regions.

Figure 2:  Identification of potential looping sites using an experimental overlap strategy.
Due to the fact that individual gRNAs recognize different 20 bp sequences in the genome, it isexpected that off-target binding sites will differ between experiments. Each gRNA will have aunique set of off-target binding sites. Therefore, any peaks found in common between experiments performed with different gRNAs targeting the same genomic locus are expected to bepotential looping sites rather than off-target binding.

To identify common peaks, we recommend using the ‘mergepeaks’ function in HOMER10.
(http://homer.salk.edu/homer/)mergePeaks –venn outputFile.txt –prefix OverlappingRegions gRNA1peakFile.bed
gRNA2peakFile.bed

The resulting text file contains an all-by-all matrix for each peak file being compared enumerating peaks found in common-between or
unique-to each data set. Using the ‘-prefix’ option will result in the generation of new peak files containing overlapping and unique regions
identified in the overlap, and the name provided after ‘-prefix’ will be appended onto the beginning of each new peak file name. The resulting list of overlapping peaks represents a set of potential looping sites with your target locus.

Verification of Potential Looping Sites
Peaks identified in common between all independent gRNA experiments targeting the same locus (as described above) represent a condensed list of potential chromosomal interactions. enChIP-seq can now be employed to verify these interactions in a reciprocal experiment. If a genuine interaction between the two chromosomal loci exists, designing two or more gRNAs to any of these potential looping
regions should yield a common peak at the original target site as depicted in Figure 3.

Figure 3:  A strategy for validating potential chromosomal looping sites.
Top panel:  Targeting a single genomic locus with several independent gRNAs yields potential looping sites.
Bottom panel:  To verify these potential looping events, several independent gRNAs are designed for each potential looping locus.
Identification of the original target site as a peak in this reciprocal experiment serves as verification of this chromosomal interaction.

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CTCF plays a role in the 3D organization of chromatin by binding to insulator elements, which separate active regions of the genome from
repressed regions. CTCF-bound insulator elements have been shown to form clusters of chromosomal looping events7. To determine the extent to which a specific CTCF binding site plays a role in chromosomal looping, four gRNAs were designed to target a binding site on chromosome 19 as shown in FIGURE 4. Each gRNA gave a specific peak at the target site (Bottom left panel) as well as several peaks distributed
across the genome. An overlap of all four data sets yielded 520 peaks in common. The verification of one such regions, the promoter of theCARM1 gene on chromosome 19 is shown in the bottom right panel. Each gRNA targeting the CTCF binding site yielded a distinct peak at
the CARM1 promoter, and when a gRNA was designed to target the CARM1 promoter, a peak was detected at the original CTCF binding site.

Figure 4:  Identification and verification of looping events with a CTCF binding site on chromosome 19.
UCSC Genome Browser snapshot showing the CTCF peak in HEK293T cells (black mound). Four separate gRNAs were designed to target
this locus within a 200 bp region. Below the UCSC track are the enChIP-seq peaks identified for each gRNA at the target locus compared
to a no gRNA control. The right panel shows a looping site identified in each independent experiment targeting the CTCF binding site. AgRNA targeting this site yielded a peak at the original CTCF binding site, verifying the looping event (lower blue track).

As we have shown here, enChIP provides the ability to identify chromosomal looping events with a genomic locus of interest. We find thismethod to be analogous to existing methods for identifying chromosomal interactions and encourage researchers to cross-validate theirexperiments using these methods. For an in-depth guide on how to use 4C technology to identify chromosomal looping events, pleaserefer to the Splinter, E. et al. Methods paper11.

References
1.

2.
3.
4.
5.

Fujita T and Fujii H: Efficient isolation of specific genomic regions and identification of associated proteins by engineered DNAbinding molecule-mediated chromatin immunoprecipitation (enChIP) using CRISPR. Biochem. Biophys. Res. Commun. 2013,439(1):  132–136.
Fujita T, Asano Y, Ohtsuka J, Takada Y, Saito K, Ohki R, Fujii H: Identification of telomere-associated molecules by engineered DNAbinding molecule-mediated chromatin immunoprecipitation (enChIP). Sci. Rep. 2013, 3:  3171.
Fujita T and Fujii H: Identification of Proteins Associated with an IFNg-Responsive Promoter by a Retroviral Expression Systemfor enChIP Using CRISPR. PLoS ONE 2014, 9(7):  e103084.
Fujita T, Yuno M, Okuzaki D, Ohki R, Fujii H: Identification of Non-Coding RNAs Associated with Telomeres Using a Combination ofenChIP and RNA Sequencing. PLoS ONE 2015, 10(4):  e0123387.
Fujii H and Fujita T: Isolation of Specific Genomic Regions and Identification of Their Associated Molecules by Engineered DNABinding Molecule-Mediated Chromatin Immunoprecipitation (enChIP) Using the CRISPR System and TAL Proteins. Int. J. Mol. Sci.
2015, 16(9):  21802–21812.
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6. Fujita T, Yuno M, Suzuki Y, Sugano S, Fujii H: Identification of physical interactions between genomic regions by enChIP-Seq.
bioRxiv 2016:  036160.
7. Rao SSP, Huntley MH, Durand NC, Stamenova EK, Bochkov ID, Robinson JT, Sanborn AL, Machol I, Omer AD, Lander ES, Aiden EL: A 3D
map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 2014, 159(7):1665–1680.
8. de Wit E, de Laat W: A decade of 3C technologies: insights into nuclear organization. Genes Dev 2012, 26(1):  11–24.
9. Qi LS, Larson MH, Gilbert LA, Doudna JA, Weissman JS, Arkin AP, Lim WA: Repurposing CRISPR as an RNA-guided platform forsequence-specific control of gene expression. Cell 2013, 152(5):  1173–1183.
10. Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK: Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Molecular Cell 2010,38(4):  576–589.
11. Splinter E, de Wit E, van de Werken HJG, Klous P, de Laat W: Determining long-range chromatin interactions for selected genomic
sites using 4C-seq technology: From fixation to computation. Methods 2012, 58(3):  221–230.

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