We would like to thank Denis Lafontaine for protocol development and Sergey Venev for Bioinformatic assistance. This work was supported by a grant from the National Institutes of Health Common Fund 4D Nucleome Program to J.D. (U54-DK107980, UM1-HG011536). J.D. is an investigator of the Howard Hughes Medical Institute.
This article is subject to HHMI&#39;s Open Access to Publications policy. HHMI lab heads have previously granted a nonexclusive CC BY 4.0 license to the public and a sublicensable license to HHMI in their research articles. Pursuant to those licenses, the author-accepted manuscript of this article can be made freely available under a CC BY 4.0 license immediately upon publication.

<ol>
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The authors have no conflicts of interest to disclose.

Critical steps for cell handling 
Although it is possible to use a lower number of input cells, this protocol has been optimized for ~5 &#215; 106 cells per sequencing lane (~400 M reads) to ensure proper complexity after deep sequencing. Cells are best counted prior to fixation. For the generation of ultradeep libraries, we generally multiply the number of lanes (and cells) until the desired read-depth is reached. For optimal fixation, serum-containing medium should be replaced with PBS prior to FA fixation, and fixative solutions should be added immediately and without concentration gradients15,22. For cell harvesting, scraping is preferred over trypsinization, because the transition from a flatter to a spherical shape after trypsinization could affect the nuclear conformation. After the addition of DSG, loose and clumpy cell pellets are easily lost. Be careful when handling cells at this stage and add up to 0.05% BSA to decrease clumping.
Modifications to the method 
This protocol was developed using human cells17. Yet, based on experience with chromosome conformation capture, this protocol should work for most eukaryotic cells. For a significantly lower input (~1 &#215; 106 cells), we advise using half the volumes for the lysis and conformation capture procedures [steps 2.1-2.4]. This would also allow DNA isolation [step 2.5] to be performed in a tabletop centrifuge with 1.7 mL tubes, which could improve pelleting for low DNA concentrations. The quantification of DNA (step 2.6.6) will indicate how to proceed. For low amounts of isolated DNA (1-5 &#181;g), we suggest skipping the size selection (step 3.3) and proceed with biotin removal after reducing the volume from 130 &#181;L to ~45 &#181;L with a CFU.
This protocol was developed specifically to ensure high-quality data after subsequent crosslinking with FA and DSG and digestion with DpnII and DdeI. However, alternative crosslinking strategies such as FA followed by EGS (ethylene glycol bis(succinimidyl succinate)), which is also used in ChIP-seq23 and ChIA-PET24, might work equally well17. Similarly, different enzyme combinations, such as DpnII and HinfI18 or MboI, MseI, and NlaIII19 can be used for digestion. When adapting enzyme combinations, be sure to use biotinylated nucleotides that can fill in the specific 5&#39; overhangs and use the most optimal buffers for each cocktail. DpnII comes with its own buffer and the enzyme manufacturer recommends a specific buffer for DdeI digestion. Yet, for the double-digestion with DpnII and DdeI in this protocol, Restriction Buffer is recommended because it is rated at 100% activity for both enzymes.
Troubleshooting conformation capture 
The three key steps in chromosome conformation capture: crosslinking, digestion, and religation have all been performed before the results can be visualized on gel. To determine the quality of each of these three steps and discern where problems could have arisen, aliquots before (CI) and after digestion (DC) are taken and loaded on the gel along with the ligated Hi-C sample (Figure 2). This gel is used to determine the quality of the Hi-C sample and whether it will be worth continuing the protocol. Without the CI and DC, it is difficult to pinpoint potential suboptimal step(s). It is worth noting that suboptimal ligation could be due to a problem in the ligation itself, the fill-in, or a problem with crosslinking. To troubleshoot crosslinking, be sure not to use more than 1 &#215; 107 cells per library and start with fresh crosslinking reagents and clean cells (i.e., rinsed with PBS). For ligation, make sure cells and ligation mixture are kept on ice. Add T4 DNA ligase just before the 4 h incubation at 16 &#176;C and mix well.
Troubleshooting library preparation 
If more than 10 PCR cycles are needed or no PCR product can be seen on gel after PCR titration (Figure 4), there are a few options to save the Hi-C sample. Working back from the PCR titration, the first option is to try the PCR again. If there is still not enough product, it is possible to attempt another round of A-tailing and adapter ligation (step 3.6) after washing the beads twice with 1x TLE buffer. After this additional A-tailing and adapter ligation, one can proceed to the PCR titration as before. If there is still no product, the last option is to resonicate the 0.8x fraction from step 3.3 and proceed from there.
Limitations and advantages of Hi-C3.0 
It is important to realize that Hi-C is a population-based method that captures the average frequency of interactions between pairs of loci in the cell population. Some computational analyses are designed to disentangle combinations of conformations from a population25, but in principle, Hi-C is blind to differences between cells. Although it is possible to perform single-cell Hi-C26,27 and computational inferences can be made28, single-cell Hi-C is not suitable for obtaining ultrahigh-resolution 3C information. An additional limitation of Hi-C is that it only detects pairwise interactions. To detect multicontact interactions, one can either use frequent cutters combined with short-read sequencing (Illumina)16 or perform multicontact 3C29 or 4C30, using long-read sequencing from PacBio or Oxford Nanopore platforms. Hi-C derivatives to specifically detect contacts between and along sister chromatids have also been developed31,32.
Although Hi-C19 and Micro-C33 can be used to generate contact maps at subkilobase resolutions, both require a large amount of sequencing reads and this can become a costly undertaking. To get to similar or even higher resolution without the costs, enrichment for specific genomic regions (capture-C34) or specific protein interactions (ChiA-PET35, PLAC-seq36, Hi-ChIP37) can be applied. The strength and downside of these enrichment applications is that only a limited number of interactions are sampled. With such enrichments, the global aspect of Hi-C (and the option of global normalization) is lost.
Importance and potential applications of Hi-C3.0 
This protocol was designed to enable high-resolution, ultradeep 3C while simultaneously detecting large-scale folding features such as TADs and compartments17 (Figure 6). This protocol starts with 5 &#215; 106 cells per tube for each Hi-C library, which should be more than enough material to sequence one or two lanes on a flow cell to obtain up to 1 billion paired-end reads. For ultradeep sequencing, multiple tubes of 5 &#215; 106 cells should be prepared, depending on the number of mapped reads and PCR duplicates. At the highest resolution (&#60;1 kb), looping interactions are mostly found between CTCF sites, but promoter-enhancer interactions can also be detected. Readers can refer to Akgol Oksuz et al.17 for a detailed description of the data analysis.

Chromosome conformation capture has been used since 20021. Fundamentally, every conformation capture variant relies on the fixation of DNA-protein and protein-protein interactions to preserve 3D chromatin organization. This is followed by DNA fragmentation, usually by restriction digestion, and, finally, religation of nearby DNA ends to convert spatially proximal loci into unique covalent DNA sequences. Initial 3C protocols used PCR to sample specific, &#34;one-to-one&#34; interactions. Subsequent 4C assays allowed the detection of &#34;one-to-all&#34; interactions2, while 5C detected &#34;many-to-many&#34; interactions3. Chromosome conformation capture came to full fruition after implementing next-generation, high-throughput sequencing (NGS), which allowed detection of &#34;all-to-all&#34; genomic interactions using, genome-wide Hi-C4 and comparable techniques such as 3C-seq5, TCC6 and Micro-C7,8 (see also review by Denker and De Laat9).
In Hi-C, biotinylated nucleotides are used to mark 5&#8242; overhangs after digestion and before ligation (Figure 1). This allows for the selection of properly digested and religated fragments using streptavidin-coated beads, setting it apart from GCC10. An important update to the Hi-C protocol was implemented by Rao et al.11, who performed the digestion and religation in intact nuclei (i.e., in situ) to reduce spurious ligation products. Moreover, substituting HindIII digestion with MboI (or DpnII) digestion reduced the fragment size and increased the resolution potential of Hi-C. This increase allowed the detection of relatively small-scale structures and a more precise genomic localization of points of contact, such as DNA loops between small cis-elements, e.g., loops between CTCF-bound sites generated by loop extrusion11,12. However, this potential comes at a cost. First, a two-fold increase in resolution requires a four-fold (22) increase in sequencing reads13. Second, the small fragment sizes increase the possibility of mistaking undigested neighboring fragments for digested and religated fragments14. As mentioned, in Hi-C, digested and religated fragments differ from undigested fragments by the presence of biotin at the ligation junction. However, proper biotin removal from unligated ends is required to assure that only ligation junctions are pulled down14,15.
With the decreasing cost of NGS, it becomes feasible to study chromosome folding in greater detail. To decrease the size of DNA fragments, and thereby increase resolution, the Hi-C protocol can be adapted to use more frequently cutting restriction enzymes16 or to use combinations of restriction enzymes17,18,19. Alternatively, MNase7,8 in Micro-C and DNase in DNase Hi-C20 can be titrated to achieve optimal digestion.
A recent systematic evaluation of the fundamentals of 3C methods showed that the detection of chromosome folding features at every length scale greatly improved with sequential crosslinking with 1% FA followed by 3 mM DSG17. Furthermore, Hi-C with HindIII digestion was the best option for detecting large-scale folding features, such as compartments, and that Micro-C was superior at detecting small-scale folding features such as DNA loops. These results led to the development of a single, high-resolution &#34;Hi-C 3.0&#34; strategy, that uses the combination of FA and DSG crosslinkers followed by double digestion with DpnII and DdeI endonucleases21. Hi-C 3.0 provides an effective strategy for general use because it accurately detects folding features across all length scales17. The experimental portion of the Hi-C 3.0 protocol is detailed here and typical results that can be expected after sequencing are shown.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64001/64001fig01.jpg" /> 
Figure 1: Hi-C procedure in six steps. Cells are fixed first with FA, and then DSG (1). Then, lysis precedes a double digestion with DdeI and DpnII (2). Biotin is added by overhang fill-in and proximal blunted ends are ligated (3) before DNA purification (4). Biotin is removed from unligated ends before sonication and size selection (5). Finally, pull-down of biotin allows for adapter ligation and library amplification by PCR (6). Abbreviations: FA = formaldehyde; DSG = disuccinimidyl glutarate; B = Biotin. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/64001/64001fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1 kb Ladder</td>
			<td>New England Biolabs</td>
			<td>N3232L</td>
			<td></td>
		</tr>
		<tr>
			<td>Agarose</td>
			<td>Invitrogen</td>
			<td>16500100</td>
			<td></td>
		</tr>
		<tr>
			<td>Agencourt AMPure XP magnetic beads , 60 mL</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td></td>
		</tr>
		<tr>
			<td>Amicon Ultra-0.5 Centrifugal Filter Unit (CFU)</td>
			<td>EMD Millipore</td>
			<td>UFC500396</td>
			<td></td>
		</tr>
		<tr>
			<td>Annealing Buffer (5x)</td>
			<td>See recipe in supplemental materials</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>ATP 10 mM</td>
			<td>ThermoFisher</td>
			<td>R0441</td>
			<td></td>
		</tr>
		<tr>
			<td>Avanti J-25i High Speed Refrigerated ultra-centrifuge</td>
			<td>Beckman Coulter</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>beckman ultracentrifuge tube 35 mL</td>
			<td>Beckman Coulter</td>
			<td>357002</td>
			<td></td>
		</tr>
		<tr>
			<td>Binding Buffer (2x)</td>
			<td>See recipe in supplemental materials</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>biotin-14-dATP 0.4 mM</td>
			<td>Invitrogen</td>
			<td>19524-016</td>
			<td></td>
		</tr>
		<tr>
			<td>BSA 10 mg/mL</td>
			<td>New England Biolabs</td>
			<td>B9000S</td>
			<td>dilute from 20 mg/mL</td>
		</tr>
		<tr>
			<td>Cell scraper</td>
			<td>Falcon</td>
			<td>353089</td>
			<td></td>
		</tr>
		<tr>
			<td>Cell scraper</td>
			<td>Corning</td>
			<td>3008</td>
			<td></td>
		</tr>
		<tr>
			<td>Conical polypropylene tubes 50 mL</td>
			<td>Denville</td>
			<td>C1062-P</td>
			<td></td>
		</tr>
		<tr>
			<td>Conical tube 15 mL</td>
			<td>Denville</td>
			<td>C1017-P</td>
			<td></td>
		</tr>
		<tr>
			<td>Covaris micro tube AFA fiber with snap-cap 130 &#181;L</td>
			<td>Covaris</td>
			<td>520045/520077</td>
			<td></td>
		</tr>
		<tr>
			<td>Covaris Sonicator</td>
			<td>Covaris</td>
			<td>E220/E220evolution/M220</td>
			<td></td>
		</tr>
		<tr>
			<td>Culture flask 175 cm2</td>
			<td>Falcon</td>
			<td>353112</td>
			<td></td>
		</tr>
		<tr>
			<td>Culture plates 150 mm x 25 mm</td>
			<td>Corning</td>
			<td>430599</td>
			<td></td>
		</tr>
		<tr>
			<td>dATP 1 mM</td>
			<td>Invitrogen</td>
			<td>56172</td>
			<td></td>
		</tr>
		<tr>
			<td>dATP 10 mM</td>
			<td>Invitrogen</td>
			<td>56172</td>
			<td></td>
		</tr>
		<tr>
			<td>dCTP 10 mM</td>
			<td>Invitrogen</td>
			<td>56173</td>
			<td></td>
		</tr>
		<tr>
			<td>DdeI</td>
			<td>New England Biolabs</td>
			<td>R0175L</td>
			<td></td>
		</tr>
		<tr>
			<td>dGTP 10 mM</td>
			<td>Invitrogen</td>
			<td>56174</td>
			<td></td>
		</tr>
		<tr>
			<td>DMSO</td>
			<td>Sigma</td>
			<td>D2650-5x10ML</td>
			<td></td>
		</tr>
		<tr>
			<td>dNTP mix 25 mM</td>
			<td>Invitrogen</td>
			<td>10297117</td>
			<td></td>
		</tr>
		<tr>
			<td>Dounce homogenizer</td>
			<td>DWK Life Sciences</td>
			<td>8853010002/8853030002</td>
			<td></td>
		</tr>
		<tr>
			<td>DPBS</td>
			<td>Gibco</td>
			<td>14190-144</td>
			<td></td>
		</tr>
		<tr>
			<td>DpnII</td>
			<td>New England Biolabs</td>
			<td>R0543M</td>
			<td></td>
		</tr>
		<tr>
			<td>DSG</td>
			<td>ThermoScientific</td>
			<td>20593</td>
			<td></td>
		</tr>
		<tr>
			<td>dTTP 10 mM</td>
			<td>Invitrogen</td>
			<td>56175</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethanol 70%</td>
			<td>Fisher</td>
			<td>A409-4</td>
			<td>Diluted from 100%</td>
		</tr>
		<tr>
			<td>Ethidium Bromide</td>
			<td>Fisher</td>
			<td>BP1302-10</td>
			<td></td>
		</tr>
		<tr>
			<td>Formaldehyde (37%)</td>
			<td>Fisher</td>
			<td>BP531-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Gel loading dye (6x )</td>
			<td>New England Biolabs</td>
			<td>B7024S</td>
			<td></td>
		</tr>
		<tr>
			<td>Glycine in ultrapure water 2.5 M</td>
			<td>Sigma</td>
			<td>G8898-1KG</td>
			<td></td>
		</tr>
		<tr>
			<td>HBSS</td>
			<td>Gibco</td>
			<td>14025-092</td>
			<td></td>
		</tr>
		<tr>
			<td>Igepal CA-630 detergent</td>
			<td>MP Biomedicals</td>
			<td>198596</td>
			<td></td>
		</tr>
		<tr>
			<td>Klenow DNA polymerase 5 U/&#181;L</td>
			<td>New England Biolabs</td>
			<td>M0210L</td>
			<td></td>
		</tr>
		<tr>
			<td>Klenow Fragment 3--&#62;5&#8217; exo-, 5 U/&#181;L</td>
			<td>New England Biolabs</td>
			<td>M0212L</td>
			<td></td>
		</tr>
		<tr>
			<td>ligation buffer (10x)</td>
			<td>New England Biolabs</td>
			<td>B7203S</td>
			<td></td>
		</tr>
		<tr>
			<td>Liquid nitrogen</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>LoBind microcentrifuge tube 1.7 mL</td>
			<td>Eppendorf</td>
			<td>22431021</td>
			<td></td>
		</tr>
		<tr>
			<td>Low Molecular Weight DNA Ladder</td>
			<td>New England Biolabs</td>
			<td>N3233L</td>
			<td></td>
		</tr>
		<tr>
			<td>Lysis buffer</td>
			<td>See recipe in supplemental materials</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Magnetic Particle separator</td>
			<td>ThermoFisher</td>
			<td>12321D</td>
			<td></td>
		</tr>
		<tr>
			<td>Microfuge tubes 1.7 mL</td>
			<td>Axygen</td>
			<td>MCT-175-C</td>
			<td></td>
		</tr>
		<tr>
			<td>MyOne Streptavidin C1 beads</td>
			<td>Invitrogen</td>
			<td>65001</td>
			<td></td>
		</tr>
		<tr>
			<td>NEBuffer 2.1 (10x)</td>
			<td>New England Biolabs</td>
			<td>B7002S</td>
			<td></td>
		</tr>
		<tr>
			<td>NEBuffer 3.1 (10x)</td>
			<td>New England Biolabs</td>
			<td>B7203S</td>
			<td></td>
		</tr>
		<tr>
			<td>PBS</td>
			<td>Gibco</td>
			<td>70013-032</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR (strip) tubes</td>
			<td>Biorad</td>
			<td>TBS0201/ TCS0803</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR thermocycler</td>
			<td>Biorad</td>
			<td>T100</td>
			<td></td>
		</tr>
		<tr>
			<td>Pfu Ultra II Buffer (10x)</td>
			<td>Agilent</td>
			<td></td>
			<td>Comes with Pfu Ultra</td>
		</tr>
		<tr>
			<td>PfuUltra II Fusion HS DNA Polymerase&#160;</td>
			<td>Agilent</td>
			<td>600674</td>
			<td></td>
		</tr>
		<tr>
			<td>Phase lock tube 15 mL</td>
			<td>Qiagen</td>
			<td>129065</td>
			<td></td>
		</tr>
		<tr>
			<td>Phase lock tubes 2 mL</td>
			<td>Qiagen</td>
			<td>129056</td>
			<td></td>
		</tr>
		<tr>
			<td>Phenol:chloroform:isoamyl alcohol</td>
			<td>Invitrogen</td>
			<td>15593-049</td>
			<td></td>
		</tr>
		<tr>
			<td>Protease inhibitor cocktail</td>
			<td>ThermoFisher</td>
			<td>78440</td>
			<td></td>
		</tr>
		<tr>
			<td>Proteinase K in ultrapure water 10 mg/mL</td>
			<td>Invitrogen</td>
			<td>25530-031</td>
			<td></td>
		</tr>
		<tr>
			<td>Refrigerated Centrifuge</td>
			<td>Eppendorf</td>
			<td>5810R</td>
			<td></td>
		</tr>
		<tr>
			<td>RNase A, DNase and protease-free 10 mg/mL</td>
			<td>Thermo Scientific</td>
			<td>EN0531</td>
			<td></td>
		</tr>
		<tr>
			<td>Rotator</td>
			<td>Argos technologies</td>
			<td>EW-04397-40 or rocking platform</td>
			<td></td>
		</tr>
		<tr>
			<td>SDS 1%</td>
			<td>Fisher</td>
			<td>BP13111</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium acetate pH = 5.2, 3 M</td>
			<td>Sigma</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sub-Cell GT Horizontal Electrophoresis System</td>
			<td>Biorad</td>
			<td>1704401</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA ligase 1 U/&#181;L</td>
			<td>Invitrogen</td>
			<td>100004817</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA polymerase</td>
			<td>New England Biolabs</td>
			<td>M0203L</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA polymerase</td>
			<td>New England Biolabs</td>
			<td>M0203L</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA polymerase 3 U/&#181;L</td>
			<td>New England Biolabs</td>
			<td>M0203L</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 ligation buffer (5x)</td>
			<td>Invitrogen</td>
			<td>Y90001</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 polynucleotide kinase 10 U/&#181;L</td>
			<td>New England Biolabs</td>
			<td>M0201L</td>
			<td></td>
		</tr>
		<tr>
			<td>Tabletop centrifuge</td>
			<td>Eppendorf</td>
			<td>5425</td>
			<td></td>
		</tr>
		<tr>
			<td>TBE buffer</td>
			<td>See recipe in supplemental materials</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Tris Low EDTA Buffer (TLE)</td>
			<td>See recipe in supplemental materials</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100 (10%)</td>
			<td>Sigma</td>
			<td>93443</td>
			<td></td>
		</tr>
		<tr>
			<td>Truseq adapter oligos</td>
			<td>Integrated DNA Technologies (IDT))</td>
			<td>https://www.idtdna.com/site/order/oligoentry</td>
			<td>250 nmole and HPLC purified</td>
		</tr>
		<tr>
			<td>Tween 20 detergent</td>
			<td>Fisher</td>
			<td>9005-64-5</td>
			<td></td>
		</tr>
		<tr>
			<td>Tween Wash Buffer</td>
			<td>See recipe in supplemental materials</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Vortex</td>
			<td>Scientific Industries</td>
			<td>(G560)SI-0236</td>
			<td></td>
		</tr>
	</tbody>
</table>

capturing chromosome conformation across length scales

Chromosome conformation capture (3C) is used to detect three-dimensional chromatin interactions. Typically, chemical crosslinking with formaldehyde (FA) is used to fix chromatin interactions. Then, chromatin digestion with a restriction enzyme and subsequent religation of fragment ends converts three-dimensional (3D) proximity into unique ligation products. Finally, after reversal of crosslinks, protein removal, and DNA isolation, DNA is sheared and prepared for high-throughput sequencing. The frequency of proximity ligation of pairs of loci is a measure of the frequency of their colocalization in three-dimensional space in a cell population.
A sequenced Hi-C library provides genome-wide information on interaction frequencies between all pairs of loci. The resolution and precision of Hi-C relies on efficient crosslinking that maintains chromatin contacts and frequent and uniform fragmentation of the chromatin. This paper describes an improved in situ Hi-C protocol, Hi-C 3.0, that increases the efficiency of crosslinking by combining two crosslinkers (formaldehyde [FA] and disuccinimidyl glutarate [DSG]), followed by finer digestion using two restriction enzymes (DpnII and DdeI). Hi-C 3.0 is a single protocol for the accurate quantification of genome folding features at smaller scales such as loops and topologically associating domains (TADs), as well as features at larger nucleus-wide scales such as compartments.

The figures in this manuscript were generated from a separate, replicate experiment of the one published previously by Lafontaine et al.21. After obtaining high-throughput sequencing data, the Open Chromatin Collective (Open2C:&#160;https://github.com/open2c) was used to process the Hi-C data. A similar pipeline can be found on the data portal of the 4D Nucleome project (https://data.4dnucleome.org/resources/data-analysis/hi_c-processing-pipeline). Briefly, the Nextflow pipeline distiller (https://github.com/open2c/distiller-nf) was implemented to (1) align the sequences of Hi-C molecules to the reference genome, (2) parse .sam alignment and form files with Hi-C pairs, (3) filter PCR duplicates, and (4) aggregate pairs into binned matrices of Hi-C interactions. These HDF5 formatted matrices, called coolers, can then be (1) viewed on a HiGlass server (https://higlass.io/) and (2) analyzed using a large set of open source computational tools present in the &#8220;cooltools&#8221; collection maintained by the Open Chromatin Collective (https://github.com/open2c/cooltools) to extract and quantify folding features such as compartments, TADs, and loops.
Some quality indicators of the Hi-C3.0 libraries can be assessed immediately after mapping read pairs to a reference genome, using a few simple metrics/indicators. First, typically ~50% of sequenced read pairs can be uniquely mapped for human cells. Due to the polymeric nature of chromosomes, most of these mapped reads (~60%-90%) represent interactions within a chromosome (cis), with interaction frequencies rapidly decaying with increasing genomic distance (distance-dependent decay).&#160;The distance-dependent decay can be visualized best in a &#34;scaling plot&#34;, which shows the contact probability (per chromosome arm) as a function of genomic distance. We found that the use of different crosslinkers and enzymes can alter the distance-dependent decay at long- and short-range distances17. The addition of DSG crosslinking increases the detectability of interactions at short distances when combined with enzymes such as Mnase and combinations of DpnII-DdeI that produce smaller fragments (Figure 6A).
Distance-dependent decay can also be observed directly from 2D interaction matrices: interactions become more infrequent when located further away from the central diagonal (Figure 6B). Additionally, genomic folding features, such as compartments, TADs, and loops can be identified from Hi-C matrices and scaling plots as deviations from the general genome-wide average distance-dependent decay. Importantly, crosslinking with DSG in addition to FA decreases random ligations, which are unrestricted due to the polymer nature of chromosomes and, therefore, more likely to occur between chromosomes (in trans) (Figure 6C). Reducing random ligation leads to increased signal-to noise ratios, especially for inter-chromosomal and very long range (&#62;10-50 Mb) intrachromosomal interactions.
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/64001/64001fig6v2.jpg" /> 
Figure 6: Representative results of mapped and filtered Hi-C libraries. (A) Scaling plots with contact probability and its derivative for various enzymes, ordered by fragment length (top) and crosslinking with either FA or FA + DSG (bottom). Digestion with MNAse (microC) or DpnII-DdeI (Hi-C 3.0) significantly increases short range contacts (top) as does adding DSG to FA (bottom). (B) Columns show Hi-C heatmaps of DpnII digestion after just FA crosslinking and DpnII or DdeI digestion after FA+DSG crosslinking. White arrows show increasing strength of &#34;dots&#34; after DSG crosslinking and DdeI digestion, implying better detection of DNA loops. Rows show different parts of chromosome 3 at increasing resolution, aligning with panel C: top row: entire chromosome 3 (0-198,295,559 Mb); middle row: 186-196 Mb; bottom row: 191.0-191.5 Mb. (C) Coverage graphs for the regions depicted in A. Black arrows show the lower coverage (%cis reads) for FA-only crosslinking. Abbreviations: FA = formaldehyde; DSG = disuccinimidyl glutarate; chr = chromosome. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/64001/64001fig6v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Not all mapped reads are useful. A second quality indicator is the number of PCR duplicates. Exact duplicate reads are highly unlikely to occur by chance after ligation and sonication. Thus, such reads likely resulted from PCR amplification and need to be filtered out. Duplicates often arise when too many PCR cycles are required to amplify low complexity libraries. Generally, for Hi-C, most libraries only need 5-8 cycles of final PCR amplification, as determined by titration PCR (see step 3.9; Figure 4). However, libraries with sufficient complexity can be obtained even after 14 cycles of PCR amplification.
Another category of duplicate reads, so-called optical duplicates, can arise from the amplification process on Illumina sequencing platforms that use patterned flow cells (such as HiSeq4000). Optical duplicates are found from either overloading the flow cell, causing (large) clusters to be called two separate clusters, or from local reclustering of the original paired-end molecule after a first round of PCR. Because both types of optical duplicates are local, they can be identified and distinguished from PCR duplicates by their location on the flow cell. Whereas libraries with &#62;15% PCR duplicates would need regeneration, libraries with optical duplicates can be reloaded after optimizing the loading process.
Supplemental Table S1: Buffers and solutions. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/64001/64001_Suppl TableS1.xlsx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Capturing Chromosome Conformation Across Length Scales at JoVE.com

Capturing Chromosome Conformation Across Length Scales

Hi-C 3.0 is an improved Hi-C protocol that combines formaldehyde and disuccinimidyl glutarate crosslinkers with a cocktail of DpnII and DdeI restriction enzymes to increase the signal-to-noise ratio and the resolution of chromatin interaction detection.

Chromosome conformation capture (3C) is used to detect three-dimensional chromatin interactions. Typically, chemical crosslinking with formaldehyde (FA) ...

capturing-chromosome-conformation-across-length-scales

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3.3K Views.  University of Massachusetts Medical School. Hi-C 3.0 is an improved Hi-C protocol that combines formaldehyde and disuccinimidyl glutarate crosslinkers with a cocktail of DpnII and DdeI restriction enzymes to increase the signal-to-noise ratio and the resolution of chromatin interaction detection.

Video: Capturing Chromosome Conformation Across Length Scales

Improved Polymerase Chain Reaction-restriction Fragment Length Polymorphism Genotyping of Toxic Pufferfish by Liquid Chromatography/Mass Spectrometry

An improved version of a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) method for genotyping toxic pufferfish species by liquid chromatography/electrospray ionization mass spectrometry (LC/ESI-MS) is described. DNA extraction is carried out using a silica membrane-based DNA extraction kit. After the PCR amplification using a detergent-free PCR buffer, restriction enzymes are added to the solution without purifying the reaction solution. A reverse-phase silica monolith column and a Fourier transform high resolution mass spectrometer having a modified Kingdon trap analyzer are employed for separation and detection, respectively. The mobile phase, consisting of 400 mM 1,1,1,3,3,3-hexafluoro-2-propanol, 15 mM triethylamine (pH 7.9) and methanol, is delivered at a flow rate of 0.4 ml/min. The cycle time for LC/ESI-MS analysis is 8 min including equilibration of the column. Deconvolution software having an isotope distribution model of the oligonucleotide is used to calculate the corresponding monoisotopic mass from the mass spectrum. For analysis of oligonucleotides (range 26-79 nucleotides), mass accuracy was 0.62 &#177; 0.74 ppm (n = 280) and excellent accuracy and precision were sustained for 180 hr without use of a lock mass standard.

An improved polymerase chain reaction-restriction fragment length polymorphism method for genotyping pufferfish species by liquid chromatography/mass spectrometry is described. A reverse-phase silica monolith column is employed for separating digested amplicons. This method can elucidate the monoisotopic masses of oligonucleotides, which is useful for identifying base composition.

An improved version of a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) method for genotyping toxic pufferfish species by ...

Peptide-derived Method to Transport Genes and Proteins Across Cellular and Organellar Barriers in Plants

The capacity to introduce exogenous proteins and express (or down-regulate) specific genes in plants provides a powerful tool for fundamental research as well as new applications in the field of plant biotechnology. Viable methods that currently exist for protein or gene transfer into plant cells, namely Agrobacterium and microprojectile bombardment, have disadvantages of low transformation frequency, limited host range, or a high cost of equipment and microcarriers. The following protocol outlines a simple and versatile method, which employs rationally-designed peptides as delivery agents for a variety of nucleic acid- and protein-based cargoes into plants. Peptides are selected as tools for development of the system due to their biodegradability, reduced size, diverse and tunable properties as well as the ability to gain intracellular/organellar access. The preparation, characterization and application of optimized formulations for each type of the wide range of delivered cargoes (plasmid DNA, double-stranded DNA or RNA, and protein) are described. Critical steps within the protocol, possible modifications and existing limitations of the method are also discussed.

Existing methods for the modification of plants have limited applicability. The novel peptide-derived technology proposed here promises both simplicity and efficiency in the introduction of exogenous protein or genes into the desired intracellular compartments of intact plants.

The capacity to introduce exogenous proteins and express (or down-regulate) specific genes in plants provides a powerful tool for fundamental research as ...

High-resolution Melting PCR for Complement Receptor 1 Length Polymorphism Genotyping: An Innovative Tool for Alzheimer's Disease Gene Susceptibility Assessment

Complement receptor 1 (CR1), a transmembrane glycoprotein that plays a key role in the innate immune system, is expressed on many cell types, but especially on red blood cells (RBCs). As a receptor for the complement components C3b and C4b, CR1 regulates the activation of the complement cascade and promotes the phagocytosis of immune complexes and cellular debris, as well as the amyloid-beta (A&#946;) peptide in Alzheimer's disease (AD). Several studies have confirmed AD-associated single nucleotide polymorphisms (SNPs), as well as a copy-number variation (CNV) in the CR1 gene. Here, we describe an innovative method for determining the length polymorphism of the CR1 receptor. The receptor includes three domains, called long homologous repeats (LHR)-LHR-A, LHR-C, and LHR-D-and an n domain, LHR-B, where n is an integer between 0 and 3. Using a single pair of specific primers, the genetic material is used to amplify a first fragment of the LHR-B domain (the variant amplicon B) and a second fragment of the LHR-C domain (the invariant amplicon). The variant amplicon B and the invariant amplicon display differences at five nucleotides outside of the hybridization areas of said primers. The numbers of variant amplicons B and of invariant amplicons is deduced using a quantitative tool (high-resolution melting (HRM) curves), and the ratio of the variant amplicon B to the invariant amplicon differs according to the CR1 length polymorphism. This method provides several advantages over the canonical phenotype method, as it does not require fresh material and is cheaper, faster, and therefore applicable to larger populations. Thus, the use of this method should be helpful to better understand the role of CR1 isoforms in the pathogenesis of diseases such as AD.

Here, we describe an innovative method to determine complement receptor 1 (CR1) length polymorphisms for use in several applications, particularly the assessment of susceptibility to diseases such as Alzheimer&#39;s disease (AD). This method could be useful to better understand the role of CR1 isoforms in the pathogenesis of AD.

Complement receptor 1 (CR1), a transmembrane glycoprotein that plays a key role in the innate immune system, is expressed on many cell types, but ...

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation

Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome assays is traditionally a manual, labor-intensive process not well suited to handle the volume of samples which may require examination in the wake of a mass casualty event. Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates this process by examining sets of metaphase images using machine learning-based image processing techniques. The software selects appropriate images for analysis by removing unsuitable images, classifies each object as either a centromere-containing chromosome or non-chromosome, further distinguishes chromosomes as monocentric chromosomes (MCs) or dicentric chromosomes (DCs), determines DC frequency within a sample, and estimates biological radiation dose by comparing sample DC frequency with calibration curves computed using calibration samples. This protocol describes the usage of ADCI software. Typically, both calibration (known dose) and test (unknown dose) sets of metaphase images are imported to perform accurate dose estimation. Optimal images for analysis can be found automatically using preset image filters or can also be filtered through manual inspection. The software processes images within each sample and DC frequencies are computed at different levels of stringency for calling DCs, using a machine learning approach. Linear-quadratic calibration curves are generated based on DC frequencies in calibration samples exposed to known physical doses. Doses of test samples exposed to uncertain radiation levels are estimated from their DC frequencies using these calibration curves. Reports can be generated upon request and provide summary of results of one or more samples, of one or more calibration curves, or of dose estimation.

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

The cytogenetic dicentric chromosome (DC) assay quantifies exposure to ionizing radiation. The Automated Dicentric Chromosome Identifier and Dose Estimator software accurately and rapidly estimates biological dose from DCs in metaphase cells. It distinguishes monocentric chromosomes and other objects from DCs, and estimates biological radiation dose from the frequency of DCs.

Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome ...

Pooled shRNA Screen for Reactivation of MeCP2 on the Inactive X Chromosome

Forward genetic screens using reporter genes inserted into the heterochromatin have been extensively used to investigate mechanisms of epigenetic control in model organisms. Technologies including short hairpin RNAs (shRNAs) and clustered regularly interspaced short palindromic repeats (CRISPR) have enabled such screens in diploid mammalian cells. Here we describe a large-scale shRNA screen for regulators of X-chromosome inactivation (XCI), using a murine cell line with firefly luciferase and hygromycin resistance genes knocked in at the C-terminus of the methyl CpG binding protein 2 (MeCP2) gene on the inactive X-chromosome (Xi). Reactivation of the construct in the reporter cell line conferred survival advantage under hygromycin B selection, enabling us to screen a large shRNA library and identify hairpins that reactivated the reporter by measuring their post-selection enrichment using next-generation sequencing. The enriched hairpins were then individually validated by testing their ability to activate the luciferase reporter on Xi.

We report a small hairpin RNA (shRNA) and next generation sequencing-based protocol for identifying regulators of X-chromosome inactivation in a murine cell line with firefly luciferase and hygromycin resistance genes fused to the methyl CpG binding protein 2 (MeCP2) gene on the inactive X chromosome.

Forward genetic screens using reporter genes inserted into the heterochromatin have been extensively used to investigate mechanisms of epigenetic control ...

Generation of Genome-wide Chromatin Conformation Capture Libraries from Tightly Staged Early Drosophila Embryos

Investigating the three-dimensional architecture of chromatin offers invaluable insight into the mechanisms of gene regulation. Here, we describe a protocol for performing the chromatin conformation capture technique in situ Hi-C on staged Drosophila melanogaster embryo populations. The result is a sequencing library that allows the mapping of all chromatin interactions that occur in the nucleus in a single experiment. Embryo sorting is done manually using a fluorescent stereo microscope and a transgenic fly line containing a nuclear marker. Using this technique, embryo populations from each nuclear division cycle, and with defined cell cycle status, can be obtained with very high purity. The protocol may also be adapted to sort older embryos beyond gastrulation. Sorted embryos are used as inputs for in situ Hi-C. All experiments, including sequencing library preparation, can be completed in five days. The protocol has low input requirements and works reliably using 20 blastoderm stage embryos as input material. The end result is a sequencing library for next generation sequencing. After sequencing, the data can be processed into genome-wide chromatin interaction maps that can be analyzed using a wide range of available tools to gain information about topologically associating domain (TAD) structure, chromatin loops, and chromatin compartments during Drosophila development.

Generation of Genome-wide Chromatin Conformation Capture Libraries from Tightly Staged Early Drosophila Embryos

This work describes a protocol for the generation of high resolution in situ Hi-C libraries from tightly staged pre-gastrulation Drosophila melanogaster embryos.

Investigating the three-dimensional architecture of chromatin offers invaluable insight into the mechanisms of gene regulation. Here, we describe a ...

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near full-length (intact and defective), HIV-1 proviruses. FLIPS allows determination of the genetic composition of integrated HIV-1 within a cell population. Through identifying defects within HIV-1 proviral sequences that arise during reverse transcription, such as large internal deletions, deleterious stop codons/hypermutation, frameshift mutations, and mutations/deletions in cis acting elements required for virion maturation, FLIPS can identify integrated proviruses incapable of replication. The FLIPS assay can be utilized to identify HIV-1 proviruses that lack these defects and are&#160;therefore potentially replication-competent. The FLIPS protocol involves: lysis of HIV-1 infected cells, nested PCR of near full-length HIV-1 proviruses (using primers targeted to the HIV-1 5&#39; and 3&#39; LTR), DNA purification and quantification, library preparation for Next-generation Sequencing (NGS), NGS, de novo assembly of proviral contigs, and a simple process of elimination for identifying replication-competent proviruses. FLIPS provides advantages over traditional methods designed to sequence integrated HIV-1 proviruses, such as single-proviral sequencing. FLIPS amplifies and sequences near full-length proviruses enabling replication competency to be determined, and also uses fewer amplification primers, preventing the consequences of primer mismatches. FLIPS is a useful tool for understanding the genetic landscape of integrated HIV-1 proviruses, especially within the latent reservoir, however, its utilization can extend to any application in which the genetic composition of integrated HIV-1 is required.

Full-length individual proviral sequencing (FLIPS) provides an efficient and high-throughput method for the amplification and sequencing of single, near full-length (intact and defective) HIV-1 proviruses and allows for determination of their potential replication-competency. FLIPS overcomes limitations of previous assays designed to sequence the latent HIV-1 reservoir.

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

A Non-random Mouse Model for Pharmacological Reactivation of Mecp2 on the Inactive X Chromosome

X chromosome inactivation (XCI) is the random silencing of one X chromosome in females to achieve gene dosage balance between the sexes. As a result, all females are heterozygous for X-linked gene expression. One of the key regulators of XCI is Xist, which is essential for the initiation and maintenance of XCI. Previous studies have identified 13 trans acting X chromosome inactivation factors (XCIFs) using a large-scale, loss-of-function genetic screen. Inhibition of XCIFs, such as ACVR1 and PDPK1, using short-hairpin RNA or small molecule inhibitors, reactivates X chromosome-linked genes in cultured cells. But the feasibility and tolerability of reactivating the inactive X chromosome in vivo remains to be determined. Towards this goal, a Xist&#916;:Mecp2/Xist:Mecp2-Gfp mouse model has been generated with non-random XCI due to deletion of Xist on one X chromosome. Using this model, the extent of inactive X reactivation was quantitated in the mouse brain following treatment with XCIF inhibitors. Recently published results show, for the first time, that pharmacological inhibition of XCIFs reactivates Mecp2 from the inactive X chromosome in cortical neurons of the living mouse brain.

Here, we describe a protocol to generate a viable female murine model with non-random X chromosome inactivation, i.e., the maternally-inherited X chromosome is inactive in 100% of the cells. We also describe a protocol to test feasibility, tolerability, and safety of pharmacological reactivation of the inactive X chromosome in vivo.

X chromosome inactivation (XCI) is the random silencing of one X chromosome in females to achieve gene dosage balance between the sexes. As a result, all ...

Preparation of Meiotic Chromosome Spreads from Zebrafish Spermatocytes

Meiosis is the key cellular process required to create haploid gametes for sexual reproduction. Model organisms have been instrumental in understanding the chromosome events that take place during meiotic prophase, including the pairing, synapsis, and recombination events that ensure proper chromosome segregation. While the mouse has been an important model for understanding the molecular mechanisms underlying these processes, not all meiotic events in this system are analogous to human meiosis. We recently demonstrated the exciting potential of the zebrafish as a model of human spermatogenesis. Here we describe, in detail, our methods to visualize meiotic chromosomes and associated proteins in chromosome spread preparations. These preparations have the advantage of allowing high resolution analysis of chromosome structures. First, we describe the procedure for dissecting testes from adult zebrafish, followed by cell dissociation, lysis, and spreading of the chromosomes. Next, we describe the procedure for detecting the localization of meiotic chromosome proteins, by immunofluorescence detection, and nucleic acid sequences, by fluorescence in situ hybridization (FISH). These techniques comprise a useful set of tools for the cytological analysis of meiotic chromatin architecture in the zebrafish system. Researchers in the zebrafish community should be able to quickly master these techniques and incorporate them into their standard analyses of reproductive function.

Nuclear surface spreads are an indispensable tool for studying chromosome events during meiosis. Here we demonstrate a method to prepare and visualize meiotic chromosomes during prophase I from zebrafish spermatocytes.

Meiosis is the key cellular process required to create haploid gametes for sexual reproduction. Model organisms have been instrumental in understanding ...

Capturing Chromosome Conformation Across Length Scales

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Improved Polymerase Chain Reaction-restriction Fragment Length Polymorphism Genotyping of Toxic Pufferfish by Liquid Chromatography/Mass Spectrometry

Peptide-derived Method to Transport Genes and Proteins Across Cellular and Organellar Barriers in Plants

High-resolution Melting PCR for Complement Receptor 1 Length Polymorphism Genotyping: An Innovative Tool for Alzheimer's Disease Gene Susceptibility Assessment

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation

Pooled shRNA Screen for Reactivation of MeCP2 on the Inactive X Chromosome

Generation of Genome-wide Chromatin Conformation Capture Libraries from Tightly Staged Early Drosophila Embryos

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

A Non-random Mouse Model for Pharmacological Reactivation of Mecp2 on the Inactive X Chromosome

Preparation of Meiotic Chromosome Spreads from Zebrafish Spermatocytes