This research was funded by the Max Planck Society. C.B.H. was supported by a fellowship from the International Max Planck Research School &#8211; Molecular Biomedicine. We thank Shelby Blythe and Eric Wieschaus for kindly providing the eGFP-PCNA Drosophila melanogaster line.

<ol>
	<li>Bonev, B., Cavalli, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organization+and+function+of+the+3D+genome.">Organization and function of the 3D genome.</a> Nat Rev Genet. 17 (11), 661-678 (2016).</li><li>Lieberman-Aiden, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comprehensive+mapping+of+long-range+interactions+reveals+folding+principles+of+the+human+genome.">Comprehensive mapping of long-range interactions reveals folding principles of the human genome.</a> Science. 326 (5950), 289-293 (2009).</li><li>Dixon, J. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Topological+domains+in+mammalian+genomes+identified+by+analysis+of+chromatin+interactions.">Topological domains in mammalian genomes identified by analysis of chromatin interactions.</a> Nature. 485 (7398), 376-380 (2012).</li><li>Jin, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+high-resolution+map+of+the+three-dimensional+chromatin+interactome+in+human+cells.">A high-resolution map of the three-dimensional chromatin interactome in human cells.</a> Nature. , (2013).</li><li>Rao, S. S. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+3D+Map+of+the+Human+Genome+at+Kilobase+Resolution+Reveals+Principles+of+Chromatin+Looping.">A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping.</a> Cell. 159 (7), 1665-1680 (2014).</li><li>Darbellay, F., Duboule, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Topological+Domains,+Metagenes,+and+the+Emergence+of+Pleiotropic+Regulations+at+Hox+Loci.">Topological Domains, Metagenes, and the Emergence of Pleiotropic Regulations at Hox Loci.</a> Current topics in developmental biology. 116, 299-314 (2016).</li><li>Beagan, J. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Local+Genome+Topology+Can+Exhibit+an+Incompletely+Rewired+3D-Folding+State+during+Somatic+Cell+Reprogramming.">Local Genome Topology Can Exhibit an Incompletely Rewired 3D-Folding State during Somatic Cell Reprogramming.</a> Cell stem cell. 18 (5), 611-624 (2016).</li><li>Andrey, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+hundreds+of+regulatory+landscapes+in+developing+limbs+reveals+two+regimes+of+chromatin+folding.">Characterization of hundreds of regulatory landscapes in developing limbs reveals two regimes of chromatin folding.</a> Genome Res. 27 (2), 223-233 (2017).</li><li>Krijger, P. H. L., de Laat, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+disease-associated+gene+expression+in+the+3D+genome.">Regulation of disease-associated gene expression in the 3D genome.</a> Nature Reviews. Molecular Cell Biology. 17 (12), 771-782 (2016).</li><li>Sexton, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+folding+and+functional+organization+principles+of+the+Drosophila+genome.">Three-dimensional folding and functional organization principles of the Drosophila genome.</a> Cell. 148 (3), 458-472 (2012).</li><li>Ghavi-Helm, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhancer+loops+appear+stable+during+development+and+are+associated+with+paused+polymerase.">Enhancer loops appear stable during development and are associated with paused polymerase.</a> Nature. 512 (7512), 96-100 (2014).</li><li>Foe, V. E., Alberts, B. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Studies+of+nuclear+and+cytoplasmic+behaviour+during+the+five+mitotic+cycles+that+precede+gastrulation+in+Drosophila+embryogenesis.">Studies of nuclear and cytoplasmic behaviour during the five mitotic cycles that precede gastrulation in Drosophila embryogenesis.</a> J Cell Sci. 61, 31-70 (1983).</li><li>Blythe, S. A., Wieschaus, E. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zygotic+Genome+Activation+Triggers+the+DNA+Replication+Checkpoint+at+the+Midblastula+Transition.">Zygotic Genome Activation Triggers the DNA Replication Checkpoint at the Midblastula Transition.</a> Cell. 160 (6), 1169-1181 (2015).</li><li>Blythe, S. A., Wieschaus, E. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Establishment+and+maintenance+of+heritable+chromatin+structure+during+early+Drosophila+embryogenesis.">Establishment and maintenance of heritable chromatin structure during early Drosophila embryogenesis.</a> eLife. 5, e20148 (2016).</li><li>JoVE Science Education Database. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Embryo+and+Larva+Harvesting+and+Preparation.">Embryo and Larva Harvesting and Preparation.</a> Biology I: yeast, Drosophila and C. elegans. Drosophila melanogaster. , (2017).</li><li>Sicaeros, B., O'Dowd, D. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparation+of+Neuronal+Cultures+from+Midgastrula+Stage+Drosophila+Embryos.">Preparation of Neuronal Cultures from Midgastrula Stage Drosophila Embryos.</a> Journal of Visualized Experiments. (5), (2007).</li><li>Shermoen, A. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparation+of+Baskets+for+Drosophila+Egg+Collections,+Treatments,+and+Incubations.">Preparation of Baskets for Drosophila Egg Collections, Treatments, and Incubations.</a> Cold Spring Harbor Protocols. (10), (2008).</li><li>Ay, F., Noble, W. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+methods+for+studying+the+3D+architecture+of+the+genome.">Analysis methods for studying the 3D architecture of the genome.</a> Genome biology. 16 (1), 183 (2015).</li><li>Lazaris, C., Kelly, S., Ntziachristos, P., Aifantis, I., Tsirigos, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HiC-bench:+comprehensive+and+reproducible+Hi-C+data+analysis+designed+for+parameter+exploration+and+benchmarking.">HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking.</a> BMC Genomics. 18 (1), (2017).</li><li>Servant, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HiC-Pro:+an+optimized+and+flexible+pipeline+for+Hi-C+data+processing.">HiC-Pro: an optimized and flexible pipeline for Hi-C data processing.</a> Genome Biology. 16 (1), (2015).</li><li>Durand, N. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Juicer+Provides+a+One-Click+System+for+Analyzing+Loop-Resolution+Hi-C+Experiments.">Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments.</a> Cell systems. 3 (1), 95-98 (2016).</li><li>Lajoie, B. R., Dekker, J., Kaplan, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Hitchhiker's+guide+to+Hi-C+analysis:+Practical+guidelines.">The Hitchhiker's guide to Hi-C analysis: Practical guidelines.</a> Methods. 72, 65-75 (2015).</li><li>Schmitt, A. D., Hu, M., Ren, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+mapping+and+analysis+of+chromosome+architecture.">Genome-wide mapping and analysis of chromosome architecture.</a> Nature Reviews. Molecular Cell Biology. 17 (12), 743-755 (2016).</li><li>Shin, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TopDom:+an+efficient+and+deterministic+method+for+identifying+topological+domains+in+genomes.">TopDom: an efficient and deterministic method for identifying topological domains in genomes.</a> Nucleic Acids Res. 44 (7), e70 (2016).</li><li>Kruse, K., Hug, C. B., Hern&#225;ndez-Rodr&#237;guez, B., Vaquerizas, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TADtool:+visual+parameter+identification+for+TAD-calling+algorithms.">TADtool: visual parameter identification for TAD-calling algorithms.</a> Bioinformatics. 32 (20), 3190-3192 (2016).</li><li>L&#233;vy-Leduc, C., Delattre, M., Mary-Huard, T., Robin, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Two-dimensional+segmentation+for+analyzing+Hi-C+data.">Two-dimensional segmentation for analyzing Hi-C data.</a> Bioinformatics. 30 (17), i386-i392 (2014).</li><li>Filippova, D., Patro, R., Duggal, G., Kingsford, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+alternative+topological+domains+in+chromatin.">Identification of alternative topological domains in chromatin.</a> Algorithms for molecular biology: AMB. 9 (1), 14 (2014).</li><li>Crane, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Condensin-driven+remodelling+of+X+chromosome+topology+during+dosage+compensation.">Condensin-driven remodelling of X chromosome topology during dosage compensation.</a> Nature. 523 (7559), 240-244 (2015).</li><li>Durand, N. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Juicebox+Provides+a+Visualization+System+for+Hi-C+Contact+Maps+with+Unlimited+Zoom.">Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom.</a> Cell systems. 3 (1), 99-101 (2016).</li><li>Zhou, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exploring+long-range+genome+interactions+using+the+WashU+Epigenome+Browser.">Exploring long-range genome interactions using the WashU Epigenome Browser.</a> Nature Methods. 10 (5), 375-376 (2013).</li><li>Ram&#237;rez, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-resolution+TADs+reveal+DNA+sequences+underlying+genome+organization+in+flies.">High-resolution TADs reveal DNA sequences underlying genome organization in flies.</a> bioRxiv. , 115063 (2017).</li><li>Kerpedjiev, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HiGlass:+Web-based+Visual+Comparison+And+Exploration+Of+Genome+Interaction+Maps.">HiGlass: Web-based Visual Comparison And Exploration Of Genome Interaction Maps.</a> bioRxiv. , 121889 (2017).</li><li>Hug, C. B., Grimaldi, A. G., Kruse, K., Vaquerizas, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromatin+Architecture+Emerges+during+Zygotic+Genome+Activation+Independent+of+Transcription.">Chromatin Architecture Emerges during Zygotic Genome Activation Independent of Transcription.</a> Cell. 169 (2), (2017).</li><li>Berkum, N. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hi-C:+a+method+to+study+the+three-dimensional+architecture+of+genomes.">Hi-C: a method to study the three-dimensional architecture of genomes.</a> Journal of Visualized Experiments: JoVE. (39), (2010).</li><li>Naumova, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organization+of+the+mitotic+chromosome.">Organization of the mitotic chromosome.</a> Science. 342 (6161), 948-953 (2013).</li><li>Denker, A., de Laat, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+second+decade+of+3C+technologies:+detailed+insights+into+nuclear+organization.">The second decade of 3C technologies: detailed insights into nuclear organization.</a> Genes &amp; development. 30 (12), 1357-1382 (2016).</li><li>Belaghzal, H., Dekker, J., Gibcus, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hi-C+2.0:+An+optimized+Hi-C+procedure+for+high-resolution+genome-wide+mapping+of+chromosome+conformation.">Hi-C 2.0: An optimized Hi-C procedure for high-resolution genome-wide mapping of chromosome conformation.</a> Methods (San Diego, Calif). 123, 56-65 (2017).</li></ol>

The authors have nothing to disclose.

The protocol presented here is very effective at generating high-quality maps of the chromatin architecture in early Drosophila embryos. Compared to an earlier protocol34, the approach described here uses an up-to-date in situ Hi-C procedure5, resulting in quicker processing, higher resolution, and less reagent usage. The overall procedure including the in situ Hi-C protocol is expected to work on a wide range of stages and experimental systems besides Drosophila. Since the protocol has a low input requirement, it could also be used on isolated cell populations. In Drosophila, when using the protocol for embryos outside the range described here, some parameters, in particular the fixation of the material, might need to be adjusted. Since older embryos develop a highly impermeable cuticle, raising the concentration of formaldehyde and prolonging fixation may be appropriate. For collection of embryos at stages other than nuclear cycle 14, the incubation times of embryos at 25 &#176;C in step 1.4 need to be adjusted as follows: nuclear cycle 12, 70 min; nuclear cycle 13, 90 min; 3&#8211;4 hpf, 3:30 h.
During the 13 cleavage divisions (stage 1-4), the nuclei density roughly doubles with each division. The nuclei can easily be identified by their bright GFP fluorescence. During mitosis, eGFP-PCNA is not located in the nucleus, and its signal is dispersed throughout the embryo. This feature makes identifying embryos that are undergoing a synchronous cleavage division possible. For studying chromatin conformation, these mitotic embryos are usually not desirable, since the mitotic organization of chromatin is drastically different than the interphase organization35. It is possible to adapt the protocol to specifically select embryos undergoing a synchronous mitotic division. In this case, only embryos with dispersed, non-nuclear distribution of eGFP-PCNA should be kept, and all other embryos should be discarded. Since the nuclear density cannot be determined, alternative methods to stage embryos by their morphology viewed in transmitted light microscopy must be employed. Presence of pole cells and nuclei at the embryo periphery indicate that the embryo has completed at least nuclear cycle 9, whereas visible cellularization at the periphery indicates nuclear cycle 1412.
Hi-C experiments can be successfully performed using a wide selection of restriction enzymes5. Current approaches typically use enzymes that recognize either a 4-base sequence, such as MboI, or a 6-base recognition site, such as HindIII. The advantage of 4-base cutters over 6-base cutters is that they offer higher potential resolution, given enough sequencing depth, and a more even coverage of restriction sites across the genome. There is no clear advantage in choosing one 4-base cutter over another5,23,36,37. The two most commonly used enzymes, MboI and DpnII, both recognize the same GATC recognition site. DpnII is less sensitive to CpG methylation, which is of no concern in Drosophila. The protocol presented here can also be successfully completed using DpnII as a restriction enzyme. In section 4.2. restriction enzyme and buffer have to be adjusted for DpnII compatibility, according to the manufacturer&#39;s recommendations.
If the fragment size of the sequencing library deviates significantly from the range shown in Figure 2A, cluster formation during sequencing may be less efficient or fail completely. In this case, the size distribution after shearing should be checked and shearing parameters adjusted accordingly. Peaks in the distribution of DNA fragments of very small (&#60;100 bp) or very large (&#62;1,000 bp) sizes indicates problems with size selection, such as carry over of beads or supernatant that are supposed to be discarded. Often these libraries with small peaks at these undesirable sizes, such as the one pictured, are still sequenced successfully with only a minor decrease in clustering efficiency.
High rates of PCR duplication should be avoided because this drastically reduces the number of usable sequence reads. The rate of PCR duplicates is directly related to the amount of input material. Using more input therefore usually alleviates problems with PCR duplication.
Higher numbers of reads filtered due to read orientation (Figure 2B) indicate insufficient digestion, which can be the result of using too little enzyme, too much input material, or incomplete homogenization of the embryos.

Chromatin conformation capture (3C) has emerged as an exceptionally useful method to study the topology of chromatin in the nucleus1. The 3C variant Hi-C allows measuring the contact frequencies of all chromatin interactions that occur in the nucleus in a single experiment2. Application of Hi-C has played an important role in the discovery and characterization of many fundamental principles of chromatin organization, such as TADs, compartments, and loops3,4,5.
Studies of chromatin architecture in the context of developmental transitions and cell differentiation are increasingly used to unravel the mechanisms of gene regulation during these processes6,7,8,9. One of the model organisms of great interest is Drosophila melanogaster, whose development and genome are well characterized. However, few studies that investigate chromatin architecture in Drosophila outside of in vitro tissue culture settings have been conducted10,11. In embryos 16&#8211;18 h post fertilization, TADs and compartments reminiscent of similar structures in mammals were identified10, which raises the question of which role they are playing in gene regulation during Drosophila embryo development. Especially in the early stages of development, prior to gastrulation, such studies are technically challenging. Before gastrulation, Drosophila embryos undergo 13 synchronous nuclear divisions that proceed at an extremely rapid pace of 8&#8211;60 min per cycle12,13. In addition to this, the lack of visual features to distinguish the different stages make it difficult to obtain tightly staged embryo material in sufficient quantities.
In order to develop a protocol that allows studying chromatin architecture in early Drosophila development at nuclear cycle resolution, we combined two existing techniques: in situ Hi-C, which allows the generation of high resolution whole genome contact maps5, and embryo staging using a transgenic Drosophila line expressing a eGFP-PCNA transgene13,14. This transgene localizes to the nucleus during interphase and disperses throughout the syncytial blastoderm during mitosis. Using this property, it is possible to easily distinguish different stages by their nuclear density and mitotic embryos by the dispersion of the GFP signal.
Together, these techniques enable studying the three-dimensional structure of chromatin in high resolution from as few as 20 Drosophila embryos. This protocol includes the instructions for harvesting and sorting Drosophila embryos to obtain populations of embryos from a single nuclear division cycle. It further describes how the obtained embryos are used to perform in situ Hi-C. The end result is a nucleotide library suitable for sequencing on next generation sequencing machines. The resulting sequencing reads can then be processed into detailed chromatin interaction maps covering the entire Drosophila genome.

<table>
	<tbody>
		<tr>
			<td>Biotin-14-dATP</td>
			<td>Life Technologies</td>
			<td>19524016</td>
			<td></td>
		</tr>
		<tr>
			<td>MboI</td>
			<td>New England Biolabs</td>
			<td>R0147L</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA Polymerase I Klenow Fragment</td>
			<td>New England Biolabs</td>
			<td>M0210L</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA Ligase</td>
			<td>Thermo Fisher</td>
			<td>EL0012</td>
			<td>T4 DNA Ligase Buffer included</td>
		</tr>
		<tr>
			<td>T4 DNA Polymerase</td>
			<td>New England Biolabs</td>
			<td>M0203L</td>
			<td></td>
		</tr>
		<tr>
			<td>Proteinase K</td>
			<td>AppliChem</td>
			<td>A4392</td>
			<td></td>
		</tr>
		<tr>
			<td>GlycoBlue</td>
			<td>Life Technologies</td>
			<td>AM9516</td>
			<td></td>
		</tr>
		<tr>
			<td>Complete Ultra EDTA-free protease inhibitors</td>
			<td>Roche</td>
			<td>5892791001</td>
			<td></td>
		</tr>
		<tr>
			<td>NEBNext Multiplex Oligos for Illumina&#160;(Index Primers Set 1)</td>
			<td>New England Biolabs</td>
			<td>E7335</td>
			<td>Sequencing Adaptor, Forward (unindexed) PCR primer and Reverse (indexed) PCR primer and USER enzyme used in the Library preparation section are components of this kit</td>
		</tr>
		<tr>
			<td>NEBNext Ultra II DNA Library Prep Kit</td>
			<td>New England Biolabs</td>
			<td>E7645</td>
			<td>End Prep Enzyme Mix, End Prep Reaction Buffer, Ligation Enhancer, Ligation Master Mix and Polymerase Master Mix used in the Library preparation section are components of this kit</td>
		</tr>
		<tr>
			<td>Covaris S2 AFA System</td>
			<td>Covaris</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DNA LoBind Tubes, 1.5 mL</td>
			<td>Eppendorf</td>
			<td>0030108051</td>
			<td></td>
		</tr>
		<tr>
			<td>Falcon cell strainer 100 &#181;m</td>
			<td>Corning</td>
			<td>352360</td>
			<td>Embryo collection baskets</td>
		</tr>
		<tr>
			<td>37% formaldehyde</td>
			<td>VWR</td>
			<td>437536C</td>
			<td></td>
		</tr>
		<tr>
			<td>Heptane</td>
			<td>AppliChem</td>
			<td>122062.1612</td>
			<td></td>
		</tr>
		<tr>
			<td>M165 FC fluorescent stereo microscope</td>
			<td>Leica</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>M165 FC DFC camera</td>
			<td>Leica</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Metal micro pestle</td>
			<td>Carl Roth</td>
			<td>P985.1</td>
			<td>Used to lyse embryos in step 4.1.4</td>
		</tr>
		<tr>
			<td>RNase A</td>
			<td>AppliChem</td>
			<td>A3832,0050</td>
			<td></td>
		</tr>
		<tr>
			<td>Dynabeads MyOne Streptavidin C1</td>
			<td>Life Technologies</td>
			<td>65002</td>
			<td>Streptavidin coated magnetic beads</td>
		</tr>
		<tr>
			<td>Ampure XP beads</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit 3.0 Fluorometer</td>
			<td>Thermo Fisher Scientific</td>
			<td>Q33216</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit assay tubes</td>
			<td>Thermo Fisher Scientific</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit dsDNA HS Assay Kit</td>
			<td>Thermo Fisher Scientific</td>
			<td>Q32854</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate buffered saline (PBS)</td>
			<td>Sigma-Aldrich</td>
			<td>P4417</td>
			<td></td>
		</tr>
		<tr>
			<td>eGFP-PCNA flies</td>
			<td>Gift from S. Blythe and E. Wieschaus</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium hypochlorite 13%</td>
			<td>Thermo Fisher</td>
			<td>AC219255000</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100</td>
			<td>AppliChem</td>
			<td>A4975</td>
			<td></td>
		</tr>
		<tr>
			<td>Tris buffer pH 8.0 (1 M) for molecular biology</td>
			<td>AppliChem</td>
			<td>A4577</td>
			<td></td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>AppliChem</td>
			<td>A2942</td>
			<td></td>
		</tr>
		<tr>
			<td>IGEPAL CA-630</td>
			<td>Sigma-Aldrich</td>
			<td>I8896</td>
			<td></td>
		</tr>
		<tr>
			<td>1.5 mL microcentrifuge tubes</td>
			<td>Greiner Bio-One</td>
			<td>616201</td>
			<td></td>
		</tr>
		<tr>
			<td>SDS for molecular biology</td>
			<td>AppliChem</td>
			<td>A2263</td>
			<td></td>
		</tr>
		<tr>
			<td>10x CutSmart buffer</td>
			<td>New England Biolabs</td>
			<td>B7204S</td>
			<td>Restriction enzyme buffer</td>
		</tr>
		<tr>
			<td>PCR Nucleotide Mix</td>
			<td>Sigma-Aldrich</td>
			<td>11814362001</td>
			<td>Unmodified dCTP, dGTP, dTTP</td>
		</tr>
		<tr>
			<td>BSA, Molecular Biology Grade</td>
			<td>New England Biolabs</td>
			<td>B9000S</td>
			<td></td>
		</tr>
		<tr>
			<td>EDTA 0.5M solution for molecular biology</td>
			<td>AppliChem</td>
			<td>A4892</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium acetate 3M pH 5.2</td>
			<td>Sigma-Aldrich</td>
			<td>S7899</td>
			<td></td>
		</tr>
		<tr>
			<td>DynaMag-2 Magnet</td>
			<td>Life Technologies</td>
			<td>12321D</td>
			<td>Magnetic stand</td>
		</tr>
		<tr>
			<td>Intelli-Mixer RM-2L</td>
			<td>Omnilab</td>
			<td>5729802</td>
			<td>Rotator</td>
		</tr>
		<tr>
			<td>ThermoMixer F1.5</td>
			<td>Eppendorf</td>
			<td>5384000012</td>
			<td>Mixer</td>
		</tr>
		<tr>
			<td>Small Embryo Collection Cages</td>
			<td>Flystuff.com</td>
			<td>59-100</td>
			<td>Egg collection cage</td>
		</tr>
		<tr>
			<td>Centrifuge 5424&#160;R</td>
			<td>Eppendorf</td>
			<td>5404000413</td>
			<td></td>
		</tr>
		<tr>
			<td>C1000 Touch Thermal Cycler</td>
			<td>Bio-Rad</td>
			<td>1851148</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR tube strips</td>
			<td>Greiner Bio-One</td>
			<td>673275</td>
			<td></td>
		</tr>
		<tr>
			<td>NEBuffer 2.1</td>
			<td>New England Biolabs</td>
			<td>B7202S</td>
			<td>T4 DNA Polymerase buffer</td>
		</tr>
	</tbody>
</table>

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.

Sorted embryo populations at nuclear cycle 12, 13, and 14 (corresponding to 1:30, 1:45, and 2:10 hours post fertilization, respectively12) and 3&#8211;4 h post fertilization (hpf) were obtained according to the procedures described in the protocol. By taking pictures of the eGFP-PCNA signal of each sorted embryo batch, it is possible to document the precise stage and cell cycle status of every single embryo that is used in downstream experiments. Example pictures of embryos from sorted populations are shown in Figure 1B-E. The output of the in situ Hi-C protocol is a nucleotide library ready to be sequenced on next generation sequencing machines. For this purpose, a final library concentration of at least 2&#8211;4 nM is usually required. Using the recommended amounts of input material, this concentration is reliably achieved (Table 1).
The expected size distribution of DNA fragments after size selection is between 300&#8211;600 bp, with a maximum at around 500 bp (Figure 2A), depending on the exact shearing and size selection parameters. For sequencing, we recommend paired-end reads of at least 75 bp length to minimize the number of unmappable restriction fragments in the genome. High-resolution maps with 1&#8211;2 kb bin size can be obtained from 400 million reads. We recommend sequencing multiple biological replicates at a lower depth of ~150 million reads each, instead of sequencing a single replicate at very high depth. This allows assessment of the biological variation and leads to a lower number of discarded reads due to PCR duplication. For visual representation, the replicates can be combined. Before committing to sequencing a sample at high depth, we recommend running samples using shallow sequencing (a few million reads per sample) to determine basic library quality parameters as in Figure 2B.
Analysis of Hi-C data requires significant computational resources and bioinformatics expertise. As a rough overview, the paired reads are mapped independently to the reference genome, the resulting alignments are filtered for quality and orientation, then a matrix of contacts at a given bin resolution or fragment level can be generated from the filtered alignments. The contact matrix is the basis for all further downstream analysis exploring TADs, loops, and compartments. For the initial analysis of the sequencing reads, several bioinformatics pipelines are available that enable processing of raw reads into contact matrices without much specialized bioinformatics knowledge18,19,20,21,22,23. How further analysis is carried out depends largely on the exact biological question under study and might require significant experience in programming and scripting in R or Python. However, several tools and algorithms to call TADs are available5,24,25,26,27,28, as well as software to analyze and explore Hi-C data in the web browser and as stand-alone desktop applications29,30,31,32.
Once processed, the quality of the library can be determined using different metrics (Figure 2B). First, the rate of PCR duplicates, which is the number of sequenced read pairs arising from the same original molecule, should be as low as possible to limit the amount of wasted sequence reads. However, even libraries with &#62;40% PCR duplication can be processed into high-quality contact maps if the duplicates are filtered. Second, the rate of filtered reads due to their orientation, as described in4, should consistently be lower than 10% of aligned read pairs.
During pre-gastrular development of Drosophila between nuclear cycle 12 and 14, the nuclear architecture is drastically remodeled33 (Figure 3). At nuclear cycle 12, few TADs are detected, and the overall distribution of contacts is very smooth without many discernable features. This is dramatically changed at nuclear cycle 13 and 14, when TADs are increasingly prominent and unspecific long-range contacts are depleted.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57001/57001fig1.jpg" /> 
Figure 1: Representative pictures of eGFP-PCNA embryos during sorting. (A) eGFP-PCNA signal from an unsorted population of embryos after 60 min collection and 2 h incubation at 25 &#176;C (B-E) Examples of embryos from sorted populations at nuclear cycle 12 (B), nuclear cycle 13 (C), nuclear cycle 14 (D), and from embryos undergoing synchronous mitosis (E). Scale bars = 200 &#181;m. <a href="https://cloudflare.jove.com/files/ftp_upload/57001/57001fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57001/57001fig2.jpg" /> 
Figure 2: Examples of in situ Hi-C library quality metrics. (A) Bioanalyzer traces showing the distribution of DNA fragment sizes from a successful Hi-C library (Library 1, top) and from a library that displays a peak of fragments that are too large for sequencing (Library 2, bottom). Library 2 was successfully sequenced, but even larger amounts of undesired DNA fragments may lead to decreased sequencing yields. (B) Filtering statistics of two Hi-C libraries: displayed is the number of aligned read pairs that are excluded from further analysis due to read orientation and distance (inward, outward)4 or PCR duplication (duplicate). In each bar, the number of reads passing the filter (remaining) and failing (filtered) are plotted. The percentage of reads passing the filter is additionally shown as text. <a href="https://cloudflare.jove.com/files/ftp_upload/57001/57001fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57001/57001fig3.jpg" /> 
Figure 3: Hi-C interaction maps from staged embryos. Hi-C interaction maps are binned at 10 kb resolution and balanced as described before33. Shown is a region on chromosome 2L. <a href="https://cloudflare.jove.com/files/ftp_upload/57001/57001fig3large.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>Library</td>
			<td>Stage</td>
			<td>Number of embryos</td>
			<td>Amount DNA before shearing (ng)</td>
			<td>PCR cycles</td>
			<td>Final library concentration (nM)</td>
		</tr>
		<tr>
			<td>1</td>
			<td>nuclear cycle 12</td>
			<td>71</td>
			<td>46</td>
			<td>12</td>
			<td>28.2</td>
		</tr>
		<tr>
			<td>2</td>
			<td>nuclear cycle 12</td>
			<td>46</td>
			<td>40</td>
			<td>12</td>
			<td>22.2</td>
		</tr>
		<tr>
			<td>3</td>
			<td>nuclear cycle 12</td>
			<td>60</td>
			<td>13</td>
			<td>13</td>
			<td>12.3</td>
		</tr>
		<tr>
			<td>4</td>
			<td>nuclear cycle 13</td>
			<td>36</td>
			<td>39</td>
			<td>12</td>
			<td>22.2</td>
		</tr>
		<tr>
			<td>5</td>
			<td>nuclear cycle 13</td>
			<td>35</td>
			<td>10</td>
			<td>12</td>
			<td>5.0</td>
		</tr>
		<tr>
			<td>6</td>
			<td>nuclear cycle 13</td>
			<td>48</td>
			<td>18</td>
			<td>12</td>
			<td>8.7</td>
		</tr>
		<tr>
			<td>7</td>
			<td>nuclear cycle 14</td>
			<td>33</td>
			<td>30</td>
			<td>12</td>
			<td>39.8</td>
		</tr>
		<tr>
			<td>8</td>
			<td>nuclear cycle 14</td>
			<td>24</td>
			<td>36</td>
			<td>12</td>
			<td>20.4</td>
		</tr>
		<tr>
			<td>9</td>
			<td>nuclear cycle 14</td>
			<td>14</td>
			<td>8</td>
			<td>12</td>
			<td>4.2</td>
		</tr>
		<tr>
			<td>10</td>
			<td>3-4 hpf</td>
			<td>17</td>
			<td>30</td>
			<td>12</td>
			<td>24.0</td>
		</tr>
		<tr>
			<td>11</td>
			<td>3-4 hpf</td>
			<td>18</td>
			<td>42</td>
			<td>11</td>
			<td>19.1</td>
		</tr>
		<tr>
			<td>12</td>
			<td>3-4 hpf</td>
			<td>22</td>
			<td>63</td>
			<td>11</td>
			<td>48.4</td>
		</tr>
	</tbody>
</table>
Table 1: List of representative sequencing library statistics. For each library in the list, the number of embryos that were used for its generation, the amount of total DNA before biotin pulldown and shearing measured by Qubit, the number of PCR cycles used for amplification, and the final concentration of the sequencing library after purification and size selection are indicated.

Watch this Scientific Journal Video about Generation of Genome-wide Chromatin Conformation Capture Libraries from Tightly Staged Early Drosophila Embryos at JoVE.com

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.

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 ...

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19.6K Views.  Max Planck Institute for Molecular Biomedicine. This work describes a protocol for the generation of high resolution in situ Hi-C libraries from tightly staged pre-gastrulation Drosophila melanogaster embryos.

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

Genome-wide Determination of Mammalian Replication Timing by DNA Content Measurement

Replication of the genome occurs during S phase of the cell cycle in a highly regulated process that ensures the fidelity of DNA duplication. Each genomic region is replicated at a distinct time during S phase through the simultaneous activation of multiple origins of replication. Time of replication (ToR) correlates with many genomic and epigenetic features and is linked to mutation rates and cancer. Comprehending the full genomic view of the replication program, in health and disease is a major future goal and challenge.
This article describes in detail the &#34;Copy Number Ratio of S/G1 for mapping genomic Time of Replication&#34; method (herein called: CNR-ToR), a simple approach to map the genome wide ToR of mammalian cells. The method is based on the copy number differences between S phase cells and G1 phase cells. The CNR-ToR method is performed in 6 steps: 1. Preparation of cells and staining with propidium iodide (PI); 2. Sorting G1 and S phase cells using fluorescence-activated cell sorting (FACS); 3. DNA purification; 4. Sonication; 5. Library preparation and sequencing; and 6. Bioinformatic analysis. The CNR-ToR method is a fast and easy approach that results in detailed replication maps.

We describe here a relatively fast and simple approach for mapping genome-wide mammalian replication timing, from cell isolation to the basic analysis of the sequencing results. A genomic map of a representative replication program will be provided following the protocol.

Replication of the genome occurs during S phase of the cell cycle in a highly regulated process that ensures the fidelity of DNA duplication. Each genomic ...

Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae

Genome-wide mapping of protein-DNA interactions is critical for understanding gene regulation, chromatin remodeling, and other chromatin-resident processes. Formaldehyde crosslinking followed by chromatin immunoprecipitation and high-throughput sequencing (X-ChIP-seq) has been used to gain many valuable insights into genome biology. However, X-ChIP-seq has notable limitations linked to crosslinking and sonication. Native ChIP avoids these drawbacks by omitting crosslinking, but often results in poor recovery of chromatin-bound proteins. In addition, all ChIP-based methods are subject to antibody quality considerations. Enzymatic methods for mapping protein-DNA interactions, which involve fusion of a protein of interest to a DNA-modifying enzyme, have also been used to map protein-DNA interactions. We recently combined one such method, chromatin endogenous cleavage (ChEC), with high-throughput sequencing as ChEC-seq. ChEC-seq relies on fusion of a chromatin-associated protein of interest to micrococcal nuclease (MNase) to generate targeted DNA cleavage in the presence of calcium in living cells. ChEC-seq is not based on immunoprecipitation and so circumvents potential concerns with crosslinking, sonication, chromatin solubilization, and antibody quality while providing high resolution mapping with minimal background signal. We envision that ChEC-seq will be a powerful counterpart to ChIP, providing an independent means by which to both validate ChIP-seq findings and discover new insights into genomic regulation.

Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae

We describe chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq), a chromatin immunoprecipitation (ChIP)-orthogonal method for mapping protein binding sites genome-wide with micrococcal nuclease (MNase) fusion proteins.

Genome-wide mapping of protein-DNA interactions is critical for understanding gene regulation, chromatin remodeling, and other chromatin-resident ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution based analysis methodology (nucleosome density ChIP-seq; ndChIP-seq) that enables the generation of combined measurements of micrococcal nuclease (MNase) accessibility with histone modification genome-wide. Nucleosome position and local density, and the posttranslational modification of their histone subunits, act in concert to regulate local transcription states. Combinatorial measurements of nucleosome accessibility with histone modification generated by ndChIP-seq allows for the simultaneous interrogation of these features. The ndChIP-seq methodology is applicable to small numbers of primary cells inaccessible to cross-linking based ChIP-seq protocols. Taken together, ndChIP-seq enables the measurement of histone modification in combination with local nucleosome density to obtain new insights into shared mechanisms that regulate RNA transcription within rare primary cell populations.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) methodology for the generation of sequence datasets suitable for a nucleosome density ChIP-seq analytical framework integrating micrococcal nuclease (MNase) accessibility with histone modification measurements.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution ...

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions of chromatin. These regions represent regulatory DNA elements (e.g., promoters, enhancers, locus control regions, insulators) to which transcription factors bind. Mapping the accessible chromatin landscape is a powerful approach for uncovering active regulatory elements across the genome. This information serves as an unbiased approach for discovering the network of relevant transcription factors and mechanisms of chromatin structure that govern gene expression programs. ATAC-seq is a robust and sensitive alternative to DNase I hypersensitivity analysis coupled with next-generation sequencing (DNase-seq) and formaldehyde-assisted isolation of regulatory elements (FAIRE-seq) for genome-wide analysis of chromatin accessibility and to the sequencing of micrococcal nuclease-sensitive sites (MNase-seq) to determine nucleosome positioning. We present a detailed ATAC-seq protocol optimized for human primary immune cells i.e. CD4+ lymphocytes (T helper 1 (Th1) and Th2 cells). This comprehensive protocol begins with cell harvest, then describes the molecular procedure of chromatin tagmentation, sample preparation for next-generation sequencing, and also includes methods and considerations for the computational analyses used to interpret the results. Moreover, to save time and money, we introduced quality control measures to assess the ATAC-seq library prior to sequencing. Importantly, the principles presented in this protocol allow its adaptation to other human immune and non-immune primary cells and cell lines. These guidelines will also be useful for laboratories which are not proficient with next-generation sequencing methods.

Assay for Transposase-Accessible Chromatin coupled with high-throughput sequencing (ATAC-seq) is a genome-wide method to uncover accessible chromatin. This is a step-by-step ATAC-seq protocol, from molecular to the final computational analysis, optimized for human lymphocytes (Th1/Th2). This protocol can be adopted by researchers without prior experience in next-generation sequencing methods.

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions ...

Determining Genome-wide Transcript Decay Rates in Proliferating and Quiescent Human Fibroblasts

Quiescence is a temporary, reversible state in which cells have ceased cell division, but retain the capacity to proliferate. Multiple studies, including ours, have demonstrated that quiescence is associated with widespread changes in gene expression. Some of these changes occur through changes in the level or activity of proliferation-associated transcription factors, such as E2F and MYC. We have demonstrated that mRNA decay can also contribute to changes in gene expression between proliferating and quiescent cells. In this protocol, we describe the procedure for establishing proliferating and quiescent cultures of human dermal foreskin fibroblasts. We then describe the procedures for inhibiting new transcription in proliferating and quiescent cells with Actinomycin D (ActD). ActD treatment represents a straightforward and reproducible approach to dissociating new transcription from transcript decay. A disadvantage of ActD treatment is that the time course must be limited to a short time frame because ActD affects cell viability. Transcript levels are monitored over time to determine transcript decay rates. This procedure allows for the identification of genes and isoforms that exhibit differential decay in proliferating versus quiescent fibroblasts.

We describe a protocol for generating proliferating and quiescent primary human dermal fibroblasts, monitoring transcript decay rates, and identifying differentially decaying genes.

Quiescence is a temporary, reversible state in which cells have ceased cell division, but retain the capacity to proliferate. Multiple studies, including ...

Chromatin Immunoprecipitation (ChIP) of Histone Modifications from Saccharomyces cerevisiae

Histone post-translational modifications (PTMs), such as acetylation, methylation and phosphorylation, are dynamically regulated by a series of enzymes that add or remove these marks in response to signals received by the cell. These PTMS are key contributors to the regulation of processes such as gene expression control and DNA repair. Chromatin immunoprecipitation (chIP) has been an instrumental approach for dissecting the abundance and localization of many histone PTMs throughout the genome in response to diverse perturbations to the cell. Here, a versatile method for performing chIP of post-translationally modified histones from the budding yeast Saccharomyces cerevisiae (S. cerevisiae) is described. This method relies on crosslinking of proteins and DNA using formaldehyde treatment of yeast cultures, generation of yeast lysates by bead beating, solubilization of chromatin fragments by micrococcal nuclease, and immunoprecipitation of histone-DNA complexes. DNA associated with the histone mark of interest is purified and subjected to quantitative PCR analysis to evaluate its enrichment at multiple loci throughout the genome. Representative experiments probing the localization of the histone marks H3K4me2 and H4K16ac in wildtype and mutant yeast are discussed to demonstrate data analysis and interpretation. This method is suitable for a variety of histone PTMs and can be performed with different mutant strains or in the presence of diverse environmental stresses, making it an excellent tool for investigating changes in chromatin dynamics under different conditions.

Chromatin Immunoprecipitation ChIP of Histone Modifications from Saccharomyces cerevisiae

Here, we describe a protocol for chromatin immunoprecipitation of modified histones from the budding yeast Saccharomyces cerevisiae. Immunoprecipitated DNA is subsequently used for quantitative PCR to interrogate the abundance and localization of histone post-translational modifications throughout the genome.

Histone post-translational modifications (PTMs), such as acetylation, methylation and phosphorylation, are dynamically regulated by a series of enzymes ...

Adaptation of Hybridization Capture of Chromatin-associated Proteins for Proteomics to Mammalian Cells

The hybridization capture of chromatin-associated proteins for proteomics (HyCCAPP) technology was initially developed to uncover novel DNA-protein interactions in yeast. It allows analysis of a target region of interest without the need for prior knowledge about likely proteins bound to the target region. This, in theory, allows HyCCAPP to be used to analyze any genomic region of interest, and it provides sufficient flexibility to work in different cell systems. This method is not meant to study binding sites of known transcription factors, a task better suited for Chromatin Immunoprecipitation (ChIP) and ChIP-like methods. The strength of HyCCAPP lies in its ability to explore DNA regions for which there is limited or no knowledge about the proteins bound to it. It can also be a convenient method to avoid biases (present in ChIP-like methods) introduced by protein-based chromatin enrichment using antibodies. Potentially, HyCCAPP can be a powerful tool to uncover truly novel DNA-protein interactions. To date, the technology has been predominantly applied to yeast cells or to high copy repeat sequences in mammalian cells. In order to become the powerful tool we envision, HyCCAPP approaches need to be optimized to efficiently capture single-copy loci in mammalian cells. Here, we present our adaptation of the initial yeast HyCCAPP capture protocol to human cell lines, and show that single-copy chromatin regions can be efficiently isolated with this modified protocol.

This is a method to identify novel DNA-interacting proteins at specific target loci, relying on sequence-specific capture of crosslinked chromatin for subsequent proteomic analyses. No prior knowledge about potential binding proteins, nor cell modifications are required. Initially developed for yeast, the technology has now been adapted for mammalian cells.

The hybridization capture of chromatin-associated proteins for proteomics (HyCCAPP) technology was initially developed to uncover novel DNA-protein ...

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

CRISPR-Mediated Reorganization of Chromatin Loop Structure

Recent studies have clearly shown that long-range, three-dimensional chromatin looping interactions play a significant role in the regulation of gene expression, but whether looping is responsible for or a result of alterations in gene expression is still unknown. Until recently, how chromatin looping affects the regulation of gene activity and cellular function has been relatively ambiguous, and limitations in existing methods to manipulate these structures prevented in-depth exploration of these interactions. To resolve this uncertainty, we engineered a method for selective and reversible chromatin loop re-organization using CRISPR-dCas9 (CLOuD9). The dynamism of the CLOuD9 system has been demonstrated by successful localization of CLOuD9 constructs to target genomic loci to modulate local chromatin conformation. Importantly, the ability to reverse the induced contact and restore the endogenous chromatin conformation has also been confirmed. Modulation of gene expression with this method establishes the capacity to regulate cellular gene expression and underscores the great potential for applications of this technology in creating stable de novo chromatin loops that markedly affect gene expression in the contexts of cancer and development.

Chromatin looping plays a significant role in gene regulation; however, there have been no technological advances that allow for selective and reversible modification of chromatin loops. Here we describe a powerful system for chromatin loop re-organization using CRISPR-dCas9 (CLOuD9), demonstrated to selectively and reversibly modulate gene expression at targeted loci.

Recent studies have clearly shown that long-range, three-dimensional chromatin looping interactions play a significant role in the regulation of gene ...

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Accurate transcription is required for the faithful expression of genetic information. Surprisingly though, little is known about the mechanisms that control the fidelity of transcription. To fill this gap in scientific knowledge, we recently optimized the circle-sequencing assay to detect transcription errors throughout the transcriptome of Saccharomyces cerevisiae, Drosophila melanogaster, and Caenorhabditis elegans. This protocol will provide researchers with a powerful new tool to map the landscape of transcription errors in eukaryotic cells so that the mechanisms that control the fidelity of transcription can be elucidated in unprecedented detail.

This protocol provides researchers with a new tool to monitor the fidelity of transcription in multiple model organisms.

Accurate transcription is required for the faithful expression of genetic information. Surprisingly though, little is known about the mechanisms that ...