This work is supported by the Israel Science Foundation (grant 748/14), Marie Curie Integration grant (CIG)- FP7-PEOPLE-20013-CIG-618763 and I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation grant no. 41/11.

All the procedures were approved by institutional review board of Bar Ilan University and the protocol follows guidelines provided by the committee approving the experiments.
1. Purification of Na&#239;ve Human CD4+ Cells and Polarization to T Helper 1 (Th1) and Th2 Cells
Note: Here we describe the procedure starting from frozen human peripheral blood mononuclear cells (PBMCs). The first step consists of isolating CD4+ cells using microbeads and columns that usually give us more than 95% of CD4+ cells. However, this step may vary according to the preferred protocol in each lab. The protocol for T cell activation and polarization was modified from Jenner et al. (2009)18. Isolation of CD4+ cells from 10 million PBMCs gives rise to 4 - 6 million of CD4+ cells. They are split into two flasks and grown under Th1 and Th2 polarizing conditions yielding 3-5 million Th1 and Th2 cells within just a week.
Note: Cool down the centrifuge to 4 &#176;C before starting.
<ol>
	<li>Thaw 1 mL of human PBMCs (107 cells) in a 50 mL tube containing 10 mL of RPMI medium supplemented with 1% Penicillin-Streptomycin, 2 mM L-glutamine and 10% heat-inactivated fetal bovine serum. Centrifuge at 500 x g for 5 min. Remove the supernatant and resuspend the cells with a sterile 25 mL pipette in 15 mL of supplemented RPMI medium. Transfer the cells (with sterile 25 mL pipette) to a T75 culture flask.</li>
	<li>Leave the cells overnight in a humidified incubator (37 &#176;C, 5% CO2).</li>
	<li>Transfer the floating cells with a sterile 25 mL pipette to 50 mL tube. Determine cell number and viability by trypan blue exclusion.</li>
	<li>Isolate CD4+ cells from 10 million live non-adherent PBMCs by positive selection using CD4+ microbeads and columns according to the manufacturer&#39;s recommendations (see Table of Materials/Equipment) with the following modifications: 107 PBMCs are labeled with 30 &#181;L of CD4 microbeads in 120 &#181;L of 0.5% BSA in PBS.</li>
	<li>Activate the CD4+ T cells for 72 h by rhIL-2 (10 ng/mL), plate-bound anti-CD3 (5 &#181;g/mL) and soluble anti-CD28 (2 &#181;g/mL). For Th1 polarization, add rhIL-12 (20 ng/mL) and anti-IL-4 (10 &#181;g/mL). For Th2 polarization, add rhIL-4 (40 ng/mL) and anti-IFN-&#947; (10 &#181;g/mL).</li>
	<li>Culture the cells for additional 7 days in the presence of rhIL-2 (10 ng/mL) and the same polarizing cytokines (rhIL-12 for Th1 and rhIL-4 for Th2).</li>
</ol>
2. Nuclei Isolation
NOTE: ATAC-seq is performed with intact nuclei. Lysis buffer containing 0.05% nonylphenyl polyethylene glycol (see Table of Materials/Equipment) was calibrated for isolating nuclei from primary human Th1 and Th2 cells. We recommend calibrating this step with the laboratory reagents and cells. An excess of intact cells from insufficient detergent decreases the efficiency of the transposition reaction. Cell lysis efficiency is determined by the number of nuclei (trypan blue positive cells) relative to the total number of cells. 
NOTE: Prepare the lysis buffer (10 mM Tris-HCl, pH 7.5, 10 mM NaCl, 3 mM MgCl2). Cool down a centrifuge with a swing-bucket rotor to 4 &#176;C. Pelleting the cells in a swing-bucket centrifuge instead of a fixed angle centrifuge reduces cell/nuclei loss. To avoid nuclei or cell loss, pipet carefully when discarding the supernatant.
<ol>
	<li>Add fresh nonylphenyl polyethylene glycol (to a final concentration of 0.05%) and 100x protease inhibitors (to a final concentration of 1x) to the cold lysis buffer immediately before use. Keep the buffer on ice.</li>
	<li>Count T cells to determine their amount and viability using trypan blue method. Viability that is lower than 90% results in higher non-specific digestion.</li>
	<li>Transfer 0.5 x 106 T cells (Th1 or Th2) to 1.5 mL microtubes. Spin down at 500 x g for 5 min at 4 &#176;C.</li>
	<li>Resuspend the cell pellet in 1 mL of cold phosphate-buffered saline (PBS) solution. Spin down at 500 x g for 5 min at 4 &#176;C.</li>
	<li>Resuspend the cell pellet in 1 mL of cold lysis buffer (containing nonylphenyl polyethylene glycol and protease inhibitors). Keep the tube on ice. Pipette gently to avoid disrupting the nuclei.</li>
	<li>Quickly take 10 &#181;L and count the cells with an automated cell counter while the microtube with lysed cells is on ice. This step should not exceed five minutes to avoid damaging the nuclei. At least 80% of the cells should be lysed.</li>
	<li>Continue immediately with the transposition reaction. Keep the prepared nuclei on the ice.</li>
</ol>
3. Transposition reaction
NOTE: In this step, isolated nuclei are incubated with prokaryotic Tn5 transposase (TDE1) loaded with adapters for NGS sequencing. Hyperactive Tn5 simultaneously fragments DNA and ligates adapters into accessible regions of the genome (tagmentation process). The ratio between nuclei and Tn5 transposase is critical for preferential cleavage at accessible chromatin. This protocol is calibrated for 100,000 nuclei in a 100 &#956;L reaction volume. However, the reaction can be scaled down.
<ol>
	<li>Set temperature in a thermal shaker to 37 &#176;C.</li>
	<li>Transfer 100,000 nuclei to a 1.5 mL microtube.</li>
	<li>Centrifuge at 500 x g for 10 min at 4 &#176;C and gently remove the supernatant.</li>
	<li>Add the transposition reaction components to the nuclei as specified in Table 1.</li>
	<li>Resuspend by gentle pipetting.</li>
	<li>Incubate the transposition reaction in a thermal shaker at 37 &#176;C for 30 min with gentle shaking (500 rpm). 
	Note: DNA Cleanup is performed by solid-phase reversible immobilization beads19 (see Table of Materials/Equipment) or PCR purification columns. At the end of the cleanup, elute the DNA fragments in 20 &#181;L of 10 mM Tris-HCl, pH 8. Avoid EDTA in the elution buffer.</li>
</ol>
4. PCR Enrichment of ATAC-seq Libraries
NOTE: This step is aimed to amplify the ATAC-seq library i.e., DNA fragments with inserted adapters. To allow mixing of several ATAC-seq libraries in the same next-generation sequencing lane (&#34;multiplexing&#34;) use unindexed Primer 1 (Ad1_noMx)1 for all samples, and a different indexed (barcoded) Primer 2 (Ad 2.1 - 2.24)1 for each sample. The primer sequences are provided in the supplemented Table of Materials/Equipment.
<ol>
	<li>Initial PCR amplification 
	NOTE: The working concentration of Primer 1 (Ad1_noMx) and Primer 2 is 25 &#181;M. All the primers are diluted from original stock of 100 &#181;M to 25 &#181;M. In all of the PCR reactions, use Primer 1 (Ad1_noMx) and only one of the indexed Primer 2.
	<ol>
		<li>Add the components of the PCR reaction as specified in Table 2 to a sterile PCR tube.</li>
		<li>Place PCR tube into a thermal cycler and perform PCR amplification using the cycling conditions detailed in Table 3.</li>
	</ol>
	</li>
	<li>Assessment of number of additional amplification cycles 
	NOTE: The number of additional PCR cycles should yield sufficient amount of library fragments for a successful next-generation sequencing run, while minimized to avoid GC and size bias20. The determination of the number of PCR cycles (N) required for optimal library fragment amplification is done by quantitative PCR (qPCR).
	<ol>
		<li>Dilute Primers 1 (Ad1_noMx) and 2 (used for initial library amplification) from 25 &#181;M to 6.25 &#181;M.</li>
		<li>Add the components to optical PCR tubes or a plate as stated in Table 4.</li>
		<li>Place in a qPCR instrument and cycle as specified in Table 5.</li>
		<li>To estimate the required number of additional amplification cycles (N), plot cycle number on the x-axis and relative fluorescence (RFU) on the y-axis.</li>
		<li>The number of additional amplification cycles (N) is 1/3 of the number of cycles at which the qPCR reaction reached the plateau. Figure 2 provides examples for three ATAC-seq libraries that reached plateau at ~2,350 relative fluorescence units, RFU (thick green line). The number of PCR cycles in which one third of the maximal amount (783 RFU, marked on y-axis) is amplified corresponds to 8 cycles for two of the libraries (red and blue amplification curves) and 9 PCR cycles for the third library (pink).</li>
	</ol>
	</li>
	<li>Final PCR amplification
	<ol>
		<li>Amplify the remaining 45 &#181;L of the PCR reaction. Place a PCR tube containing amplification reaction from step 4.1.2 in a thermal cycler. Run the PCR program described in Table 6. Use the previously determined (step 4.2.5) number of amplification cycles (N).</li>
	</ol>
	</li>
</ol>
5. Size Selection of ATAC-Seq Libraries
NOTE: In our experience, size selection of amplified ATAC-seq libraries improves next-generation sequencing results because it eliminates high molecular weight library fragments from the final ATAC-seq library. 
NOTE: Allow the magnetic beads to warm to room temperature 30 min before use. 
Prepare fresh 70% ethanol in nuclease-free water.
<ol>
	<li>Resuspend the magnetic beads by mixing.</li>
	<li>Add nuclease-free water to the ATAC-seq libraries (obtained in step 4.3.1.) and bring up to 100 &#181;L.</li>
	<li>Add 50 &#181;L (0.5x) of resuspended DNA-binding magnetic beads to 100 &#181;L of amplified libraries. Mix by pipetting up and down at least 10 times. Incubate samples for 5 min at room temperature. If necessary, quickly spin down the microtubes.</li>
	<li>Place the tube on an appropriate magnetic stand for 2 min to separate the magnetic beads from the supernatant. After 2 min, transfer the supernatant to a new microtube.</li>
	<li>Measure the volume of the supernatant by pipetting and add 0.7x of magnetic beads. Mix by pipetting up and down at least 10 times.</li>
	<li>Incubate 5 min at room temperature. Place on a magnetic stand for 2 min.</li>
	<li>After the 2 min incubation, discard the supernatant. Add 200 &#181;L freshly made 70% ethanol to wash the beads while the tubes are on the magnetic stand.</li>
	<li>Keep the microtube on the magnet for 30 s and then discard the ethanol.Repeat step 5.7.for two final ethanol washes.</li>
	<li>Completely remove the remaining ethanol and let the beads air-dry for 5 min while the tube is on the magnet. If necessary, briefly spin the microtube. Remove the traces of ethanol with a p10 pipette tip.</li>
	<li>Remove the microtube from the magnet and add 22 &#181;L of 10 mM Tris-HCl, pH 8. Do not elute the ATAC-seq libraries in buffer containing EDTA.</li>
	<li>Incubate the tube for 2 min at room temperature and then place on the magnetic stand.</li>
	<li>When the solution is clear, transfer 20 &#181;L of eluted libraries to a new sterile microtube.</li>
	<li>Store the size selected ATAC-seq libraries at -20 &#176;C.</li>
</ol>
6. Quality Analysis of the ATAC-Seq Libraries
<ol>
	<li>Validation of the quality of ATAC-seq libraries by Real-Time PCR 
	NOTE: It is important to assess the signal to noise ratio of the ATAC-seq libraries prior to next-generation sequencing. This is done by determining the relative amount of DNA fragments from accessible and inaccessible loci using quantitative PCR (qPCR). The inaccessible loci (negative control, chr1:48,137,860-48,137,934 and chr1:193,093,748-193,093,827) are amplified by primer pairs 1 and 2. The accessible loci (positive control, chr19:30,336,166-30,336,253 and chr19:11546154-11546237) are amplified by primer pairs 3 and 4. Positive and negative loci were defined from chromatin accessibility (DHS-seq) profiles of human CD4+ cells (ENCODE accessions ENCSR000EQE and ENCSR000EQG). Negative primer 1 is located in a large heterochromatic intergenic region (230 kb from TRADB2 and 88 kb from FOXD2). Negative control region 2 is in within the first intron of CDC73 gene. Positive primer pair 3 is within an open chromatin region downstream of the Cyclin E (CCNE1) gene while positive primer pair 4 is centered within the promoter of protein kinase C substrate 80K-H (PRKCSH). Importantly, these control loci show a similar pattern of accessibility in other human cell types from the ENCODE project3, suggesting that they can be applied to monitor ATAC-seq libraries from a broad spectrum of human cell types. Primer efficiency and specificity of all primer pairs was verified by qPCR on a serial dilution of genomic DNA (from human Th cells) and a melting curve analysis of obtained amplified products.
	<ol>
		<li>Isolate genomic DNA using a commercially available kit (see Table of Materials/Equipment).</li>
		<li>Dilute the amplified ATAC-seq library 1:10 (1 &#181;L library + 9 &#181;L of nuclease-free water) and genomic DNA to ~5 ng/&#181;L.</li>
		<li>Prepare reaction mixture (Table 7) for each positive and negative control primer pair, taking into account that the reactions are performed in triplicate.</li>
		<li>Incubate in qPCR thermal cycler according to the protocol recommended by qPCR master mix supplier.</li>
		<li>Analyze the results in qPCR instrument&#39;s software (see Table of Materials/Equipment). Choose genomic DNA as a control sample. The obtained values represent an enrichment of accessible regions (amplified by positive control primers). An example is shown in Table 8. 
		NOTE: Estimation of the average library size and concentration: the size distribution of DNA fragments from ATAC-seq libraries is determined by high-sensitivity automated electrophoresis systems according to the manufacturer&#39;s instructions. It is advisable to measure the sample concentration on a fluorometer using dsDNA high-sensitivity kit and at least 2 &#181;L of each DNA sample. 
		NOTE: Next-generation sequencing - prior to multiplexing the libraries, calculate the molarity of each ATAC-seq library by using the formula: (ng/&#181;L x 106)/(660 x average library fragment length). Aim for &#62; 30 million reads of each ATAC-seq library to assess open chromatin regions of human samples. If you wish to determine if the library is good enough for NGS sequencing, initially aim for ~10 million reads (5% of the sequencing lane on DNA sequencing instrument in rapid run mode). Keep in mind that to infer nucleosome positioning, paired-end sequencing is needed1.</li>
	</ol>
	</li>
</ol>
7. Analysis of the Obtained Next-Generation Sequencing Results
<ol>
	<li>Infer the quality of the sequencing reads by inspecting the FastQC files, separately for every library.</li>
	<li>Align the reads to human reference genome (hg19 assembly) using Bowtie21 software in the Unix/Linux environment. The command is &#39;bowtie -m 1 -q -S genome directory reads.fastq output_aligned.sam&#39;. Genome directory stands for the folder where the genome indexes of Bowtie are stored. The parameter -m 1 is for not allowing alignment of reads to more than one locus in the genome, -q is for the input file that should be in fastq format, -S is for the output that is in SAM format.</li>
	<li>Remove duplicate reads using SAMtools22 rmdup option in the Unix/Linux environment. The commands are &#39;samtools view -S output_aligned.sam -b | samtools sort -o -output_aligned &#62; output_aligned.bam&#39;, 
	samtools rmdup -s output_aligned.bam output_aligned _rmdup.bam&#39;. The first command, view, changes the SAM format into BAM format which is then sorted. The option of rmdup is then applied on the sorted BAM file. Optionally one can adjust the reads for the transposon insertion site, as described in the original ATAC-seq paper1.This is done using BEDtools commands23 in the Unix/Linux environment. The commands are &#39;bamToBed -i output_aligned _rmdup.bam &#62; output_aligned _rmdup.bed &#39;, &#39;shiftBed -i output_aligned _rmdup.bed -p 4 -m -5 -g genome &#62; output_aligned _rmdup_adjusted.bed&#39;. The first command, bamTobed, changes the BAM format into BED format which can then be used for the shiftBed command. The genome file is a tab delimited file that contains the length of each chromosome in the genome. The file is usually added in the BEDtools directory.</li>
	<li>Perform peak calling using model-based analysis of ChIP-seq (MACS2)24 software in the Unix/Linux environment on the shifted BED file with the following parameters: --nomodel --extsize 75 --shift -30. These parameters are used to adjust the reads so that the transposon insertion site is in the middle of each sequencing read.</li>
</ol>

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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=Refined+DNase-seq+protocol+and+data+analysis+reveals+intrinsic+bias+in+transcription+factor+footprint+identification.">Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification.</a> Nat Methods. 11 (1), 73-78 (2013).</li><li>Madrigal, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+Accounting+for+Sequence-Specific+Bias+in+Genome-Wide+Chromatin+Accessibility+Experiments:+Recent+Advances+and+Contradictions.">On Accounting for Sequence-Specific Bias in Genome-Wide Chromatin Accessibility Experiments: Recent Advances and Contradictions.</a> Front Bioeng Biotechnol. 3, 1-4 (2015).</li><li>Qin, Q., 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=ChiLin:+a+comprehensive+ChIP-seq+and+DNase-seq+quality+control+and+analysis+pipeline.">ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline.</a> BMC Bioinformatics. 17 (1), (2016).</li><li>Bao, 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=A+novel+ATAC-seq+approach+reveals+lineage-specific+reinforcement+of+the+open+chromatin+landscape+via+cooperation+between+BAF+and+p63.">A novel ATAC-seq approach reveals lineage-specific reinforcement of the open chromatin landscape via cooperation between BAF and p63.</a> Genome Biol. 16 (1), 284 (2015).</li><li>Maurano, M. 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=Systematic+localization+of+common+disease-associated+variation+in+regulatory+DNA.">Systematic localization of common disease-associated variation in regulatory DNA.</a> Science. 337 (6099), 1190-1195 (2012).</li></ol>

The authors have nothing to disclose.

The ATAC-seq protocol described here has been successfully employed for the analysis of accessible chromatin in primary cells (human Th1, Th2 cells, and B cells) as well as the cultured cell lines (MCF10A human breast cancer cells and U261 glioblastoma cells). Applying ATAC-seq to other cell types may require some protocol optimization, especially in the lysis step. If the concentration of non-ionic detergent is too high, there may be a higher percentage of mitochondrial DNA contamination. This can be reduced by decreasing the detergent concentration in the lysis buffer without reducing the nuclei yield. In our experience, lysis buffer with 0.05% of detergent gave the most satisfactory results. In addition, spinning the nuclei in a swing-bucket instead of fixed angle rotor allowed reducing the G force to 500, which reduced the mitochondria in the pellet. Researchers may also test other types of detergents, for example, digitonin17. However, even with optimized lysis conditions, mtDNA contamination is inevitable. To completely remove the mtDNA, the CRISPR/Cas9 system can be used15. In this case, ATAC-seq libraries are incubated with sgRNAs to target mtDNA and Cas9 nuclease to digest mtDNA15.
The number of nuclei required for this ATAC-seq protocol (100,000) may be limiting in cases where cell number from clinical samples is scarce7. ATAC-seq has been successfully scaled down to 5,000 and 500 cells1,13,17 by reducing the reaction volume1,13, performing cleanup with magnetic beads instead of with columns13, or avoiding the cleanup step1. In addition, single-cell ATAC-seq (scATAC-seq) may be performed using a microfluidic device to separate individual nuclei16. Notably, other methods for measuring chromatin accessibility, such as DNase-seq and FAIRE-seq, require more starting material and a few more days to perform the experiment.
It is now widely appreciated that biases in various NGS methods are common phenomena25. One of the causes for variations in different chromatin accessibility measures is the enzymatic cleavage step25. It has been shown that DNase I shows cleavage bias26 and now it is recognized that Tn5 transposase shows cleavage preference as well27. Fortunately, the potential bias can be identified computationally by using a quality control pipeline such as ChiLin28. Another common source of bias is the PCR amplification step20,25. This frequently manifests as a bias for the amplification of GC-rich fragments25. Since the bias increases with every PCR amplification step, we do not exceed 9 additional cycles (N) in the final PCR amplification of ATAC-seq libraries.
The proper ratio between Tn5 transposase and nuclei is critical for successful ATAC-seq2. An excess of enzyme would lead to &#34;over transposition&#34; in inaccessible loci and high background. This is reflected in high amplification of the negative control regions in the qPCR quality control step. An excess of nuclei would lead to &#34;under-transposition&#34;. In this case, too distant cleavage sites will result in fewer PCR-amplified fragments and low library complexity. To determine the number of nuclei accurately, we introduced an additional counting step after cell lysis and prior to the transposition reaction.
Chromatin accessibility is an important epigenetic regulatory layer as it permits the activity of transcription regulators at specific genomic locations. Thus, the DNA sequence within the accessible chromatin profile provides a wealth of information about the identity and target loci of tens of possible transcription factors. Combining this information (obtained by ATAC-seq) with an RNA expression profile allows a focus on the relevant transcription factors that can be further analyzed by ChIP-seq13,22. In addition, only 10% of disease-associated polymorphisms are in the coding genome30. Thus applying ATAC-seq to clinical samples can reveal which of the non-coding variants are at regulatory elements that may affect gene regulation in the disease state (for example, in systemic lupus erythematosus8). We hope that this ATAC-seq protocol will help and encourage interested investigators to use this powerful method to advance their research.

ATAC-seq1,2 is a robust method that enables identification of regulatory3 open chromatin regions and nucleosome positioning. This information is applied for inferring the location, identity, and activity of transcription factors. The method&#39;s sensitivity for measuring quantitative variations in chromatin structure allows the study of the activity of chromatin factors, including chromatin remodelers and modifiers, as well as the transcriptional activity of RNA polymerase II1. Thus ATAC-seq provides a powerful and unbiased approach for deciphering mechanisms that govern transcriptional regulation in any cell type of interest. We describe the adaptation of ATAC-seq to primary human Th1 and Th2 cells.
In ATAC-seq, hyperactive Tn5 transposase loaded with adaptors for next-generation sequencing (NGS) couples DNA fragmentation with tagging of DNA with adaptors (i.e., the &#34;tagmentation&#34; process)1. Following PCR amplification, the resulting DNA libraries are ready for next-generation sequencing (Figure 1). The preferential tagmentation of accessible chromatin is detected by the analysis of local enrichment of ATAC-seq sequencing reads.
The short experimental procedure and requirement for less starting material, relative to other methods for measuring chromatin accessibility and nucleosomal positioning such as DNase-seq4, FAIRE-seq5, and MNase-seq6, has promoted the use of ATAC-seq in multiple biological systems including human primary cells1,7 and clinical samples8, as well as unicellular organisms9, plants10, fruit flies11, and various mammals12.
The identity of transcription factors which are bound to accessible loci can be uncovered by analyzing the enrichment of their binding sequence motifs or combining ATAC-seq with chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq). This approach enabled the identification of lineage-specific transcription factors important for hematopoiesis in mouse13. The unbiased and global nature of ATAC-seq allows studying gene regulation in organisms for which reagents such as antibodies for ChIP analysis are not available. For example, evolutionary variations in cis-regulatory regions have been identified by studying cranial neural crest cells from humans and chimpanzees14, developmental variations in regulatory elements during early mouse embryogenesis15, changes in the regulatory landscape during a life cycle of unicellular C. owzarzaki9, and the evolution of promoters and enhancers across 20 mammal species12.
ATAC-seq has also been instrumental for measuring chromatin accessibility in single cells, thus revealing variability within cell populations, which usually evades genome-wide studies7,16. In addition, ATAC-seq can be used to study changes that occur in DNA regulatory regions in disease conditions, in which samples are rare. For example, ATAC-seq can be used to study changes in the regulatory landscape during the onset of acute myeloid leukemia (AML)17 or Ras-driven oncogenesis11.

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.

The final outcome of this protocol is an ATAC-seq library of typically 3 - 20 ng/&#181;L. When run on a system for DNA integrity analysis (see Table of Materials/Equipment), they show ladder-like appearance2 (Figure 3A). The average size of DNA fragments is typically ~450 - 530 bp.
Proper quality control of the ATAC-seq libraries prior to performing next-generation sequencing is important to save time and money. We consider the libraries suitable for next-generation sequencing (NGS) when the enrichment of positive controls is more than 25- and 75-fold (for primer pairs 3 and 4, respectively) relative to negative controls (Figure 3B) and when they show the previously mentioned nucleosomal, ladder-like appearance. When analyzing qPCR data, we are also verifying that the Cq values for negative and positive control primers are similar in the reactions with the genomic DNA as a template and that the Cq values for the negative control regions (in the reactions with ATAC-seq DNA fragments) are constant between the experiments. For example, in the case of suddenly lower Cq values, we suspect that the nuclei were over-transposed and thus DNA fragments originating from heterochromatin regions are over-represented. Moreover, if the gel image (obtained by high-sensitivity tape-based electrophoresis) of ATAC-seq libraries indicates the presence of the adaptors (~120 bp), excessive DNA degradation (the majority of the fragments are ~200 bp), or large fragments (over 1 kb), we would not continue to the NGS step.
Furthermore, we always perform initial NGS in which we aim for 10 million reads per library. If the results of this sequencing are satisfactory (the sample passes all the parameters in FastQC report file and we can obtain 1000 - 2000 peaks after performing peak calling), the libraries are sequenced more deeply (more than 30 million reads/ATAC-seq library).
In ATAC-seq experiments on mammalian cells, anywhere from ~ 30 - 70% of the sequenced reads can come from mtDNA10. In contrast, our libraries contained 6-20% reads mapped to the mitochondrial genome. This is lower than the reported 46% in the ATAC-seq library from human CD4+ T lymphocytes1. After eliminating these contaminating reads, we were left with ~7 - 32 million unique reads mapping to the reference human genome (58%-91% of all reads). From these, 0.1 - 2 million reads (6.8% - 12% of all reads) were in ATAC-seq peaks (Figure 4).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56313/56313fig1.jpg" /> 
Figure 1. Workflow of experimental steps. Representation of the major steps in this ATAC-seq protocol. Stopping points are indicated by yellow hexagons. An optional step is represented with an orange hexagon. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56313/56313fig1large.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/56313/56313fig2.jpg" /> 
Figure 2. Calculation of the additional number of PCR cycles required for the final enrichment of ATAC-seq libraries. PCR amplification curves for three different ATAC seq libraries are shown in red, blue and pink. The amplification reactions reached a plateau at 2,350 RFU (upper green&#160;horizontal line). The number of additional PCR cycles intersects with 783 RFU (2,350/3) on the amplification curve. Two libraries (red and blue) require 8 additional amplification cycles while the third library (pink) requires 9 cycles. Non-template control (NTC) is shown as the lower green line. X-axis, cycle number. Y-axis, RFU units. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56313/56313fig2large.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/56313/56313fig3.jpg" /> 
Figure 3. Quality control analysis of ATAC-seq libraries. (A) Results of tape-based automated electrophoresis of amplified ATAC-seq libraries. L, ladder; A-D, libraries of biological repeats from Th1 and Th2 cells. (B) qPCR quality control analysis of ATAC-seq libraries. Genomic DNA and four ATAC-seq libraries were amplified by negative control primer pairs (1 and 2) and positive control primers (3 and 4). The obtained values for ATAC-seq libraries (blue) were first normalized to the amplification levels of genomic DNA (arbitrarily set to a value of 1; red). Subsequently, values for the positive control regions were normalized to the negative control regions (lower chart). Libraries #1 and #2 were sent to NGS sequencing. The values represent mean &#177; SEM. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56313/56313fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56313/56313fig4.jpg" /> 
Figure 4. Genome browser snapsh ots of accessible chromatin regions in Th1 and Th2 cells. ATAC-seq tracks are shown for NFKB1, JUN, CD28, IFNG (expressed only in Th1) and IL4 and IL13 (expressed only in Th2) loci in Th1 and Th2 cells (two biological repeats for each). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56313/56313fig4large.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>TD buffer</td>
			<td>50</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>TDE1 transposase</td>
			<td>5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>45</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>100</td>
			<td>&#956;L</td>
		</tr>
	</tbody>
</table>
Table 1: Preparation of transposition reaction mixture.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>ATAC-seq library</td>
			<td>15</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Primer 1 (Ad1_noMx) *</td>
			<td>2.5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Primer 2 *</td>
			<td>2.5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>NEBNext High-Fidelity 2 x PCR Master Mix**</td>
			<td>25</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>50</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="3">*Final concentration of each primer is 1.25 &#956;M.</td>
		</tr>
		<tr>
			<td colspan="3">**PCR reagent provided in the kit are not recommended</td>
		</tr>
		<tr>
			<td colspan="3">&#160;(Buenrostro et al., 2015. ATAC-seq: A method for assaying chromatin accessibility genome-wide) .&#160;</td>
		</tr>
		<tr>
			<td colspan="3">In addition, we have also performed successful amplifications with&#160;</td>
		</tr>
		<tr>
			<td colspan="3">NEBNext Q5 Hot Start HiFi PCR Master Mix (extension temperature is 65 &#176;C).</td>
		</tr>
	</tbody>
</table>
Table 2: Components of initial PCR reaction mix (step 5.1.1.).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>CYCLE STEP</td>
			<td>TEMPERATURE</td>
			<td>TIME</td>
			<td>CYCLES</td>
		</tr>
		<tr>
			<td>Extension*</td>
			<td>72 &#176;C</td>
			<td>5 min</td>
			<td rowspan="2">1</td>
		</tr>
		<tr>
			<td>Initial Denaturation</td>
			<td>98 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Denaturation</td>
			<td>98 &#176;C</td>
			<td>10 s</td>
			<td rowspan="3">5</td>
		</tr>
		<tr>
			<td>Annealing</td>
			<td>63 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Extension</td>
			<td>72 &#176;C</td>
			<td>3 min</td>
		</tr>
		<tr>
			<td>Hold</td>
			<td>4 &#176;C</td>
			<td>&#8734;</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="4">*This step is required to extend both&#160;</td>
		</tr>
		<tr>
			<td colspan="4">ends of the primers after transposition reaction.</td>
		</tr>
	</tbody>
</table>
Table 3: PCR cycling conditions for initial library amplification (step 5.1.2.)
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Aliquot of PCR reaction (step 4.1.1) *</td>
			<td>5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Primer 1 (Ad1_noMx)**</td>
			<td>1</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Primer 2</td>
			<td>1</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>2x SYBR master mix ***</td>
			<td>7.5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>0.5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>15</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="3">*For non-template control instead of the DNA template add ultra-pure water.&#160;</td>
		</tr>
		<tr>
			<td colspan="3">**The final concentration of each primer is 417 nM.</td>
		</tr>
		<tr>
			<td colspan="3">***Use preferred master mix for qPCR.&#160;</td>
		</tr>
		<tr>
			<td colspan="3">It should contain polymerase, dNTPs, MgCl2, and fluorescent dye.</td>
		</tr>
	</tbody>
</table>
Table 4: Preparation of qPCR reaction mixture (step 5.2.2).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>CYCLE STEP</td>
			<td>TEMPERATURE</td>
			<td>TIME</td>
			<td>CYCLES</td>
		</tr>
		<tr>
			<td>Initial denaturation</td>
			<td>98 &#176;C</td>
			<td>30 s</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Denaturation</td>
			<td>98 &#176;C</td>
			<td>10 s</td>
			<td rowspan="3">20</td>
		</tr>
		<tr>
			<td>Annealing</td>
			<td>63 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Extension</td>
			<td>72 &#176;C</td>
			<td>3 min</td>
		</tr>
		<tr>
			<td>Hold</td>
			<td>4 &#176;C</td>
			<td>&#8734;</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 5: Cycling conditions for qPCR-based assesment of additional number of amplification cycles (N) (step 5.2.3.)
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>CYCLE STEP</td>
			<td>TEMPERATURE</td>
			<td>TIME</td>
			<td>CYCLES</td>
		</tr>
		<tr>
			<td>Initial denaturation</td>
			<td>98 &#176;C</td>
			<td>30 s</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Denaturation</td>
			<td>98 &#176;C</td>
			<td>10 s</td>
			<td rowspan="3">N</td>
		</tr>
		<tr>
			<td>Annealing</td>
			<td>63 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Extension</td>
			<td>72 &#176;C</td>
			<td>3 min</td>
		</tr>
		<tr>
			<td>Hold</td>
			<td>4 &#176;C</td>
			<td>&#8734;</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 6: Cycling conditions for the final PCR enrichment step (step 5.3.).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="3">For a single&#160; PCR reaction:&#160;</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Dilution of the library of genomic DNA</td>
			<td>2.5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>10 &#956;M Primer F (F1 or F2 or F3 or F4)*</td>
			<td>0.3</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>10 &#956;M Primer R (R1 or R2 or R3 or R4)**</td>
			<td>0.3</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>2x SYBR master mix ***</td>
			<td>5</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>1.9</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>10</td>
			<td>&#956;L</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="3">*The final concentration of each primer in the reaction mixture is 300 nM.</td>
		</tr>
		<tr>
			<td colspan="3">**If using primer F1 than the R primer should be R1 etc.</td>
		</tr>
		<tr>
			<td colspan="3">***Use preferred 2x master mix suitable for the qPCR instrument in your laboratory.</td>
		</tr>
	</tbody>
</table>
Table 7: Reaction conditions for QC analysis (step 7.1.3.).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Target</td>
			<td>Sample</td>
			<td>Mean Cq</td>
			<td>Cq SEM</td>
			<td>Relative quantity</td>
			<td>Normalized</td>
		</tr>
		<tr>
			<td rowspan="2">1</td>
			<td rowspan="4">Negative control</td>
			<td>ATAC-seq</td>
			<td>30.39</td>
			<td>0.11</td>
			<td>1</td>
			<td>1.01</td>
		</tr>
		<tr>
			<td>gDNA</td>
			<td>30.4</td>
			<td>0.16</td>
			<td>0.99</td>
			<td>1</td>
		</tr>
		<tr>
			<td rowspan="2">2</td>
			<td>ATAC-seq</td>
			<td>30.3</td>
			<td>0.18</td>
			<td>1</td>
			<td>1</td>
		</tr>
		<tr>
			<td>gDNA</td>
			<td>30.34</td>
			<td>0.09</td>
			<td>0.99</td>
			<td>1</td>
		</tr>
		<tr>
			<td rowspan="2">3</td>
			<td rowspan="4">Positive control</td>
			<td>ATAC-seq</td>
			<td>23.27</td>
			<td>0.03</td>
			<td>1</td>
			<td>173.14</td>
		</tr>
		<tr>
			<td>gDNA</td>
			<td>30.7</td>
			<td>0.06</td>
			<td>0.01</td>
			<td>1</td>
		</tr>
		<tr>
			<td rowspan="2">4</td>
			<td>ATAC-seq</td>
			<td>21.55</td>
			<td>0.24</td>
			<td>1</td>
			<td>750.31</td>
		</tr>
		<tr>
			<td>gDNA</td>
			<td>31.1</td>
			<td>0.03</td>
			<td>0</td>
			<td>1</td>
		</tr>
	</tbody>
</table>
Table 8: Calculation of the enrichment of positive controls over negative controls (step 7.1.5.).

Watch this Scientific Journal Video about Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq at JoVE.com

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

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 ...

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Nanyang Technological University

Research

JoVE Journal

Genetics

17.9K Views.  Bar-Ilan University. 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.

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

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 ...

Chromatin Immunoprecipitation (ChIP) in Mouse T-cell Lines

Signaling pathways regulate gene expression programs via the modulation of the chromatin structure at different levels, such as by post-translational modifications (PTMs) of histone tails, the exchange of canonical histones with histone variants, and nucleosome eviction. Such regulation requires the binding of signal-sensitive transcription factors (TFs) that recruit chromatin-modifying enzymes at regulatory elements defined as enhancers. Understanding how signaling cascades regulate enhancer activity requires a comprehensive analysis of the binding of TFs, chromatin modifying enzymes, and the occupancy of specific histone marks and histone variants. Chromatin immunoprecipitation (ChIP) assays utilize highly specific antibodies to immunoprecipitate specific protein/DNA complexes. The subsequent analysis of the purified DNA allows for the identification the region occupied by the protein recognized by the antibody. This work describes a protocol to efficiently perform ChIP of histone proteins in a mature mouse T-cell line. The presented protocol allows for the performance of ChIP assays in a reasonable timeframe and with high reproducibility.

Chromatin Immunoprecipitation ChIP in Mouse T-cell Lines

This work describes a protocol for chromatin immunoprecipitation (ChIP) using a mature mouse T-cell line. This protocol is suitable to investigate the distribution of specific histone marks at specific promoter sites or genome-wide.

Signaling pathways regulate gene expression programs via the modulation of the chromatin structure at different levels, such as by post-translational ...

Retroviral Scanning: Mapping MLV Integration Sites to Define Cell-specific Regulatory Regions

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV integration sites can be used as functional markers of active regulatory elements. Here, we present a retroviral scanning tool, which allows the genome-wide identification of cell-specific enhancers and promoters. Briefly, the target cell population is transduced with an mLV-derived vector and genomic DNA is digested with a frequently cutting restriction enzyme. After ligation of genomic fragments with a compatible DNA linker, linker-mediated polymerase chain reaction (LM-PCR) allows the amplification of the virus-host genome junctions. Massive sequencing of the amplicons is used to define the mLV integration profile genome-wide. Finally, clusters of recurrent integrations are defined to identify cell-specific regulatory regions, responsible for the activation of cell-type specific transcriptional programs.
The retroviral scanning tool allows the genome-wide identification of cell-specific promoters and enhancers in prospectively isolated target cell populations. Notably, retroviral scanning represents an instrumental technique for the retrospective identification of rare populations (e.g. somatic stem cells) that lack robust markers for prospective isolation.

Here, we describe a protocol for genome-wide mapping of the integration sites of Moloney murine leukemia virus-based retroviral vectors in human cells.

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV ...

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 ...

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 ...

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 ...

ATAC-seq Assay with Low Mitochondrial DNA Contamination from Primary Human CD4+ T Lymphocytes

ATAC-seq has become a widely used methodology in the study of epigenetics due to its rapid and simple approach to mapping genome-wide accessible chromatin. In this paper we present an improved ATAC-seq protocol that reduces contaminating mitochondrial DNA reads. While previous ATAC-seq protocols have struggled with an average of 50% contaminating mitochondrial DNA reads, the optimized&#160;lysis buffer introduced in this protocol reduces mitochondrial DNA contamination to an average of 3%. This improved ATAC-seq protocol allows for a near 50% reduction in the sequencing cost. We demonstrate how these high-quality ATAC-seq libraries can be prepared from activated CD4+ lymphocytes, providing step-by-step instructions from CD4+ lymphocyte isolation from whole blood through data analysis. This improved ATAC-seq protocol has been validated in a wide range of cell types and will be of immediate use to researchers studying chromatin accessibility.

Here, we present a protocol to perform an assay for transposase-accessible chromatin sequencing (ATAC-seq) on activated CD4+ human lymphocytes. The protocol has been modified to minimize contaminating mitochondrial DNA reads from 50% to 3% through the introduction of a new lysis buffer.