Decision letter: Efficient chromatin accessibility mapping in situ by nucleosome-tethered tagmentation

Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Chromatin accessibility mapping is a powerful approach to identify potential regulatory elements. A popular example is ATAC-seq, whereby Tn5 transposase inserts sequencing adapters into accessible DNA (‘tagmentation’). CUT&Tag is a tagmentation-based epigenomic profiling method in which antibody tethering of Tn5 to a chromatin epitope of interest profiles specific chromatin features in small samples and single cells. Here, we show that by simply modifying the tagmentation conditions for histone H3K4me2 or H3K4me3 CUT&Tag, antibody-tethered tagmentation of accessible DNA sites is redirected to produce chromatin accessibility maps that are indistinguishable from the best ATAC-seq maps. Thus, chromatin accessibility maps can be produced in parallel with CUT&Tag maps of other epitopes with all steps from nuclei to amplified sequencing-ready libraries performed in single PCR tubes in the laboratory or on a home workbench. As H3K4 methylation is produced by transcription at promoters and enhancers, our method identifies transcription-coupled accessible regulatory sites. eLife digest Cells keep their DNA tidy by wrapping it into structures called nucleosomes. Each of these structures contains a short section of DNA wound around a cluster of proteins called histones. Not only do nucleosomes keep the genetic code organized, they also control whether the proteins that can switch genes on or off have access to the DNA. When genes turn on, the nucleosomes unwrap, exposing sections of genetic code called 'gene regulatory elements'. These elements attract the proteins that help read and copy nearby genes so the cell can make new proteins. Determining which regulatory elements are exposed at any given time can provide useful information about what is happening inside a cell, but the procedure can be expensive. The most popular way to map which regulatory elements are exposed is using a technique called Assay for Transposase-Accessible Chromatin using sequencing, or ATAC-seq for short. The 'transposase' in the acronym is an enzyme that cuts areas of DNA that are not wound around histones and prepares them for detection by DNA sequencing. Unfortunately, the data from ATAC-seq are often noisy (there are random factors that produce a signal that is detected but is not a ‘real’ result), so more sequencing is required to differentiate between real signal and noise, increasing the expense of ATAC-seq experiments. Furthermore, although ATAC-seq can identify unspooled sections of DNA, it cannot provide a direct connection between active genes and unwrapped DNA. To find the link between unspooled DNA and active genes, Henikoff et al. adapted a technique called CUT&Tag. Like ATAC-seq, it also uses transposases to cut the genome, but it allows more control over where the cuts occur. When genes are switched on, the proteins reading them leave chemical marks on the histones they pass. CUT&Tag attaches a transposase to a molecule that recognizes and binds to those marks. This allowed Henikoff et al. to guide the transposases to unspooled regions of DNA bordering active genes. The maps of gene regulatory elements produced using this method were the same as the best ATAC-seq maps. And, because the transposases could only access gaps near active genes, the data provided evidence that genes switching on leads to regulatory elements in the genome unwrapping. This new technique is simple enough that Henikoff et al. were able to perform it from home on the countertop of a laundry room. By tethering the transposases to histone marks it was possible to detect unspooled DNA that was active more efficiently than with ATAC-seq. This lowers laboratory costs by reducing the cost of DNA sequencing, and may also improve the detection of gaps between nucleosomes in single cells. Introduction Identification of DNA accessibility in the chromatin landscape has been used to infer active transcription ever since the seminal description of DNaseI hypersensitivity by Weintraub and Groudine more than 40 years ago (Weintraub and Groudine, 1976). Because nucleosomes occupy most of the eukaryotic chromatin landscape and regulatory elements are mostly free of nucleosomes when they are active, DNA accessibility mapping can potentially identify active regulatory elements genome-wide. Several additional strategies have been introduced to identify regulatory elements by DNA accessibility mapping, including digestion with Micrococcal Nuclease (MNase) (Reeves, 1978) or restriction enzymes (Jack and Eggert, 1990), DNA methylation (Gottschling, 1992), physical fragmentation (Schwartz et al., 2005) and transposon insertion (Bownes, 1990). With the advent of genome-scale mapping platforms, beginning with microarrays and later short-read DNA sequencing, mapping regulatory elements based on DNaseI hypersensitivity became routine (Crawford et al., 2004; Dorschner et al., 2004). Later innovations included FAIRE (Giresi et al., 2007) and Sono-Seq (Auerbach et al., 2009), based on physical fragmentation and differential recovery of cross-linked chromatin, and ATAC-seq (Buenrostro et al., 2013), based on preferential insertion of the Tn5 transposase. The speed and simplicity of ATAC-seq, in which the cut-and-paste transposition reaction inserts sequencing adapters in the most accessible genomic regions (tagmentation), has led to its widespread adoption in many laboratories for mapping presumed regulatory elements. For all of these DNA accessibility mapping strategies, it is generally unknown what process is responsible for creating any particular accessible sites within the chromatin landscape. Furthermore accessibility is not all-or-none, with the median difference between an accessible and a non-accessible site in DNA estimated to be only ~20%, with no sites completely accessible or inaccessible in a population of cells (Chereji et al., 2019; Oberbeckmann et al., 2019). Despite these uncertainties, DNA accessibility mapping has successfully predicted the locations of active gene enhancers and promoters genome-wide, with excellent correspondence between methods based on very different strategies (Karabacak Calviello et al., 2019). This is likely because DNA accessibility mapping strategies rely on the fact that nucleosomes have evolved to repress transcription by blocking sites of pre-initiation complex formation and transcription factor binding (Kornberg and Lorch, 2020), and so creating and maintaining a nucleosome-depleted region (NDR) is a pre-requisite for promoter and enhancer function. A popular alternative to DNA accessibility mapping for regulatory element identification is to map nucleosomes that border NDRs, typically by histone marks, including ‘active’ histone modifications, such as H3K4 methylation and H3K27 acetylation, or histone variants incorporated during transcription, such as H2A.Z and H3.3. The rationale for this mapping strategy is that the enzymes that modify histone tails and the chaperones that deposit nucleosome subunits are most active close to the sites of initiation of transcription, which typically occurs bidirectionally at both gene promoters and enhancers to produce stable mRNAs and unstable enhancer RNAs. Although the marks left behind by active transcriptional initiation ‘point back’ to the NDR, this cause-effect connection between the NDR and the histone marks is only by inference (Wang et al., 2020), and direct evidence is lacking that a histone mark is associated with an NDR. Here, we show that a simple modification of our Cleavage Under Targets and Tagmentation (CUT&Tag) method for antibody-tethered in situ tagmentation can identify NDRs genome-wide at regulatory elements adjacent to transcription-associated histone marks in human cells. We provide evidence that reducing the ionic concentration during tagmentation preferentially attracts Tn5 tethered to the H3K4me2 histone modification via a Protein A/G fusion to the nearby NDR, shifting the site of tagmentation from nucleosomes bordering the NDR to the NDR itself. Almost all transcription-coupled accessible sites correspond to ATAC-seq sites and vice-versa, and lie upstream of paused RNA Polymerase II (RNAPII). ‘CUTAC’ (Cleavage Under Targeted Accessible Chromatin) is conveniently performed in parallel with ordinary CUT&Tag, producing accessible site maps from low cell numbers with signal-to-noise as good as or better than the best ATAC-seq datasets. Results Streamlined CUT&Tag produces high-quality datasets with low cell numbers We previously introduced CUT&RUN, a modification of Laemmli’s Chromatin Immunocleavage (ChIC) method (Schmid et al., 2004), in which a fusion protein between Micrococcal Nuclease (MNase) and Protein A (pA-MNase) binds sites of antibodies bound to chromatin fragments in nuclei or permeabilized cells immobilized on magnetic beads. Activation of MNase with Ca++ results in targeted cleavage, releasing the antibody-bound fragment into the supernatant for paired-end DNA sequencing. More recently, we substituted the Tn5 transposase for MNase in a modified CUT&RUN protocol, such that addition of Mg++ results in a cut-and-paste ‘tagmentation’ reaction, in which sequencing adapters are integrated around sites of antibody binding (Kaya-Okur et al., 2019). In CUT&Tag, DNA purification is followed by PCR amplification, eliminating the end-polishing and ligation steps required for sequencing library preparation in CUT&RUN. Like CUT&RUN, CUT&Tag requires relatively little input material, and the low backgrounds permit low sequencing depths to sensitively map chromatin features. We have developed a streamlined version of CUT&Tag that eliminates tube transfers, so that all steps can be efficiently performed in a single PCR tube (Kaya-Okur et al., 2020). However, we had not determined the suitability of the single-tube protocol for profiling low cell number samples. During the COVID-19 pandemic, we adapted this CUT&Tag-direct protocol for implementation with minimal equipment and space requirements that uses no toxic reagents, so that it can be performed conveniently and safely on a home workbench (Figure 1—figure supplement 1). To ascertain the ability of our CUT&Tag-direct protocol to produce DNA sequencing libraries at home with data quality comparable to those produced in the laboratory, we used frozen aliquots of native human K562 cell nuclei prepared in the laboratory and profiled there using the streamlined single-tube protocol. Aliquots of nuclei were thawed and serially diluted in Wash buffer from ~60,000 down to ~60 starting cells, where the average yield of nuclei was ~50%. We used antibodies to H3K4me3, which preferentially marks nucleosomes immediately downstream of active promoters, and H3K27me3, which marks nucleosomes within broad domains of polycomb-dependent silencing. Aliquots of nuclei were taken home and stored in a kitchen freezer, then thawed and diluted at home and profiled for H3K4me3 and H3K27me3. In both the laboratory and at home, we performed all steps in groups of 16 or 32 samples over the course of a single day through the post-PCR clean-up step, treating all samples the same regardless of cell numbers. Whether produced at home or in the lab, all final barcoded sample libraries underwent the same quality control, equimolar pooling, and final SPRI bead clean-up steps in the laboratory prior to DNA sequencing. Tapestation profiles of libraries produced at home detected nucleosomal ladders down to 200 cells for H3K27me3 and nucleosomal and subnucleosomal fragments down to 2000 cells for H3K4me3 (Figure 1A–B). Sequenced fragments were aligned to the human genome using Bowtie2 and tracks were displayed using IGV. Similar results were obtained for both at-home and in-lab profiles for both histone modifications (Figure 1C–D) using pA-Tn5 produced in the laboratory, and results using commercial Protein A/Protein G-Tn5 (pAG-Tn5) were at least as good. All subsequent experiments reported here were performed at home using commercial pAG-Tn5, which provided results similar to those obtained using batches of lab-produced pA-Tn5 run in parallel. Figure 1 with 1 supplement see all Download asset Open asset CUT&Tag-direct produces high-quality datasets on the benchtop and at home. Starting with a frozen human K562 cell aliquot, CUT&Tag-direct with amplification for 12 cycles yields detectable nucleosomal ladders for intermediate and low numbers of cells for both (A) H3K4me3 and (B) H3K27me3. The higher yield of smaller fragments with decreasing cell number suggests that reducing the total available binding sites increases the binding of antibody and/or pAG-Tn5 in limiting amounts. (C) Comparison of H3K4me3 CUT&Tag-direct results produced in the laboratory to those produced at home and to an ENCODE dataset (GSM733680). (D) Same as (C) for H3K27me3 comparing CUT&Tag-direct results to CUT&Tag datasets using the standard protocol (Kaya-Okur et al., 2019), and to an ENCODE dataset (GSM788088). pA-Tn5 was used except as indicated by asterisks for datasets produced at home using commercial pAG-Tn5 (Epicypher cat. no. 15–1017). NDRs attract Tn5 tethered to nearby nucleosomes during low-salt tagmentation Because the Tn5 domain of pA-Tn5 binds avidly to DNA, it is necessary to use elevated salt conditions to avoid tagmenting accessible DNA during CUT&Tag. High-salt buffers included 300 mM NaCl for pA-Tn5 binding, washing to remove excess protein, and tagmentation at 37°C. We have found that other protocols based on the same principle but that do not include a high-salt wash step result in chromatin profiles that are dominated by accessible site tagmentation (Kaya-Okur et al., 2020). To better understand the mechanistic basis for the salt-suppression effect, we bound pAG-Tn5 under normal high-salt CUT&Tag incubation conditions, then tagmented in low salt. We used either rapid 20-fold dilution with a prewarmed solution of 2 mM or 5 mM MgCl2 or removal of the pAG-Tn5 incubation solution and addition of 50 µL 10 mM TAPS pH8.5, 5 mM MgCl2. All other steps in the protocol followed our CUT&Tag-direct protocol (Kaya-Okur et al., 2020; Figure 2). Tapestation capillary gel electrophoresis of the final libraries revealed that after a 20 min incubation the effect of low-salt tagmentation on H3K4me2 CUT&Tag samples was a marked reduction in the oligo-nucleosome ladder with an increase in faster migrating fragments (Figure 3A and Figure 3—figure supplement 1A–B). CUT&Tag profiles using antibodies to most chromatin epitopes in the dilution protocol showed either little change or elevated levels of non-specific background tagmentation that obscured the targeted signal (Figure 3—figure supplement 2), as expected considering that we had omitted the high-salt wash step needed to remove unbound pAG-Tn5. Strikingly, under low-salt conditions, high-resolution profiles of H3K4me3 and H3K4me2 showed that the broad nucleosomal distribution of CUT&Tag around promoters for these two modifications was mostly replaced by single narrow peaks (Figure 3B and Figure 3—figure supplement 3). Figure 2 Download asset Open asset CUT&Tag with low-salt tagmentation (CUTAC). Steps in gray are lab-based and other steps were performed at home. Tagmentation can be performed by dilution, removal or post-wash. MEDS (mosaic end double-stranded annealed oligonucleotides). Figure 3 with 4 supplements see all Download asset Open asset Low-salt tagmentation of H3K4me2/3 CUT&Tag samples sharpen peaks. (A) Tapestation gel image showing the change in size distribution from standard CUT&Tag (CnT), tagmented in the presence of 300 mM NaCl with low-salt tagmentation using the dilution protocol. (B) Representative tracks showing the shift observed with low-salt dilution tagmentation. (C) Average plots showing the narrowing of peak distributions upon low-salt tagmentation using the dilution protocol. (D) Heatmaps showing narrowing of H3K4me2 peaks after removing pAG-Tn5 (removal), after a stringent wash (post-wash), and after a stringent wash with low-salt tagmentation including a 1% pAG-Tn5 spike-in (Add-back). MACS2 was used to call peaks and heatmaps were ordered by density over the peak summits (sites). (E) Heatmaps showing dilution tagmentation and further narrowing of H3K4me2 peak distributions upon low-salt tagmentation (after removal) for 20 min at 37°C in the presence of 10% 1,6-hexanediol (hex) and 10% dimethylformamide (DMF) or both for 1 hr at 55°C. (F) Average plots showing effects of tagmentation with hex and/or DMF over time of low-salt tagmentation (after removal). (G) Smaller fragments (≤120 bp) dominate NDRs. Comparisons of small (≤120 bp) and large (>120 bp) fragments from CUTAC hex and DMF datasets show narrowing for small fragments around their summits. For each dataset a 3.2 million fragment random sample was split into small and large fragment groups.Removal of large fragments increases the number of peaks called (sites). To evaluate the generality of peak shifts we used MACS2 to call peaks, and plotted the occupancy over aligned peak summits. For all three H3K4 methylation marks using normal CUT&Tag high-salt tagmentation conditions we observed a bulge around the summit representing the contribution from adjacent nucleosomes on one side or the other of the peak summit (Figure 3C). In contrast, tagmentation under low-salt conditions revealed much narrower profiles for H3K4me3 and H3K4me2 (~40% peak width at half-height), less so for H3K4me1 (~60%), which suggests that the shift is from H3K4me-marked nucleosomes to an adjacent NDR. To determine whether free pAG-Tn5 present during tagmentation contributes, we removed the pAG-Tn5 then added 5 mM MgCl2 to tagment, and again observed narrowing of the H3K4me2 peak (Figure 3D ‘Removal’ and Figure 3—figure supplement 1C-D). We also observed a narrowing if we included a stringent 300 mM washing step before low-salt tagmentation (Figure 3D, ‘Post-wash’), which indicates that peak narrowing does not require free pAG-Tn5. Inclusion of a stringent post-wash step improves consistency relative to the Dilution or Removal protocols, although it resulted in lower yields and reduced library complexity (Figure 3—figure supplement 1E-F). However, if a small amount of pAG-Tn5 was included during tagmentation we obtained higher yields with increased peak narrowing (Figure 3D ‘Add-back’). Because Tn5 is inactive once it integrates its payload of adapters, and each fragment is generated by tagmentation at both ends, it is likely that a small amount of free pA(G)-Tn5 is sufficient to generate the additional small fragments where tethered pA(G)-Tn5 is limiting, albeit with higher background. Salt ions compete with protein-DNA binding and so we suppose that tagmentation in low salt resulted in increased binding of epitope-tethered Tn5 to a nearby NDR prior to tagmentation. As H3K4 methylation is deposited in a gradient of tri- to di- to mono-methylation downstream of the +1 nucleosome from the transcriptional start site (TSS) (Henikoff and Shilatifard, 2011; Soares et al., 2017), we reasoned that the closer proximity of di- and tri-methylated nucleosomes to the NDR than mono-methylated nucleosomes resulted in preferential proximity-dependent ‘capture’ of Tn5. Consistent with this interpretation, we observed that the shift from broad to more peaky NDR profiles and heatmaps by H3K4me2 low-salt tagmentation was enhanced by addition of 1,6-hexanediol, a strongly polar aliphatic alcohol, and by 10% dimethylformamide, a strongly polar amide, both of which enhance chromatin accessibility (Figure 3E–F). NDR-focused tagmentation persisted even in the presence of both strongly polar compounds at 55°C. Enhanced localization by chromatin-disrupting conditions suggests improved access of H3K4me2-tethered Tn5 to nearby holes in the chromatin landscape during low-salt tagmentation. Localization to NDRs is more precise for small (≤120 bp) than large (>120 bp) tagmented fragments, and by resolving more closely spaced peaks inclusion of these compounds increased the number of peaks called (Figure 3G), also for H3K4me3-tethered Tn5 (Figure 3—figure supplement 4). CUT&Tag low-salt tagmentation fragments coincide with ATAC-seq and DNaseI hypersensitive sites CUT&Tag, we previously showed that most ATAC-seq sites are by nucleosomes in K562 cells (Kaya-Okur et al., 2019). However, ATAC-seq datasets over peaks called using H3K4me2 CUT&Tag data resulted in the broad distribution of peak over nucleosome NDRs (Figure In contrast, of ATAC-seq datasets over peaks called using low-salt tagmented CUT&Tag data produced narrow for the of peaks (Figure To the close between fragments by H3K4me2-tethered low-salt tagmentation as by ATAC-seq using we to low-salt H3K4me2 and H3K4me3 CUT&Tag tagmentation as Cleavage Under Targeted Accessible Chromatin (CUTAC). Figure 4 with 2 supplements see all Download asset Open asset H3K4me2 CUTAC peaks correspond to ATAC-seq and DNaseI hypersensitivity peaks. Heatmaps showing the correspondence between H3K4me2 CUTAC and ATAC-seq sites. over each the of fragments mapping to the indicated of MACS2 peak ordered by occupancy over the over each CUT&Tag and CUTAC sites are from samples in where CUTAC tagmentation was performed by 20-fold dilution and 20 min 37°C incubation pAG-Tn5 (E) of H3K4me2 and H3K4me3 CUTAC and ATAC-seq data for K562 cells. (F) Heatmaps showing for H3K4me2 CUT&Tag, CUTAC and ATAC-seq at DNaseI hypersensitive sites. on left site We the between CUTAC and ATAC-seq by H3K4me2 CUT&Tag and CUTAC datasets over peaks called from data (Figure In a between CUTAC and we not detect that a of peaks found by one but not the other dataset (Figure supplement 1). To further evaluate the of between CUTAC and ATAC-seq, we aligned the ENCODE ATAC-seq dataset over peaks called using and where all datasets were down to 3.2 million fragments with fragments heatmaps produced using either or CUTAC peak for the same ENCODE ATAC-seq data showed occupancy of for both of peaks of Figure We found between ENCODE ATAC-seq peaks and peaks called from either or CUTAC data (Figure supplement 2). This between H3K4me2 CUTAC and when to ENCODE ATAC-seq that CUTAC and detect the same chromatin features. This does not for H3K4me3 because similar of ENCODE ATAC-seq data resulted in only peak occupancy (Figure and lower (Figure which we to the of H3K4me3 around promoters than enhancers relative to To evaluate whether CUTAC peaks also correspond to sites of DNaseI we aligned H3K4me2 CUT&Tag and CUTAC over factor as peaks of DNaseI in K562 and cells. We nucleosomal fragments by using only We observed that of the DNaseI hypersensitive sites are by CUTAC signal relative to regions (Figure which suggests of CUTAC and DNaseI hypersensitive sites. We also found that the H3K4me2 CUT&Tag sample showed detectable signal at only of the sites. This in detection of sites by H3K4me2 CUTAC over H3K4me2 CUT&Tag the potential of using CUTAC fragment data to improve the and of transcription factor binding site To evaluate signal-to-noise genome-wide, we called peaks using MACS2 and the of in a data quality introduced by the ENCODE et al., For both ENCODE and our CUT&RUN data we for 3.2 million fragments, for CUT&Tag, improved signal-to-noise relative to chromatin profiling methods (Kaya-Okur et al., 2019). H3K4me2 CUT&Tag for 3.2 million fragments and peaks 4 tagmentation by dilution in 2 mM MgCl2 resulted in for 3.2 million fragments and peaks with similar for tagmentation by removal peaks In we lower after stringent washing conditions, increased background. We also the number of peaks and for CUTAC to those for ATAC-seq for K562 cells and observed that CUTAC data quality was similar to that for the method et al., 2017), better than ENCODE ATAC-seq et al., 2020), and much better than et al., a over ATAC-seq (Buenrostro et al., Figure CUTAC is relatively to tagmentation with similar numbers of peaks and similar for samples tagmented for 20 and min (Figure We the of CUT&Tag and CUTAC to the tethering of Tn5 to specific chromatin so that when tagmentation to there is little Tn5 that increase background When we peak numbers and for ATAC-seq for K562 data deposited in the from we observed a of data quality (Figure even from very from 1 and Figure supplement 1). We this to the of background by excess free Tn5 in ATAC-seq protocols and subsequent of non-specific nucleosomal fragments et al., 2020). Figure 5 with 3 supplements see all Download asset Open asset CUTAC data quality is similar to the best available ATAC-seq K562 cell fragments from the indicated datasets were and peaks were called using (A) of peaks and of in peaks for CUT&Tag H3K4me2 CUTAC and ATAC-seq is an improved version of ATAC-seq that et al., and is an improved version that improves signal-to-noise et al., is the ENCODE standard et al., 2020). (B) other K562 ATAC-seq datasets from different laboratories were in and to MACS2 was used to call peaks. numbers and a of data quality found in ATAC-seq datasets. (C) H3K4me2 CUTAC fragments improve DMF 1 CUTAC data quality is similar to that of the best ATAC-seq datasets. K562 and cell ATAC-seq datasets were from and Bowtie2 was used to map fragments to A sample of 3.2 million fragments was used for by MACS2 to of to or is is of fragments to DNA. CUT&Tag-direct CUT&Tag-direct CUTAC CUTAC K562 K562 K562 K562 K562 K562 K562 K562 low-salt tagmentation peaks of DNA accessibility because tethering to nucleosomes increases the of tagmentation in small holes in the chromatin then we smaller fragments to dominate CUTAC peaks. this is what we for heatmaps (Figure supplement 2), tracks (Figure supplement peak and (Figure fragments results in better more peaks and higher both of which approach a with the addition of strongly polar compounds during tagmentation a in peak and (Figure and large fragments not improve ATAC-seq peak and which indicates that tethering to H3K4me2 is

Topic: RNA modifications and cancer
Subfield: Molecular Biology
Field: Biochemistry, Genetics and Molecular Biology
Domain: Life Sciences