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. Author manuscript; available in PMC: 2020 Feb 5.
Published in final edited form as: Nature. 2019 Feb 18;566(7745):558–562. doi: 10.1038/s41586-019-0949-1
Multiplex Chromatin Interactions with Single Molecule Precision
1The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
2Department of Genetics and Genome Sciences, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, CT 06030, USA
3School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China
4Huazhong Agricultural University, Wuhan, Hubei 430070, China
Author contribution
M.Z., Y.R., and C.L.W. conceptualized the ChIA-Drop strategy and designed the studies. M.Z. conducted experiments with assistance from Z. L., R.M., and C.Y.N. for ChIA-Drop library construction and sequencing. P.W., E.P., and J.J.Z. contributed RNAPII ChIA-PET data. X.R., D.C., and S.Z.T. contributed PacBio results. S.Z.T., M.K., D.C., and B.L. developed the computational pipeline ChIA-DropBox with C.H.W’s assistance. M.Z. and Y.R. wrote the manuscript with input from D.C., M.K., S.Z.T., and B.L. All co-authors read and approved the manuscript.
*
Correspondence and requests for materials should be addressed to yijun.ruan@jax.org
The publisher's version of this article is available at Nature
Abstract
Genomes of higher organisms are extensively folded into three-dimensional (3D) chromosome territories within the nucleus1. Advanced 3D genome mapping methods that combine proximity ligation and high-throughput sequencing (Hi-C)2, plus chromatin immunoprecipitation (ChIA-PET)3, have revealed topologically associating domains (TADs)4 with frequent chromatin contacts and have identified chromatin loops mediated by specific protein factors for insulation and transcriptional regulation5–7. However, these methods rely on pairwise proximity ligation and reflect population-level views, and thus cannot reveal the detailed nature of chromatin interactions. Although single-cell Hi-C8 could potentially overcome this issue, it may be limited by data sparsity inherent to current single-cell assays. Recent advances in microfluidics have opened new opportunities for droplet-based genomic analysis9, yet this approach has not been adapted to chromatin interaction analysis. Here, we describe a strategy for multiplex chromatin interaction analysis via droplet-based and barcode-linked sequencing (ChIA-Drop). We demonstrate the robustness of ChIA-Drop in capturing complex chromatin interactions with unprecedented single-molecule precision, which has not been possible with previous methods based on population-level pairwise contacts. Applying ChIA-Drop in Drosophila cells reveals that chromatin topological structures are predominantly comprised of multiplex chromatin interactions with high heterogeneity, and that promoter-centered multivalent interactions provide novel topological insights into transcription.
Reporting summary
Further information on research design is available in the Nature Research Reporting Summary linked to this paper.
To develop ChIA-Drop, we used Drosophila S2 cells, a well-characterized model10, and adopted the Chromium microfluidics system (10X Genomics), which was established for high-molecular-weight genomic DNA9. In ChIA-Drop, a crosslinked and fragmented chromatin sample is directly loaded to the microfluidics device without proximity ligation or DNA purification. Each chromatin complex is partitioned in a Gel-bead-in-Emulsion (GEM) droplet that contains unique DNA oligonucleotides and reagents for linear amplification and barcoding. The barcoded amplicons with GEM-specific indices are then pooled for high-throughput sequencing, and the sequencing reads with identical barcodes are computationally assigned to the same GEM of origin. Mapping of the sequencing reads to the reference genome identifies which remote genomic loci are in close spatial proximity. Thus, multiplex chromatin interactions can be inferred (Fig. 1a). We optimized and verified that this microfluidic-based approach can produce high-quality and reproducible data directly from the crosslinked chromatin sample (Supplementary Methods, Supplementary Table 1; Extended Data Fig. 1–2).
Concurrently, we developed a comprehensive analysis and visualization pipeline, ChIA-DropBox (Supplementary Note 1). From sequencing reads, ChIA-DropBox first identifies the droplet barcode (GEMcode). After mapping, high-quality reads with same GEMcode are grouped, and overlapping reads are merged to represent DNA fragments. Fragments tagged with same GEMcode are assumed to originate from the same GEM, ideally from a single chromatin complex tethering multiple distal DNA fragments. Due to randomness of the emulsion process of droplet formation, multiple chromatin complexes could potentially be partitioned into the same GEM. Given that most chromatin contacts are intra-chromosomal, chromatin complexes of inter-chromosomal origins in a GEM can be separated computationally into intra-chromosomal sub-GEMs, representing putative chromatin complexes. For example, in one ChIA-Drop dataset of 5.7 million chromatin fragments assembled from 51 million reads, we identified 1.2 million intra-chromosomal putative complexes from 1.6 million GEMs (Supplementary Note 1). A major source of noise was singleton DNA fragments, which are readily filtered out in downstream analysis. Furthermore, we developed a “domain-based distance test” algorithm based on polymer physics11 and information theory12 to further characterize intra-chromosomal complexes (Supplementary Note 1).
In theory, ChIA-Drop should detect the same spectrum of chromatin contacts as Hi-C. To compare ChIA-Drop with Hi-C data13, we devised an in silico ligation algorithm to generate pairwise contacts from ChIA-Drop data (Supplementary Note 1) and show that their chromatin structural features are comparable (Fig. 1b–c, Extended Data Fig. 2d). Unlike Hi-C, ChIA-Drop can resolve the multiplex nature of chromatin interactions. Indeed, about half (n=1,493,818) of ChIA-Drop complexes contained three or more fragments, some (n=19,778) even had up to hundreds of chromatin fragments (Supplementary Table 2). We decomposed the ChIA-Drop data based on fragment numbers and visualized each class separately with 2D maps. Most of the contacts from low-fragment-number complexes (F=2–5) appeared randomly scattered, whereas high-fragment-number complexes tended to cluster into distinct topological structures along the diagonal (Fig. 1d, Extended Data Fig. 2g), which was also observed in the cumulative distribution of pairwise distances by fragment number (Fig. 1e, Extended Data Fig. 2h).
We then focused on high-fragment-number ChIA-Drop complexes (F≥6; n=170,752) for further analysis. We visualized these complexes in their linear alignment along genomic bins, with complexes organized by similarity along the y-axis via hierarchical clustering (Fig. 2a; Supplementary Note 1). Notably, the fragment clusters were closely associated with topological domains, indicating that single-molecule ChIA-Drop complexes provided genuine information on chromatin conformation. ChIA-Drop complexes associated with TADs contained more fragments on average than those associated with gap regions (Fig. 2a, Extended Data Fig. 2i–j). Overall, 85% (82,506) of ChIA-Drop complexes associated with TADs fall within a single TAD, though 15% (14,630) cover several TADs (Fig. 2b). Many of these inter-TAD interactions (4,757 of 9,723) were significant by a “frequency-based binomial test”, suggesting higher-order chromatin organization (Supplementary Note 1). Therefore, our ChIA-Drop data demonstrate extensive multiplexity of chromatin interactions inside and between TADs.
We validated the single-molecule multiplex nature of ChIA-Drop complexes using an orthogonal protocol based on PacBio long-read sequencing of proximity-ligated chromatin fragments (Supplementary Methods). Although most of the long-reads included only one chromatin fragment, we identified thousands that included multiple fragments and showed high heterogeneity within TADs, similar to the intra-TAD ChIA-Drop data (Extended Data Fig. 3a–b).
Additionally, we applied 4-color 3D FISH to confirm the inter-TAD multiplexity of the ChIA-Drop complexes. For a genomic segment (1.1 Mb) in chr2L that contains three interacting TADs and one non-interacting TAD, we designed fluorescent DNA probes corresponding to the 4 TAD regions (Fig. 2c), where probe T2* was expected to be an internal negative control, and two T4 probes (T4a and T4b) served as intra-TAD references. As expected, the spatial distance measured by FISH between T4a and T4b was small (mode = 0.22 μm) (Fig. 2d, Extended Data Fig. 3k). The spatial distance of T1-T4b was substantially shorter than the distance of T2*-T4b, even though T2* is closer in linear genomic distance. We defined FISH signals as “colocalized” based on a distance cutoff (0.28 μm), and calculated the percentage of colocalization for two- and three-probe combinations and compared these with ChIA-Drop complexes. Overall, the FISH patterns and colocalization percentages were highly consistent with ChIA-Drop (Fig. 2d–e). Additional FISH validations also supported the observed ChIA-Drop interactions14,15 (Extended Data Fig. 3c–j).
Most ChIA-Drop TADs in Drosophila S2 cells were closely associated with repressed chromatin, whereas boundary gaps were transcriptionally active (Fig. 2f, Extended Data Fig. 2d–e), consistent with previously reported findings16. Additionally, two architectural proteins had interesting binding patterns: BEAF-3217 tended to define TAD boundaries, whereas Su(Hw)18 tended to occur within TADs, potentially for heterochromatin compaction (Fig. 2g). Together, ChIA-Drop data revealed a single-molecule view of complex chromatin contacts represented individually in many cells, instead of the topological approximation based on aggregated pairwise contacts from bulk cells (Fig. 2h).
We next investigated multiplex chromatin interactions involved in transcriptional regulation by adding RNAPII chromatin immunoprecipitation to the ChIA-Drop protocol (Fig. 1a; Supplementary Methods). Replicates of RNAPII ChIA-Drop were high-quality and reproducible (Supplementary Table 1; Extended Data Fig. 2a), with 80% of chromatin contacts (frequency count ≥ 3) observed across replicates (Extended Data Fig. 4e). We identified ~2 million chromatin complexes in S2 cells by RNAPII ChIA-Drop (F ≥ 2) (Supplementary Table 1 and 3). In general, RNAPII ChIA-Drop recapitulated similar topological structures as ChIA-Drop, but, as expected, exhibited considerable signal reduction in repressed domains (TADs) and enrichment in active regions (boundary gaps) (Fig. 3a).
We then compared RNAPII ChIA-Drop to RNAPII ChIA-PET. In RNAPII ChIA-PET data, transcriptionally active regions often contain interconnected daisy-chain loops referred to as RNAPII-associated interaction domains (RAIDs) (Supplementary Note 1, Supplementary Table 1; Extended Data Fig. 5). Using RNAPII ChIA-PET data, we called 476 RAIDs in S2 cells (Supplementary Table 4, Supplementary Note 2). We converted RNAPII ChIA-Drop data to pairwise loops, which were mostly enriched in RAIDs, with some inter-RAID contacts as also seen in RNAPII ChIA-PET and in Kc167 cells16 (Fig. 3b, Extended Data Fig. 6).
We validated the multiplex RNAPII ChIA-Drop complexes using 4-color 3D FISH. In a chromatin segment (1.12 Mb) in chr2L, RNAPII ChIA-Drop complexes connected several RAIDs for which we designed 4 probes (Fig. 3c). Since RNAPII-mediated chromatin architectures in Drosophila are sensitive to heat-shock (HS)19, we used HS treatment as a negative control. As expected, in many normal cells the probes were spatially colocalized, whereas in most HS cells the probes were scattered (Fig. 3d–e, Extended Data Fig. 3l). Thus, the RNAPII ChIA-Drop data, including the 16 chromatin complexes involving 3 RAIDs in this region (Fig. 3c), are likely to reflect true multiplex chromatin interactions in single molecules.
Next, we analyzed the multiplexity of chromatin complexes by comparing to a binomial model of expected interaction complexity (Supplementary Note 2). Overall, the multiplexity of chromatin complexes in RAIDs was lower than expected, whereas that in TADs was higher (Extended Data Fig. 6j–k). We also quantified the heterogeneity of multiplex chromatin complexes in RAIDs and in TADs, which may reflect cell-to-cell variation (Supplementary Note 2). Chromatin interactions within RAIDs and TADs are both heterogeneous, though to a higher degree in TADs (Fig. 3f, top). The subset of complexes in RAIDs that involve promoters tends to be less heterogeneous (Fig. 3f, bottom), suggesting possible exclusivity behavior of promoter-involving interactions. A similar level of heterogeneity was observed by single-cell RNA-Seq (Fig. 3f, bottom), indicating a commonality with transcriptional function.
The multiplex single-molecule complexes from RNAPII ChIA-Drop provide an unprecedented opportunity to explore topological mechanisms of transcription, which led us to focus on complexes involving promoters in RAIDs (F≥2; n=175,294). Notably, 80% of such RNAPII complexes included only one promoter (Fig. 4a). For instance, an active region including luna and Shn genes had interconnected daisy-chain loops in RNAPII ChIA-PET data (Extended Data Fig. 8a) and in pairwise loops of the RNAPII ChIA-Drop data (Fig. 4b), but the single-molecule fragment views of the RNAPII ChIA-Drop revealed that promoters are rarely interconnected (Fig. 4b; Extended Data Fig. 7a). This suggest that in individual cells most promoters are not spatially inter-connected (Fig. 3b; Extended Data Fig. 7a). Nonetheless, we still captured more than 2,700 complexes that simultaneously connected at least three promoters (Supplementary Note 2; Fig. 4a), supporting the notion that multiplex promoter interactions occur in single molecules, but not as extensively as previously suggested5.
To explore the properties of co-transcriptionally regulated genes5, we focused on RNAPII ChIA-Drop complexes involving 3 promoters and obtained 4 clusters based on gene expression (Supplementary Table 5, Supplementary Note 2; Extended Data Fig. 7b). Group I and group II are imbalanced with 1 and 2 dominant gene(s), respectively, while groups III and IV are balanced with three equally expressed genes. This suggests at least two different mechanisms for transcription coordination: “co-transcription” (groups III and IV), where all the promoters are active, and “imbalanced-transcription” (groups I and II), where promoters of weak genes behave like enhancers to support the expression of the dominant genes as previously postulated5. Indeed, the weak promoters exhibited a enhancer-like status, as measured by the ratio of H3K4me/me3 ChIP-Seq signals (Fig. 4c, Extended Data Fig. 7c–e).
RNAPII ChIA-Drop data also revealed abundant intragenic contacts with orientation biased towards the downstream direction of transcription (Fig. 4b, Extended Data Fig. 7f), particularly for large genes over 100 Kb length such as luna20. An aggregation plot for all promoter-involving RNAPII ChIA-Drop complexes along a normalized gene body model (Supplementary Note 2) demonstrates that, genome-wide, intragenic chromatin contacts are directionally biased toward the transcriptional end site (TES) (Fig. 4d). At the luna gene locus (Fig. 4e), RNAPII ChIA-PET data displayed a remarkable chromatin contact “stripe” starting from the promoter, suggesting a likely transcriptional processivity of chromatin looping. RNAPII ChIA-Drop identified 87 complexes involving the luna promoter, of which the majority (72; 83%) extended downstream from TSS towards TES, where each of the RNAPII ChIA-Drop complexes represents a possible chromatin looping structure anchored at the promoter site (Fig. 4f, Extended Data Fig. 8).
The orientation-bias pattern may potentially support a one-sided extrusion model for transcription, which is different from a conventional tracking model21. Here, we envision that the RNAPII protein cluster with co-factors is assembled at the promoter site, or that gene promoters are attracted to RNAPII clusters. When transcription starts, the promoter site is in steady position, while the DNA template is reeled through the transcriptional apparatus for RNA synthesis. Interestingly, in chromatin complexes containing fewer fragments, the chromatin contacts were a short distance from the luna promoter, reflecting the starting phase of DNA extrusion and the formation of small loops. In larger complexes (more fragments), there were more chromatin contacts far away from the promoter and closer to TES, indicating more complicated chromatin looping structures (inset of Fig. 4f).
In summary, ChIA-Drop is a simple, robust and effective method for capturing multiplex chromatin interactions at the single-molecule level, an advance over previous pairwise, population-level methods like Hi-C and ChIA-PET. The protocol requires only ~5×103 cells, or ~6×104 cells for a ChIP-enriched experiment. We anticipate that ChIA-Drop will be rapidly adopted for a wide range of biomedical questions and applications. We demonstrated in S2 cells that TADs are composed of interactions with high complex-to-complex heterogeneity, analogous to the dynamics reported using a super-resolution imaging approach in single cells22. More importantly, we characterized transcriptional multiplex interactions. Contrary to previous population-level analyses that suggested extensive promoter-promoter interactions5, RNAPII ChIA-Drop data revealed that 80% of transcriptionally-active chromatin complexes involve interactions of only one promoter with non-promoter distal elements, consistent with recent studies using super-resolution microscopy of RNAPII foci23,24. The 20% of chromatin complexes involving multiple promoters support the idea of transcription factories25, but that these may not be as prevalent as previously suggested5. We provided evidence for at least two putative mechanisms of transcriptional coordination: co-transcription and imbalanced-transcription. Moreover, we detected processive multiplex chromatin contacts connected to active gene promoters in the direction of transcriptional orientation, and accordingly we propose a promoter-centered one-sided extrusion model for RNAPII-mediated transcription.
This study is supported by a Jackson Laboratory Director’s Innovation Fund (DIF19000-18-02). Y.R. and C.L.W. are funded by 4DN (U54 DK107967) and ENCODE (UM1 HG009409) consortia. Y.R. is also funded by Human Frontier Science Program (RGP0039/2017), and supported by Florine Roux Endowment.
Footnotes
Data Availability
The ChIA-Drop datasets, RNAPII ChIA-Drop datasets, RNAPII ChIA-PET datasets have been deposited in the Gene Expression Omnibus database with accession number GSE109355. A manuscript is in preparation on the ChIA-DropBox computational pipeline, and all software will be released as open-source code with that manuscript.
Online Content
Supplementary Methods, Supplementary Notes, Research reporting summaries, including statements of data availability and any associated accession codes and references, are available in the online version of the paper. Full statistics in Supplementary Methods.
The authors declare no competing interests.
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