Tracking chromatin structure changes by single-cell multi-epigenomics with RNA polymerase II binding profiles

Tracking chromatin structure changes by single-cell multi-epigenomics with RNA polymerase II binding profiles | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Tracking chromatin structure changes by single-cell multi-epigenomics with RNA polymerase II binding profiles Yasuyuki Ohkawa, Akihito Harada, Takeru Fujii, Kosuke Tomimatsu, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4503255/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Transcription factor-bound chromatin structures regulate cell lineages in multicellular organisms. Single-cell epigenomics has the potential to reveal lineage determination on chromatin structure, but the methodology is still in development. Here, we develop single-cell combinatorial-indexing multi-target Chromatin Integration Labeling followed by sequencing (sci-mtChIL-seq) as a single-cell multi-epigenomics approach, which enables simultaneous single-cell analysis of both RNA polymerase II binding to chromatin and epigenomic factors such as transcription factors/histones. We apply sci-mtChIL-seq to analyze the binding dynamics of skeletal-muscle-specific transcription factor MyoD during mouse embryonic myogenesis. Based on RNA polymerase II-bound gene profiles, single-cells are efficiently classified into myogenic-clusters and ordered pseudotemporally. MyoD exhibits genome-wide binding in the muscle-progenitor-cell population, but in myocytes, this transitions toward enrichment in muscle-specific genes on active chromatin. Thus, sci-mtChIL-seq can be a powerful tool to analyze epigenomic dynamics in cell fate determination. Biological sciences/Biological techniques/Epigenetics analysis/Chromatin analysis Biological sciences/Developmental biology/Embryogenesis/Cell lineage Biological sciences/Biotechnology/Sequencing/Next-generation sequencing Biological sciences/Molecular biology/Chromatin/Chromatin structure Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations Yes there is potential Competing Interest. The authors declare no competing financial interests except A.H., H.Ku., Yu.S., H.Ki. and Y.O., who are involved in a patent related to ChIL. Supplementary Files Supplementaryinformation.docx Supplementarytables.xlsx ExtendedDataFig1240530.pdf Extended Data Fig. 1 Overview of sci-ChIL-seq. a, sci-ChIL-seq scheme. A total of 10-30k biotinylated cells per well were combined in 96-well avidin-coated plates and stained with primary antibody (1st Ab) and sci-ChIL probe (see Fig. 1b). Tn5 transposition via Tn5 transposase integrates the sci-ChIL probe’s indexed DNA into the genome around the primary antibody of the cell (cells are indexed with a unique sci-ChIL probe per well). The cells in the 96-well plate are then pooled, and 25 cells per well are added to another 96-well plate with a cell sorter, so that cells with different primary indexes are placed in the wells. The integrated regions are then amplified as RNA by in vitro transcription using T7 RNA polymerase. Transcribed RNA is purified and converted to cDNA for sequencing library preparation; a second index is added by PCR prior to sequencing. PCR is performed with a set of primers with unique i5 and i7 sequences per well. A library with a different primary index and the same secondary index was generated for each well. Overall, a library of approximately 2400 cells with different primary and secondary indices is produced. b, Example of sci-ChIL probe index usage (extensibility). One single-target sequence includes one set of 96 sci-ChIL probes with T5 barcodes, and two sets of multi-target sequences is used. ExtendedDataFig22405292.pdf Extended Data Fig. 2 Quality control of sci-mtChIL-seq. a, Scatter plots showing the number of reads obtained for the two epigenomic factors relative to the index used in sci-mtChIL-seq. The horizontal axis shows read counts for RNAPII, and the vertical axis shows the read counts for H3K4me3 (top) or H3K27me3 (bottom). Scatter plots are shown by embryo day. b, Genomic feature distributions. Each graph shows the RNAPII (top left) and H3K4me3 reads (top right) of sci-mtChIL-seq RNAPII-H3K4me3 or the RNAPII reads (bottom left) and H3K27me3 reads (bottom right) of sci-mtChIL-seq RNAPII-H3K27me3 dataset for each embryo day, and shows the percentage of reads in the promoter, CpG-island, intron, exon, enhancer, and intergenic regions. c, Violin plot showing the number of genes detected in RNAPII-H3K4me3 or RNAPII-H3K27me3. Plots of RNAPII (top left) and H3K4me3 (top right) in RNAPII-H3K4me3 and RNAPII (bottom left) and H3K27me3 (bottom right) in RNAPII-H3K27me3 are shown for each embryo stage. The medians, 25th/75th percentiles, and 1.5 interquartile range (IQR) were used to construct the box plots. Source data are provided as a Source Data file. ExtendedDataFig3240529.pdf Extended Data Fig. 3 Classification of cell types by RNAPII is independent of paired factors. a, UMAP visualization of 3 sci-mtChIL-seq datasets using RNAPII signals. The right panel (pair = MyoD) corresponds to Fig 2d. The color represents each cell type. Each cell type was determined in the same way as in Figs. 2d–2e. b, IGV track view showing the distribution of reads. For each dataset, reads were aggregated by cell type, showing the region around the marker gene for each cell type. The colors are the same as in a. c, Correlation of RNAPII binding to genes. For each dataset, the mean RNAPII binding per gene per cluster was calculated, and Pearson’s correlation coefficients were calculated. The sci-mtChIL-seq RNAPII and cell types of H3K4me3, H3K27me3, and MyoD are shown in the indicated colors. d, Plot showing the proportion of cell types per stage of the sampled embryos. The colors correspond to the explicitly indicated cell type. ExtendedDataFig4240529.pdf Extended Data Fig. 4 Efficiency of muscle trans-differentiation with the Tet-On 3G system. a, Representative cell immunostaining fluorescence microscopy images showing MyoD (left) and Myog (right) expression in each cell stage. Each stain is shown in red; nuclear staining with Hoechst is shown in blue. The scale bar indicates 50 mm. Bars show the percentage of MyoD- and Myog-positive cells relative to the number of cells indicated by each stain. The error bars indicate mean ± standard deviation of the nine fields. b, Violin plot showing the number of genes detected by sci-mtChIL-seq in NIH3T3 cells. The medians, 25th/75th percentiles, and 1.5 interquartile range (IQR) were used to construct the box plots. Source data are provided as a Source Data file. ExtendedDataFig5240529.pdf Extended Data Fig. 5 Pseudotime analysis of NIH3T3 muscle trans-differentiation using RNAPII data from each sci-mtChIL-seq dataset. a, Various sci-mtChIL-seq data visualized by UMAP and PHATE. The colors indicate the samples. Points connected by lines indicate identical cells. b, Pseudotime trajectory estimated using PHATE. The pairs of antibodies are clearly indicated in the diagram. c, Density plot showing the distribution of the PHATE coordinates in D0h (top), D24h (middle), and D72h (bottom) cells. The data are in the same order as in b. ExtendedDataFig6240529.pdf Extended Data Fig. 6 Consistency of estimated pseudotime of each RNAPII signal. a, Dot plot showing GO enrichment analysis of differentially expressed genes (DEGs) using sci-mtChIL-seq RNAPII counts over time. For each gene group, the two biological processes with the highest gene ratios were extracted and shown. The size of the dots represents the gene ratio, and the color represents the adjusted p -value. The numbers below represent the numbers of genes analyzed. b. Examples of DEGs identified using sci-mtChIL-seq RNAPII counts over time (left; genes with increased RNAPII binding; right, genes with decreased RNAPII binding). The color indicates the pair of antibodies. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4503255","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":310855798,"identity":"1ed0e70d-757e-40a8-a238-87f1d10a4d89","order_by":0,"name":"Yasuyuki Ohkawa","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-6440-9954","institution":"Kyushu University","correspondingAuthor":true,"prefix":"","firstName":"Yasuyuki","middleName":"","lastName":"Ohkawa","suffix":""},{"id":310855799,"identity":"95e2699a-e8fa-4ecf-9021-044a8da76e43","order_by":1,"name":"Akihito Harada","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Akihito","middleName":"","lastName":"Harada","suffix":""},{"id":310855800,"identity":"a710674d-2de3-414f-9984-3f7126a3a3ce","order_by":2,"name":"Takeru Fujii","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Takeru","middleName":"","lastName":"Fujii","suffix":""},{"id":310855801,"identity":"52ca6453-1433-4a1c-a3cc-3ed9d899cb60","order_by":3,"name":"Kosuke Tomimatsu","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Kosuke","middleName":"","lastName":"Tomimatsu","suffix":""},{"id":310855802,"identity":"40ffdd32-dee1-4ef5-9e96-99e25c8ed034","order_by":4,"name":"Michiko Kato","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Michiko","middleName":"","lastName":"Kato","suffix":""},{"id":310855803,"identity":"8cab3303-22d5-4573-935c-ba51bfa7942f","order_by":5,"name":"Miho Ito","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Miho","middleName":"","lastName":"Ito","suffix":""},{"id":310855804,"identity":"ae373899-8aeb-4a31-9067-9c8a89b0f6f1","order_by":6,"name":"Kazumitsu Maehara","email":"","orcid":"https://orcid.org/0000-0002-2933-5176","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Kazumitsu","middleName":"","lastName":"Maehara","suffix":""},{"id":310855805,"identity":"cada4041-101e-495d-9f02-44c20a0379aa","order_by":7,"name":"Shoko Sato","email":"","orcid":"","institution":"Tokyo University","correspondingAuthor":false,"prefix":"","firstName":"Shoko","middleName":"","lastName":"Sato","suffix":""},{"id":310855806,"identity":"784a3b00-4e06-4d5f-b673-3152b20ea7c1","order_by":8,"name":"Hitoshi Kurumizaka","email":"","orcid":"https://orcid.org/0000-0001-7412-3722","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Hitoshi","middleName":"","lastName":"Kurumizaka","suffix":""},{"id":310855807,"identity":"5688a605-0009-434a-9b86-ad1f06964a07","order_by":9,"name":"Yuko Sato","email":"","orcid":"","institution":"Tokyo Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yuko","middleName":"","lastName":"Sato","suffix":""},{"id":310855808,"identity":"e458cef0-95b1-4799-91db-8e0de6b9cd4c","order_by":10,"name":"Hiroshi Kimura","email":"","orcid":"https://orcid.org/0000-0003-0854-083X","institution":"Tokyo Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Kimura","suffix":""}],"badges":[],"createdAt":"2024-05-30 13:10:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4503255/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4503255/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57887818,"identity":"c4b28193-b7a6-4070-9189-9d4f8af1b9f4","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1297309,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDevelopment of the sci-mtChIL-seq method.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Procedure for sci-ChIL-seq indexing. The indexing of sci-ChIL-seq is performed by a combination of two indices: an index in the ChIL DNA sequence of the sci-ChIL probe and an index in the PCR index primer. \u003cstrong\u003eb\u003c/strong\u003e, Structure of the sci-ChIL probe DNA. The ChIL index consists of 6 random bases; PEG is polyethylene glycol. \u003cstrong\u003ec\u003c/strong\u003e, Illustration of the process of fixation and detachment of cells to the plate using biotin–avidin interactions. \u003cstrong\u003ed\u003c/strong\u003e, Efficient binding of cell surface-biotinylated cells onto avidin plates. Images of formalin-fixed biotinylated cells bound to avidin plates (left). Scale bar indicates 1 mm. Bars graphs show the number of unfixed and fixed cells labeled with different amounts of biotin-SS-Sulfo-OSu bound on the plate (right). After the cells were placed on avidin plates (Ctrl), they were washed three times with PBS (Treated). The cells were counted under a microscope, and the nuclei were stained with Hoechst dye. The error bars indicate mean ± standard deviation of the three independent experiments. Two-sided Welch’s t-test was performed, and provided the \u003cem\u003ep\u003c/em\u003e-values. \u003cstrong\u003ee\u003c/strong\u003e, Efficient detachment of biotinylated cells from avidin plates. Image of biotinylated cells remaining in wells after an avidin-coated plate was treated with Accumax and DTT (left). Scale bar indicates 1 mm. Bars graphs show the number of cells remaining when cell-bound avidin plates were subjected to different conditions (right); Ctrl indicates no treatment; Treated indicates treatment with each condition indicated in the graph. Cells were counted under a microscope, and the nuclei were stained with Hoechst dye. The error bars indicate mean ± standard deviation of the three independent experiments. Two-sided Student’s t-test was performed, and provided the \u003cem\u003ep\u003c/em\u003e-values. \u003cstrong\u003ef\u003c/strong\u003e, Schematic of E10.5 to E14.5 embryos showing the organs and cell types collected during embryonic myogenesis. \u003cstrong\u003eg\u003c/strong\u003e, Aggregation plot of reads on gene bodies and around 5 kb flanking regions in highly (magenta) or poorly (cyan) expressed genes in embryonic stages. Gene sets were obtained from limb RNA-seq data downloaded from ENCODE (ENCSR750YSX, ENCSR347SQR and ENCSR216NEG). TSS represents the transcription start site, and TES represents the transcription end site. \u003cstrong\u003eh\u003c/strong\u003e, Track view of sci-mtChIL-seq signals in the Hoxd cluster. Bulk RNA-seq, bulk ChIP-seq, aggregated sci-mtChIL-seq, and 200 single-cell tracks are shown. Single-cell tracks showing signals counted every 5 kb. RNAPII-H3K4me3 (left) and RNAPII-H3K27me3 (right) single-cell tracks are ordered by total read counts. Bulk RNA-seq data on limb development in mouse embryos were obtained from ENCODE ENCFF333AEH (E10.5) and ENCODE ENCFF525YIT (E14.5); ChIP-seq data for H3K4me3 were obtained from ENCODE ENCFF945LBC (E10.5) and ENCODE ENCFF742VVS (E14.5); and H3K27me3 data were downloaded from ENCODE ENCFF465HTC (E10.5) and ENCODE ENCFF687PZG (E14.5). sci-mtChIL-seq RNAPII-H3K4me3 (\u003cstrong\u003ei\u003c/strong\u003e) and RNAPII-H3K27me3 (\u003cstrong\u003ej\u003c/strong\u003e) datasets visualized by UMAP. Identical cells between the data points are connected by lines. The numbers below the embryo stages indicate the numbers of cells used in the analysis. Source data are provided as a Source Data file.\u003c/p\u003e","description":"","filename":"Figure1240530.png","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/bbe4b2e8ad65bf1df9830717.png"},{"id":57887819,"identity":"788365f8-4b8f-41b4-b2c4-b12ca887bfb6","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":831170,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNAPII signal of sci-mtChIL-seq can be used to classify the major cell types involved in limb formation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Scatter plots showing the number of reads obtained for the two epigenomic factors relative to the index used in sci-mtChIL-seq. The horizontal axis shows read counts for RNAPII, and the vertical axis shows the read counts for MyoD. Scatter plots are shown by embryo day. \u003cstrong\u003eb\u003c/strong\u003e, Genomic feature distributions of the RNAPII reads for each embryo day. The graph shows the percentage of reads in the promoter, CpG-island, intron, exon, enhancer, and intergenic regions.\u003cstrong\u003e c\u003c/strong\u003e, Violin plot showing the number of genes detected in RNAPII. Plots of RNAPII are shown for each embryo stage. The medians, 25th/75th percentiles, and 1.5 interquartile range (IQR) were used to construct the box plots. Cell type classification by RNAPII signal of sci-mtChIL-seq RNAPII-MyoD. Color-coded RNAPII-MyoD by cluster (\u003cstrong\u003ed\u003c/strong\u003e). Dot plot showing RNAPII counts (\u003cstrong\u003ee\u003c/strong\u003e). The dot size indicates the average count of RNAPII, and the color indicates the fraction of cells in which that marker was detected. \u003cstrong\u003ef\u003c/strong\u003e, IGV track view showing the distribution of RNAPII signal. Fragments were aggregated by cell type, and regions around marker genes for each cell type are shown. The colors are the same as in d. Source data are provided as a Source Data file.\u003c/p\u003e","description":"","filename":"Figure22405292.png","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/8b752bbad907e5e61861532d.png"},{"id":57887823,"identity":"579a51d6-b89b-443c-8a42-900327ddbe0e","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":954576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMyoD binding in the embryonic skeletal muscle lineage is dynamic.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, UMAP visualization of a subset of paraxial mesoderm and myocyte by RNAPII in sci-mtChIL-seq RNAPII-MyoD. The colors represent the cell types. \u003cstrong\u003eb\u003c/strong\u003e, Classification of subcluster cell types by RNAPII signal; Subclusters are color-coded by clustering and classified using marker genes (left); dot plots showing RNAPII counts (right). The size of the dots represents the scaled cluster mean of RNAPII counts for selected marker genes per cell type, and the color represents the percentage of cells in which that marker was detected. \u003cstrong\u003ec\u003c/strong\u003e, Trajectory from the paraxial mesoderm cells to myocytes and osteoblast progenitors visualized by PHATE. The colors correspond to the colors of the cell types in Fig. 4b, and the cell type name at the endpoint of the trajectory is indicated. \u003cstrong\u003ed\u003c/strong\u003e, Two trajectories from paraxial mesoderm cells were detected by slingshot. Lineage 1 shows the trajectory to osteoblast progenitors (left), and Lineage 2 shows the trajectory to myocytes (right). \u003cstrong\u003ee\u003c/strong\u003e, Heatmap showing RNAPII signals on genes during pseudotime progression. RNAPII signals were counted in the range from TSS to TES+5 kbp for each gene. L1 and L2 represent Lineage 1 and Lineage 2, respectively. \u003cstrong\u003ef\u003c/strong\u003e, Line plot showing the change in MyoD counts over time. Total counts of MyoD were normalized to total counts of RNAPII. The colors indicate the respective lineages. The gray areas indicate 95% confidence intervals. \u003cstrong\u003eg\u003c/strong\u003e, The 500 cells corresponding to the starting point (paraxial mesoderm), branching point, and end point (osteoblast progenitor and myocyte) were extracted based on pseudotime (top). Heatmap showing the enrichment of known TF motifs in the MyoD signals of the cell population at each point (bottom). \u003cstrong\u003eh\u003c/strong\u003e, IGV track view of sci-mtChIL-seq RNAPII-MyoD showing MyoD and RNAPII signals in representative gene regions. \u003cem\u003eMyh3, Myl1, Rbm24\u003c/em\u003e, and \u003cem\u003eNpnt \u003c/em\u003eare myocyte genes, and \u003cem\u003eNeurod6\u003c/em\u003e is used as a control. The myocyte cCRE data were downloaded from ENCODE ENCFF823SEA. Source data are provided as a Source Data file.\u003c/p\u003e","description":"","filename":"Figure3240529.png","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/e6ea2afd0335a915998a632f.png"},{"id":57887821,"identity":"6a03ca87-62e5-4fad-8e27-acb8f79d2354","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1017671,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMyoD binding is associated with activation of chromatin on skeletal muscle genes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Muscle trans-differentiation experimental design. In NIH3T3 mouse fibroblasts (NIH3T3/Tet-On 3G cells), the MyoD gene inserted under the control of the TRE3G promoter is driven by the TRE3G promoter and activated by binding of the Tet-On 3G transactivator in the presence of Dox. The cells were cultured in the absence of Dox [Dox(-)] and incubated with Dox for 24 h to induce MyoD (D0h); then, after the medium was replaced with low-serum medium (2% HS) to induce skeletal muscle differentiation, and after 24 h (D24h) and 72 h (D72h), the cells were collected for subsequent sci-mtChIL-seq analysis. \u003cstrong\u003eb\u003c/strong\u003e, PHATE visualization of the RNAPII signal of sci-mtChIL-seq RNAPII-MyoD. The colors indicate samples (left). Pseudotime was inferred using RNAPII signal along the trajectory (right). \u003cstrong\u003ec\u003c/strong\u003e, Line plot showing changes in MyoD read counts over time for all peaks (left) or each cluster (right). MyoD counts were normalized by cell density per each pseudotime bin (see Methods). The colors represent the respective clusters. \u003cstrong\u003ed\u003c/strong\u003e, Heatmap showing enrichment of known TF motifs in MyoD signal in each cluster. \u003cstrong\u003ee\u003c/strong\u003e, Dot plot showing enrichment of GO terms for genes overlapping with each MyoD peak cluster in the region from TSS-5kbp to TES. The top five biological processes are plotted in order of the highest gene ratio. The size of the dots represents the gene ratio, and the color represents the adjusted \u003cem\u003ep\u003c/em\u003e-value. The numbers below represent the number of genes analyzed. \u003cstrong\u003ef\u003c/strong\u003e, IGV track view of sci-mtChIL-seq signals of various chromatin factors before and after differentiation in representative gene regions with MyoD peaks. Myocyte cCREs, MyoD peaks in Clusters 1 and 2, and aggregated sci-mtChIL-seq tracks are shown. The sci-mtChIL-seq signal aggregates 500 cells corresponding to early and late stages based on pseudotime, respectively. Myocyte cCRE are the same as those in Fig. 4h. The color represents each antibody. \u003cstrong\u003eg\u003c/strong\u003e, Line plot showing changes in epigenomic factors ±5 kbp around the MyoD peak over time. The data were normalized as shown in Fig. 5e. The gray areas indicate 95% confidence intervals. \u003cstrong\u003eh\u003c/strong\u003e, Schematic of the role of the two MyoD binding patterns found by sci-mtChIL-seq analysis. The role of MyoD is predicted to involve the formation of an activated chromatin state on myogenic genes, but not on non-myogenic genes. In skeletal muscle genes and related regions, after MyoD binding, the binding of H3K4me3, Brg1, and H3K27ac increases as differentiation initiates. In addition, the binding of the transcription factor Myog also increases. Finally, the transcription of skeletal muscle genes is induced. Source data are provided as a Source Data file.\u003c/p\u003e","description":"","filename":"Figure4240529.png","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/94f4a91fff52197d22d2e899.png"},{"id":57888852,"identity":"d47205a8-1552-45e3-a214-332c4b06201d","added_by":"auto","created_at":"2024-06-07 05:48:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2638036,"visible":true,"origin":"","legend":"","description":"","filename":"HaradaetalscimtChILseqNB240530.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1_covered_5e04bc75-6eef-4c07-a2f4-d6d0dd7d93e0.pdf"},{"id":57887817,"identity":"00e70af1-f909-436e-9e26-82cceaf73d05","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12810,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/6db8dfd9d72b8be86ff9303f.docx"},{"id":57887820,"identity":"ba5fb211-e767-4b69-89bd-905c8bf7a11d","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":59196,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/18d3eb7650ea94fe684c2132.xlsx"},{"id":57887828,"identity":"9f714278-4ca2-4abb-975f-8c455c1c0286","added_by":"auto","created_at":"2024-06-07 05:32:16","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":572169,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 1 Overview of sci-ChIL-seq.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, sci-ChIL-seq scheme. A total of 10-30k biotinylated cells per well were combined in 96-well avidin-coated plates and stained with primary antibody (1st Ab) and sci-ChIL probe (see Fig. 1b). Tn5 transposition via Tn5 transposase integrates the sci-ChIL probe’s indexed DNA into the genome around the primary antibody of the cell (cells are indexed with a unique sci-ChIL probe per well). The cells in the 96-well plate are then pooled, and 25 cells per well are added to another 96-well plate with a cell sorter, so that cells with different primary indexes are placed in the wells. The integrated regions are then amplified as RNA by \u003cem\u003ein vitro\u003c/em\u003etranscription using T7 RNA polymerase. Transcribed RNA is purified and converted to cDNA for sequencing library preparation; a second index is added by PCR prior to sequencing. PCR is performed with a set of primers with unique i5 and i7 sequences per well. A library with a different primary index and the same secondary index was generated for each well. Overall, a library of approximately 2400 cells with different primary and secondary indices is produced. \u003cstrong\u003eb\u003c/strong\u003e, Example of sci-ChIL probe index usage (extensibility). One single-target sequence includes one set of 96 sci-ChIL probes with T5 barcodes, and two sets of multi-target sequences is used.\u003c/p\u003e","description":"","filename":"ExtendedDataFig1240530.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/16821662f576fc2b0ee0ae2a.pdf"},{"id":57887824,"identity":"c59b1c5f-22ef-4796-96b8-0cfdeae2a091","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3661670,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 2 Quality control of sci-mtChIL-seq.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Scatter plots showing the number of reads obtained for the two epigenomic factors relative to the index used in sci-mtChIL-seq. The horizontal axis shows read counts for RNAPII, and the vertical axis shows the read counts for H3K4me3 (top) or H3K27me3 (bottom). Scatter plots are shown by embryo day. \u003cstrong\u003eb\u003c/strong\u003e, Genomic feature distributions. Each graph shows the RNAPII (top left) and H3K4me3 reads (top right) of sci-mtChIL-seq RNAPII-H3K4me3 or the RNAPII reads (bottom left) and H3K27me3 reads (bottom right) of sci-mtChIL-seq RNAPII-H3K27me3 dataset for each embryo day, and shows the percentage of reads in the promoter, CpG-island, intron, exon, enhancer, and intergenic regions.\u003cstrong\u003e c\u003c/strong\u003e, Violin plot showing the number of genes detected in RNAPII-H3K4me3 or RNAPII-H3K27me3. Plots of RNAPII (top left) and H3K4me3 (top right) in RNAPII-H3K4me3 and RNAPII (bottom left) and H3K27me3 (bottom right) in RNAPII-H3K27me3 are shown for each embryo stage. The medians, 25th/75th percentiles, and 1.5 interquartile range (IQR) were used to construct the box plots. Source data are provided as a Source Data file.\u003c/p\u003e","description":"","filename":"ExtendedDataFig22405292.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/99c80aa1b6ff6014a36e1aec.pdf"},{"id":57888241,"identity":"966b5be5-f4e5-4b89-8779-dc6844362790","added_by":"auto","created_at":"2024-06-07 05:40:16","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1540148,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 3 Classification of cell types by RNAPII is independent of paired factors.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, UMAP visualization of 3 sci-mtChIL-seq datasets using RNAPII signals. The right panel (pair = MyoD) corresponds to Fig 2d. The color represents each cell type. Each cell type was determined in the same way as in Figs. 2d–2e. \u003cstrong\u003eb\u003c/strong\u003e, IGV track view showing the distribution of reads. For each dataset, reads were aggregated by cell type, showing the region around the marker gene for each cell type. The colors are the same as in a. \u003cstrong\u003ec\u003c/strong\u003e, Correlation of RNAPII binding to genes. For each dataset, the mean RNAPII binding per gene per cluster was calculated, and Pearson’s correlation coefficients were calculated. The sci-mtChIL-seq RNAPII and cell types of H3K4me3, H3K27me3, and MyoD are shown in the indicated colors. \u003cstrong\u003ed\u003c/strong\u003e, Plot showing the proportion of cell types per stage of the sampled embryos. The colors correspond to the explicitly indicated cell type.\u003c/p\u003e","description":"","filename":"ExtendedDataFig3240529.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/44b6127a224d6be377297981.pdf"},{"id":57887825,"identity":"580f6b4b-b849-40ff-846e-5f6abc07f8c6","added_by":"auto","created_at":"2024-06-07 05:32:16","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":38426516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 4 Efficiency of muscle trans-differentiation with the Tet-On 3G system.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Representative cell immunostaining fluorescence microscopy images showing MyoD (left) and Myog (right) expression in each cell stage. Each stain is shown in red; nuclear staining with Hoechst is shown in blue. The scale bar indicates 50 mm. Bars show the percentage of MyoD- and Myog-positive cells relative to the number of cells indicated by each stain. The error bars indicate mean ± standard deviation of the nine fields. \u003cstrong\u003eb\u003c/strong\u003e, Violin plot showing the number of genes detected by sci-mtChIL-seq in NIH3T3 cells. The medians, 25th/75th percentiles, and 1.5 interquartile range (IQR) were used to construct the box plots. Source data are provided as a Source Data file.\u003c/p\u003e","description":"","filename":"ExtendedDataFig4240529.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/898108ecc580ba8fbbcf5a11.pdf"},{"id":57887827,"identity":"98cf2c1b-2f6c-425c-96f4-24f82d4a8a4d","added_by":"auto","created_at":"2024-06-07 05:32:16","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":23520704,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 5 Pseudotime analysis of NIH3T3 muscle trans-differentiation using RNAPII data from each sci-mtChIL-seq dataset.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Various sci-mtChIL-seq data visualized by UMAP and PHATE. The colors indicate the samples. Points connected by lines indicate identical cells. \u003cstrong\u003eb\u003c/strong\u003e, Pseudotime trajectory estimated using PHATE. The pairs of antibodies are clearly indicated in the diagram. \u003cstrong\u003ec\u003c/strong\u003e, Density plot showing the distribution of the PHATE coordinates in D0h (top), D24h (middle), and D72h (bottom) cells. The data are in the same order as in b.\u003c/p\u003e","description":"","filename":"ExtendedDataFig5240529.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/ad80b8519ce52b7ed50c1890.pdf"},{"id":57887822,"identity":"9306301d-f178-4599-b140-ec7f95ff1c12","added_by":"auto","created_at":"2024-06-07 05:32:15","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":603996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtended Data Fig. 6 Consistency of estimated pseudotime of each RNAPII signal.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Dot plot showing GO enrichment analysis of differentially expressed genes (DEGs) using sci-mtChIL-seq RNAPII counts over time. For each gene group, the two biological processes with the highest gene ratios were extracted and shown. The size of the dots represents the gene ratio, and the color represents the adjusted \u003cem\u003ep\u003c/em\u003e-value. The numbers below represent the numbers of genes analyzed. \u003cstrong\u003eb\u003c/strong\u003e. Examples of DEGs identified using sci-mtChIL-seq RNAPII counts over time (left; genes with increased RNAPII binding; right, genes with decreased RNAPII binding). The color indicates the pair of antibodies.\u003c/p\u003e","description":"","filename":"ExtendedDataFig6240529.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4503255/v1/0e56bb974d5f87cae49d68cf.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nThe authors declare no competing financial interests except A.H., H.Ku., Yu.S., H.Ki. and Y.O., who are involved in a patent related to ChIL.","formattedTitle":"Tracking chromatin structure changes by single-cell multi-epigenomics with RNA polymerase II binding profiles","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4503255/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4503255/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Transcription factor-bound chromatin structures regulate cell lineages in multicellular organisms. Single-cell epigenomics has the potential to reveal lineage determination on chromatin structure, but the methodology is still in development. Here, we develop single-cell combinatorial-indexing multi-target Chromatin Integration Labeling followed by sequencing (sci-mtChIL-seq) as a single-cell multi-epigenomics approach, which enables simultaneous single-cell analysis of both RNA polymerase II binding to chromatin and epigenomic factors such as transcription factors/histones. We apply sci-mtChIL-seq to analyze the binding dynamics of skeletal-muscle-specific transcription factor MyoD during mouse embryonic myogenesis. Based on RNA polymerase II-bound gene profiles, single-cells are efficiently classified into myogenic-clusters and ordered pseudotemporally. MyoD exhibits genome-wide binding in the muscle-progenitor-cell population, but in myocytes, this transitions toward enrichment in muscle-specific genes on active chromatin. Thus, sci-mtChIL-seq can be a powerful tool to analyze epigenomic dynamics in cell fate determination.","manuscriptTitle":"Tracking chromatin structure changes by single-cell multi-epigenomics with RNA polymerase II binding profiles","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-07 05:32:10","doi":"10.21203/rs.3.rs-4503255/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c04295a5-b412-4488-ab29-e8f269107560","owner":[],"postedDate":"June 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32851274,"name":"Biological sciences/Biological techniques/Epigenetics analysis/Chromatin analysis"},{"id":32851275,"name":"Biological sciences/Developmental biology/Embryogenesis/Cell lineage"},{"id":32851276,"name":"Biological sciences/Biotechnology/Sequencing/Next-generation sequencing"},{"id":32851277,"name":"Biological sciences/Molecular biology/Chromatin/Chromatin structure"}],"tags":[],"updatedAt":"2024-07-15T14:45:11+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-07 05:32:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4503255","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4503255","identity":"rs-4503255","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}