Abstract
Recent studies have elucidated cell-lineage-specific three-dimensional genome organization; however, how such specific architecture is established or maintained is unclear. We hypothesized that lineage-defining transcription factors maintain cell identity via global control of genome organization. These factors bind many genomic sites outside of the genes that they directly regulate and thus are potentially implicated in three-dimensional genome organization. Using chromosome-conformation-capture techniques, we show that the transcription factor Paired box 5 (Pax5) is critical for the establishment and maintenance of the global lineage-specific architecture of B cells. Pax5 was found to supervise genome architecture throughout B cell differentiation, until the plasmablast stage, in which Pax5 is naturally silenced and B cell–specific genome structure is lost. Crucially, Pax5 did not rely on ongoing transcription to organize the genome. These results implicate sequence-specific DNA-binding proteins in global genome organization to establish and maintain lineage fidelity.
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Data availability
Sequence data that support the findings of this study are tabulated in the supplementary tables and are available in the GEO database under accession number GSE99163. Additional information can be found in the Nature Research Reporting Summary for this study.
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Acknowledgements
We thank T. Mason for animal husbandry and N. Iannarella for technical support. This work was supported by grants and fellowships from the National Health and Medical Research Council of Australia (S.L.N., 1054925 and 1058238; G.K.S., 1058892; A.T.L.L. and G.K.S., 1054618; R.S.A. and T.M.J., 1049307 and 1100451; T.M.J., 1124081) and the Australian Research Council (R.S.A., 130100541). This study was made possible through the Victorian State Government Operational Infrastructure Support and Australian Government NHMRC Independent Research Institute Infrastructure Support scheme.
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T.M.J. designed the research, performed experiments, analyzed data and wrote the paper. A.T.L.L. and H.D.C. designed critical software packages, performed bioinformatics experiments and analyzed data. T.T. performed experiments and analyzed data. G.K.S. designed and supervised bioinformatics analysis and contributed to writing the paper. S.L.N. and R.S.A. designed and supervised the research and wrote the paper.
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Integrated supplementary information
Supplementary Figure 1 Cell isolation and library quality checks.
(a), Flow cytometry of homogenized C57BL/6 Pep3b mouse spleen stained with antibodies against TCRβ, CD4, CD8, CD62L, CD44. CD4+ T cells were isolated as TCRβ+ CD4+ CD8− CD62L+ CD44−. (b), Flow cytometry of homogenized C57BL/6 Pep3b mouse spleen stained with antibodies against TCRβ, CD19, B220, IgM, IgD. B cells were isolated as TCRβ- CD19+ B220+ IgM+ IgD+. (c), Flow cytometry of homogenized C57BL/6 Pep3b mouse bone marrow stained with antibodies against TCRβ, CD19, B220, Ly6C, Ly6G. Granulocytes were isolated as TCRβ- CD19− Ly6Cint Ly6G+. (d), Representative MA plots comparing bin pair counts between CD4+ T cell, B cell and granulocytes in situ Hi-C libraries, before and after normalization using a loess-based approach with the normOffsets function of the diffHic package. Y-axis shows log2 fold change in interaction intensity while the x-axis shows average log2 intensity. (e), Representative histogram of distribution of fragment lengths in in situ Hi-C libraries. Data derived from one of two independent experiments with similar results. (f), Representative plot of strand orientation of fragments in in situ Hi-C libraries with respect to the log-insert size (that is distance between paired reads on the same chromosome). Data derived from one of two independent experiments with similar results. (g), Percentage of DNA loop anchor bin pairs overlapped by CTCF binding sites in CD4+ T cells, B cells and granulocytes (Supplementary Table 18). Data derived from pool of two independent experiments. (h), Flow cytometry of homogenized cKit-enriched C57BL/6 Pep3b mouse bone marrow stained with antibodies against cKit and Sca-1. LSK cells were isolated as cKit+ Sca-1+. (i), Multi-dimensional scaling plot showing the relationship between the interaction profiles of CD4+ T cells, B cells, granulocytes, LSK cells and MEFs. Distances on the plot represent leading log2-fold-changes in interaction intensity. (j), Using the change-point detection algorithm in TADbit, we determined the number and (k), size of TADs in CD4+ T cells, B cells, granulocytes, LSK cells and MEFs. Data derived from pool of two independent experiments. Box plot shows median and 5th and 95th percentiles. (l), In situ Hi-C contact matrices of CD4+ T cells and B cells were overlaid with H3K27 acetylation ChIP-seq and p300 ChIP-seq (Supplementary Table 18) from each cell type. The boundaries of statistically significant DIs (FDR < 0.05) determined the coordinates shown. Color scale indicates number of reads per bin pair
Supplementary Figure 2 B cell–stage isolation and compartment examination.
Flow cytometry of C57BL/6 Pep3b pro-B cell culture stained with antibodies against IgM and CD19. Pro-B cells were isolated as IgM−. (b), Flow cytometry of homogenized C57BL/6 Pep3b mouse spleen stained with antibodies against TCRβ, CD19, B220, IgM, and IgD. Tr/MZ B cells were isolated as TCRβ- CD19+ B220+ IgM+ IgD−. Follicular B cells were TCRββ- CD19+ B220+ IgM+ IgD+ (as seen in Supplementary Fig. 1b). (c), Flow cytometry of LPS-stimulated C57BL/6 Pep3b mouse B220+ splenic cell culture stained with antibodies against CD138 and CD22. Activated B cells were isolated as CD138− CD22+. Plasmablasts were isolated as CD138+ CD22−. (d), Using the change-point detection algorithm in TADbit, we determined the number and (e), size of TADs in pro-B cells, Tr/MZ B cells, follicular B cells (as seen in Supplementary Fig. 1b), activated B cells and plasmablasts. Data derived from pool of two independent experiments. Box plot shows median and 5th and 95th percentiles. (f), A/B compartmental interaction plots of total chromosome 1 at six stages of B cell differentiation. 50kB resolution shown
Supplementary Figure 3 The effect of Pax5 deletion and reintroduction on pro-B cells and genome organization.
(a), Flow cytometry of wild type and Pax5−/− pro-B cells stained with antibodies against IgM and CD19. Pro-B cells are isolated at IgM−. Wild type also shown in Supplementary Fig. 2a. (b), DNA content examination by flow cytometry of ethanol fixed wild type and Pax5−/− pro-B cells stained with propidium iodide. The largest peak represents cells in G0/1 of the cell cycle, the second peak G2/M, and the intervening region is made up of cells in S phase. (c), Percentage of DNA loops in wild type and Pax5−/− pro-B cells with anchors overlapping at least one CTCF binding site. (d), Multi-dimensional scaling plot constructed from the interaction intensities in wild type and Pax5−/− pro-B cells. Distances between samples represent the leading log2-fold change between samples for the top 50000 bin pairs with the largest log2-fold changes. (e), Using the change-point detection algorithm in TADbit, we determined the number and (f), size of TADs in wild type and Pax5−/− pro-B cells. Data derived from pool of two independent experiments. Box plot shows median and 5th and 95th percentiles. (g), Multi-dimensional scaling plot constructed from the interaction intensities in wild type and Pax5−/− pro-B cells and LSK cells. Distances between samples represent the leading log2-fold change between samples for the top 50000 bin pairs with the largest log2-fold changes. (h), As shown in Fig. 3c and f, percentage of DI bin pairs strengthened or weakened between follicular B cells versus pro-B cells and plasmablasts versus follicular B cells with anchors containing either pro-B cell specific, follicular B cell specific or common high (MACS2 peak threshold of 50) or low (MACS2 peak threshold of 10) stringency Pax5 binding sites. Numbers of unclustered DIs are shown. Data from duplicate libraries derived from two independent experiments were compared using Pearson’s chi-squared test with Yates’ continuity correction was used to determine significance. (i), As shown in Fig. 4c, d, percentage of DI bin pairs between Pax5−/− versus wild type pro-B cells and treated Pax5−/− Pax5:ER pro-B cells versus untreated with anchors unbound or Pax5 bound (high and low stringency) that are strengthened or weakened in the absence or 24 h reintroduction of Pax5. Numbers of unclustered DIs shown. Data from duplicate or triplicate libraries derived from two or three independent experiments were compared using Pearson’s chi-squared test with Yates’ continuity correction was used to determine significance. (j), Flow cytometry of Pax5−/− Pax5:ER untreated and 24 h β-estradiol treated pro-B cells stained with antibodies against Flt3 and CD19. Untreated Pax5−/− pro-B cells were isolated as Flt3high CD19−. 24 h treated pro-B cells (Pax5 reintroduced) were Flt3low CD19+. (k), DNA content examination by flow cytometry of ethanol fixed Pax5−/− Pax5:ER untreated and 24 h β-estradiol treated pro-B cells stained with propidium iodide. (l), Percentage of DI bin pairs between treated Pax5−/− Pax5:ER pro-B cells versus untreated with anchors unbound or Pax5 bound that are strengthened or weakened after 6 h reintroduction of Pax5. Numbers of unclustered DIs are shown. Pearson’s chi-squared test with Yates’ continuity correction was used to determine significance. (m), Flow cytometry of Pax5−/− Pax5:ER pro-B cell cultures with or without β-estradiol (βES) and/or α-amanitin. Numbers indicate the percentage of viable cells in each gate. (n), In situ Hi-C contact matrices of regions around the Pax5 target genes Spi1 and Dntt in untreated, 6 h Pax5 reintroduced and 6 h Pax5 reintroduced with α-amanitin treatment pro-B cells. Color scale indicates number of reads per bin pair
Supplementary information
Supplementary Table 1: Details of all in situ HiC libraries generated in this study.
Qualitative details of all in situ HiC libraries generated in this study, including total paired end reads generated, percentages of libraries removed through filtration and final library sizes
Supplementary Table 2: Differential interactions detected between CD4+ T cells, B cells and granulocytes.
Genomic coordinates, P-value and false discovery rate of differential interactions detected between CD4+ T cells, B cells and granulocytes
Supplementary Table 3: Differential interactions detected between CD4+ T cells, B cells, granulocytes, LSKs and MEFs.
Total numbers, genomic coordinates, P-value and false discovery rate of differential interactions detected between CD4+ T cells, B cells, granulocytes, LSKs and MEFs
Supplementary Table 4: TAD boundaries detected in CD4+ T cells, B cells, granulocytes, LSKs and MEFs
Genomic coordinates, score and size of TAD boundaries detected in CD4+ T cells, B cells, granulocytes, LSKs and MEFs
Supplementary Table 5: 1000 most differentially expressed genes between CD4+ T cells, B cells and granulocytes
List of 1000 most differentially expressed genes between CD4+ T cells, B cells and granulocytes including microarray probe set ID, fold change in expression and P-value
Supplementary Table 6: Differential interactions and TAD boundaries detected between and in different stages of B cell differentiation
Genomic coordinates, P-value and false discovery rate of differential interactions detected between stages of B cell differentiation and TAD boundaries detected at each differentiation stage
Supplementary Table 7: A/B compartment switching numbers and percentage of genome
Percentage of the genome that A/B compartment switch at each transition of B cell differentiation, and after Pax5 deletion
Supplementary Table 8: Differential interactions between proB cells and follicular B cells and the association with Pax5 binding
Genomic coordinates, P-value and false discovery rate, and association with Pax5 binding sites of differential interaction detected between pro-B cells and follicular B cells
Supplementary Table 9: Low stringency Pax5 binding sites
Genomic coordinates, width and score of low stringency (threshold>10) Pax5 binding sites in pro-B cells and follicular B cells
Supplementary Table 10: Differential interactions between follicular B cells and plasmasblasts
Genomic coordinates, P-value and false discovery rate, and association with Pax5 binding sites of differential interaction detected between follicular B cells and plasmablasts
Supplementary Table 11: Differential interactions between wild-type and Pax5−/− pro-B cells
Genomic coordinates, P-value and false discovery rate, and association with Pax5 binding sites of differential interaction detected between wild-type pro-B cells and Pax5−/− pro-B cells
Supplementary Table 12: Differential interactions detected in the Igh locus between Pax5−/− and wild type pro-B cells
Genomic coordinates, P-value and false discovery rate of differential interactions detected specifically in the Igh locus between Pax5−/− and wild type pro-B cells
Supplementary Table 13: Differential interactions detected between wild-type pro-B cells, Pax5−/− pro-B cells and LSK cells.
Genomic coordinates, P-value and false discovery rate of differential interactions detected between wild-type pro-B cells, Pax5−/− pro-B cells and LSK cells
Supplementary Table 14: High stringency Pax5 binding sites.
Genomic coordinates, width and score of high stringency (threshold >50) Pax5 binding sites in pro-B cells and follicular B cells. Includes grouping of binding sites into pro-B cell specific, follicular B cell specific or common to both cell types
Supplementary Table 15: Differential interactions between untreated and 24 h treated Pax5−/− Pax5:ER pro-B cells
Genomic coordinates, P-value and false discovery rate of differential interactions detected between untreated Pax5−/− Pax5:ER pro-B cells and those treated with β-estradiol for 24 h
Supplementary Table 16: Differential interaction detected between untreated Pax5−/− Pax5:ER pro-B cells and 6-h βestradiol treated Pax5−/−
Genomic coordinates, P value and false discovery rate of differential interactions detected between untreated Pax5−/− Pax5:ER pro-B cells and those treated with βestradiol for 6 h, with or without α-amanitin for 8 h
Supplementary Table 17: Antibodies used in this study
Target, clone and source of all antibodies used in this study
Supplementary Table 18: Publically available datasets used in this study
Cell types and techniques used to generate all publically available data used in this study, along with accession numbers for each data set
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Johanson, T.M., Lun, A.T.L., Coughlan, H.D. et al. Transcription-factor-mediated supervision of global genome architecture maintains B cell identity. Nat Immunol 19, 1257–1264 (2018). https://doi.org/10.1038/s41590-018-0234-8
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DOI: https://doi.org/10.1038/s41590-018-0234-8
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