Summary/Abstract
B-cell development is initiated by the stepwise differentiation of hematopoietic stem cells into lineage committed progenitors, ultimately generating the mature B-cells that mediate protective immunity. This highly regulated process also generates clonal immunological diversity via recombination of immunoglobulin genes. While several transcription factors that control B-cell development and V(D)J recombination have been defined, how these processes are initiated and coordinated into a precise regulatory network remains poorly understood. Here, we show that the transcription factor ETS Related Gene (Erg) is essential for the earliest steps in B-cell differentiation. Erg initiates a transcriptional network involving the B-cell lineage defining genes, Ebf1 and Pax5, that directly promotes the expression of key genes involved in V(D)J recombination and formation of the B-cell receptor. Complementation of the Erg-deficiency with a productively rearranged immunoglobulin gene rescued B-cell development, demonstrating that Erg is an essential and exquisitely stage specific regulator of the gene regulatory network controlling B-lymphopoiesis.
INTRODUCTION
Transcription factors are critical for controlling the expression of genes that regulate B-cell development. The importance of specific B-cell transcription factors is highlighted by the phenotype of gene knockout models. Failure of B-cell lineage specification from multi-potential progenitors occurs with deletion of Ikzf1 1 and Spi1 (Pu.1) 2, while deletion of Tcf3 (E2A) 3 and Foxo1 4 results in failure of B-cell development from common lymphoid progenitors (CLPs). Developmental arrest at later B-cell stages is observed with deletion of Ebf1 and Pax5 at the pre-proB and proB stages respectively 5,6. This sequential pattern of developmental arrest associated with loss of gene function, along with ectopic gene complementation studies 2, gene expression profiling 7 and analysis of transcription factor binding to target genes, support models in which transcription factors are organised into hierarchical gene regulatory networks that specify B-cell lineage fate, commitment and function 8.
Two transcription factors that have multiple roles during B-cell development are Ebf1, a member of the COE family, and Pax5, a member of the PAX family. While Ebf1 and Pax5 have been shown to bind to gene regulatory elements of a common set of target genes in a co-dependent manner during later stages of B-lineage commitment 9, both manifest distinct roles during different B-cell developmental stages. Ebf1 forms an early B-cell transcriptional network with E2A and Foxo1 in CLPs that appears important in early B-cell fate determination 10, while during later stages of B-cell development, Ebf1 acts as a pioneer transcription factor that regulates chromatin accessibility at a subset of genes co-bound by Pax5 11 as well as at the Pax5 promoter itself 12. Pax5 in contrast, regulates B-cell genomic organisation 13 including the Immunoglobulin heavy chain (Igh) locus during V(D)J recombination, co-operating with factors such as CTCF 14, as well as transactivating 15 and facilitating the activity of the recombinase activating gene complex 16.
It is unclear, however, how these various functions of Ebf1 and Pax5 are co-ordinated during different stages of B-cell development. In particular, it would be important to ensure co-ordinated Ebf1 and Pax5 co-expression before the pre-BCR checkpoint, such that Ebf1 and Pax5 co-regulated target genes required for V(D)J recombination and pre-B-cell receptor complex formation are optimally expressed 9.
Here we show that the ETS related gene (Erg), a member of the ETS family of transcription factors, plays this vital role in B-lymphopoiesis. Deletion of Erg from early lymphoid progenitors resulted in B-cell developmental arrest at the early pre-proB cell stage and loss of VH-to-DJH recombination. Gene expression profiling, DNA binding analysis and complementation studies demonstrated Erg to be a stage-specific master transcriptional regulator that lies at the apex of an Erg-dependent Ebf1 and Pax5 gene regulatory network in pre-proB cells. This co-dependent transcriptional network directly controls expression of the Rag1/Rag2 recombinase activating genes and the Lig4 and Xrcc6 DNA repair genes required for V(D)J recombination, as well as expression of components of the pre-BCR complex such as CD19, Igll1, Vpreb1 and Vpreb2. Taken together, we define an essential Erg-mediated transcription factor network required for regulation of Ebf1 and Pax5 expression that is exquisitely stage specific during B-cell development.
RESULTS
Erg is required for B-cell development
To build on prior work defining the role of the hematopoietic transcription factor Erg in regulation of haematopoietic stem cells (HSCs) 17 and megakaryocyte-erythroid specification 18, we sought to identify whether Erg played roles in other haemopoietic lineages. Erg expression in adult hematopoiesis was first examined by generating mice carrying the Ergtm1a(KOMP)wtsi knock-in first reporter allele (ErgKI) (Figure 1A). Consistent with the known role for Erg in hematopoiesis 17–21, significant LacZ expression driven by the endogenous Erg promoter was observed in hematopoietic stem cells (HSCs) and multi-potential progenitor cells, as well as in granulocyte-macrophage and megakaryocyte-erythroid progenitor populations, with declining activity accompanying erythroid maturation (Figure 1B with definitions of cells examined provided in Table S1 and representative flow cytometry plots in Figure S1). In other lineages, transcription from the Erg locus was evident in common lymphoid (CLP), all lymphoid (ALP) and B-cell-biased lymphoid (BLP) progenitor cells, as well as in B-lineage committed pre-proB, proB and preB cells and double-negative thymic T-lymphoid cell subsets, with a reduction in transcription with later B-cell and T-cell maturation (Figure 1B,C). We confirmed these findings with RNA sequencing (RNA-seq) analysis that showed significant Erg RNA in pre-proB, proB and preB cells (Figure 1D). This detailed characterisation of Erg expression raised the possibility that Erg plays a stage-specific function at early developmental stages of the lymphoid lineages.
To determine whether Erg had a role in lymphoid development, mice carrying floxed Erg alleles (Ergfl/fl, Figure 1A) were interbred with Rag1Cre transgenic mice that efficiently delete floxed alleles in common lymphoid (CLPs) and T- and B-committed progenitor cells 22, but have normal lymphoid development (Figure S2A). The resulting Rag1CreT/+;ErgΔ/Δ mice specifically lack Erg throughout lymphopoiesis (Figure 1E, Figure S2B). While numbers of red blood cells, platelets and other white cells were normal, Rag1CreT/+;ErgΔ/Δ mice displayed a deficit in circulating lymphocytes (Table S2). This was due to a specific absence of B-cells; the numbers of circulating T-cells and thymic progenitors were not decreased (Figure 1F, Figure S2C).
B-cells are produced from bone marrow progenitor cells that progress through regulated developmental stages. B-cell development was markedly compromised in Rag1CreT/+;ErgΔ/Δ mice, with proB, preB, immature B and mature recirculating B cells (Hardy fractions C-F, defined in Table S1) markedly reduced in number or virtually absent (Figure 1F). A B-lymphoid developmental block was clearly evident at the pre-proB (Hardy fraction A-to-B) stage, with excess numbers of these cells present in the bone marrow.
Erg deficient pre-proB cells have perturbed VH-to-DJH recombination
To further characterise the developmental B-cell block in Rag1CreT/+;ErgΔ/Δ mice, B220+ bone marrow progenitors were examined for Igh somatic recombination. Unlike cells from control Ergfl/fl mice, B220+ cells from Rag1CreT/+;ErgΔ/Δ mice had not undergone significant VH-to-DJH immunoglobulin heavy chain gene rearrangement, although DH-to-JH recombination was relatively preserved (Figure 2A).
We next investigated the abnormalities underlying Igh recombination in greater detail. We first undertook fluorescence in situ hybridization (FISH) at the Igh locus to measure the intra-chromosomal distance between distal VHJ558 and proximal VH7183 VH family genes, as cell stage specific contraction of the Igh locus is essential for efficient V(D)J recombination 23. This revealed that B-cell progenitors from Rag1CreT/+;ErgΔ/Δ mice had reduced locus contraction compared to Ergfl/fl controls (Figure 2B). To assess whether other structural perturbations across the Igh locus were also present, chromatin conformation capture and high throughput sequencing (Hi-C) was performed. This analysis revealed a reduction of long-range interactions across the Igh locus in Rag1CreT/+;ErgΔ/Δ B-cell progenitors when compared to Ergfl/fl and C57BL/6 controls (Figure 2C). As these findings were also observed in Pax5 deficient B-cell progenitors 23,13 reflecting a direct role for Pax5 in co-ordinating the structure of the IgH locus 14, we mapped Erg binding sites across the Igh locus by ChIP-seq. Unlike well-defined Pax5 binding to Pax5- and CTCF-associated intergenic regions (PAIR domains) 14,16, Erg binding to VH families was not identified across the locus (Figure 2C, Figure S4A), suggesting that Erg was unlikely to be required structurally to maintain the multiple long-range interactions and VH-to-DJH recombination lacking in the Rag1CreT/+;ErgΔ/Δ B-cell progenitors. Analysis of Igh locus accessibility by ATAC-seq did not reveal any significant difference between Rag1CreT/+;ErgΔ/Δ pre-proB cells and control cells (Figure S4A) suggesting that loss of locus accessibility either by chromatin regulation 24 or peripheral nuclear positioning with lamina-associated domain silencing 25, were not mechanisms that could adequately explain reduced Igh locus contraction, reduction of long range interactions, and loss of VH-to-DJH recombination in the absence of Erg.
A potential role for ETS family of transcription factors in regulation of immunoglobulin gene rearrangement was proposed from experiments investigating the iEμ enhancer: a complex cis-activating element located in the intronic region between the Igh joining region (JH) and constant region (Cμ) implicated in efficient VH-to-DJH recombination and Igh chain transcription 26. The iEμ enhancer is proposed to nucleate a three-loop domain at the 3’ end of Igh interacting with the VH region to juxtapose 5’ and 3’ ends of the heavy chain locus 27. Erg and its closest related ETS family member, Fli1, were shown to bind to the μA element and trans-activate iEμ co-operatively with a bHLH transcription factor in vitro 28. We therefore sought to determine whether the lack of Erg, and Erg binding in particular to the μA site of iEμ, could account for loss of VH-DJH recombination observed in Rag1CreT/+;ErgΔ/Δ mice in vivo. While ChIP-PCR demonstrated Erg binding to the iEμ enhancer containing the μA element (Figure S3A), mice in which the μA region (μAΔ/Δ) was deleted had preserved numbers of circulating mature B-cells compared to cEμΔ/+ controls (Figure 2D) and intact VH-DJH recombination (Figure S3C). This was in contrast to cEμΔ/Δ mice, in which a core 220bp element of iEμ was deleted, that demonstrated a marked reduction of circulating mature IgM+IgD+ B-cells in peripheral blood in keeping with previous models 29 (Figure 2D). Together these data show that while Erg can bind to the μA region of the iEμ in vivo, deletion of this region did not result in significant perturbation of the B-cell development. It is therefore unlikely that Erg binding to μA element of iEμ could account for the loss of VH-to-DJH recombination in particular, or the Rag1CreT/+;ErgΔ/Δ phenotype in general.
The VH10tar IgH knock-in allele permits B-lymphoid development in the absence of Erg
Given the loss of VH-DJH recombination associated with structural perturbation of the Igh locus in Erg-deficient pre-proB cells, we sought to complement the loss of formation of a functional Igh μ transcript and in doing so, determine whether failure to form a pre-BCR complex was a principal reason for the developmental block in Rag1CreT/+;ErgΔ/Δ mice 30. Complementation with a functionally re-arranged Igh allele in models of defective V(D)J recombination such as deletion of Rag1, Rag2, or components of DNA-dependent protein kinase (DNA-PK) that mediate V(D)J recombination, can overcome the pre-BCR developmental block 31,32,33,34.
The IgHVH10tar knock-in allele that expresses productive IghHEL transcripts under endogenous Igh locus regulation 32 was therefore used to generate mice that lacked Erg in B-cell progenitors but would undergo stage-appropriate expression of the rearranged IghHEL chain (Rag1CreT/+;Erg Δ/Δ;IgHVH10tar/+). The presence of the IgHVH10tar allele permits B-cell development in the absence of Erg. The bone marrow of Rag1CreT/+;ErgΔ/Δ;IgHVH10tar/+ mice contained significant numbers of B220+IgM+ B-cells and, notably, CD25+CD19+IgM- PreB cells, a population coincident with successful pre-BCR formation 35, that were virtually absent in Rag1CreT/+;ErgΔ/Δ mice (Figure 3A). Similarly, in the spleens of Rag1CreT/+;ErgΔ/Δ;IgHVH10tar/+ mice, near normal numbers of all B-lymphoid populations were observed, in contrast to the marked reduction in Rag1CreT/+;ErgΔ/Δ mice (Figure 3B). Notably, IgκL chain recombination had proceeded in Rag1CreT/+;ErgΔ/Δ;IgHVH10tar/+ cells (Figure 3C). We next tested whether the rescued Rag1CreT/+;Erg Δ/Δ;IgHVH10tar/+ splenic B-cells were functional in the absence of Erg. Rag1CreT/+;ErgΔ/Δ;IgHVH10tar/+ splenocytes were indistinguishable from wild-type controls in in vitro proliferative assays using anti-μ stimulation, T-cell dependent stimulation with CD40 ligand, IL4 and IL5, or T-cell independent stimulation using lipopolysaccharide (Figure 3D). Rag1CreT/+;Erg Δ/Δ;IgHVH10tar/+splenic B-cells were also able to differentiate normally as measured by formation of plasma cells and IgG1 class switch recombination (Figure 3E). Circulating Rag1CreT/+;ErgΔ/Δ;IgHVH10tar/+ B-cells also expressed IgD, unlike their Rag1CreT/+;ErgΔ/Δ counterparts (Figure 3F). These experiments demonstrated that loss of a functional Igh μ transcript and failure to form a pre-BCR complex was a principal reason for lack of B-cell development in Rag1CreT/+;ErgΔ/Δ mice.
Erg-deficient pre-proB cells do not express Ebf1 and Pax5 transcription factors
To define the mechanism by which Erg regulates VH-to-DJH recombination and pre-BCR formation, we undertook gene expression profiling of Rag1CreT/+;ErgΔ/Δ pre-proB cells. Differential gene expression and gene-ontogeny analysis of differentially expressed genes in Rag1CreT/+;ErgΔ/Δ pre-proB compared to Ergfl/fl pre-proB cells demonstrated deregulated expression of multiple B-cell genes (Figure 4A). These included genes encoding cell surface or adhesion receptors and core components of the pre-BCR complex CD19, CD22, Igll1, Vpreb1, Vpreb2, CD79a and CD79b, genes required for IgH recombination such as Rag1 and Rag2 and components of non-homologous end-joining repair complex associated with V(D)J recombination: Xrcc6 (Ku70) and Lig4, and importantly, transcription factors implicated in B-cell development (Ebf1, Pax5, Tcf3, Bach2, Irf4, Myc, Pou2af1, Lef1, Myb) (Figure 4B).
Ebf1 and Pax5 are critical for B-lineage specification 5 and maintenance 36, 37 and act co-operatively to regulate a gene network in early B-cell fates 9. Because we observed with loss of Erg reduced expression of several critical B-cell genes previously identified to be controlled by Ebf1 and/or Pax5, for example CD19, Vpreb1, and Igll1 (Figure 4A), we speculated that Erg may play an important role in regulating the expression of these two essential transcription factors and their targets. To determine if Erg bound Ebf1 and/or Pax5 gene regulatory regions and directly regulated their expression, we undertook ChIP-seq analysis in wild-type B-cell progenitors and ATAC-seq to assess locus accessibility at the Ebf1 and Pax5 loci in the absence of Erg in Rag1CreT/+;ErgΔ/Δ B-cell progenitors. This demonstrated direct Erg binding to the proximal (β) promoter region of Ebf1 38 as well as to the Pax5 promoter and Pax5 lymphoid specific intron 5 enhancer 12 (Figure 4C), which together with the absence of Ebf1and Pax5 expression in Rag1CreT/+;ErgΔ/Δ pre-proB cells and the loss of Ebf1 and Pax5 protein in Rag1CreT/+;ErgΔ/Δ B-cell progenitors by Western Blot, demonstrated that Erg was a direct transcriptional regulator of Ebf1 and Pax5 (Figure 4D). Importantly, the loss of Ebf1 and Pax5 expression occurred while expression of other known regulators of Ebf1 expression, namely, Foxo1, Spi1, Tcf3 and Ikzf1 were maintained (Figure 4C and Figure S4B), and both Ebf1 and Pax5 loci remained accessible by ATAC-seq in Rag1CreT/+;ErgΔ/Δ B-cell progenitors (Figure 4C).
A co-dependent gene regulatory network dependent on Erg, Ebf1 and Pax5
Because expression of multiple B-cell genes were deregulated in Rag1CreT/+;ErgΔ/Δ pre-proB cells, including those to which Ebf1 and Pax5 had been shown to directly bind and regulate, we investigated the possibility that Erg co-bound common target genes to reinforce the Ebf1 and Pax5 gene network using a genome wide motif analysis of Erg DNA binding sites in B-cell progenitors. As expected, the most highly enriched motif underlying Erg binding was the ETS motif. However, significant enrichment of Ebf1, E2A, Pax5 and Foxo1 binding motifs were also identified within 50bp of Erg binding sites (Figure 4E), suggesting that Erg may indeed act co-operatively with other transcription factors to regulate target gene expression in a co-dependent gene network. Analysis of the binding of each of Erg, Ebf1 and Pax5 to regulatory regions of genes that were differentially expressed in Rag1CreT/+;ErgΔ/Δ pre-proB cells was then undertaken. This analysis identified significant overlap of Erg, Ebf1 and Pax5 binding sites within 5kb of the transcriptional start site (TSS) of genes differentially expressed in Rag1CreT/+;ErgΔ/Δ pre-proB cells compared with control pre-proB cells (Figure 4F). Taken together, these data provided compelling evidence for a gene regulatory network, in which Erg is required for maintaining expression of Ebf1 and Pax5 at the pre-proB cell stage of development, as well as reinforcing expression of target genes within the network by co-operative binding and co-regulation of target genes with Ebf1 and Pax5.
To further explore our finding that Erg, Ebf1 and Pax5 form the core of a gene regulatory network in pre-proB cells, examination of Ebf1 and Pax5 binding to the Erg locus was undertaken. Ebf1 and Pax5 binding within intron 1 of the Erg locus associated with the H3K27ac mark was found, as was Pax5 binding at the Erg promoter (Figure S4B). To determine if Ebf1 and Pax5 directly regulate Erg expression, gene expression changes in B-cell progenitors from a publicly available dataset in which Ebf1 (Ebf1Δ/Δ) or Pax5 (Pax5Δ/Δ) had been deleted were examined (Figure 5A). Deletion of either Ebf1 or Pax5 resulted in reduced Erg expression (Figure 5B), with Ebf1 appearing to be the stronger influence. We next compared gene expression changes in Ebf1Δ/Δ and Pax5Δ/Δ B-cell progenitors to those genes regulated by Erg in pre-proB cells. As would be predicted if Erg, Ebf1 and Pax5 were components of a co-dependent gene regulatory network, this analysis showed a highly significant correlation in gene expression changes observed with Ebf1 or Pax5 deletion in B-cell progenitors and those observed with Erg deletion in pre-proB cells. This was noted for down-regulated genes in Erg, Ebf1 and Pax5 deficient B-cell progenitors in particular (Figure 5C).
Finally, to confirm that Ebf1 and Pax5 were transcriptional regulators down-stream of Erg in pre-proB cells, transfection of Rag1CreT/+;ErgΔ/Δ progenitor cells with MSCV-driven constructs for constitutive expression of Ebf1 and Pax5 was performed. This experiment demonstrated rescue of B220 expression with Ebf1 or Pax5 over-expression in Erg deficient progenitors (Figure 5D). Notably, only partial rescue of CD19 expression and VH-to-DJH recombination was observed with Ebf1 over-expression while no rescue was observed with Pax5 over-expression (Figure 5D,E). These observations suggest that while Ebf1 over-expression could partially compensate for several aspects of B-cell development in the absence of Erg, Pax5 over-expression alone could not. This is in keeping with a hierarchical model highlighting the importance of Erg as a key mediator of the network.
Taken together, these experiments demonstrated the existence of a co-dependent transcriptional network between Erg, Ebf1 and Pax5, that co-regulate critical target genes at the pre-proB cells stage of B-cell development.
To further the delineate the directly regulated target genes in an Erg-dependent Ebf1 and Pax5 transcriptional network, we undertook mapping of ChIP-seq binding of Erg, Ebf1 and Pax5 to differentially expressed genes at the pre-proB cell stage of development in Rag1CreT/+;ErgΔ/Δ cells. We identified that the majority of these target genes demonstrated direct combinatorial binding of Erg, Ebf1 and/or Pax5 to annotated promoter regions, gene body enhancer/putative enhancer regions or putative distal enhancer regions of these genes (Figure 6A). Detailed examination of several key target genes for which expression was completely dependent on Erg in pre-proB cells identified direct binding of Erg to the promoter and enhancer regions for several pre-BCR components, including CD19, Igll1, Vpreb1 and CD79a. This occurred with co-ordinate binding of Ebf1 and Pax5 to the regulatory regions of these genes 15 (Figure 6B). In addition, indirect regulation by Erg at the Rag1/Rag2 locus was also identified, with down-regulation of expression of transcription factors that bind and regulate the Rag2 promoter such Pax5, Lef1 and c-Myb in Rag1CreT/+;ErgΔ/Δ pre-proB cells (Figure 4B) 39, as well as direct binding of Erg to the conserved B-cell specific Erag enhancer 40 (Figure S4C). Importantly, the loss of Rag1 and Rag2 expression in Rag1CreT/+;ErgΔ/Δ pre-proB cells occurred while expression of Foxo1, a positive regulator of the locus 41 was relatively maintained (Figure S4B).
An Erg-Ebf1-Pax5 mediated gene regulatory network was then mapped using each target gene, expression of which was perturbed in Rag1CreT/+;ErgΔ/Δ pre-proB cells, and that was directly bound by Erg, Ebf1 and/or Pax5 at promoter, proximal or distal gene regions, to provide a comprehensive representation of this gene network (Figure 6C).
A key observation arising from our data was that the B-cell developmental block arising in Rag1CreT/+;ErgΔ/Δ pre-proB cells could be overcome with the provision of a rearranged functional IgH VH10tar allele. This suggested that once the pre-BCR checkpoint was bypassed, Erg was no longer critical for further B-cell development and function, including VLJL recombination of the Igl and BCR formation (Figure 3C,D). Indeed, beyond the pre-BCR checkpoint, re-emergence of Ebf1 and Pax5 expression occurred (Figure 4C) as well as expression of target genes of the Ebf1 and Pax5 network (Figure 6B, Figure S4B,C) in Erg-deficient Rag1CreT/+;Erg Δ/Δ;IgHVH10tar/+ proB and preB cells rescued with a VH10tar allele. This defines the role of Erg as an exquisitely stage specific regulator of early B cell development.
Discussion
In this study we explored the role of the transcription factor Erg in B-lymphopoiesis. Our studies suggest two regions controlling Erg expression during B-cell development: the Erg promoter region and the H3K27ac-marked putative enhancer region in the first intron, to which the B-cell transcription factors Ebf1 and Pax5 directly bind. Complete loss of Erg expression in Ebf1Δ/Δ Β-cell progenitors in which Pax5 and Foxo1 expression was also lost, place the initiation of Erg expression in the B-lymphoid lineage downstream of the E2A, Ebf1, Foxo1 transcriptional network at the CLP stage of lymphoid development 10. The importance of Erg in B-cell development was demonstrated in mice in which Erg had been deleted throughout lymphopoiesis, which exhibited a developmental block at the pre-proB cell stage that was associated with profound defects in VH-to-DJH recombination, Igh locus organization and transcriptional changes in multiple B-cell genes, including loss of expression of Ebf1, and Pax5. Combining RNA-seq, ChIP-seq and gene complementation studies, we were able to define a co-dependent transcriptional network between Erg, Ebf1 and Pax5, with direct Erg binding to the proximal (β) Ebf1 promoter, to which Pax5, Ets1 and Pu.1 also co-operatively bind 38, as well as Erg binding to the Pax5 promoter and potent intron 5 enhancer region, two critical Pax5 regulatory elements required for correct transcriptional initiation of Pax5 in early B-cell development 12. These data support a model (Figure 6D) in which Ebf1 expression, initially Erg-independent in CLPs, requires Erg in pre-proB cells to promote and maintain its expression. Erg is also required for simultaneous Pax5 expression at this stage of development for the establishment of an inter-dependent B-lymphoid gene regulatory network.
Together Erg, Ebf1 and Pax5 directly co-regulated the expression multiple genes that had previously been identified as direct transcriptional targets of Ebf1 and Pax5 (Figure 6D). Direct Erg binding to promoters of the pre-BCR signalling complex genes such as Igll1, VpreB and CD79a, establish Erg as a transcriptional regulator of target genes in this network. In addition to Rag1 and Rag2, we also identified network regulation of expression of Xrcc6, the gene encoding the Ku70 subunit of DNA-dependent protein kinase holoenzyme (DNA-PK) that binds DNA double strand breaks during V(D)J recombination 42, and Lig4, encoding the XRCC4 associated DNA-ligase that is required for DNA-end joining during V(D)J recombination 43 (Figure 6C, S4C). Along with direct Erg promotion of expression of Pax5 as a structural regulator of the Igh locus, these findings are sufficient to explain the Rag1CreT/+;ErgΔ/Δ phenotype in which VH-toDJH recombination was lost. Together with loss of expression of components of the pre-BCR complex, we can conclude B-cell development was blocked as a consequence of Erg deletion due to the collapse of the Erg-mediated transcriptional network.
Importantly, re-emergence of Ebf1 and Pax5 expression beyond the pre-BCR checkpoint in IgH-rescued Rag1CreT/+;ErgΔ/Δ;IgHVH10tar/+ cells was observed, along with expression of target genes of Ebf1 and Pax5. This demonstrates that Erg is a stage-specific regulator of B-cell development, with emergence of an Erg-independent Ebf1 and Pax5 gene network during later stages of B-cell development, once clones have transitioned through the pre-BCR checkpoint. This would allow IgL chain VL to JL recombination and BCR formation to proceed in preB cells in which endogenous Erg expression is also reduced (Figure 1B,C). Erg however, is critical for promoting Ebf1 and Pax5 expression in pre-pro-B cells, orchestrating a transcriptional network required for VH-to-DJH recombination, pre-BCR formation, and early B cell development. In this role, Erg not only co-ordinates the transcriptional functions of Ebf1 and Pax5, but reinforces the Erg-mediated transcriptional network by directly binding and activating critical target genes required for transition through the pre-BCR checkpoint.
Author Contribution
Conceptualization, A.P.N., M.S.Y.L, A.J.K., T.M.J., M.A.D., R.S.A., K.R., D.M.T., G.K.S., M.J.D., S.L.N. and W.S.A.; Methodology, A.P.N., M.S.Y.L, T.M.J., T.B., M.A.D., R.S.A., K.R., D.M.T., G.K.S., M.J.D., S.L.N. and W.S.A.; Investigation, A.P.N., H.C., S.H., K.B., T.M.J., M.S.Y.L., C.C.B., O.G., Y.C.C., T.B., L.D., C.D.H., H.I., S.M., E.V., T.W., K.R., G.K.S., M.J.D.; Formal analysis, A.P.N., H.C., S.H., M.S.Y.L., O.G., C.C.B., Y.C.C. T.B., K.R., M.J.D., S.L.N; Writing – Original Draft, A.P.N.; Writing – Review & Editing, A.P.N., H.C., S.H., G.K.S., S.L.N., and W.S.A.; Funding Acquisition, A.P.N. and W.S.A.; Supervision, A.P.N., M.A.D., D.M.T., G.K.S., M.J.D., S.L.N. and W.S.A.
COMPETING FINANCIAL INTERESTS
The authors declare that there are no competing financial interests.
Figure Legends
Figure 1. Expression of the Erg locus and targeted disruption of Erg in lymphopoiesis.
Figure 2. The immunoglobulin heavy chain locus in Rag1CreT/+;ErgΔ/Δ mice.
Figure 3. A Rearranged VH10tar IgH allele rescues Rag1CreT/+;ErgΔ/Δ B-lymphoid development.
Figure 4. Gene expression in Rag1CreT/+;ErgΔ/Δ pre-proB cells and Erg DNA binding.
Figure 5. Gene expression in Ebf1- and Pax5-deficient B-cell progenitors and rescue of Erg-deficient B-cell progenitors.
Figure 6. The Erg mediated Ebf1 and Pax5 gene regulatory network in pre-proB cells.
CONTACT FOR REAGENT AND RESOURCE SHARING
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Ashley Ng (ang{at}wehi.edu.au) subject to Material Transfer Agreements.
EXPERIMENTAL MODEL AND SUBJECT DETAILS
Mice
Mice carrying the Ergtm1a(KOMP)wtsi knock-first reporter allele 46 (ErgKI, KOMP Knockout Mouse Project) were generated by gene targeting in ES cells. Mice with a conditional Erg knockout allele (Ergfl) from which the IRES-LacZ cassette was excised was generated by interbreeding ErgKI mice with Flpe transgenic mice 47. Rag1Cre mice 48, in which Cre recombinase is expressed during lymphopoiesis from the CLP stage 22, were interbred with Ergfl mice to generate mice lacking Erg in lymphopoiesis (Rag1CreT/+;ErgΔ/Δ) and Rag1Cre+/+;Ergfl/fl (Ergfl/fl) controls. Mice carrying the rearranged immunoglobulin heavy chain IgHVH10tar allele 49 were a gift from Professor Robert Brink. Rag1-/- mice were obtained from the Jackson Laboratory. The cEμΔ/Δ and μΑΔ/Δ mice were generated by the MAGEC laboratory (Walter and Eliza Hall Institute of Medical Research) as previously described 50 on a C57BL/6J background. To generate cEμΔ mice, 20 ng/μl of Cas9 mRNA, 10 ng/μl of sgRNA (GTTGAGGATTCAGCCGAAAC and ATGTTGAGTTGGAGTCAAGA) and 40 ng/μl of oligo donor (CAAGCTAAAATTAAAAGGTTGAACTCAATAAGTTAAAAGAGGACCTCTCCAGTT TCGGCTCAACTCAACATTGCTCAATTCATTTAAAAATATTTGAAACTTAATTTATT ATTGTTAAAA) were injected into the cytoplasm of fertilized one-cell stage embryos. To generate μΑΔ mice, 20 ng/μl of Cas9 mRNA, 10 ng/μl of sgRNA (GAACACCTGCAGCAGCTGGC) and 40 ng/μl of oligo donor (GCTACAAGTTTACCTAGTGGTTTTATTTTCCCTTCCCCAAATAGCCTTGCCACAT GACCTGCCAGCTGCTGCAGGTGTTCTGGTTCTGATCGGCCATCTTGACTCCAACT CAACATTGCT) were injected into the cytoplasm of fertilized one-cell stage embryos. Twenty-four hours later, two-cell stage embryos were transferred into the oviducts of pseudo-pregnant female mice. Viable offspring were genotyped by next-generation sequencing. Mice were analysed from 5 to 14 weeks of age. Male and female mice were used. Experimental procedures were approved by the Walter and Eliza Hall Institute of Medical Research Animal Ethics Committee.
Primary cell culture
B-cell progenitors were obtained from bone marrow that was lineage depleted using biotinylated Ter119, Mac1, Gr1, CD3, CD4, and CD8 antibodies, anti-biotin microbeads and LS columns (Miltenyi Biotec) and cultured on OP9 stromal cells in Iscove’s Modified Dulbecco’s Medium (Gibco, Invitrogen) supplemented with 10% (v/v) foetal calf serum (Gibco, Invitrogen), 50μM β-mercaptoethanol as well as murine interleukin-7 (10ng/mL) at 37°C in 10% CO2 for 7 days. Splenic B-cells were purified by negative selection using a B-cell isolation kit (Miltenyi Biotec) as described 51 and purity was confirmed by flow cytometry prior to labelling with Cell Trace Violet (CTV; Life technologies) as per manufacturer instructions. Labelled cells were seeded at 5×104 cells per well and cultured for 90 hours.
METHOD DETAILS
Haematology
Blood was collected into tubes containing EDTA (Sarstedt) and analysed on an Advia 2120 analyser (Bayer).
Flow Cytometry
Single-cell suspensions from bone marrow, lymph node or spleen were prepared in balanced salt solution (BSS-CS: 0.15M NaCl, 4mM KCl, 2mM CaCl2, 1mM MgSO4, 1mM KH2PO4, 0.8mM K2HPO4, and 15mM HEPES supplemented with 2% [vol/vol] bovine calf serum). Analysis of blood was performed after erythrocyte lysis in buffered 156mM NH4Cl. Staining was performed using biotinylated or fluorochrome-conjugated antibodies specific for murine antigens Ter119 (Ly-76), CD41 (MWReg30), Gr1 (Ly6G and Ly6C), Mac1 (CD11b), NK1.1, CD11c (N418), CD45R/B220 (RA3-6B2), CD19 (1D3), CD3 (17A2), CD4 (GK1.5), CD8a (53.6.7), Sca1 (Ly6A/E, D7), cKit (CD117, ACK4 or 2B8), CD150 (TC15-12F12.2), CD105 (MJ7/18), CD16/32 (24G2), CD127 (A7R34), CD135 (A2F10), Ly6D (49-H4), CD21/CD35 (7G6), CD23 (B3B4), CD93 (AA4.1), CD24 (M1/69), CD43 (S7), CD45.2 (S450-15-2), CD45.1 (A20), IgMb (AF6-78), IgD (11-26c.2a), CD138 (281.2), IgG1 (X56), CD25 (3C7), CD44 (IM7). Secondary staining used streptavidin PE-Texas-Red (Invitrogen). FACS-Gal analysis was performed using warm hypotonic loading of fluorescein di β-D-galactopyranoside (Molecular Probes) on single cells as described 52 followed by immunophenotyping using relevant surface antigens as defined in Table S1. Cells were analyzed using a LSR II or FACS Canto flow cytometer (Becton Dickinson) or sorted using a FACSAria II (Becton Dickinson) flow cytometer after antibody staining and lineage selection or depletion using anti-biotin beads and LS columns (Miltenyi Biotec). Data was analysed using FlowJo software (Version 8.8.7, Tree Star).
Genomic PCR
Genomic DNA was extracted using DirectPCR lysis reagent (Viagen) with proteinase K (Sigma-Aldrich) or the DNeasy minikit (Qiagen). 1μL of supernatant from murine tail samples lysed in 200μL or 50-100ng of genomic DNA were used for each reaction. Conditional Erg genomic deletion was detected using primers designed to detect the wild-type, floxed or deleted Erg alleles (Table S3). Degenerate PCR primers for detection of genomic recombination across distal VH558 or proximal VH7183, VHQ52 regions, the DH region or Mu0 regions to J3 segments 53, and Vκ 54 were used as described, as were primers to detect TCR VβJ recombination 55, 56 and the IgHVH10tar allele 57 (Table S3) 58,59–61. PCR products were separated by agarose gel electrophoresis and visualized with ethidium bromide staining. For quantitative genomic PCR using SYBR green (Life technologies), primers spanning individual Erg exons were used as described 19 and relative quantitation was performed using the 2-ΔΔCT method 62.
Splenic B-cell culture
Splenic B-cells were purified and purity was confirmed by flow cytometry prior to labelling with Cell Trace Violet (CTV; Life technologies) as per manufacturer instructions. Labelled cells were seeded at 5×104 cells per well and cultured for 90 hours with either AffiniPure F(ab’)₂ Fragment Goat Anti-Mouse IgM µ Chain Specific (20mg/ml; Jackson Immunoresearch), CD40L (produced in-house as described 63) supplemented with IL4 (10ng/ml; R&D systems) and IL5 (5ng/ml; R&D systems) to assess T-cell dependent responses, or LPS (25mg/ml; Difco) to assess T-cell independent responses, and analysed by flow cytometry.
RNA-seq of primary B-cell progenitor samples
Total RNA was extracted using the RNeasy Plus minikit (Qiagen) from bone marrow B-lymphoid populations sorted independently from two Rag1CreT/+;ErgΔ/Δ and Rag1Cre+/+;Ergfl/fl mice at 7-10 weeks of age. Sequencing was performed on an Illumina Hi-Seq 2500 to generate 100bp paired-end reads. Two biological replicates were sequenced for each mouse strain and B-cell development stage. Adapter sequences were removed using Trimgalore (https://github.com/FelixKrueger/TrimGalore). Reads were aligned to the mm10 mouse genome using STAR 64. Genewise counts were obtained using featureCounts 65 with Rsubread’s built-in Entrez Gene annotation 66. Downstream analysis as conducted using edgeR 3.22.5 67. For each B-cell stage, genes were filtered as non-expressed if they were assigned 0.5 counts per million mapped reads (CPM) in fewer than two libraries. Library sizes were TMM normalized and differential expression was assessed using quasi-likelihood F-tests 68. Genes were called differentially expressed if they achieved a false discovery rate of 0.05 (Table S4). For plotting purposes, counts were converted to Fragments Per Kilobase of transcript per Million mapped reads (FPKM) using edgeR’s rpkm function. These data have been deposited in Gene Expression Omnibus database (accession number GSE132854).
Analysis of publicly available RNA-seq datasets
FASTQ files containing RNA-seq profiles of B-cell progenitor cells were downloaded from GEO for Ebf1Δ/Δ (GSM2879293, GSM2879294, GSM2879295), Pax5Δ/Δ (GSM2879296, GSM2879297, GSM2879298) and wildtype mice (GSM2879299, GSM2879300, GSM2879301). Reads were aligned to the mm10 genome using Rsubread’s align function and read counts were summarized at the gene level as for the primary B-cell samples 66. Genes were filtered from downstream analysis using edgeR’s filterByExpr function and library sizes were TMM normalized. Counts were transformed to log2-CPM and the mean-variance relationship estimated using the voom function in limma 69. Heatmaps were generated using heatmap.2 function in gplots. Genes were tested for differential expression using linear modelling in limma 3.38.2 70. Gene set testing was performed using camera 45 and barcode plots were generated with limma.
Chromatin Immunoprecipitation (ChIP)
Chromatin immunoprecipitation was performed on 2×107 cultured ProB cells or primary Rag1CreT/+;ErgΔ/Δ thymocytes as a negative control for Erg binding. Cells were cross-linked with 1% formaldehyde for 15 min at room temperature, terminated by the addition of 0.125M glycine. Cells were then lysed in 1% SDS, 10mM EDTA, 50mM Tris-HCl, pH8.0, and protease inhibitors. Lysates were sonicated in a Covaris ultrasonicator to achieve a mean DNA fragment size of 500 bp. Immunoprecipitation was performed using 10μg of antibodies for a minimum of 12h at 4°C in modified RIPA buffer (1% Triton X-100, 0.1% deoxycholate, 90mM NaCl, 10mM Tris-HCl, pH8.0 and protease inhibitors). An equal volume of protein A and G magnetic beads (Life Technologies) were used to bind the antibody and associated chromatin. Reverse crosslinking of DNA was performed at 65°C overnight with RNaseA digestion followed by DNA purification using QIAquick PCR purification kits (Qiagen). Immunoprecipitated DNA was analysed on an Applied Biosystems StepOnePlus System with SYBR green reagents for iEμ μA and intergenic negative control regions using specific primers as detailed in Table S2. Relative ChIP PCR enrichment of the iEμ μA containing region in ProB cells compared to Rag1CreT/+;ErgΔ/Δ thymocytes was performed and normalized to the intergenic negative control region using the 2-ΔΔCT method 62.
ChIP-seq
For sequencing analysis of immunoprecipitated DNA, DNA was quantified using the Qubit dsDNA HS Assay (Life Technologies). Library preparations were performed using the standard ThruPLEXTM-FD Prep Kit protocol (Rubicon Genomics) and size selected for 200–400bp fragments using Pippen Prep (Sage Science Inc.). Fragment sizes were confirmed using either the High Sensitivity DNA assay or the DNA 1000 kit and 2100 bioanalyzer (Agilent Technologies). Libraries were quantified with qPCR, normalized and pooled to 2nM before sequencing with single-end 75bp reads using standard protocols on the NextSeq (Illumina). DNA reads were adapter trimmed using Trimmomatic 71 and aligned to the GRCm38/mm10 build of the Mus musculus genome using the BWA aligner 72. Peaks were called using MACS2 73 with default parameters to identify peaks using C17 antibody for Erg binding with Rag1CreT/+;ErgΔ/Δ thymocytes as a negative control to filter peaks not due to Erg binding, and were annotated to closest (peak start within 10kb from TSS) and overlapping genes using the R/Bioconductor package ChIPpeakAnno 74 (Table S5). These data have been deposited in Gene Expression Omnibus database (accession number GSE132853). Publicly available FASTQ files for Ebf1 (GSM1296532, GSM1296537), Pax5 (GSM932924), H3K4me3 (GSM2255547) and H3K27Ac (GSM2255552) ChIP-seq experiments were aligned to the mm10 mouse reference genome (GRCm38, December 2011) using Rsubread 75. Peak-calling was performed using MACS2 73 against input FASTQ files (GSM1296537, GSM1145867). Coordinates for Pu.1, Pax5, Irf4, YY1, Rad21 and CTCF binding were as published 76, while coordinates from annotated immunoglobulin heavy chains were obtained from Ensemble/Biomart (accessed 6th March 2017) and coordinates for 3’ regulatory region (3’RR) hypersensitivity regions, 3’αE, iEμ, were as published 77,78,79,14.
ATAC-seq analysis
ATAC-seq 80 was performed on sorted pre-proB, proB and preB populations. Briefly, 5×104 nuclei were fragmented by sonication for 30 minutes at 37°C and the DNA purified prior to amplification with indexing primers (HiFi Ready Mix, Kapa Biosciences) for 13 PCR cycles followed by quality assessment by Bioanalyser. High quality libraries were size selected (150 – 700 base pairs) and sequenced using a high output paired end 75 base pair kit on the Nextseq 500 (Illumina) to a minimum of 50 million reads. ATAC-seq reads were aligned to mm10 genome using Bowtie2 81 (http://bowtie-bio.sourceforge.net/bowtie2/index.shtml accessed 6th March 2017). Peak calling was performed using MACS2 73. Intersections of genetic coordinates were performed using Bedtools (http://bedtools.readthedocs.io/en/latest/ accessed 6th March 2017). Heatmaps of unique peaks were generated using pHeatmap in R. These data have been deposited in Gene Expression Omnibus database (accession number GSE132852).
Visualisation of RNA-seq, ChIP-seq and ATASeq data
RNA-seq, ChIP-seq and ATAC-seq files were converted to BigWig files using deepTools (version 2) 82 and uploaded to Cyverse (www.cyverse.org) for visualization in UCSC Genome Browser 83 (genome.ucsc.edu).
Gene Network Analysis
All Ebf1, Pax5 and Erg ChIP-seq peaks mapping to differentially expressed genes in Rag1CreT/+;ErgΔ/Δ pre-proB cells within 10Kb of the transcriptional start sites (TSS) were identified. Peaks inside the gene body were annotated as “proximal targets”, peaks overlapping the TSS were labelled as promoter regulated targets, peaks less than 3kb upstream or downstream of the TSS were labelled as putative promoter regulated targets, peaks more than 3kb upstream or downstream TSS were labelled as putative distal targets. Gene Ontogeny (GO) annotation of differentially expressed genes was performed and underwent expert manual curation. The network was constructed using 84 CRAN package, and exported to Cytoscape 85 for customization using RCy3 86 R/Bioconductor package.
Hi-C Analysis
In situ Hi-C was performed as previously described 87. The data preprocessing and analysis was performed as previously described with changes in parameters 13. In brief, primary immune cell libraries were generated in biological duplicates for each genotype. An Illumina NextSeq 500 was used to sequence libraries with 80bp paired-end reads to produce libraries of sizes between 42 million and 100 million valid read pairs. Each sample was aligned to the mm10 genome using the diffHic package v1.14.0 88 which utilizes cutadapt v0.9.5 89 and bowtie2 v2.2.5 81 for alignment. The resultant BAM file was sorted by read name, the FixMateInformation command from the Picard suite v1.117 (https://broadinstitute.github.io/picard/) was applied, duplicate reads were marked and then re-sorted by name. Read pairs were determined to be dangling ends and removed if the pairs of inward-facing reads or outward-facing reads on the same chromosome were separated by less than 1000 bp for inward-facing reads and 6000 bp for outward-facing reads. Read pairs with fragment sizes above 1000 bp were removed. An estimate of alignment error was obtained by comparing the mapping location of the 3’ segment of each chimeric read with that of the 5’ segment of its mate. A mapping error was determined to be present if the two segments were not inward-facing and separated by less than 1000 bp, and around 1-2% were estimated to have errors. Differential interactions (DIs) between the three different groups were detected using the diffHic package 88. Read pairs were counted into 100 kbp bin pairs. Bins were discarded if found on sex chromosomes, contained a count of less than 10, contained blacklisted genomic regions as defined by ENCODE for mm10 90 or were within a centromeric or telomeric region. Filtering of bin-pairs was performed using the filterDirect function, where bin pairs were only retained if they had average interaction intensities more than 5-fold higher than the background ligation frequency. The ligation frequency was estimated from the inter-chromosomal bin pairs from a 500 kbp bin-pair count matrix. The counts were normalized between libraries using a loess-based approach. Tests for DIs were performed using the quasi-likelihood (QL) framework 68 of the edgeR package. The design matrix was constructed using a one-way layout that specified the cell group to which each library belonged and the mouse sex. A mean-dependent trend was fitted to the negative binomial dispersions with the estimateDisp function. A generalized linear model (GLM) was fitted to the counts for each bin pair 91, and the QL dispersion was estimated from the GLM deviance with the glmQLFit function. The QL dispersions were then squeezed toward a second mean-dependent trend, using a robust empirical Bayes strategy 92. A p-value was computed against the null hypothesis for each bin pair using the QL F-test. P-values were adjusted for multiple testing using the Benjamini-Hochberg method. A DI was defined as a bin pair with a false discovery rate (FDR) below 5%.
DIs adjacent in the interaction space were aggregated into clusters using the diClusters function to produce clustered DIs. DIs were merged into a cluster if they overlapped in the interaction space, to a maximum cluster size of 1 Mbp. The significance threshold for each bin pair was defined such that the cluster-level FDR was controlled at 5%. Cluster statistics were computed using the csaw package v1.16.0 93. Overlaps between unclustered bin pairs and genomic intervals were performed using the InteractionSet package 94. Plaid plots were constructed using the contact matrices and the plotHic function from the Sushi R package 95. The color palette was inferno from the viridis package 96 and the range of color intensities in each plot was scaled according to the library size of the sample. The plotBedpe function of the Sushi package was used to plot the unclustered DIs as arcs where the z-score shown on the vertical access was calculated as -log10(p-value). These data have been deposited in Gene Expression Omnibus database (accession number GSE133246).
Fluorescence In Situ Hybridisation
Cultured B-cell progenitors were resuspended in hypotonic 0.075M KCl solution and warmed to 37°C for 20 minutes. Cells were pelleted and resuspended in 3:1 (vol/vol) methanol:glacial acetic acid fixative. Fixed cells were dropped onto coated ShandonTM polysine slides (ThermoFisher Scientific) and air dried. The cells were hybridized with FISH probes (Creative Bioarray) at 37°C for 16 hours beneath a coverslip sealed with Fixogum (Marabu) after denaturation at 73°C for 5 minutes. Cells were washed at 73°C in 0.4x SSC/0.3%NP40 for 2 minutes followed by 2x SSC/0.1%NP40 for less than 1 minute at room temperature and air dried in the dark and cover slipped. Images of nuclei were captured on an inverted Zeiss LSM 880 confocal using a 63x/1.4 NA oil immersion objective. Z-stacks of images were then captured using the lambda scan mode, a 405 and a multi-band pass beam splitter (488/561/633). The following laser lines were used: 405, 488, 561 and 633 nm. Spectral data was captured at 8 nm intervals. In all cases, images were set up with a pixel size of 70 nm and an interval of 150 nm for z-stacks. Single dye controls using the same configuration were captured and spectra imported for spectral unmixing using the Zen software (Zen 2.3, Zeiss Microscopy). Unmixed data was then deconvolved using the batch express tool in Huygens professional software (Scientific Volume Imaging). Images were analysed using TANGO software 97 after linear deconvolution. Nuclear boundaries were extracted in TANGO using the background nuclear signal in the Aqua channel. A 3D median filter was applied and the 3D image projected with maximum 2D image projection for nuclei detection using the Triangle method for automated thresholding in ImageJ 98. Binary image holes were filled and a 2D procedure implemented to separate touching nuclei using ImageJ 2D watershed implementation. The 2D boundaries of the detected nuclei were expanded in 3D and inside each 3D delimited region, Triangle thresholding was applied to detect the nuclear boundary in the 3D space. Acquired images from immunofluorescent probes were first filtered using 3D median and 3D tophat filter to enhance spot-like structures followed by application of the “spotSegmenter” TANGO plugin with only the best 4 spots having the brightest intensity kept for analysis. The spots identified by TANGO were manually verified against the original immunofluorescent image to identify and record the correct distance computed by TANGO between the aqua and 5-Rox immunofluorescent probes for both Igh alleles within a nucleus.
Statistical Analysis
Student’s unpaired two-tailed t-tests were used using GraphPad Prism (GraphPad Software), unless otherwise specified. Unless otherwise stated, a P value of < 0.05 was considered significant.
KEY RESOURCES TABLE
Inventory of Supplemental Information
Supplemental Figures
Figure S1. Representative flow cytometry plots indicating gating strategies for analysis of hematopoietic cell populations. Related to Figure 1
Figure S2. B-lymphopoiesis in Rag1CreT/+ mice and T-lymphopoiesis in Rag1CreT/+;ErgΔ/Δ mice. Related to Figure 1.
Figure S3. In vivo Erg binding to the iEμ enhancer in pre-proB cells. Related to Figure 2.
Figure S4. RNA-seq and Erg, Ebf1 and Pax5 binding and chromatin accessibility at selected gene loci. Related to Figure 2, 4, 6.
Supplemental Tables
Table S1. Immunophenotype of hematopoietic cell populations. Related to Figure 1.
Table S2. Peripheral blood counts of Rag1CreT/+;ErgΔ/Δ mice. Related to Figure 1.
Table S3. Primers and PCR reactions. Related to Figure 2, 3.
Table S4. RNA-seq. Differentially expressed genes in Rag1CreT/+;ErgΔ/Δ pre-proB cells, and Ebf1Δ/Δ Pax5Δ/Δ B-cell progenitors (EXCEL FILE). Related to Figure 4.
Table S5. Erg, Ebf1 and Pax5 ChIP binding coordinates to differentially expressed genes in Rag1CreT/+;ErgΔ/Δ pre-proB cells (EXCEL FILE). Related to Figure 6.
Supplementary Tables
Table S1. Immunophenotype of hematopoietic cell populations. See Figure 1.
Table S2. Peripheral blood counts of Rag1CreT/+;ErgΔ/Δ mice. See Figure 1.
Table S3. Primers and PCR reactions. See Figure 2, 3.
Table S4. RNA-seq. Differentially expressed genes in Rag1CreT/+;ErgΔ/Δ pre-proB cells, and Ebf1Δ/Δ Pax5Δ/Δ B-cell progenitors (EXCEL FILE). See Figure 4.
Table S5. Erg, Ebf1 and Pax5 ChIP binding coordinates to differentially expressed genes in Rag1CreT/+;ErgΔ/Δ pre-proB cells (EXCEL FILE). See Figure 6
Acknowledgements
We thank Janelle Lochland, Jason Corbin, Jasmine McManus, Melanie Salzone, Carolina Alvarado, Keti Stoev, Nicole Lynch and Shauna Ross for skilled assistance. We thank Professor Robert Brink for the VH10tar knock-in mouse line. This work was supported by Program Grants (1113577, 1016647, 1054618, 1054925), Project Grant (APN 1060179, 1122783), Fellowship (DMT 1060675, SLN 1155342, WSA 1058344, TMJ 1124081), C.R.B. Blackburn Scholarship (MSYL, Australian National Health and Medical Research Council jointly with Royal Australasian College of Physicians) and Independent Research Institutes Infrastructure Support Scheme Grant (361646) from the Australian National Health and Medical Research Council, the Australian Cancer Research Fund and Victorian State Government Operational Infrastructure Support. YCC was supported through Maddie Riewoldt’s Vision. The MAGEC laboratory was supported by the Australian Phenomics Network and the Australian Government through the National Collaborative Research Infrastructure Strategy Program.
Footnotes
Conflict of Interest: None
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