Differential genomic targeting of the transcription factor TAL1 in alternate haematopoietic lineages
2010; Springer Nature; Volume: 30; Issue: 3 Linguagem: Inglês
10.1038/emboj.2010.342
ISSN1460-2075
AutoresCarmen G. Palii, Carolina Perez‐Iratxeta, Zizhen Yao, Yi Cao, Fengtao Dai, Jerry Davison, Harold Atkins, David Allan, F. Jeffrey Dilworth, Robert Gentleman, Stephen J. Tapscott, Marjorie Brand,
Tópico(s)T-cell and Retrovirus Studies
ResumoArticle21 December 2010Open Access Differential genomic targeting of the transcription factor TAL1 in alternate haematopoietic lineages Carmen G Palii Carmen G Palii The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author Carolina Perez-Iratxeta Carolina Perez-Iratxeta The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author Zizhen Yao Zizhen Yao Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Yi Cao Yi Cao Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Fengtao Dai Fengtao Dai The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada Search for more papers by this author Jerry Davison Jerry Davison Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Harold Atkins Harold Atkins The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author David Allan David Allan The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author F Jeffrey Dilworth F Jeffrey Dilworth The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada Search for more papers by this author Robert Gentleman Robert Gentleman Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Stephen J Tapscott Stephen J Tapscott Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Marjorie Brand Corresponding Author Marjorie Brand The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada Search for more papers by this author Carmen G Palii Carmen G Palii The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author Carolina Perez-Iratxeta Carolina Perez-Iratxeta The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author Zizhen Yao Zizhen Yao Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Yi Cao Yi Cao Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Fengtao Dai Fengtao Dai The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada Search for more papers by this author Jerry Davison Jerry Davison Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Harold Atkins Harold Atkins The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author David Allan David Allan The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Search for more papers by this author F Jeffrey Dilworth F Jeffrey Dilworth The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada Search for more papers by this author Robert Gentleman Robert Gentleman Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Stephen J Tapscott Stephen J Tapscott Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA Search for more papers by this author Marjorie Brand Corresponding Author Marjorie Brand The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada Search for more papers by this author Author Information Carmen G Palii1,‡, Carolina Perez-Iratxeta1,‡, Zizhen Yao2, Yi Cao2, Fengtao Dai1,3, Jerry Davison2, Harold Atkins1, David Allan1, F Jeffrey Dilworth1,3, Robert Gentleman2, Stephen J Tapscott2 and Marjorie Brand 1,3 1The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada 2Department of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA 3Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada ‡These authors contributed equally to this work *Corresponding author. The Sprott Center for Stem Cell Research, Department of Regenerative Medicine, Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, Canada K1H 8L6. Tel.: +1 613 737 7700/Ext 70336; Fax: +1 613 739 6294; E-mail: [email protected] The EMBO Journal (2011)30:494-509https://doi.org/10.1038/emboj.2010.342 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info TAL1/SCL is a master regulator of haematopoiesis whose expression promotes opposite outcomes depending on the cell type: differentiation in the erythroid lineage or oncogenesis in the T-cell lineage. Here, we used a combination of ChIP sequencing and gene expression profiling to compare the function of TAL1 in normal erythroid and leukaemic T cells. Analysis of the genome-wide binding properties of TAL1 in these two haematopoietic lineages revealed new insight into the mechanism by which transcription factors select their binding sites in alternate lineages. Our study shows limited overlap in the TAL1-binding profile between the two cell types with an unexpected preference for ETS and RUNX motifs adjacent to E-boxes in the T-cell lineage. Furthermore, we show that TAL1 interacts with RUNX1 and ETS1, and that these transcription factors are critically required for TAL1 binding to genes that modulate T-cell differentiation. Thus, our findings highlight a critical role of the cellular environment in modulating transcription factor binding, and provide insight into the mechanism by which TAL1 inhibits differentiation leading to oncogenesis in the T-cell lineage. Introduction Cell differentiation is regulated by finely tuned mechanisms directed by cell-specific and ubiquitous transcription factors. Mutations (e.g. deletions, fusions) that affect the integrity of transcription factors by altering their DNA-binding specificity and/or capacity to interact with cofactors can transform these proteins into potent oncogenes. At the same time, wild-type (WT) (non-mutated) transcription factors can also become oncogenic when aberrantly expressed in an inappropriate cell type (Tenen, 2003; O'Neil and Look, 2007). While this argues for an important role of the cellular context in modifying transcription factors' ability to control cell fate, the extent to which the cellular environment affects the function of transcription factors is unclear (Pan et al, 2009). The basic helix-loop-helix (bHLH) protein TAL1 (also called SCL) displays distinct, sometimes opposite, functions in different cell types (Begley and Green, 1999; Lecuyer and Hoang, 2004). Indeed, TAL1 expression is necessary for the specification, survival and competence of haematopoietic stem cells and for the differentiation of megakaryocytes and erythrocytes (Lecuyer and Hoang, 2004; Reynaud et al, 2005; Brunet de la Grange et al, 2006; Souroullas et al, 2009; Lacombe et al, 2010). Yet TAL1, which is normally turned off early in the lymphoid lineage, exhibits oncogenic properties when aberrantly expressed in lymphoid tissue (Condorelli et al, 1996; Kelliher et al, 1996). Importantly, wild-type TAL1 is aberrantly expressed in over 60% of T-cell acute lymphoblastic leukaemia (T-ALL) patients and is considered a major factor in initiating leukaemic transformation via perturbation of the transcriptional regulatory network (Aifantis et al, 2008). TAL1-mediated leukaemogenesis has been linked to both an early arrest in the T-cell differentiation program and elevated levels of anti-apoptotic genes (Ferrando et al, 2002). While the mechanism of TAL1-mediated leukaemogenesis is unclear, it has been proposed that TAL1 interferes with the function of bHLH E-proteins (i.e. E2A, HEB or E2-2), which are important regulators of T-cell differentiation and whose inactivation leads to T-cell tumours in mice (Quong et al, 2002). Indeed, TAL1 binding to E-box DNA motifs (CANNTG) requires heterodimerization with an E-protein and in vitro binding selection experiments have identified a TAL1/E-protein heterodimer's preferred E-box (CAGATG), which differs from the E-protein homodimers' preferred E-box (CAGGTG) (Hsu et al, 1994). Interestingly, E-box recognition is not always an important determinant of TAL1 binding as it has been proposed to be tethered to genes via other DNA-binding transcription factors, including GATA3 in leukaemic T cells (Ono et al, 1998), and SP1 (Lecuyer et al, 2002) or GATA1 (Wadman et al, 1997) in erythroid cells. Recent ChIP-seq experiments in erythroid cells have revealed a strong correlation between GATA and TAL1 recognition motifs, with genomic sites bound by TAL1 being frequently associated to GATA motifs while GATA1-bound sites are enriched in E-boxes (Cheng et al, 2009; Fujiwara et al, 2009; Kassouf et al, 2010; Soler et al, 2010). In addition, GATA1 and TAL1 cooccupancy appears to correlate with active genes in erythroid cells, although these two transcription factors can be cobound to genes that are repressed (Cheng et al, 2009; Tripic et al, 2009; Soler et al, 2010). Interestingly, degenerate selection experiments for TAL1 binding in vitro have identified a composite E-box/Gata motif where the two DNA-binding sites are separated by 8–10 bp (Wadman et al, 1997). This particular distance is thought to be important for binding of a pentameric protein complex in which a TAL1/E2A heterodimer and a GATA factor are bridged by LMO2 and LDB1 proteins (Wadman et al, 1997). While this composite E-box/Gata motif was recently shown to be enriched under TAL1 peaks identified in erythroid cells (Kassouf et al, 2010; Soler et al, 2010), it has not been identified in ChIP-microarray studies performed in T-ALL cells (Palomero et al, 2006). As such, our lack of knowledge regarding the mechanism of how TAL1 recognizes binding sites in vivo represents one of the major limitations to our understanding of the role of this bHLH protein in promoting different cell fates depending on the lineage. Results TAL1 promotes erythroid differentiation while it blocks T-cell differentiation To identify features that distinguish the role of TAL1 in different cell types, we employed a comparative strategy whereby the transcriptional network of TAL1 is contrasted between an erythroid environment in which TAL1 promotes cellular differentiation and a T-cell context in which TAL1 promotes oncogenic transformation. Our strategy combines phenotypic analysis and gene expression profiling after TAL1 knockdown (KD) with chromatin immunoprecipitation and deep sequencing (ChIP-seq). To study TAL1 in the erythroid lineage we used primary erythroid cells differentiated ex vivo from human haematopoietic multipotential progenitors, a system that mimics the differentiation of erythroid cells in vivo (Giarratana et al, 2005) (Supplementary Figure S1 and data not shown). TAL1 KD was induced in pro-erythroblasts using lentivirus-delivered shRNA (Figure 1A). Following TAL1 KD (Figure 1B and C), we observed a strong diminution in cell growth (Figure 1D), which is due to both a decrease in cell proliferation (Figure 1E), and an increase in apoptosis (Figure 1F). Cell cycle analysis demonstrates accumulation of cells in the G0/G1 phases, suggesting a block at the G1/S transition (Figure 1G). To determine whether TAL1 KD also affects erythroid differentiation, we analysed accumulation of haemoglobin (Figure 1H; Supplementary Figure S2B), CD36, CD71 and GPA cell surface markers (Supplementary Figure S2C) as well as Gpa (Figure 1I) and β-globin (Figure 4C) transcripts. We found that these erythroid markers are all decreased in TAL1 KD cells confirming the importance of TAL1 for terminal erythroid differentiation. Figure 1.TAL1 knockdown in pro-erythroblasts leads to decreased proliferation and differentiation. (A) Timeline for induction of TAL1 KD in primary pro-erythroblasts using a lentiviral shRNA delivery system. (B, C) TAL1 level is decreased after infection with lentivirus expressing anti-Tal1 (TAL1 KD) but not scramble (Scr) shRNA, as verified by RT–qPCR (B) and western blot (C). Molecular weight markers (in kDa) are indicated on the left. (D) TAL1 KD leads to a profound decrease in cell growth. (E–G) Characterization of TAL1 KD. (Left panels) FACS histograms of representative experiments. (Right panels) Mean percentage of positive cells in three independent experiments. (E) TAL1 KD leads to a decrease in cell proliferation, as measured by BrdU incorporation. (F) TAL1 KD leads to an increase in apoptosis, as measured by Annexin V staining. Necrotic cells that are positive for 7AAD are excluded. (G) TAL1 KD leads to cell cycle arrest at the G1/S transition. DNA content is measured by propidium iodide (PI) staining. (H) TAL1 KD leads to a decrease in haemoglobin synthesis, as measured by benzidine staining. (I) TAL1 KD leads to a decrease in Glycophorin A (Gpa) transcription as measured by RT–qPCR. Error bars represent standard deviations of biological triplicates. (B, C, E–I) correspond to analyses performed on day 12 of (A). Download figure Download PowerPoint To study TAL1 in a T-cell environment, we first used the TAL1-expressing Jurkat cell line, which was originally derived from a T-ALL patient and represents a prototypical immature transformed T cell (Schneider et al, 1977). To KD TAL1 in Jurkat cells, clonal lines expressing a Dox-inducible shRNA against Tal1 were generated (Figure 2A and B). Similarly to erythroid cells, we observed a dramatic decrease in the growth of Jurkat cells upon TAL1 KD (Figure 2C). This is mostly due to apoptosis as shown by a 10-fold increase in Annexin V positive cells (Figure 2E), as well as a decrease in mitochondrial transmembrane potential and an increase in caspases 3 and 8 activities (data not shown). While TAL1 KD also led to a limited decrease in BrdU incorporation (Figure 2D), progression through the cell cycle is not affected (Figure 2F). Comparable phenotypic effects were observed in a second TAL1 KD clone stably expressing a distinct anti-Tal1 shRNA sequence (data not shown). Figure 2.TAL1 knockdown in Jurkat cells leads to apoptosis. (A, B) TAL1 level is decreased upon 72 h Dox treatment in a Jurkat clone stably expressing a Dox-dependent TAL1 shRNA, as verified by RT–qPCR (A) and western blot (B). Molecular weight markers (in kDa) are indicated on the left. (C) TAL1 KD leads to a profound decrease in cell growth. (D–F) Characterization of TAL1 KD after 72 h of Dox. (Left panels) FACS histograms of representative experiments. (Right panels) Mean percentage of positive cells in three independent experiments. (D) TAL1 KD leads to a decrease in cell proliferation, as measured by BrdU incorporation. (E) TAL1 KD leads to an increase in apoptosis, as measured by Annexin V staining. Necrotic cells that are positive for 7AAD are excluded. (F) TAL1 KD has no effect on cell cycle progression. DNA content is measured by PI staining. Error bars represent standard deviations of biological triplicates. Download figure Download PowerPoint Gene expression analysis upon TAL1 KD To gain further insight into the genes affected by TAL1 KD in erythroid and Jurkat cells, expression profiling by microarray was performed on WT and KD cells (Supplementary Figure S3). These experiments used Jurkat cells (WT) and their counterparts treated with Dox for 72 h (KD), as well as pro-erythroblasts at day 12 of differentiation that were either infected with lentiviruses expressing scrambled shRNA (WT) or infected with lentiviruses expressing anti-Tal1 shRNA (KD) as indicated on Figure 1A. We found that in erythroid cells, the majority of differentially expressed transcripts are downregulated upon TAL1 KD—442 transcripts downregulated versus 148 transcripts upregulated (Supplementary Figure S3). In contrast, the majority of differentially expressed transcripts in Jurkat cells are upregulated upon TAL1 KD—370 transcripts upregulated versus 249 transcripts downregulated. Microarray results were confirmed by RT–qPCR for all five tested TAL1-dependent genes in erythroid cells (Supplementary Figure S4A) and for 44 of the 45 genes tested in Jurkat cells (Supplementary Figure S4B and data not shown). In agreement with the observed phenotypic effects, Gene Ontology (GO) analysis of genes that are downregulated upon TAL1 KD in erythroid cells identified biological process categories related to cell cycle control, DNA replication and erythroid-related functions (Supplementary Figure S3C; Supplementary Table I). The same analysis of genes that are upregulated upon TAL1 KD in Jurkat cells identified categories related to apoptosis, negative regulation of growth and T-cell differentiation (Supplementary Figure S3B; Supplementary Table II). This last GO category suggested to us that upon TAL1 KD, Jurkat cells might have partially re-entered the T-cell differentiation transcriptional program. For example, four transcription factors that act as master regulators of T-cell differentiation (i.e. Gata3 (Ting et al, 1996), Sox4 (Schilham et al, 1997), Ikzf3 (coding for the Ikaros homolog Aiolos (Morgan et al, 1997)) and the thymocyte selection-associated gene Tox (Aliahmad and Kaye, 2008)), are among the genes identified by microarray (and confirmed by RT–qPCR (Supplementary Figure S4)) as being upregulated upon TAL1 KD. Furthermore, the increased expression of GATA3 and Aiolos upon TAL1 KD was confirmed at the protein level (Figure 3D). Figure 3.Jurkat cells are blocked at an immature stage resembling CD4+ intrathymic progenitors but partially re-enter the transcriptional program of T-cell differentiation upon TAL1 knockdown. (A–C) Gene set enrichment analysis (GSEA) was performed comparing microarray expression profiling of Jurkat cells upon TAL1 KD with signature gene sets established from expression profiling of purified normal primary human CD4+ T cells at different stages of differentiation (Lee et al, 2004). This analysis indicates that signature sets corresponding to early CD4+ intrathymic T-cell progenitors (sets 1 and 2) are enriched in the WT phenotype (in blue) while sets corresponding to more differentiated states (sets 3–6) are enriched in TAL1 KD phenotype (in red). For a detailed description of gene sets, see Supplementary data. (A) GSEA leading edge analysis heat map and list of enriched genes. (B) Enrichment plots for the six T-cell signature sets. NES, normalized enrichment score; FDR, false discovery rate. (C) Diagram summarizing the correlation between changes in gene expression profiles upon TAL1 KD in Jurkat cells and during CD4+ T-cell maturation. CD4ISP, CD4 immature single positive; DP, CD4 CD8 double positive; SP4, CD4 single positive; CB4, CD4 single positive from cord blood; AB4, CD4 single positive from adult blood. (D) TAL1 KD leads to profound changes in the protein levels of T-cell transcription factors. TAL1 KD was induced in Jurkat cells by the addition of Dox for 72 h. Nuclear extracts were prepared and analysed by western blot using antibodies indicated on the right. Molecular weight markers (in kDa) are indicated on the left. Download figure Download PowerPoint Figure 4.ChIP-seq analysis of TAL1 genomic binding in erythroid versus Jurkat cells. (A) Less than 10% of TAL1 peaks are located within promoters (defined as the region covering 5 kb upstream of TSS). GO analysis of genes closest to TAL1 peaks is represented below the Venn diagrams. P-values (P) are indicated. For a full list of GO terms, see Supplementary Tables III and IV. (B) Frequency of TAL1 peaks location relative to the TSS of their closest gene shows a bias around TSS. The P-value for Jurkat cells was calculated using Wilcoxon matched-pairs signed-ranks test. (C) Representative examples of ChIP-seq results showing TAL1 binding to the β-globin locus (LCR, locus control region), to the cdk6 second intron and to the cd69 promoter. Binding of TAL1 to locations indicated by a hatched square was validated by independent ChIP–qPCR. ChIP–qPCR values are expressed as a fraction of the input with error bars corresponding to standard deviations. Transcription was analysed by RT–qPCR with or without KD of TAL1. RT–qPCR values are normalized using 18S RNA with error bars corresponding to standard deviations. Download figure Download PowerPoint Genes that are differentially expressed at particular stages during human CD4+ T-cell differentiation were previously identified from purified human cells, and sorted into signature sets (Lee et al, 2004). To further examine the possibility that a decrease of TAL1 in CD4+ Jurkat cells leads to partial re-entry into the T-cell transcriptional program, we used gene set enrichment analysis (GSEA) to compare genes that are differentially expressed upon TAL1 KD in Jurkat cells to these signature sets (Figure 3). We found that gene sets corresponding to early CD4+ intrathymic T-cell progenitors (sets 1 and 2) are enriched in Jurkat cells, while gene sets upregulated in further differentiated T-cell states are enriched in the TAL1 KD condition (sets 3–6) (Figure 3). Notably, an increase in Tox, Sox4 and Gata3 transcript level upon TAL1 KD was again identified in this GSEA analysis (Figure 3A). Combined results from all six gene sets enrichments indicate that Jurkat cells resemble T cells blocked at the CD4+ immature single-positive stage (CD4ISP), and that upon TAL1 KD these cells partially resume the transcriptional program of T-cell differentiation before dying by apoptosis. Identification of TAL1 genomic binding sites by ChIP sequencing To understand how TAL1 might regulate the expression of genes identified by microarray, we performed genome-wide binding analysis. For each cell type (i.e. Jurkat cells and pro-erythroblasts at day 12 of differentiation, see Figure 1A), two biologically independent TAL1 ChIPs were performed, and the resulting DNA was amplified, subjected to high-throughput sequencing and aligned to the human reference genome (Supplementary Figure S5A). Examination of chromosome 2 indicates that TAL1 peaks are more abundant in erythroid compared with Jurkat cells (Supplementary Figure S5C). Genome wide, we counted 6315 TAL1 peaks in erythroid cells while in Jurkat cells the number of peaks decreases down to 2547 (Figure 4A). Considering the high frequency of E-boxes in the human genome, these numbers of TAL1-binding sites reflect a restricted genomic binding. An analysis based on the rate at which background signal is converted to foreground signal shows that we have attained sufficient sequencing depth for genome coverage (data not shown). Confirming the quality of our data set, ChIP-seq analysis identified a number of previously characterized TAL1 targets, including Epb42 (Xu et al, 2003), Gypa (Lahlil et al, 2004), DNase I hypersensitive site (HS) 2 of the β-globin locus (Song et al, 2007), c-kit (Lecuyer et al, 2002), Runx1 (Wilson et al, 2009) and Lmo2 (Landry et al, 2009) in erythroid cells, and Aldh1a2 (Ono et al, 1998), Tcra (Bernard et al, 1998), Chrna5 (Palomero et al, 2006) and Nfkb1 (Chang et al, 2006) in Jurkat cells (Figure 4; Supplementary Figures S6 and S7 and data not shown). In addition, we identified TAL1 peaks in pericentromeric regions (Supplementary Figure S5C and data not shown), which is consistent with reported TAL1 binding to satellite DNA (Wen et al, 2005). Validating the quality of our ChIP-seq results, all 23 known and novel TAL1 genomic targets that we tested (with peak heights ranging from 8 to 178 reads) were confirmed by independent ChIP-qPCR experiments (Figure 4C; Supplementary Figures S6 and S7 and data not shown). In agreement with the different functions of TAL1 in erythroid versus T-ALL cells, the proportion of overlapping TAL1 peaks between the two cell types is relatively small representing 6% of total peaks in erythroid cells and 15% of total peaks in Jurkat cells (Figure 4A). Functional annotation analyses of genes associated to the nearest TAL1 peak in erythroid and Jurkat cells identified overrepresented GO terms related to erythroid and T-cell differentiation, respectively (Figure 4A; Supplementary Tables III and IV). We also observed that while there is a higher local density of TAL1 peaks near TSSs in both erythroid and Jurkat cells (Figure 4B), the majority of TAL1 peaks are located away from promoter regions of known genes, mostly within introns and intergenic regions (Figure 4A). Binding at intergenic regions could represent in some cases binding to distal regulatory elements such as enhancers. For example, in erythroid cells TAL1 is bound to the four erythroid-specific DNase I HSs that comprise the distal β-globin locus control region LCR (Figure 4C). TAL1 is also frequently bound to introns as shown for the Cdk6 regulator of T-cell differentiation (Grossel and Hinds, 2006), whose expression is upregulated by TAL1 in T-ALL cells (Figure 4C). An example of TAL1 binding to a promoter region is shown on the Cd69 gene (Figure 4C), which is expressed transiently in immature thymocytes undergoing positive selection (Bendelac et al, 1992) and is also one of the earliest inducible cell surface glycoprotein acquired during lymphoid activation (Sancho et al, 2005). In contrast to Cdk6, the Cd69 gene is downregulated by TAL1 in Jurkat cells. Interestingly, the KD of TAL1 in an erythroid environment does not affect Cd69 expression despite TAL1 binding to this gene's promoter. Together, these ChIP-seq data provide us with a number of novel TAL1 genomic targets in both erythroid and T-ALL cellular environments. Identification of TAL1-target genes functionally regulated by TAL1 A major question arising in genome-wide studies of transcription factor binding is that of the association between binding events and regulated genes. As a first approximation, we associated TAL1 peaks to their closest genes. Functional annotation of these genes led to the identification of biological categories that are consistent with TAL1 function (Figure 4A), providing confidence that TAL1 indeed regulates some genes by binding to their promoter (e.g. Cd69; Figure 4C). However, in many cases, TAL1 is bound away from promoters. Therefore, a simple association of TAL1 peaks to their closest genes may miss target genes regulated by TAL1 via binding to a distal regulatory element. To identify TAL1 targets that are also functionally regulated by this factor, we took advantage of our identification of TAL1-dependent genes by microarray and restricted our analysis to genes that are differentially expressed upon TAL1 KD. To remain permissive to distal regulatory elements, differentially expressed genes were associated to TAL1 peaks located within 50 kb upstream or downstream of their TSS. Using this approach, 289 genes were identified in erythroid cells, including 246 that are downregulated upon TAL1 KD (thereafter called 'TAL1-activated genes') and 43 that are upregulated (thereafter called 'TAL1-repressed genes') (Supplementary Table V). This result is consistent with previous studies, which have predominantly associated TAL1 to active genes in erythroid cells (Cheng et al, 2009; Tripic et al, 2009; Soler et al, 2010). In agreement with our phenotypic analyses (Figure 1), many TAL1-activated genes in erythroid cells are involved in the regulation of DNA replication, cell cycle and erythroid differentiation. In Jurkat cells, we identified 73 TAL1-repressed genes and 44 TAL1-activated genes (Supplementary Table VI). Among them, we note the presence of genes that are upregulated upon TAL1 KD and code for important T-cell-specific transcription factors such as TOX (Aliahmad and Kaye, 2008) and Aiolos/ikzf3 (Morgan et al, 1997). Conversely, the TAL1-target gene Cdk6, which is normally downregulated during T-cell differentiation (Grossel and Hinds, 2
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