A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation Sandeep N. Wontakala,1, Xingyi Guob,1, Cameron Smithc,2, Thomas MacCarthyc,d,2, Emery H. Bresnicke, Aviv Bergmanc, Michael P. Snyderf,g, Sherman M. Weissmanh,3, Deyou Zhengb,i,3, and Arthur I. Skoultchia,3 Departments of aCell Biology, bNeurology, cSystems and Computational Biology, and iGenetics and Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461; dDepartment of Applied Mathematics and Statistics, State University of New York, Stony Brook, NY 11794; eWisconsin Institutes for Medical Research, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705; hDepartment of Genetics, Yale University School of Medicine, New Haven, CT 06520; fDepartment of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520; and gDepartment of Genetics, Stanford University, Stanford, CA 94305 Contributed by Sherman M. Weissman, December 29, 2011 (sent for review October 10, 2011) Two mechanisms that play important roles in cell fate decisions are PU.1, is a negative regulator of terminal erythroid differentiation control of a “core transcriptional network” and repression of alter- (16–19). Surprisingly, PU.1 was found to occupy more genes in native transcriptional programs by antagonizing transcription fac- erythroid progenitors than the three erythroid-promoting factors tors. Whether these two mechanisms operate together is not (20). However, the extent of overlap between the genes bound by known. Here we report that GATA-1, SCL, and Klf1 form an erythroid PU.1 and the three erythroid factors is not known. core transcriptional network by co-occupying >300 genes. Impor- In this study, we provide genomic evidence for the existence of tantly, we find that PU.1, a negative regulator of terminal erythroid a core erythroid network of >300 genes that are co-occupied and differentiation, is a highly integrated component of this network. regulated by GATA-1, SCL, and Klf1. This network has charac- GATA-1, SCL, and Klf1 act to promote, whereas PU.1 represses ex- teristic features of core transcriptional networks, including pression of many of the core network genes. PU.1 also represses the a multi-input motif and feed-forward loops. Furthermore, we also genes encoding GATA-1, SCL, Klf1, and important GATA-1 cofactors. find that PU.1 binds to and represses most of the genes in this Conversely, in addition to repressing PU.1 expression, GATA-1 also network, indicating that PU.1 is a highly integrated negative > binds to and represses 100 PU.1 myelo-lymphoid gene targets in regulator of the core erythroid network. Conversely, we also find erythroid progenitors. Mathematical modeling further supports that that GATA-1 binds to and represses >100 PU.1 myelo-lymphoid this dual mechanism of repressing both the opposing upstream acti- gene targets in erythroid progenitors. Finally, mathematical vator and its downstream targets provides a synergistic, robust fi modeling reveals that the dual mechanism used by both GATA-1 mechanism for lineage speci cation. Taken together, these results and PU.1 to repress an alternative lineage-specific transcriptional amalgamate two key developmental principles, namely, regulation program provides a robust mechanism for lineage specification. of a core transcriptional network and repression of an alternative transcriptional program, thereby enhancing our understanding of Results the mechanisms that establish cellular identity. GATA-1 Preferentially Binds Distal to Genes. To begin to investigate the possible existence of a “core erythroid network,” we carried ChIP sequencing | erythropoiesis | cross antagonism out ChIP-Seq experiments on endogenous GATA-1 in normal, murine ES cell-derived erythroid progenitors (ES-EP) (21) in lthough cells have hundreds of transcriptional regulators, the both proliferating and differentiating conditions. The following Afunction of only a few key factors has been proposed to be results indicate that our ChIP-Seq data are of high quality. critical for establishing and/or maintaining cellular identity (1). Several well-established GATA-1 binding sites are found in the Studies in just a few cell types, particularly embryonic stem (ES) dataset, including binding sites in the β-globin locus control re- cells, support this concept (2, 3). In ES cells, the “core pluri- C ” ∼ gion (LCR) (Fig. S1 ). GATA-1 bound regions in both pro- potency factors Oct4, Nanog, and Sox2 co-occupy 300 genes liferating and differentiating conditions are highly enriched with that are enriched for developmental regulators and genes in- a characteristic GATA-1 binding motif (Fig. S1D), similar to that volved in self-renewal (2). The gene network formed by these observed in recent studies (12, 13). Using quantitative chromatin three core ES cell factors exhibits several types of regulatory immunoprecipitation (qChIP) for GATA-1, we validated 100% circuitry including a multi-input motif and feed-forward loops (2, (18/18) of the sites bound in both proliferating and differenti- 3). However, whether such a “core transcriptional network” exists ating conditions (Fig. S2). in hematopoietic cells is not known. Several recent reports describe genome-wide occupancy of GATA-1, SCL, and Klf1 are three essential erythroid pro- GATA-1 in several murine and human erythroid cell lines (12, moting transcription factors that play critical roles in establishing fi erythroid identity through the up-regulation of erythroid-specific 13, 22, 23). Similar to these other reports, we nd that GATA-1 genes (4, 5). GATA-1 regulates expression of some erythroid- specific genes, such as globin genes, in association with SCL (6–8) and Klf1 (9–11). Recent studies of transcription factor occupancy Author contributions: S.N.W., S.M.W., and A.I.S. designed research; S.N.W., C.S., and T.M. performed research; S.N.W., X.G., C.S., T.M., E.H.B., S.M.W., M.P.S., and D.Z. contributed in erythroid progenitors by chromatin immunoprecipitation and new reagents/analytic tools; S.N.W., X.G., C.S., T.M., A.B., S.M.W., D.Z., and A.I.S. analyzed high-throughput sequencing (ChIP-Seq) revealed that GATA-1 data; and X.G., C.S., T.M., S.N.W., D.Z., and A.I.S. wrote the paper. bound regions are enriched for SCL binding elements (12, 13), The authors declare no conflict of interest. SCL bound regions are enriched for potential GATA-1 binding Database deposition: The data reported in this paper have been deposited in the Gene sites (14), and Klf1 occupied regions are enriched for putative Expression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE35385). GATA-1 and SCL binding motifs (15). Although there is evidence 1S.N.W. and X.G. contributed equally to this work. that these three factors cooperatively regulate certain erythroid- 2C.S. and T.M. contributed equally to this work. fi speci c genes, whether they form a network with features similar 3To whom correspondence may be addressed. E-mail: [email protected], to the ES cell core transcriptional network is not known. [email protected], or [email protected]. Whereas GATA-1, SCL, and Klf1 are essential for erythroid This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. development, the myelo-lymphoid promoting transcription factor, 1073/pnas.1121019109/-/DCSupplemental. 3832–3837 | PNAS | March 6, 2012 | vol. 109 | no. 10 www.pnas.org/cgi/doi/10.1073/pnas.1121019109 Downloaded by guest on September 27, 2021 most often binds distal to gene promoters; 80–90% of GATA-1 progenitors (FL-EP) (14, 15), using the same criterion (−20 kb occupied sites are in intragenic or intergenic regions, and <20% TSS to +10 kb TES). We found that each factor binds to a large of bound regions are within 2 kb of transcription start sites (TSS) number of genes independent of the other two factors. GATA-1 (Fig. S1B). However, in contrast to the results in one of the binds 3,560 (490 + 1,810 + 1,260) genes independently, and SCL studies with murine erythroleukemia (MEL) cells (22), we find and Klf1 bind independently to 421 and 230 genes, respectively that the number of sites occupied by GATA-1 increases during (Fig. 1A). Importantly, however, the analysis revealed that 313 differentiation of erythroid progenitors, from 6,600 sites in (263 + 8 + 42) genes were co-occupied by the three factors (P − proliferating progenitors to 10,600 sites in differentiating cells. In value <2.2 × 10 16) (Fig. 1B), which is strikingly similar to the addition, we find that the magnitude of many GATA-1 ChIP-Seq number of genes that are co-occupied by the three core ES cell peaks increases during differentiation at sites occupied in both factors (353) (2). Furthermore, there is a strong bias for the three proliferating and differentiating cells (Fig. S1 A and C). These erythroid factors to bind in close proximity (within 200 bp) to one results provide unique genome-wide occupancy maps of GATA- another near these 313 genes (Fig. 1B). This bias is significantly 1 in normal erythroid progenitors, in both proliferating and different from the pairwise peak distances computed for the genes bound by only two of the three factors (Fisher’s exact test, differentiating conditions. − P value <2.2 × 10 16). This finding suggests that the three ery- Associating GATA-1 Occupancy with Gene Regulation. We next throid factors form a dense overlapping regulon and, more sought to understand the relationship between GATA-1 bound specifically, a multi-input motif, similar to the core networks sites and genes. Because there is no well-established method for described in ES, pancreatic, and liver cells (2, 3). We also find assigning transcription factor bound sites to genes (24, 25), we that the genes co-occupied by GATA-1, SCL, and Klf1 exhibit tested four different criteria and found that assigning genes to the largest changes in gene expression during the differentiation GATA-1 peaks that lie within the region spanning −20 kb of TSS of both ES-EP and MEL cells (Fig.