A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation

Abstract

Two mechanisms that play important roles in cell fate decisions are control of a "core transcriptional network" and repression of alternative transcriptional programs by antagonizing transcription factors. Whether these two mechanisms operate together is not known. Here we report that GATA-1, SCL, and Klf1 form an erythroid core transcriptional network by co-occupying >300 genes. Importantly, we find that PU.1, a negative regulator of terminal erythroid differentiation, is a highly integrated component of this network. GATA-1, SCL, and Klf1 act to promote, whereas PU.1 represses expression of many of the core network genes. PU.1 also represses the genes encoding GATA-1, SCL, Klf1, and important GATA-1 cofactors. Conversely, in addition to repressing PU.1 expression, GATA-1 also binds to and represses >100 PU.1 myelo-lymphoid gene targets in erythroid progenitors. Mathematical modeling further supports that this dual mechanism of repressing both the opposing upstream activator and its downstream targets provides a synergistic, robust mechanism for lineage specification. Taken together, these results amalgamate two key developmental principles, namely, regulation of a core transcriptional network and repression of an alternative transcriptional program, thereby enhancing our understanding of the mechanisms that establish cellular identity.

Fig. 1.

GATA-1, SCL, and Klf1 co-occupy many genes and bind in close proximity to each other. (A) Using occupancy maps derived from ChIP-Seq analysis of GATA-1 in proliferating and differentiating ES-EP along with SCL (14) and Klf1 (15) occupancy maps in FL-EP, we determined what genes were occupied by each factor. Occupancy was defined as a factor binding within −20 kb of TSS through +10 kb of TES of a given gene. A four-set Venn diagram is displayed, comparing the number of genes occupied by each factor. (B) The distance between bound sites of each factor was calculated for genes that are occupied by SCL, Klf1, and GATA-1 (in proliferating and/or differentiating cells). (C and D) Boxplots show the relative gene expression changes that occur during the differentiation of ES-EP (C) (20) or MEL cells (D) (20) for genes occupied by the indicated combination of factors. (E) The fraction of genes with the indicated occupancy of the three erythroid factors that were found to be expressed and form transcription factories with either α- or β-globin loci in erythroid cells as identified in a recent study (26).

Fig. 2.

Genes bound by GATA-1, SCL, and Klf1 are enriched for erythroid genes. (A) Ingenuity pathway analysis (IPA) was performed on genes co-occupied by all three erythroid factors. The 10 most significantly enriched molecular and cellular functions/physiological system development and functions within this set of genes are displayed. (B) Occupancy maps are shown for GATA-1, SCL, and Klf1 in the vicinity of the genes that encode for band 4.1 (Epb4.1), glycophorin C (Gypc), and aminolevulinic acid synthase 2 (Alas2), which are three erythroid-specific genes.

Fig. 3.

PU.1 is an integral repressor of a core erythroid network, and conversely, GATA-1 represses numerous PU.1 myelo-lymphoid gene targets in erythroid progenitors. (A) PU.1 ChIP-Seq analysis in ES-EP (20) was used to determine the genes occupied by PU.1 in erythroid progenitor cells. Using the same criterion for associating bound regions with genes as in Fig. 1A, a four-way Venn diagram displays the overlap of genes occupied by PU.1, GATA-1 (in proliferating and/or differentiating ES-EP cells), SCL, and Klf1. (B) GATA-1– (13, 23), Klf1- (41), SCL- (14), and PU.1-dependent (20) gene expression datasets were used to determine how each factor regulates the expression of genes co-occupied by all four factors in erythroid progenitor cells. GATA-1–dependent gene expression was generated by performing expression array analysis at multiple time points after the introduction of GATA-1 into GATA-1 null erythroblasts (13, 23). The heatmap displayed for GATA-1 represents the final time point of this induction series represented as a Z-score relative to all time points. Heatmaps for Klf1, SCL, and PU.1 represent the absolute fold change in gene expression in fetal-liver–derived erythroid progenitors from wild-type animals relative to those from mutant animals. (C and D) Occupancy maps from ChIP-Seq data for GATA-1, SCL, Klf1, and PU.1 in the vicinity of the genes encoding (C) aminolevulinic acid synthase 2 (Alas2) and (D) band 4.1 (Epb4.1). (E) Heatmaps displayed show GATA-1– (13, 23) and PU.1-dependent (20) gene regulation of 151 myelo-lymphoid genes bound by both proteins in erythroid progenitors. Myelo-lymphoid genes were identified as genes that are highly expressed in granulocytic, monocytic, T-cell, or B-cell lineages compared with other hematopoietic cells (27). The heatmap displayed for GATA-1 represents the 21-h time point of this induction series represented as a Z-score relative to all time points, whereas the PU.1 heatmap represents the absolute fold change in gene expression in fetal-liver–derived early erythroid progenitor cells from wild-type animals compared with that in mice that have ∼70% reduction in PU.1 levels. (F and G) Occupancy maps of GATA-1 and PU.1 in ES-EP cells are displayed in the vicinity of the myelo-lymphoid genes that encode for (F) Ifngr2 and (G) NfκB1.

Fig. 4.

Mathematical model demonstrating the synergistic effect of repressing both the upstream activator and its downstream targets during lineage specification. (A) We determined the equilibrium expression-level ratio of GATA-1 targets/PU.1 targets (G_T/P_T, on the z axis using logarithmic scale) following a transient stimulation of GATA-1 for different combinations of the parameter values that independently modulate the mutual inhibition between GATA-1 and PU.1 (right corner, x axis) and inhibition of the other's downstream targets (left corner, y axis) from the base network topology represented in the bottom center corner (all other parameter values are constant and tabulated in SI Materials and Methods). The top center corner represents simultaneous high-level mutual inhibition and repression of the downstream targets. (B and C) GATA-1 target (G_T) and PU.1 target (P_T) gene expression levels, respectively, used to compute the G_T/P_T ratio. The highest G_T/P_T ratio observed in the top center corner of A is due to sustained elevated G_T concentration with decreased P_T concentration relative to all other corners.