Functions of BET proteins in erythroid gene expression

Abstract

Inhibitors of bromodomain and extraterminal motif proteins (BETs) are being evaluated for the treatment of cancer and other diseases, yet much remains to be learned about how BET proteins function during normal physiology. We used genomic and genetic approaches to examine BET function in a hematopoietic maturation system driven by GATA1, an acetylated transcription factor previously shown to interact with BETs. We found that BRD2, BRD3, and BRD4 were variably recruited to GATA1-regulated genes, with BRD3 binding the greatest number of GATA1-occupied sites. Pharmacologic BET inhibition impaired GATA1-mediated transcriptional activation, but not repression, genome-wide. Mechanistically, BETs promoted chromatin occupancy of GATA1 and subsequently supported transcriptional activation. Using a combination of CRISPR-Cas9-mediated genomic engineering and shRNA approaches, we observed that depletion of either BRD2 or BRD4 alone blunted erythroid gene activation. Surprisingly, depletion of BRD3 only affected erythroid transcription in the context of BRD2 deficiency. Consistent with functional overlap among BET proteins, forced BRD3 expression substantially rescued defects caused by BRD2 deficiency. These results suggest that pharmacologic BET inhibition should be interpreted in the context of distinct steps in transcriptional activation and overlapping functions among BET family members.

Figure 1

Reorganization of BET binding following GATA1 complementation. (A) Genome browser tracks showing ChIP-seq signals for the indicated proteins at the mouse β-globin (Hbb) locus. (B) ChIP-seq signal across 4-kb regions centered on GATA1-binding sites ranked from strongest GATA1-binding signal (highest MACS score) to lowest GATA1 signal. (C) Boxplots showing BET reads per kilobase per million (RPKM) at random genomic regions (rand) or GATA1 sites (all, only those at promoters [pro], or only those at candidate enhancers [enh]). Here, we use DNaseI-hypersensitive, H3K4me1-enriched, promoter-excluded sites as enhancers as in Hsiung et al.

Figure 2

Transcriptome changes driven by GATA1 activation and BET inhibition. (A-C) Microarray expression profiles of G1E cells ± GATA1 induction in the presence or absence of JQ1. Transcript levels were normalized to cell numbers using external RNA spike-in controls. Data represent the mean of 3 biological experiments. (A) Distribution of mRNA changes upon GATA1 activation. (B) Heatmap showing relative expression of each transcript in each condition. (C) Boxplot showing relationship of activation by GATA1 with JQ1 sensitivity. Red dotted line shows no change in mRNA levels with JQ1 treatment. (D) GATA1-activated and -repressed transcript levels as determined by RT-qPCR. Data were plotted relative to untreated G1E cells normalized to cell number by RNA spike-in controls. *P < .01 (2-sample t test). Error bars represent SEM; n = 3. (E) RT-qPCR for erythroid transcripts in primary fetal liver erythroid progenitors induced to differentiate along the erythroid lineage for 24 hours in the presence or absence of 250 nM JQ1. *P < .01 (2-sample t test). Error bars represent SEM; n = 3. GAPDH, glyceraldehyde-3-phosphate dehydrogenase.

Figure 3

Effects of BET inhibition on GATA1 occupancy genome-wide. (A) Genome browser tracks showing GATA1 binding at the Hbb and Zfpm1 loci in the absence and presence of 250 nM JQ1. Tracks are from 1 biological experiment and representative of 2 with similar results. (B) GATA1 ChIP-seq read density following GATA1 induction for 24 hours in the absence or presence of JQ1. The red line shows a Loess regression; the blue diagonal demarcates no change between control and JQ1 treatment. (C) Boxplot showing relationship between BET dependence of GATA1 occupancy and transcriptional activation. GATA1 peaks are linked to nearest gene within 5 kb. P values reflect results of 2-sample t tests from indicated comparisons.

Figure 4

Transcriptional requirement of BET proteins after establishment of GATA1 occupancy. (A) ChIP for BRD4 and GATA1 in G1E GATA1-ER cells treated with 250 nM JQ1 for up to 60 minutes following GATA1 induction. Cd4 served as negative control. Error bars represent SEM; n = 3. *P < .05 that indicated JQ1-treated sample mRNA is lower than untreated (2-sample t test). (B) Primary transcript RT-qPCR of indicated transcripts following JQ1 treatment in GATA1-induced cells. Error bars represent SEM; n = 4. *P < .05 comparing JQ1 treated and control samples (2-sample t test).

Figure 5

Functions of individual BETs in GATA1-activated transcription. (A-C) Left, Western blots with antibodies against indicated BET proteins. Right, Relative transcript levels following GATA1 activation in cells depleted of (A) BRD3, (B) BRD2, or (C) BRD4. BRD4 reduction was achieved by shRNA-mediated Brd4 knockdown. P-value comparisons are the results of 2-sample t tests.

Figure 6

BRD3 function revealed in BRD2-deficient cells. (A) shRNA-mediated Brd3 knockdown in BRD2 replete vs deficient cells. Error bars represent SEM; n = 3. P-value comparisons are the results of 2-sample t tests. (B-C) BRD2 replete and deficient G1E cells in the presence and absence of GATA1 with or without retroviral BRD2 or BRD3 expression. (B) Photograph of cell pellets in wells of a 96-well plate. One representative experiment is shown of 3 with similar results. (C) mRNA levels. Error bars represent SEM; n = 3. *P < .05 that sample expressing exogenous Brd2 or Brd3 has higher mRNA levels than control Brd2-deficient cells.