SLAM-seq defines direct gene-regulatory functions of the BRD4-MYC axis

Abstract

Defining direct targets of transcription factors and regulatory pathways is key to understanding their roles in physiology and disease. We combined SLAM-seq [thiol(SH)-linked alkylation for the metabolic sequencing of RNA], a method for direct quantification of newly synthesized messenger RNAs (mRNAs), with pharmacological and chemical-genetic perturbation in order to define regulatory functions of two transcriptional hubs in cancer, BRD4 and MYC, and to interrogate direct responses to BET bromodomain inhibitors (BETis). We found that BRD4 acts as general coactivator of RNA polymerase II-dependent transcription, which is broadly repressed upon high-dose BETi treatment. At doses triggering selective effects in leukemia, BETis deregulate a small set of hypersensitive targets including MYC. In contrast to BRD4, MYC primarily acts as a selective transcriptional activator controlling metabolic processes such as ribosome biogenesis and de novo purine synthesis. Our study establishes a simple and scalable strategy to identify direct transcriptional targets of any gene or pathway.

Fig. 1. Global transcriptional control by BRD4.

(A) Sample workflow of a SLAM-seq experiment mapping direct transcriptional responses to degradation of auxin-inducible degron (AID)-tagged proteins. (B) Schematic of the AID-BRD4 knock-in allele and Tir1 delivery vector SOP. Immunoblotting of BRD4 in K562^AID-BRD4 + Tir1 cells treated with 100μM IAA for the indicated time points. (C) Changes in the abundance of total and newly synthesized mRNAs (detected in SLAM-seq based on T>C conversions) in K562^AID-BRD4+Tir1 cells treated with IAA for 30 min followed by 4sU labeling over 60 min. FC, fold-change. (D) Immunoblotting of indicated transcriptional core regulators and controls in total cell lysate, chromatin fraction and supernatant of K562^AID-BRD4+Tir1 cells treated with IAA for 60 min. (E) Spike-in controlled ChIP-seq of hypo-phosphorylated, S2-phosphorylated and S5-phosphorylated Pol2 in K562^AID-BRD4+Tir1 cells treated with IAA for 60 min. Heatmaps and density diagrams show change of signals across genes at transcription start sites (TSS, +/- 1kb), gene-bodies (scaled) and transcription end sites (TES, +/- 1kb). A density scale from low (blue) to high (red) is shown. (F) Changes of Pol2 occupancy upon BRD4 degradation shown in (E) for indicated genes.

Fig. 2. Dose dependency and determinants of responses to BETi.

(A) SLAM-seq responses of K562 cells treated with indicated doses of JQ1 for 30 min before 4sU labeling for 60 min. (B) SLAM-seq responses of K562 and MV4-11 cells treated with 200nM JQ1 as in (A). (C) Pairwise comparison of SLAM-seq responses to JQ1 shown in (B). R, Pearson correlation coefficient. (D) Principal component analysis of SLAM-seq profiles from MOLM-13 cells treated with JQ1 or NVP-2 as in (A). (E) Heatmap and hierarchical clustering of Spearman’s rank correlations between SLAM-seq responses to JQ1 and NVP-2 in indicated cell lines. (F) Venn diagram showing overlap between BETi-hypersensitive genes and published super-enhancer targets in K562 cells. (G) Sample tracks of H3K27ac ChIP-seq with super-enhancer (SE) annotation exemplifying categories in (F). (H) Simplified model generation workflow for classifying BETi-hypersensitive genes based on 214 chromatin signatures. (I) ROC curve for classification of BETi-hypersensitive genes by super-enhancer assignment or two independent chromatin signature-based models assessed on a held-out test set. (J) Relative contribution of the strongest positive and negative predictors to the GLM shown in (I) based on normalized model coefficients. Heatmap shows relative ChIP-seq densities of these factors at TSS of 125 BETi-hypersensitive genes.

Fig. 3. MYC is a selective transcriptional activator of genes involved in biosynthesis processes.

(A) Schematic of the MYC-AID knock-in allele and Tir1 delivery-vector. (B) Immunoblotting of MYC in K562^MYC-AID+Tir1 cells treated with IAA. (C) SLAM-seq profile following MYC-degradation in K562^MYC-AID+Tir1 cells (30 min IAA treatment, 60 min 4sU-labeling). Highlighted are ribosome biogenesis factors (light blue) and de-novo purine synthesis enzymes (dark blue). (D) Violin plots depicting SLAM-seq responses of significantly enriched gene ontology classes. (E) Measurement of global protein synthesis by L-homopropargylglycine (HPG)-incorporation and flow cytometry in K562^MYC-AID cells treated with IAA. (F) Targeted mass spectrometry quantification of indicated metabolites in K562^MYC-AID+Tir1 cells after 48h of IAA treatment. Bars show means of 3 independent experiments. Error bars indicate one standard deviation. (G) MYC-immunoblotting in HCT116^MYC-AID+Tir1 cells as in (B). (H) Comparison of SLAM-seq responses in K562^MYC-AID+Tir1 and HCT116^MYC-AID+Tir1 cells. (I) Expression of MYC compared with a signature of the top 100 common MYC-dependent transcripts in (H) across 672 cancer cell lines. (J) MYC-target signature expression across 5583 patient samples separated based on high (top 20%) or low (bottom 20%) MYC-expression and cancer type. ****, p<0.0001 (Wilcoxon’s rank-sum test).