Promiscuous RNA binding by Polycomb repressive complex 2

Abstract

Polycomb repressive complex 2 (PRC2) is a histone methyltransferase required for epigenetic silencing during development and cancer. Long noncoding RNAs (lncRNAs) recruit PRC2 to chromatin, but the general role of RNA in maintaining repressed chromatin is unknown. Here we measure the binding constants of human PRC2 to various RNAs and find comparable affinity for human lncRNAs targeted by PRC2 as for irrelevant transcripts from ciliates and bacteria. PRC2 binding is size dependent, with lower affinity for shorter RNAs. In vivo, PRC2 predominantly occupies repressed genes; PRC2 is also associated with active genes, but most of those are not regulated by PRC2. These findings support a model in which PRC2's promiscuous binding to RNA transcripts allows it to scan for target genes that have escaped repression, thus leading to maintenance of the repressed state. Such RNAs may also provide a decoy for PRC2.

Figure 1

PRC2 binds the 5’ domain of HOTAIR RNA with sub-micromolar affinity, in the presence or absence of AEBP2. (a) Recombinant human PRC2 complexes reconstituted using the baculovirus system to include SUZ12, EZH2, EED and RBBP4 in the presence or absence of the zinc-finger subunit AEBP2 (PRC2 5m and 4m, respectively), analyzed by SDS-PAGE and stained with Coomassie blue. (b) Electrophoretic Mobility Shift Assays (EMSAs) performed using in vitro transcribed RNA including 400 nucleotides from the 5’ of HOTAIR RNA (HOTAIR 400) in the presence of various concentrations of PRC2 4m and 5m. The two gels were run for different times, so the extent of the mobility shift upon protein binding is not meaningful. (c) Complete binding curves for HOTAIR 400 with PRC2 4m and PRC2 5m. Error bars for K_d, Hill and each data point represent range of two independent experiments performed on different days.

Figure 2

Promiscuous binding of RNA by PRC2 in vitro. (a) Representative EMSAs and the corresponding binding curves show binding of PRC2 to HOTAIR 1–300, HOTAIR 400, antisense (as) HOTAIR 1–300 and E. coli MBP 1–300. K_d and Hill coefficients represented with data-range from two independent experiments performed on different days. (b) Binding competition experiment with unlabeled competitors MBP 1–300 and HOTAIR 400, radiolabeled HOTAIR 400 and PRC2 4m.

Figure 3

Binding of PRC2 to RNA is size dependent. (a) Representative EMSAs of different in vitro transcribed RNAs that comprise 10, 20, 50, 100, 300 and 800 bases from the 5’ end of E. coli MBP mRNA. The total size of each RNA includes additional five bases that were added through in vitro transcription. (b) Corresponding binding curves. (c) Linear correlation between log₁₀(K_d) and log₁₀(RNA length (bases)). (d) Dependency between RNA length and binding cooperativity (Hill coefficient). Error bars in panels b, c and d represent range of data from two independent experiments performed on different days.

Figure 4

Interaction between PRC2 and RNA shows little salt dependence. (a) Representative EMSAs of HOTAIR 400 in the presence PRC2 5m performed under different KCl concentrations. (b) Corresponding binding curves. (c) Linear correlation between log₁₀(K_d) and log₁₀(KCl concentration). The apparent number of salt bridges between the RNA and the protein is calculated from the slope of the fitted line and is less than one. Error bars, same as Fig. 3.

Figure 5

Widespread binding of RNA by PRC2 in vivo. (a) Analysis of Ezh2 RIP-seq results from mouse ESC determines the PRC2 transcriptome, using the previous criteria. Diagonal line represents Ezh2 RIP-seq Fold Enrichment (Ezh2-FE) of 3-fold for transcripts associated with Ezh2 in wt cells over Ezh2 knockout cells (Ezh2^(−/−)). Vertical line represents a cutoff of 0.4 RPKM_e. Transcripts belonging to the PRC2 transcriptome lie under the diagonal line and to the right of the vertical line. Green, selected transcripts previously suggested as associated with PRC2. Orange, negative and positive internal controls, Hotair RNA and Ezh2 mRNA, respectively. Red, selected transcripts present in the PRC2 transcriptome that belong to either highly expressed genes or PRC2 subunit mRNAs. Parentheses, Ezh2-FE values. (b) High throughput sequencing data from 35 published ChIP-seq, RNA-seq and GRO-seq experiments were subjected to different types of data acquisition and analysis using identical pipelines. Analysis resulted in 180 data vectors, each describing any of 27,874 autosomal non-redundant mouse Refseq genes. Next, data in each of these 180 data vectors were correlated against Ezh2-FE values of the corresponding genes. Finally, all 180 data vectors were ranked based on the degree of correlation and plotted as bar graph. Red dots, correlation significance as -log₁₀(p-value). Bar size, Spearman’s rho correlation coefficient. Bar color, data classification. Top: bars were color-coded based on chromatin state recorded by the data. Bottom: the same bar graph as described above was color-coded based on different cell types. See Supplementary Table 6 for full description of each dataset.

Figure 6

PRC2 associates with active genes, in addition to its predominant association with repressed chromatin. (a) EZH2-associated genes were classified based on their association with other chromatin marks. Numbers in parentheses represent the number of EZH2-associated genes identified in each cell line. (b) H3K27me3-associated genes were classified based on their association with other chromatin marks. Numbers in parentheses represent the number of H3K27me3-associated genes identified in each cell line. (c) Heatmaps for chromatin marks H3K4me3 and H3K36me3 (ChIP-seq data) and for RNA-seq in mouse E14 cell line were generated using the same datasets, but presented using different types of sorting. Refseq mouse genes were sorted by three different criteria: reads (from 0.5 kb upstream of TSSs to 0.5 kb downstream) of either H3K27me3 (blue), EZH2 (red) or differential coverage obtained by subtracting the number of normalized H3K27me3 reads from the number of normalized EZH2 reads at the same position (EZH2 - H3K27me3, red). Below, top-ranked 20% of genes, resulting from these three different types of sorting, were used to generate enrichment profiles (same color key used). Titles of enrichment profiles represent the corresponding epigenetic mark. ‘Sorting dataset’ indicates the datasets that determined the three types of sorting, namely top 20% of genes ranked according to read occupancy around TSS of either H3K27me3 (blue), EZH2 (red) or EZH2 – H3K27me3 (red).

Figure 7

Knockdown of SUZ12 in HEK293T/17 cells, combined with ChIP-seq and RNA-seq, confirms widespread association of EZH2 with H3K4me2/3 and Pol II Ser5, but expression of the vast majority of these genes does not respond to SUZ12 knockdown. (a) Knockdown of SUZ12 achieved after 48 hours, confirmed by qPCR and RNA-seq (right) and immunoblotting (left) and accompanied by global depletion of the H3K27me3 mark (left). (b) Top Euler diagram demonstrates large overlap between genes associated with EZH2, H3K4me2/3 and Pol II Ser5 in HEK293T/17 cells. Bottom Euler diagram demonstrates the small intersect between genes that responded to SUZ12 knockdown, identified based on two biological replicates, and genes associated with EZH2. (c) Only a small fraction of EZH2-associated genes is transcriptionally regulated by PRC2.

Figure 8

The Junk Mail Model for repressed chromatin maintenance by PRC2 utilizing promiscuous RNA binding. Upon inappropriate transcription of a genuine polycomb target gene, recruitment of PRC2 through promiscuous RNA binding results in recognition of previously deposited H3K27me3 marks, stimulation of PRC2 histone methyltransferase activity and restoration of repression. Contrarily, if PRC2 binds to a nascent transcript of an active gene, in the absence of the H3K27me3 mark and in the presence of H3K36me3 and H3K4me3 marks, the histone methyltransferase activity of PRC2 is inhibited and its affinity to nucleosomes reduced, resulting in inefficient deposition to chromatin.