Mutations that attenuate homologous recombination (HR)-mediated repair promote tumorigenesis and sensitize cells to chemotherapeutics that cause replication fork collapse, a phenotype known as ‘BRCAness’1. BRCAness tumours arise from loss-of-function mutations in 22 genes1. Of these genes, all but one (CDK12) function directly in the HR repair pathway1. CDK12 phosphorylates serine 2 of the RNA polymerase II C-terminal domain heptapeptide repeat2,3,4,5,6,7, a modification that regulates transcription elongation, splicing, and cleavage and polyadenylation8,9. Genome-wide expression studies suggest that depletion of CDK12 abrogates the expression of several HR genes relatively specifically, thereby blunting HR repair3,4,5,6,7,10,11. This observation suggests that the mutational status of CDK12 may predict sensitivity to targeted treatments against BRCAness, such as PARP1 inhibitors, and that CDK12 inhibitors may induce sensitization of HR-competent tumours to these treatments6,7,10,11. Despite growing clinical interest, the mechanism by which CDK12 regulates HR genes remains unknown. Here we show that CDK12 globally suppresses intronic polyadenylation events in mouse embryonic stem cells, enabling the production of full-length gene products. Many HR genes harbour more intronic polyadenylation sites than other expressed genes, and these sites are particularly sensitive to loss of CDK12. The cumulative effect of these sites accounts for the enhanced sensitivity of HR gene expression to CDK12 loss, and we find that this mechanism is conserved in human tumours that contain loss-of-function CDK12 mutations. This work clarifies the function of CDK12 and underscores its potential both as a chemotherapeutic target and as a tumour biomarker.
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Sequencing data have been deposited in the Gene Expression Omnibus under accession number GSE116017.
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We thank the Sharp laboratory, J. Arribere, F. Solomon, and L. Cote for discussions and reading the manuscript. pAC4 and PBNeoTetO-Dest, the OVCAR4 cells, and THZ531 were gifts from A. Cheng, S. Correa Echavarria, and N. Gray respectively. We thank H. Suzuki for the first stable nucleosome coordinates and F. Lam for assistance with Comet assays. The results shown here are in part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/. We thank the Koch Institute’s Robert A. Swanson (1969) Biotechnology Center at MIT for technical support, specifically G. Paradis of the Flow Cytometry Core and S. Levine of the MIT BioMicro Center. The research described here was supported by Program Project Grant P01-CA042063 from the NCI (P.A.S.), by United States Public Health Service grants R01-GM034277 and R01-CA133404 from the NIH (P.A.S.), and by the Koch Institute Support (core) grant P30-CA14051 from the NCI. S.J.D. was also supported by a David H. Koch Fellowship and NIH Pre-Doctoral Training Grant T32-GM007287 (MIT Biology Department).
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Extended data figures and tables
Extended Data Fig. 1 Generation of Cdk12 genetic knockouts in mES cells and phenotypic data from a second, independently derived Cdk12Δ clone.
a, Schematic of Cdk12Δ cell line generation, LoxP sites (red triangles), sgRNA cut sites (*), endogenous promoter (black arrows) and doxycycline-inducible promoter (orange arrow). b, PCR products across the Cdk12 locus flanking exon 4 (primers shown as orange arrows) for wild type mES cells and Cdk12∆ clones. Clones 28 and 36 used throughout this study are indicated in red. c–h, Phenotypic data from the second of two independently derived Cdk12Δ clones shown corresponding to results shown in Fig. 1a–f for the other clone. c, Representative immunoblot for CDK12 transgene (HA epitope) expression after doxycycline (Dox) withdrawal. d, Fold-change in live cells over previous 24 h quantified by FACS; bars represent mean fold change (± s.e.m.) for n = 3 biological replicates. Cells were grown continuously in Dox (blue bars), withdrawn from Dox at time 0 and maintained off Dox (red bars), or withdrawn from Dox at time 0 and reintroduced to Dox after 48 h (orange bars) or 72 h (yellow bars) for remainder of the time course. e, FACS-based cell cycle profiling of one representative replicate for the same conditions as in d (top) and quantification (bottom). f, FACS-based quantification of cleaved caspase 3-positive (apoptotic) cells. One representative biological replicate shown. g, Neutral comet assay to quantify degree of unrepaired DNA double-stranded breaks in Cdk12Δ cells after 48 h of doxycycline withdrawal. Boxplots: median value with 25th and 75th quartiles; whiskers show minimum to maximum. P value based on one-sided Mann–Whitney U test. h, Immunoblot for total and phosphorylated Ser15 (P-Ser15) p53 upon CDK12 loss for the indicated times. HSP90 serves as a loading control.
Extended Data Fig. 2 Gene expression changes in CDK12-depleted mES cells are dominated by increased IPA usage.
a, Volcano plots of significant gene expression events at the total gene level after 24 h (left) or 48 h (right) of Dox withdrawal. y-axis: FDR-adjusted P value determined by the DESeq package in R; coloured dots: PPDE > 0.95 (determined by the EBSeq package in R). b, Pie chart indicating genes that decreased (left) or increased (right) in total gene expression at a statistically significant level after 24 or 48 h of Dox withdrawal (combined). Likely secondary effects are indicated: p53 repressed genes (red), p53 enhanced genes (blue), bivalent promoter genes (yellow), p53 repressed and bivalent promoter genes (orange), and p53 enhanced and bivalent promoter genes (green). Genes belonging to none of the above groups are indicated in grey. c, Table summarizing significant alternative splicing events observed after 24 and 48 h of Dox depletion in Cdk12Δ cells. d–g, Isoform-specific RT–qPCR corroborating differential isoform usage observed in the RNA sequencing data. Blue bars (+Dox) and red bars (–Dox 48 h) represent mean ( ± s.e.m.), n = 4 biological replicates. Seven IPA isoforms from five genes were validated in two independent Cdk12Δ clones in d, e and the corresponding distal polyadenylation isoforms in those five genes were validated in f, g. d, f and e, g represent corresponding data from the two independently derived Cdk12Δ clones used throughout this study. h, Left, IPA sites exhibiting a statistically significant (Padj < 0.05, FDR adjusted P value determined by the DEXSeq package in R) change (orange) or not (blue) in expressed genes after 24 or 48 h of Dox depletion. Right, expressed genes with terminal polyadenylation sites that are significantly changed (orange) or not statistically significant (blue) as normalized to the rest of the transcript. i, Scatterplot showing log2 fold-change upon CDK12 loss in distal exons (y-axis) versus IPA sites (x-axis) in genes that have both a statistically significant (Padj < 0.05) IPA site and a statistically significant distal polyadenylation change; n = 4 biological replicates per condition.
Extended Data Fig. 3 ChIP antibodies recognizing the same target protein exhibit strongly overlapping metagene patterns.
Metagene profiles broken down by individual antibodies used. Blue lines: normalized read density for the specific ChIP antibody in n = 2 biological replicates. Orange lines: negative control (combined whole-cell extract and all antibody negative controls, n = 4 biological replicates). Black dashed lines: fold-enrichment (specific ChIP/negative control). Shaded areas: −log10 (bin-wise P values, Kolmogorov–Smirnov one-sided test) of the difference in read depth, with blue shading indicating that the plus CDK12 signal is significantly greater. The −log10 of the P value is shown in the axis on the right, and the horizontal dashed line is P = 0.05. TSS, transcription start site. Distal polyA, distal polyadenylation site.
a, Schematic of biological replicate and antibody replicate experimental design. Each ChIP set (RNAPII and Ser2p, in CDK12+ or CDK12− cells) consisted of two biological replicates, each ChIP’ed with two different antibodies recognizing the same protein. These four replicates were then combined for the ChIP metagene analyses. b–d, Schematic of the steps used to determine average read densities for the ChIP assays, and the statistical test used to determine significant differences in read density that depend on CDK12 expression.
a, Length and expression quartiles of genes that showed significant changes (Padj < 0.05, FDR adjusted P value determined by the DEXSeq package in R) in IPA or distal isoforms. Boxplots: median value, 25th and 75th quartiles; whiskers show 1.5 × interquartile range. n = 4 biological replicates per condition. Top panels: size distributions (log10 of length in nucleotides) of each length quartile (left) and gene expression distributions (log10 of transcripts per million) of each expression quartile (right) compared to the respective distributions of all expressed genes. Bottom panels: expression distributions for each length quartile (left) and length distributions for each expression quartile (right). Note that gene length is generally inversely correlated with expression level, but the median expression of all quartiles of the significantly changing IPA/distal isoforms is higher than the median for all expressed genes. In addition, the median length of all expression quartiles of the significantly changing IPA/distal isoforms is longer than the median for all expressed genes. Thus, the genes that comprise the significantly changing IPA/distal isoform set are longer and more highly expressed for their length than the broader gene population. b, Metagene profiles of RNAPII density in genes with a statistically significant CDK12-sensitive IPA or terminal site divided into length-based quartiles. In the shortest quartile, the CDK12-depleted cells show a trend towards increased density at the 3′ end, but the shortest genes terminate before the polymerase can reach a higher density than the CDK12 competent cells. Conversely, the longest genes are expressed at a lower level (see a), resulting in a lower RNAPII ChIP signal. For these reasons, the shortest and longest length quartiles were excluded in Fig. 3b, d. c, Metagene profiles of RNAPII density in genes with a statistically significant CDK12-sensitive IPA or terminal site divided into expression-based quartiles. b, c, Solid lines indicate normalized read density with (blue, n = 4 independent ChIPs) or without (red, n = 4 independent ChIPs) CDK12; shaded areas indicate −log10 (bin-wise P value, Kolmogorov–Smirnov one-sided test) of the difference in read density (blue indicates that CDK12+ signal is greater, pink indicates that CDK12− signal is greater). Horizontal dashed line: P = 0.05. DPA, distal polyadenylation site.
a, Metagene profile of RNAPII density in a set of control genes length-matched to the set of genes with significantly changing IPA or distal isoforms. Top, all control genes. Bottom, shortest and longest quartiles removed (as in Fig. 3b). b, Metagene profile of RNAPII density in a set of control genes length-matched to the set of genes with significantly changing IPA or distal isoforms, divided into length quartiles. c, Metagene profile of RNAPII density in a set of control genes expression-matched to the set of genes with significantly changing IPA or distal isoforms. d, Metagene profile of RNAPII density in a set of control genes expression-matched to the set of genes with significantly changing IPA or distal isoforms, divided into expression quartiles. a–d, Solid lines indicate normalized read density with (blue, n = 4 independent ChIPs) or without (red, n = 4 independent ChIPs) CDK12; shaded areas indicate −log10 (bin-wise P value, Kolmogorov–Smirnov one-sided test) of the difference in read density (blue indicates that CDK12+ signal is greater, pink indicates that CDK12− signal is greater). Horizontal dashed line: P = 0.05.
Extended Data Fig. 7 Increased RNAPII upstream and decreased RNAPII downstream of first stable nucleosome occurs in all gene expression quartiles.
Total RNAPII metagene density 1 kb upstream and 1 kb downstream of the first stable nucleosome for genes with significantly changing IPA or distal isoforms, divided into gene expression quartiles. As in Fig. 3c, solid lines indicate normalized read depth with (blue) or without (red) CDK12, and shaded areas indicate −log10 (bin-wise P values, Kolmogorov–Smirnov one-sided test) of the difference in read depth, with blue shading indicating that the plus CDK12 signal is significantly greater, and pink shading indicating that the minus CDK12 signal is significantly greater. Horizontal dashed line is P = 0.05. Vertical dashed line indicates the position of the first stable nucleosome dyad. n = 4 biological replicates per condition.
Extended Data Fig. 8 Ser2p is depleted by CDK12 loss and metagene patterns are influenced by gene expression and length.
Left, metagene profiles of Ser2p RNAPII density in genes with a statistically significant (Padj < 0.05, FDR adjusted P value determined by the DEXSeq package in R) CDK12-sensitive IPA or terminal site divided into length-based quartiles. As in Fig. 3d, solid blue lines indicate average normalized read density in CDK12+ cells, red solid lines are the average normalized read density in CDK12-depleted samples. Light blue shading indicates that the plus CDK12 signal is significantly greater. n = 4 biological replicates per condition. Right, metagene profiles of Ser2p RNAPII density in genes with a statistically significant CDK12-sensitive IPA or terminal site divided into expression-based quartiles. n = 4 biological replicates per condition.
Top, as RNAPII transcribes through a region of a gene (exonic regions shown in blue with 5′ and 3′ splice sites (SS) indicated, introns in grey) containing an IPA site (red octagon), CDK12-dependent RNAPII-CTD Ser2 phosphorylation suppresses IPA site usage. Bottom, in the absence of CDK12, RNAPII-CTD Ser2 phosphorylation is decreased. IPA site usage increases, resulting in increased truncated isoforms and decreased distal-most isoforms. RNAPII that transcribes through the downstream exon accumulates with increasing density towards the 3′ end of the gene. IPA usage is in competition with the splicing of its encompassing intron. Decreasing the efficiency of splicing or increasing the activity of cleavage and polyadenylation could both increase IPA usage. Alternatively, a decrease in the efficiency of transcription elongation could alter the kinetic balance to favour IPA usage. Indeed, previous studies have suggested that slower RNAPII elongation rates, due to mutant polymerases or alterations in transcription elongation factors, increase IPA usage over that of distal sites48,49,50,51. All three of these possibilities have been related to RNAPII Ser2p, but it is unclear how CDK12-dependent phosphorylation of Ser2p is related to these non-mutually-exclusive possibilities.
Extended Data Fig. 10 Upregulated IPA usage in human tumours is specific to CDK12 LOF mutations and not mutations in other BRCAness genes; treatment of human ovarian and prostate cancer cell lines with THZ531 phenocopies the increased IPA site usage observed upon CDK12 genetic loss.
a, RNA-seq read density from TCGA tumours from patients with prostate adenocarcinoma or ovarian cystadenocarcinoma with the indicated mutational status at a CDK12-sensitive IPA site in the human ATM locus (ATM IPA #2). Tumours shown in blue are wild-type for CDK12 and diploid unless marked as amplified (A). Tumours shown in red carry missense putative driver mutations, truncating mutations, or shallow (SD) or deep (DD) gene deletions at the CDK12 locus. Of note, all of the ovarian cystadenocarcinoma tumours that carry CDK12 point mutations also have a shallow deletion at the CDK12 locus except for the tumour with the CDK12(R882L) missense mutation, which is diploid across the locus. The 23 tumours in orange harbour putative driver mutations in the other BRCAness genes (ATM, BRCA1, BRCA2, FANCA, or CHEK2) as noted. b, Quantification of usage of two different IPA sites in human ATM and at IPA sites in FANCD2 and WRN in human prostate and ovarian tumours from TCGA data (combined in this analysis). Tumours with wild-type or amplified CDK12 are shown in blue (WT), those with CDK12 deletions, missense mutations, or truncating mutations in red (Mut), and those with putative driver mutations in the five BRCAness genes (ATM, BRCA1, BRCA2, FANCA, and CHEK2) in orange. Medians are indicated by horizontal black bars and sample sizes are indicated below. P values were determined by one-sided Mann–Whitney U test. c, Immunoblots showing the effect of 4 h of THZ531 treatment versus DMSO on RNAPII pSer2 (3E10 antibody) in two prostate carcinoma cell lines (22RV1 and PC-3) and one high-grade serous ovarian carcinoma cell line (OVCAR4). Total RNAPII (8WG16 antibody), HSP90, and Vinculin are shown as loading controls. d, e, Isoform-specific RT–qPCR used to assay for the expression of IPA and distal polyadenylation isoforms in two prostate carcinoma cell lines (22RV1 and PC-3) and one high-grade serous ovarian carcinoma cell line (OVCAR4) after 4 h of 400 nM THZ531 treatment compared to vehicle (DMSO). Blue bars (DMSO) and red bars (THZ531) represent mean (± s.e.m.) for n = 3 biological replicates. d, Four IPA sites were assayed. Three IPA sites were identified in the TCGA data from human ovarian and prostate tumours (ATM IPA #1, FANCD2 IPA, and WRN IPA; Fig. 4f, g and Extended Data Fig. 10a, b). One IPA site corresponded to a significantly changing IPA site in our mES cell Cdk12Δ clones (APAF1). e, Distal polyadenylation isoforms for the genes in d.
This file contains Supplementary Figures 1-2. Supplementary Figure 1 includes example FACS gating strategies used in Fig. 1b, 1c, 1d and Extended Data Fig. 1d, 1e, 1f. Supplementary Figure 2 contains the uncropped Western blots for Fig. 1a, 1f, 4d, 4e and Extended Data Fig. 1c, 1h, 10c.
Total gene expression changes after 24 hours of Cdk12 depletion; Total gene expression changes after 48 hours of Cdk12 depletion; Classification of genes as p53 transcriptional targets or bivalent promoter genes.
Genome-wide intronic polyadenylation (IPA) cleavage sites.
Intronic polyadenylation site (IPA) isoforms with significant changes after 24 or 48 hours Cdk12 depletion.
Distal polyadenylation site isoforms with significant changes after 24 or 48 hours Cdk12 depletion.
sgRNA and repair constructs used to make Cdk12-Flox and Cdk12Δ V5-tagged Atm, Brca2, and Fancd2 cell lines.
A list of qPCR primer sequences.
About this article
CDK12 loss in cancer cells affects DNA damage response genes through premature cleavage and polyadenylation
Nature Communications (2019)
Cellular and Molecular Life Sciences (2019)