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BRCA1 and RNAi factors promote repair mediated by small RNAs and PALB2–RAD52

Nature volume 591, pages 665–670 (2021)Cite this article

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Abstract

Strong connections exist between R-loops (three-stranded structures harbouring an RNA:DNA hybrid and a displaced single-strand DNA), genome instability and human disease1,2,3,4,5. Indeed, R-loops are favoured in relevant genomic regions as regulators of certain physiological processes through which homeostasis is typically maintained. For example, transcription termination pause sites regulated by R-loops can induce the synthesis of antisense transcripts that enable the formation of local, RNA interference (RNAi)-driven heterochromation6. Pause sites are also protected against endogenous single-stranded DNA breaks by BRCA17. Hypotheses about how DNA repair is enacted at pause sites include a role for RNA, which is emerging as a normal, albeit unexplained, regulator of genome integrity8. Here we report that a species of single-stranded, DNA-damage-associated small RNA (sdRNA) is generated by a BRCA1–RNAi protein complex. sdRNAs promote DNA repair driven by the PALB2–RAD52 complex at transcriptional termination pause sites that form R-loops and are rich in single-stranded DNA breaks. sdRNA repair operates in both quiescent (G0) and proliferating cells. Thus, sdRNA repair can occur in intact tissue and/or stem cells, and may contribute to tumour suppression mediated by BRCA1.

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Fig. 1: BRCA1 interacts with Dicer, AGO1 and AGO2 to prevent R-loop damage.
Fig. 2: A new species of sRNA mediates locus-specific DNA damage repair.
Fig. 3: BRCA1–Dicer–AGO1–AGO2 promotes sdRNA production and PALB2–RAD52 promotes sdRNA-mediated repair.
Fig. 4: Biological outcome of the interplay between sdRNA, PALB2 and RAD52 in pause-site DNA damage repair.

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Data availability

All of the FASTQ sequence files from the sequencing of the sRNA and larger RNA RIP libraries are available from the SRA database under BioProject accession number PRJNA667516.

Code availibility

The code used for the identification of sdRNAs was developed in the Dana Farber Cancer Institutes Center for Computational Biology/Harvard School of Public Health’s Quantitative Biomedical Research Center, and the code is available at GitHub (https://github.com/dkdeconti/sdRNAPeaksIdentification).

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Acknowledgements

We thank all members of the Livingston laboratory for support, technical advice and discussions; members of the Center for Cancer Computational Biology (CCCB), and, in particular, F. O. Abderazzaq and R. Rubio for their expertise in small-RNA library preparation and sequencing; D. Pellman and M. Brown for their comments during manuscript preparation and W. Foulkes for discussions of PALB2 genetics. E.H. and other members of the D.M.L. laboratory were supported by grants from the National Cancer Institute (NCI), BRCA1 Function in Post Damage Foci (5R01CA136512-05) and Deciphering the Mechanism Underlying BRCA1 Breast Cancer Development (5R35CA242143-02)—as well as by grants from the Susan B. Komen Foundation for the Cure, The Breast Cancer Research Foundation, The Gray Foundation, The BRCA Foundation and the Murray Winsten Foundation. E.H. was also supported by grants from the Dana-Farber Cancer Institute (Barr Award project 9618425 and Friend’s of Dana-Farber). L.G. was also supported by a Research Supplement to Promote Diversity in Health-Related Research Programs (3R01CA136512-08S1). K.S.-S. was supported by a Sir Henry Wellcome Fellowship (grant 101489/Z/13/Z). D.K.D. and Y.E.W. were supported by grants from the National Cancer Institute (NCI) (5U24CA194354) and J.Q. by NCI grants 1R35CA220523, 5U24CA194354 and 5U01CA190234.

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Author notes

  1. These authors contributed equally: Liana Goehring, Serena Landini, Konstantina Skourti-Stathaki

Authors and Affiliations

  1. Department of Genetics, Harvard Medical School, Boston, MA, USA

    Elodie Hatchi, Liana Goehring, Serena Landini, Fieda O. Abderazzaq, Priyankana Banerjee, Timothy M. Demers & David M. Livingston

  2. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Elodie Hatchi, Liana Goehring, Serena Landini, Fieda O. Abderazzaq, Priyankana Banerjee, Timothy M. Demers & David M. Livingston

  3. Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA

    Elodie Hatchi, Liana Goehring, Serena Landini, Fieda O. Abderazzaq, Priyankana Banerjee, Timothy M. Demers & David M. Livingston

  4. Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK

    Konstantina Skourti-Stathaki

  5. Quantitative Biomedical Research Center, Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA

    Derrick K. DeConti, Yaoyu E. Wang & John Quackenbush

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Contributions

E.H. and D.M.L. originally conceived the rationale for this project and were responsible for planning its experimental direction. E.H. designed the overall project. E.H., L.G. and S.L. performed all of the experiments. E.H. analysed the experimental data unless otherwise stated. Cell samples needed for the various analyses were prepared and collected by S.L., L.G. and T.M.D. L.G. performed all ChIP–qPCR experiments and analyses. F.O.A. prepared all of the samples for NGS and helped with the rescue ChIP–qPCR experiments. Co-immunoprecipitation, immunoblots, RIP and RNA pull-down assays were performed by S.L. qPCR and TaqMan analyses were performed by L.G. and T.M.D. P.B. and S.L. performed all of the BELD experiments. K.S.-S. provided advice and performed RIP analyses and certain Dicer and AGO2 ChIP experiments. D.K.D., Y.E.W. and J.Q. designed the custom pipeline to analyse the small-RNA-sequencing data. D.K.D. created the figures related to bioinformatics analyses. E.H. and D.M.L. wrote the manuscript. All authors contributed to manuscript editing.

Corresponding authors

Correspondence to Elodie Hatchi or David M. Livingston.

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Competing interests

D.M.L. is a member of the external Advisory Boards of the Sidney Kimmel (Johns Hopkins) and the MIT Cancer Centers, is a member of the Oncode (the Netherlands) International Advisory Board and is a Science Partner of Nextech and is also a scientific advisor to Constellation Pharma and Cancer Research UK. The Sidney Kimmel (Johns Hopkins) and the MIT Cancer Center, Oncode, Nextech, Constellation Pharma and Cancer Research UK had no influence in the design and analysis of the experiments, preparation of the manuscript and decision to publish. The other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 BRCA1 interaction with RNAi factors.

a, The co-IP of endogenous SETX, BRCA1, Dicer or AGO1 using HeLa nuclear extracts shows that RAD51, an established BRCA1-binding partner involved in homologous recombination, did not co-immunoprecipitate with SETX and co-immunoprecipitated very weakly, if at all, with Dicer and AGO1. Representative blot from n = 3 experiments. b, Endogenous BRCA1 co-IP of HeLa nuclear extracts using two BRCA1 antibodies, each of which recognizes a different epitope (Ab#1, N terminus; Ab#2, C terminus). Representative blot from n = 3 experiments. c, BRCA1 co-IP performed using nuclear extracts from BRCA1 siRNA (siBRCA1)-transfected HeLa cells. Representative blot from n = 3 experiments. d, e, co-IP of endogenous BRCA1 and RNAi factors that are present in subcellular HeLa fractions (d) and confirmed in HMECs and human fibroblasts (BJ-hTert) (e). Representative blot from n = 4 experiments. Chrom, chromatin; Cyt, cytoplasm; NS, nuclear soluble. f, BRCA1 was co-immunoprecipitated, using three monospecific antibodies, in HeLa nuclear extracts from cells overexpressing (+) or not overexpressing (–) RNase H1. Immunoblots showed using antibody 2 (Ab#2) that a BRCA1–SETX–RNAi complex was R-loop sensitive. Representative blot from n = 2 experiments. g, Dicer, AGO1 and AGO2 ChIPs were performed in BRCA1-depleted (BRCA1-KD) HeLa cells. Recruitment of Dicer, AGO1 and AGO2 to ACTB pause sites was BRCA1-dependent (n = 2–5 biological replicates). h, Representative immunoblots demonstrating siRNA-mediated silencing efficiency in HeLa cells and HMECs. Representative blot from n = 10 experiments. i, Representative DNA damage analysis using separate siRNAs for each relevant target. j, DNA damage analyses at ENSA (R-loop-positive) and AKIRIN1 CoTC (cotranscriptional cleavage, R-loop-negative) transcription termination sites (n = 3–7 biological replicates). k, The BELD strategy used to identify DNA breaks at the ACTB pause site. l, m, BELD quantification of breaks at the ACTB pause site. l, BELD performed at the ACTB pause site in BRCA1-depleted cells with or without prior in vitro nick and gap repair (±NGR) of breaks performed before terminal deoxynucleotidyl transferase labelling. m, BELD performed on the reverse strand of the ACTB pause site. A representative example of each BELD analysis is shown, and the histograms depict the mean ± s.d. values of qPCR replicates. All ChIP data are represented as an mean ± s.e.m. fold change of the relevant knockdown condition compared to the mock condition. g, i, j, Data were analysed using multiple t-test (g), two-way ANOVA with post hoc Tukey HSD and unpaired t-test (i), and compared to results obtained with the undamaged locus or with relevant control cells (j).

Extended Data Fig. 2 BRCA1 interacts with Dicer, AGO1 and AGO2 to prevent damage at termination pause sites throughout the cell cycle.

a, b, Immunoblots of cyclin A and BRCA1 from whole-cell extracts of FUCCI HeLa cells sorted according to the expression of the G1 marker, mKO2-hCdt1 (a) or the S/G2 phase mAG-hGeminin marker (b). Representative blot from n = 4 experiments. c, Cell-cycle-dependent analysis of DNA damage using γ-H2AX ChIP signals in HeLa FUCCI cells sorted according to the S/G2 hGeminin marker. The results indicate that G1 cells develop as much damage as S/G2 cells. A representative experiment is shown, and the histograms depict the mean ± s.d. fold change of qPCR replicates. d, Immunoblots depicting the expression of BRCA1 during the various phases of the cell cycle after release of T98G cells from serum-starvation-induced G0 synchronization. Representative blot from n = 5 experiments. e, DNA damage analysis of synchronized T98G cells. f, Immunoblots validating the re-expression of BRCA1 (R) or Dicer (Flag-tagged wild-type (WT) and mutant Dicer, detected using a fluorescent quantitative method and showing their quantitative expression) after BRCA1 or DICER1 depletion, respectively, in HMECs and HeLa cells. Representative blot from n = 4 experiments. c, e, Data were analysed by one-way (c) or two-way (e) ANOVA with post hoc Tukey HSD test and compared to an undamaged locus.

Extended Data Fig. 3 Validation of the DNA damage-inducing effects of BRCA1 or Dicer loss and sdRNA destruction.

a, A Venn diagram showing a common set of deregulated sdRNAs after depletion with the indicated siRNAs in HeLa cells. b–d, Heat maps centred around the sdRNA peaks (±0.8 kb) showing the sdRNA changes in abundance after BRCA1 depletion in HMECs (b) and in HeLa cells before and after exposure to α-amanitin (c) and DRB (d).e, A correlation between the abundance of ACTB sdRNA and the nascent ACTB RNA (detected using intron 1) is shown. f, Top, schematic of the CASP16P genomic locus. Primers used for BELD on the forward (PE2-F) and reverse (PE2-R) strands and the qPCR amplicons. Bottom, BELD quantification in T98G cells of the CASP16P Pause2 site reverse strand. Representative experiment showing the relative mean ± s.d. abundance of the qPCR replicates. g–j, DNA damage quantification at the CASP16P pause site performed in G1 or S/G2 BRCA1-depleted HeLa FUCCI cells (representative graph) (g), in BRCA1-depleted, synchronized T98G cells (h; n = 3 biological replicates) or in BRCA1 (i; n = 4 biological replicates) or Dicer (j; n = 3 biological replicates) rescue experiments. k, Top left, quantification of ACTB and CASP16P sdRNA in DROSHA-depleted cells (siDrosha). mir191, positive control. Bottom, genome-wide heat maps centred around sdRNA peaks, showing that DROSHA depletion in HeLa cells does not affect sdRNA abundance. Data are mean ± s.e.m. qPCR values. Top right, DROSHA depletion did not induce DNA damage at the ACTB or CASP16P pause site. CCNB1 CoTC is a negative control (n = 3 biological replicates for both graphs). l, sdRNA quantification showing endogenous sdRNA subcellular localization (right) (n = 2–3 biological replicates) and the level of sdRNA overexpression (around tenfold) (left) (representative). m, Benzonase effect on immunoblotted proteins co-immunoprecipitated with BRCA1, Representative blot from n = 3 experiments. n, Efficacy and specificity of depletion of ACTB and CASP16P sdRNAs using separate LNA GapmeRs (n = 3–4 biological replicates). o, Heat maps centred around the sdRNA peaks (±0.8 kb) showing no genome-wide effect after depletion of ACTB or CASP16P sdRNAs. γ-H2AX ChIP analyses shown as an mean fold change compared to relevant control cells. Data were analysed by one-way (g) or two-way (h–k, n) ANOVA with post hoc Tukey HSD test or multiple/unpaired t-test (l) and compared to an undamaged locus or relevant control cells. ns, not significant.

Extended Data Fig. 4 Complementation experiments performed with small DNA or antisense sRNA do not promote repair.

a, BELD quantification of breaks on the forward (coding) strand of the CASP16P pause2 termination site in BRCA1-depleted HeLa cells complemented with either ACTB or CASP16P sdRNA, showing that only CASP16P sdRNA can prevent the accumulation of breaks at the CASP16P pause2 site. A representative experiment is shown, and the histograms depict the mean ± s.d. values of the qPCR replicates. b, c, DNA damage quantification using γ-H2AX ChIP qPCR analyses performed in complementation experiments at the ACTB and CASP16P pause sites and at the CCNB1 CoTC-type terminator. ChIP data are represented as the mean ± s.e.m. fold change compared to an undepleted relevant control. Complementation experiments were performed in BRCA1-depleted (b) or DICER1-depleted (c) HeLa cells reconstituted with the 3′-non-polymerizable sense sdRNA (3′-blocked ACTB sdRNA) (b, c) or ACTB or CASP16P antisense (AS) sdRNA (b, c) or the corresponding sense or antisense sdRNA DNA sequence (b). n = 2–6 biological replicates (b); n = 2–6 biological replicates (c). b, c, Data were analysed by two-way ANOVA with post hoc Tukey HSD test and compared to the relevant control cells.

Extended Data Fig. 5 Relative AGO1 and AGO2 binding ratio of ACTB sdRNA compared to its precursor.

a, b, BRCA1 RIP analyses of ACTB sdRNA or its precursor, showing the raw data as a percentage of input (a) or as the fold change of the signal obtained between the relevant BRCA1 antibody and a beads-only control (b). c, RIP analysis showing the binding ratio (log2-transformed) between ACTB sdRNA and its precursor (quantified using TaqMan and strand-specific reverse transcription followed by qPCR) after AGO1 or AGO2 immunoprecipitation/RIP from HeLa whole-cell extracts.

Extended Data Fig. 6 Validation of siRNA-mediated depletion of PALB2 and RAD52 and specificity of PALB2 and RAD52 immunoprecipitation.

a, Representative immunoblots showing the efficiency of siRNA-mediated depletion of PALB2 and RAD52 in HeLa cells. Representative blot from n = 7 experiments. b, Representative experiment showing γ-H2AX ChIP analyses after RAD52 siRNA-mediated depletion using two separate siRNAs. The histograms depict the mean ± s.d. values of qPCR replicates. Data were analysed by unpaired t-test and compared to the relevant control cells. c, d, co-IP of endogenous BRCA1 in subcellular fractions of HeLa cells (c) and HMECs (d). Representative blot from n = 3 experiments. PALB2 and RAD52 proteins were detected by immunoblotting using the relevant antibodies. Chrom, chromatin; Cyt, cytoplasm; NS, nuclear soluble. e, PALB2 co-IP validation in HeLa cells treated with PALB2 siRNA. Representative blot from n = 2 experiments. f, RAD52 co-IP performed with nuclear extracts from HeLa cells. Representative blot from n = 3 experiments. g, Representative RIP analysis of nuclear PALB2 and RAD52 binding affinity ratio (log2-transformed) between CASP16P sdRNA and its precursor. All immunoblots were developed using the indicated antibodies.

Extended Data Fig. 7 ACTB and CASP16P antisense sdRNA or DNA sequences do not attract the BRCA1–RNAi and the PALB2–RAD52 repair complexes.

a, RNA–protein binding assay performed in HeLa nuclear extracts using sense or antisense, synthetic biotinylated (or not) ACTB sdRNA (or its DNA sequence) or streptavidin beads only. Representative blot from n = 3 experiments. b, RNA–protein binding assay performed in HeLa nuclear extracts using sense or antisense synthetic biotinylated (or not) CASP16P sdRNA. ACTB sdRNA was used as a positive control. Representative blot from n = 3 experiments. c, RNA–protein binding assay performed in T98G subcellular fractions using synthetic, sense-strand-derived, biotinylated ACTB or CASP16P sdRNA. Representative blot from n = 2 experiments. d, RNA–protein binding assay performed in HeLa nuclear extracts using synthetic biotinylated sdRNAs with the sequence of sense or antisense ACTB sdRNA, ACTB sdRNA (−46) or ACTB sdRNA (+31). See the schematic of the ACTB locus depicting the location of the various sRNAs. ACTB sdRNA (−46) and ACTB sdRNA (+31) are, respectively, located 46 nt upsteam of the 5′ end of the ACTB sdRNA and 31 nt downstream of the 3′ end of the ACTB sdRNA. Representative blot from n = 3 experiments. The beads only were a negative control. All immunoblots were developed using the indicated antibodies. e, f, γ-H2AX ChIP analyses using the data collected from the complementation experiments using sense or antisense ACTB sdRNA, ACTB sdRNA (−46) or ACTB sdRNA (+31) performed in HeLa cells depleted of BRCA1 (e) or DICER1 (f). ChIP results are shown as the mean ± s.e.m. fold change compared to the mock siRNA. n = 2–11 biological replicates (e) and n = 2–7 biological replicates (f). Data were analysed by two-way ANOVA with post hoc Tukey HSD test and compared to the relevant control cells.

Extended Data Fig. 8 PALB2 binding affinity for sdRNA is independent of Dicer or AGO1 and AGO2, but the recruitment of PALB2 and RAD52 to pause sites is, respectively, RAD52- and PALB2-dependent.

a, PALB2 and RAD52 genome-wide RIP analyses of sRNAs are shown as heat maps centred around the sdRNA peaks identified in Fig. 2. b, PALB2 and RAD52 RIP analyses of ACTB and CASP16P sdRNA binding in RAD52- and PALB2-depleted cells, respectively. Representative experiment showing the mean ± s.d. of the qPCR replicates. c, Representative RIP analysis showing the relative abundance of PALB2-bound ACTB or CASP16P sdRNAs (quantified by TaqMan and qPCR) after depletion of DICER1 or AGO1. d, e, PALB2 (d) and RAD52 (e) ChIP analyses showing ChIP antibody specificity as well as how PALB2 or RAD52 recruitment is influenced by PALB2 or RAD52 depletion (n = 2–4 and n = 2–3 biological replicates, respectively, for PALB2 and RAD52 ChIP). f, RAD52 ChIP analyses with or without depletion of GapmeR-directed ACTB or CASP16P sdRNA. ChIP results are shown as the mean ± s.e.m. fold change compared to the mock siRNA. Data were analysed by one-way (b, c) or two-way (d, e) ANOVA with post hoc Tukey HSD test or multiple t-test (f) and compared to the relevant control cells.

Extended Data Fig. 9 PALB2 and RAD52 depletion induce DNA damage in proliferating T98G and validation of efficient G0 arrest upon PALB2 and RAD52 depletion.

a, γ-H2AX ChIP quantification analysed in proliferating BRCA1-, PALB2- or RAD52-depleted T98G cells (n = 3 biological replicates). ChIP results are shown as the mean ± s.e.m. fold change compared to the mock siRNA. b, Representative immunoblots showing the efficiency of siRNA-mediated depletion of PALB2 and RAD52 in both quiescent/G0 arrested and asynchronous T98G cells. Representative blot from n = 4 experiments. p27 is a marker of quiescence in this setting.

Extended Data Fig. 10 Overexpression of ACTB or CASP16P sdRNA results in DNA damage at the pause site of the gene that encoded it.

a, DNA damage quantification at ACTB and CASP16P termination pause sites following ACTB or CASP16P sdRNA overexpression (OE) using γ-H2AX ChIP qPCR analyses. The ChIP signal reflects the mean ± s.e.m. fold change over the untransfected condition (control). n = 4–6 biological replicates. Data were analysed by two-way ANOVA with post hoc Tukey HSD test and compared to the relevant control cells. b, Model of sdRNA-mediated DNA damage repair at R-loop-positive pause sites in proliferating and quiescent cells.

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Hatchi, E., Goehring, L., Landini, S. et al. BRCA1 and RNAi factors promote repair mediated by small RNAs and PALB2–RAD52. Nature 591, 665–670 (2021). https://doi.org/10.1038/s41586-020-03150-2

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