1. Chromosomes and Gene Expression
  2. Genetics and Genomics
Download icon

Sae2/CtIP prevents R-loop accumulation in eukaryotic cells

  1. Nodar Makharashvili
  2. Sucheta Arora
  3. Yizhi Yin
  4. Qiong Fu
  5. Xuemei Wen
  6. Ji-Hoon Lee
  7. Chung-Hsuan Kao
  8. Justin WC Leung
  9. Kyle M Miller
  10. Tanya T Paull  Is a corresponding author
  1. Howard Hughes Medical Institute, The University of Texas at Austin, United states
  2. The University of Texas at Austin, United States
  3. National Cancer Institute, National Institutes of Health, United States
  4. University of Arkansas for Medical Sciences, United States
Research Article
  • Cited 1
  • Views 1,231
  • Annotations
Cite this article as: eLife 2018;7:e42733 doi: 10.7554/eLife.42733

Abstract

The Sae2/CtIP protein is required for efficient processing of DNA double-strand breaks that initiate homologous recombination in eukaryotic cells. Sae2/CtIP is also important for survival of single-stranded Top1-induced lesions and CtIP is known to associate directly with transcription-associated complexes in mammalian cells. Here we investigate the role of Sae2/CtIP at single-strand lesions in budding yeast and in human cells and find that depletion of Sae2/CtIP promotes the accumulation of stalled RNA polymerase and RNA-DNA hybrids at sites of highly expressed genes. Overexpression of the RNA-DNA helicase Senataxin suppresses DNA damage sensitivity and R-loop accumulation in Sae2/CtIP-deficient cells, and a catalytic mutant of CtIP fails to complement this sensitivity, indicating a role for CtIP nuclease activity in the repair process. Based on this evidence, we propose that R-loop processing by 5’ flap endonucleases is a necessary step in the stabilization and removal of nascent R-loop initiating structures in eukaryotic cells.

https://doi.org/10.7554/eLife.42733.001

Introduction

Double-strand breaks in DNA are known to be lethal lesions in eukaryotic cells, and can be an important source of genomic instability during oncogenic transformation because of the possibility of misrepair, translocations, and rearrangements that initiate from these lesions (Aparicio et al., 2014). The repair of double-strand breaks in eukaryotes occurs through pathways related to either non-homologous end joining or homologous recombination, although many variations on these basic pathways can occur in cells depending on the cell cycle phase, the extent of DNA end processing that occurs, which enzymes are utilized to do the processing, and what resolution outcomes predominate (Ceccaldi et al., 2016; Symington, 2016; Symington and Gautier, 2011).

The budding yeast enzyme Sae2 and its mammalian ortholog CtIP are important for DNA end processing in eukaryotes and has been shown to act in several ways to facilitate the removal of the 5ʹ strand at DNA double-strand breaks (Makharashvili and Paull, 2015Symington, 2016). Phosphorylated Sae2/CtIP promotes the activity of the Mre11 nuclease in the Mre11/Rad50/Xrs2(Nbs1)(MRX(N)) complex, which initiates the trimming of the DNA end on the 5ʹ strand (Cannavo and Cejka, 2014). Sae2/CtIP and MRX(N) promote the removal of the Ku heterodimer, which acts as a block to resection during non-homologous end joining (Cannavo and Cejka, 2014; Reginato et al., 2017; Wang et al., 2017) and also recruit the long-range 5ʹ to 3ʹ nucleases Exo1 and Dna2 which do extensive processing of the ends (Cejka et al., 2010; Myler et al., 2016; Nicolette et al., 2010; Niu et al., 2010; Shim et al., 2010).

In addition to the activities of Sae2/CtIP that promote MRX(N) functions, the protein has also been shown to possess intrinsic nuclease activity that is important for the processing of breaks, particularly those formed in the context of protein lesions, radiation-induced DNA damage, or camptothecin (CPT) damage during S phase (Symington, 2016; Chanut et al., 2016; Makharashvili et al., 2014; Wang et al., 2014). Nuclease-deficient CtIP fails to complement human cells deficient in CtIP for survival of radiation-induced DNA damage while homologous recombination at restriction enzyme-induced break sites is comparable to wild-type-complemented cells (Makharashvili et al., 2014; Wang et al., 2014).

Eukaryotic cells lacking Sae2 or CtIP were also observed years ago to be hypersensitive to topoisomerase one (Top1) poisons such as CPT (Deng et al., 2005; Sartori et al., 2007). Top1 bound to CPT is stalled in its catalytic cycle in a covalent tyrosine 3ʹ linkage with DNA, creating a protein-linked DNA strand adjacent to a 5ʹ nick (Pommier, 2006). This lesion targets one DNA strand but can lead to double-strand breaks during replication. Importantly, Top1 is highly active at sites of ongoing transcription due to the need for the release of topological stress in front of and behind the RNA polymerase (Liu and Wang, 1987; Pommier et al., 2016; Zhang et al., 1988). Considering that MRX(N) complexes as well as Sae2/CtIP are essential for the removal of 5ʹ Spo11 conjugates during meiosis (McKee and Kleckner, 1997; Neale et al., 2005; Prinz et al., 1997) coincident with their role in 5ʹ strand processing, it is surprising that Sae2/CtIP-deficient cells exhibit such sensitivity to 3ʹ single-strand lesions, and the mechanistic role that Sae2/CtIP plays at these lesions is currently unknown.

In recent years, it has become clear that transcription can play a major role in promoting genomic instability by forming stalled transcription complexes and RNA-DNA hybrids in the genome (Sollier and Cimprich, 2015). Stable annealing of nascent RNA with the DNA template strand can occur at sites of stalled RNA polymerase complexes, and the ‘R-loops’ formed in this way can block replication as well as other DNA transactions (Santos-Pereira and Aguilera, 2015). A wealth of evidence accumulated recently suggests that these events can lead to single-strand and double-strand breaks in DNA that provide recombinogenic intermediates for misrepair events (Costantino and Koshland, 2015; Hamperl et al., 2017; Huertas and Aguilera, 2003).

The Sen1 protein in budding yeast has been shown to regulate many aspects of RNA biology, including termination of RNA polymerase II transcription, 3′ end processing of mRNA, and dissociation of RNA-DNA hybrids (Mischo et al., 2011; Steinmetz et al., 2006; Finkel et al., 2010). The human ortholog of Sen1, Senataxin, has also been shown to resolve RNA-DNA hybrids (Skourti-Stathaki et al., 2011; Yüce and West, 2013; Cohen et al., 2018) as well as to associate with replication forks to protect fork integrity when traversing transcribed genes (Alzu et al., 2012). Mutations in the gene encoding Senataxin are responsible for the neurodegenerative disorder Ataxia with Oculomotor Apraxia two as well as an early-onset form of amyotrophic lateral sclerosis (Groh et al., 2017).

In this work we sought to understand the mechanistic basis of the hypersensitivity of Sae2/CtIP-deficient cells to Top1 poisons and other forms of DNA damage, finding unexpectedly that the sensitivity of these cells can be partially suppressed by overexpression of Sen1/Senataxin or RNaseH. Genetic evidence in yeast and human cells shows that Sae2/CtIP-deficient cells require Senataxin and RNaseH enzymes for survival of genotoxic agents and that these cells exhibit high levels of RNA polymerase stalling and R-loop formation at sites of active transcription, consistent with a failure to recognize or process RNA-DNA hybrids. Based on this evidence we propose that Sae2/CtIP has an important role in processing R-loops that promotes the action of RNA-DNA helicases and ultimately cell survival after DNA damage.

Results

Transcription termination factors rescue DNA damage sensitivity of sae2Δ and mre11 nuclease-deficient yeast cells

To test for an effect of transcriptional regulation on the sae2Δ phenotype in yeast, we overexpressed several different RNA Pol II-associated factors in the mutant strain. We found that overexpression of the termination factor Sen1 markedly improved survival of the sae2Δ strain to genotoxic agents (Figure 1A). S. cerevisiae SEN1 encodes a helicase that is responsible for unwinding RNA-DNA hybrids and also promotes transcription termination through direct contact with RNA Pol II as well as 3′ end processing of RNA (Porrua and Libri, 2015). We also found that PCF11, a component of the cleavage and polyadenylation complex (CPAC) (Grzechnik et al., 2015; Birse et al., 1998), improves the survival of yeast strains lacking SAE2 when tested for survival of CPT but there was little effect of overexpressing other proteins that also regulate transcription through RNA Pol II including SSU72, RTT103, NRD1, and YSH1 (Figure 1A and Figure 1—figure supplement 1).

Figure 1 with 2 supplements see all
Transcription termination factors suppress DNA damage sensitivity of sae2Δ and mre11 nuclease-deficient strains.

(A) Full-length PCF11, SSU72, RTT103, SEN1, and sen1 mutants G1747D and R302W were expressed from a 2μ plasmid in sae2Δ cells. Fivefold serial dilutions of cells expressing the indicated Sae2 alleles were plated on nonselective media (control) or media containing camptothecin (CPT, 5.0 μg/ml) and grown for 48 hr (control) or 70 hr (CPT). (B) SEN1 was expressed from a 2μ plasmid in sae2Δ, mre11-H125N, and sae2Δ mre11-H125N cells and analyzed for CPT sensitivity as in (A). (C) Wild-type, sae2Δ, sen1-1(G1747D), and sae2Δ sen1-1(G1747D) strains were analyzed as in (A). (D) Wild-type, sae2Δ, Δrnh1 Δrnh201, and sae2Δ Δrnh1 Δrnh201 strains were analyzed as in (A). (E) sae2Δ strains with RNH1 expressed under the control of the GAL promoter were tested for sensitivity to CPT and MMS, on either galactose or glucose plates indicated.

https://doi.org/10.7554/eLife.42733.002

The ability of Sen1 overexpression to partially alleviate the toxicity of CPT was also observed with the Mre11 nuclease-deficient mutant mre11-H125N (Moreau et al., 1999) and particularly with the double mutant sae2Δ mre11-H125N (Figure 1B). A mutation located in the conserved helicase domain of Sen1 (G1747D) reduces the ability of Sen1 to overcome CPT toxicity in the sae2Δ strain (Figure 1A) but there was no effect of R302W, a mutation reported to block binding to the Rpb1 subunit of RNA Pol II (Chinchilla et al., 2012Finkel et al., 2010). The sen1-G1747D mutant is deficient in transcription termination but not in 3′ end processing of RNA (Mischo et al., 2011), thus we conclude that the termination function of the Sen1 enzyme is important for the rescue of CPT sensitivity in sae2Δ strains. In contrast, Sen1 overexpression in sae2Δ cells has no effect on the efficiency of resection (Figure 1—figure supplement 2), as measured in an assay for single-strand annealing (Vaze et al., 2002b) previously shown be dependent on SAE2 due to its importance in DNA end resection (Clerici et al., 2005).

To further investigate the genetic relationship between SEN1 and sae2Δ phenotypes, we deleted the SAE2 gene in a sen1-1 (G1747D) background. A complete deletion of SEN1 is lethal (DeMarini et al., 1992); however, the sen1-1 allele has been used as a hypomorphic mutant and is deficient in transcription termination and removal of R-loops in vivo (Mischo et al., 2011). Although the sen1-1 strain is not sensitive to the levels of DNA damaging agents used here, a combination with sae2Δ generates extreme sensitivity to both CPT and MMS (Figure 1C). Synthetic sensitivity of sen1-1 with other DNA repair mutant strains has previously been shown for HU exposure (Mischo et al., 2011). Since the Sen1 helicase acts to remove R-loops from genomic loci, we also tested whether sae2Δ strains show synthetic sensitivity to CPT in combination with deletions of RNase H enzymes which remove ribonucleotides from DNA. Deletion of both RNase H1 and H2 in a Δrnh1 Δrnh201 strain generates modest DNA damage sensitivity as previously shown (Lazzaro et al., 2012; Zimmer and Koshland, 2016; Arudchandran et al., 2000); however, this is further exacerbated by a deletion of SAE2 (Figure 1D). Conversely, overexpression of RNH1 in a sae2Δ strain from a galactose-inducible promoter partially rescues the strain upon CPT or MMS exposure (Figure 1E). Taken together, these results suggest that loss of Sae2, either by itself or in combination with Mre11 nuclease activity, generates a form of DNA damage sensitivity that requires efficient removal of RNA or ribonucleotides from DNA.

RNA-DNA hybrids form at sites of RNA polymerase pausing and can generate collisions between the transcription machinery and the replication fork (Santos-Pereira and Aguilera, 2015). We postulated that the source of lethal damage in a sae2Δ strain may be related to transcription-replication conflicts, based on the SEN1 and RNaseH observations above. To test this idea we synchronized wild-type and sae2Δ yeast strains with alpha factor and exposed the cells to CPT in either G1 or S phases of the cell cycle. As expected, the sae2Δ strain showed marked sensitivity to CPT and this was specific to exposure in S phase (Figure 2A), suggesting that movement of replication forks through Top1 DNA damage sites is important for the DNA damage sensitivity. We also tested for the effect of transcription on CPT survival by incubating cells with the general transcription inhibitor thiolutin (Jimenez et al., 1973). Inhibition of transcription completely alleviated the sensitivity of the sae2Δ strain to CPT, generating wild-type levels of survival (Figure 2B).

Sae2 associates with sites of high levels of transcription which accumulate R-loops in the absence of Sae2.

(A) The survival of wild-type and sae2Δ strains was measured by exposing cells to camptothecin (100 μM for 2 hr) while in G1 phase or S phase and plating cells on rich media. The percentage of viable colonies is shown relative to cells exposed to DMSO only, with three biological replicates (error bars represent standard deviation). (B) The survival of wild-type and sae2Δ strains was measured in the absence or presence of active transcription by exposing S phase cells to thiolutin (2.5 μg/ml for 30 min) or DMSO prior to camptothecin exposure in S phase as in (A). (C) Representative examples of Sae2-ChIP at the FBA1, HIS3, ENO2, and ADH1 genes in sae2Δ cells expressing Flag-Sae2, in S phase with CPT exposure as in (A). Reads from the immunoprecipitated sample are shown (IP) in comparison to control immunoprecipitations performed in the absence of Flag antibody (bead control, BC). (D) Data from Sae2 ChIP-seq was compared to previous data on transcription levels in wild-type yeast cells (Nagalakshmi et al., 2008; Pelechano et al., 2010; Miura et al., 2008)(See Supplementary file 2). The overlap between peaks identified by Sae2 ChIP-seq were compared to the top 10% of transcribed genes (486 genes; excluding rDNA loci) or a randomly chosen set of genes. The randomized set comparison was performed 1000 times. (E) R-loops were quantified at various loci using S9.6 immunoprecipitation in wild-type, sae2Δ, and sae2Δ + SEN1 yeast strains, all with CPT treatment in S phase, as indicated. Levels of DNA sites enriched in S9.6 immunoprecipitations are shown relative to levels in wild-type cells using primers specific for ADH1 (ADH1-2), ENO2 (ENO2-3), and FBA1 (FBA1-2). Error bars represent standard deviation from four biological replicates. * indicates p < 0.05 comparing sae2Δ to wild-type (black asterisks) or comparing sae2Δ to sae2Δ plus SEN1 (red asterisks) using 2-tailed Student's t-tests. S9.6 immunoprecipitations were also performed with RNaseH pretreatment of chromatin, ‘+RNaseH’.

https://doi.org/10.7554/eLife.42733.005

Sae2 occupancy is elevated at sites of high transcription in S phase cells

To determine if the relationship between SAE2 deletion and transcription is direct, we sought to determine the genomic locations of Sae2 protein binding in yeast. We performed ChIP assays using Flag-tagged Sae2 and analyzed the peaks in relation to the bead control (no antibody). This analysis revealed small peaks of Sae2 enrichment, primarily in the S phase +CPT sample (176 peaks identified by Model-based Analysis of ChIP-Seq v.2 (MACS2) (Zhang et al., 2008) after removal of overlaps with bead control) (Figure 2C, Supplementary file 2). In contrast, only 45 peaks were identified by this criteria in S phase in the absence of DNA damage. The locations of the sites enriched with CPT treatment did not correlate with sites of replication origins but were enriched for highly transcribed genes, measuring the overlap between the binding sites and the top 10% of highly transcribed genes (Nagalakshmi et al., 2008; Pelechano et al., 2010; Miura et al., 2008) in comparison to a randomly selected subset (Figure 2D). The enrichment for Sae2 occupancy at sites of high transcription was only observed with cells in S phase, not with the G1 phase cells, and only in cells treated with CPT. Approximately 20% (9 of 45 Sae2 peaks in S phase and 36 of 176 Sae2 peaks in S phase with CPT) overlap with the sites of RNA-DNA hybrids measured in wild-type yeast cells in a previous study (Wahba et al., 2016).

sae2Δ cells accumulate R-loops and stalled RNA pol II during CPT exposure

The results from these experiments suggested an involvement of transcription in the DNA damage sensitivity of sae2Δ cells, possibly related to an accumulation of R-loops. To test this hypothesis we used the S9.6 antibody to detect RNA-DNA hybrids (Boguslawski et al., 1986) in chromatin immunoprecipitation experiments comparing wild-type, sae2Δ, and sae2Δ with Sen1 overexpression. We synchronized yeast cells in S phase, exposed the cultures to CPT, and observed approximately 2-fold higher levels of R-loops in sae2Δ cells at the ADH1, ENO2, and FBA1 loci compared to the wild-type strain (Figure 2E). This signal was reduced with Sen1 expression and was sensitive to RNaseH treatment in vitro, consistent with this interpretation that R-loops accumulate at these loci in the absence of Sae2.

If Sae2 is localized to sites of high transcription and its loss is partially alleviated by enzymes that promote transcription termination, we reasoned that levels of RNA polymerase may be stalled at these sites in sae2Δ strains. To test this idea we utilized a tagged RNA Pol II strain (HTB-Rpb2) (Schaughency et al., 2014) to monitor the occupancy of RNA Pol II at sites in the genome with high levels of constitutive transcription where Sae2 was observed by ChIP-seq in Figure 2C. HTB-tagged Pol II complexes were isolated from wild-type, sae2Δ, and sae2Δ with Sen1 overexpression strains that were synchronized in G1 with alpha-factor and released into S phase. All of the strains showed very similar levels of RNA Pol II occupancy on the ADH1, ENO2, and FBA1 genes in the absence of DNA damage (Figure 3A). In contrast, when the strains were released into S phase in the presence of CPT, the wild-type strain showed an average of 1.5 to 2-fold higher levels of RNA Pol II occupancy, while sae2Δ strains exhibited 2.5 to 5.5-fold higher levels of polymerase stalling (Figure 3A). Importantly, sae2Δ with Sen1 overexpression showed reduced levels of polymerase occupancy, similar to the wild-type strain with CPT.

RNA Polymerase stalling at highly transcribed genes is exacerbated in sae2Δ strains with DNA damage.

(A) HTB-tagged Rpb2 (a component of RNA Pol II) levels were measured at various genes during S phase in wild-type and sae2Δ strains with or without CPT exposure and in the presence or absence of overexpressed Sen1, as indicated. Enrichment relative to input DNA is shown, with all values normalized to values obtained with the wild-type strain in the absence of damage. Error bars represent standard error from six immunoprecipitations, two biological samples with three technical replicates of the IP per sample. Approximate locations of primer sets relative to the gene are shown. * indicates p < 0.05, **p < .005, ***p < 0.0005, comparing sae2Δ to wild-type (black asterisks) or comparing sae2Δ to sae2Δ plus SEN1 (red asterisks) using 2-tailed Student's t-tests. (B) HTB-tagged Rpb2 levels were measured at various genes as in (A). SNR5 and SNR13 are non-coding nucleolar RNAs. (C) HTB-tagged Sen1 levels were measured at various genes as in (A) with CPT treatment. Primer sets used were ADH1-2, ENO2-4, and FBA1-3.

https://doi.org/10.7554/eLife.42733.006

We also examined RNA Pol II occupancy at other genomic locations where transcription termination has previously been shown to be regulated by Sen1. We do observe CPT-induced RNA Pol II stalling at the PDC1 or NRD1 genes, both known to be dependent on Sen1 (Alzu et al., 2012; Grzechnik et al., 2015), albeit at a lower level than the genes identified in our Sae2 ChIP experiment. Obvious pausing of RNA Pol II in the absence of Sae2 was also induced by CPT at the snoRNA genes SNR13 and SNR5 and the associated gene TRS31 (Figure 3B), which have been shown to be transcribed by RNA Pol II and exhibit termination read-through, altered RNA Pol II occupancy, and R-loops in the absence of Sen1 function (Steinmetz et al., 2006; Grzechnik et al., 2015). Overall, these results are consistent with the hypothesis that Sae2 is present at a subset of highly transcribed genes during CPT exposure, and that high levels of toxic R-loops form at these sites in sae2Δ strains which can be reduced by Sen1.

Based on these results we considered the possibility that Sen1 is dependent on Sae2 for recruitment to sites of stalled transcription. To examine this we used an HTB-tagged Sen1 strain (Creamer et al., 2011) and monitored Sen1 recruitment during CPT treatment at a subset of the genomic locations where we observed Sae2 occupancy and RNA polymerase accumulation. This showed that Sen1 is present at these sites (ADH1, ENO2, FBA1) in the absence of SAE2 (Figure 3C), thus the binding of the helicase to these sites is Sae2-independent.

The CPT sensitivity of CtIP deficient cells is rescued by over-expression of senataxin or inhibition of transcription

In mammalian cells, the Sae2 ortholog CtIP (Sartori et al., 2007) promotes resection of DNA double-strand breaks in conjunction with the MRN complex in mammalian cells (Makharashvili and Paull, 2015). It was previously shown that depletion of CtIP generates extreme sensitivity to topoisomerase poison induced DNA lesions, particularly CPT-induced DNA damage (Sartori et al., 2007; Huertas and Jackson, 2009; Nakamura et al., 2010; Makharashvili and Paull, 2015). To examine the role of CtIP in human cells we used a U2OS cell line with a stably integrated doxycycline-inducible CtIP shRNA cassette. The cells were complemented with either shRNA-resistant wild-type eGFP-CtIP, or with vector only (Figure 4—figure supplement 1). As expected, depletion of CtIP greatly diminishes cell survival in the presence of CPT, and re-expression of wild-type CtIP rescues the CPT sensitivity (Figure 4A).

Figure 4 with 2 supplements see all
CtIP deficiency induces R-loop accumulation at sites of DNA damage.

(A) CtIP-depleted U2OS cells complemented with vector only or constructs overexpressing eGFP-CtIP, PCF11, or Senataxin (C-terminus) as indicated were exposed to increasing concentrations of CPT (1 hr). Cell viability was determined by clonogenic survival assay in comparison to untreated cells. Results are shown from three biological replicates and error bars represent S. D. (B) Wild-type or CtIP-depleted U2OS cells were pre-treated with DRB (20 μM) prior to CPT exposure and cell viability was determined as in (A). (C) Live cell imaging was performed with U2OS cells stably expressing RNaseHD10R-E48R-mCherry. The circle indicates the site of laser damage. (D) CtIP-depleted U2OS cells were complemented with eGFP-CtIP, PCF11, or Senataxin (C-terminus) as indicated and RNaseHD10R-E48R-mCherry accumulation at the laser damage was quantified. The average of 4 cells is shown and error bars represent S. E. M. (E) RNaseHD10R-E48R-mCherry accumulation at laser damage sites was measured in CtIP-depleted U2OS cells complemented with wild-type or nuclease deficient (‘NA/HA’) eGFP-CtIP as in (D); n > 12, error bars represent S.E.M. (F) Wild-type or CtIP-depleted U2OS cells were pre-treated with DRB (20 μM) prior to measurement of RNaseHD10R-E48R-mCherry accumulation at laser damage sites as in (D); n > 5; error bars represent S.E.M. (G) RNaseHD10R-E48R-mCherry accumulation at laser damage sites was measured in wild-type or CtIP-depleted, XPG-depleted, or Senataxin (SETX)-depleted U2OS cells as in (D); n = 5; error bars represent S.E.M. (H) RNaseHD10R-E48R-mCherry accumulation at laser damage sites was measured in wild-type, CtIP-depleted, XPG-depleted, or both CtIP/XPG-depleted U2OS cells as in (D); n > 8, error bars represent S.E.M. Results shown are representative of several experiments performed.

https://doi.org/10.7554/eLife.42733.007

Based on the yeast experiments with SAE2, we hypothesized that overexpression of a helicase that specifically resolves RNA-DNA hybrids should rescue the sensitivity of CtIP-depleted cells to CPT exposure. To test this idea, we complemented the CtIP-depleted cells with the C-terminal domains (a.a. 1851–2677) of human Senataxin, the ortholog of yeast Sen1 that also acts to remove RNA-DNA hybrids and promotes transcription termination (Porrua and Libri, 2015). Remarkably, overexpression of Senataxin in the CtIP-depleted cells completely rescues the CPT sensitivity; however, unlike the yeast experiments, no effect of human PCF11 expression was detected (Figure 4A). Although Senataxin expression rescued the survival of CtIP-depleted cells after CPT exposure, only partial suppression of the defects in growth and DNA end resection were observed (Figure 4—figure supplement 1). These results also suggest that inhibition of transcription could rescue the CPT sensitivity of CtIP-depleted cells. Indeed, we observe that pre-treatment of the cells with DRB, an inhibitor of RNA polymerase II-dependent RNA synthesis, partially rescues the CPT sensitivity caused by CtIP deficiency (Figure 4B). Thus, similar to yeast, reduction of transcription during DNA damage exposure alleviates the effects of CtIP deficiency in human cells, suggesting a conserved mechanism for the repair of Top1 lesions associated with aberrant transcription.

CtIP deficiency induces accumulation of R-loops at laser micro-irradiation sites

Similar to topoisomerase-DNA adducts, UVA laser-induced DNA crosslinks present a physical barrier to RNA polymerase that could stall transcription and promote the formation of complex DNA lesions including R-loops. We utilized a live cell assay with lentiviral expression of a bacterial RNaseH catalytic mutant fused to mCherry (RNaseHD10R-E48R-mCherry) that acts as a sensor for R-loops in the genome (Bhatia et al., 2014a). The RNaseHD10R-E48R-mCherry sensor was expressed in the wild-type or CtIP-depleted U2OS cells described above, which were laser micro-irradiated in a small area of the nucleus. Measurement of the accumulation of RNaseHD10R-E48R-mCherry signal over time in these cells showed that the recruitment of RNaseH occurs to a higher intensity in CtIP-depleted cells in comparison to cells complemented with wild-type CtIP, suggesting that higher levels of R-loops are formed in the absence of CtIP (Figure 4C,D). A similar control experiment examining mCherry alone did not show this pattern, confirming the effect is specific to the RNaseH fusion (Figure 4—figure supplement 2). Since we found that overexpression of Senataxin rescues the CPT sensitivity of CtIP-depleted cells, we reasoned that it might also rescue the higher levels of R-loop accumulation in the absence of CtIP. We expressed the C-terminal domains of human Senataxin in the CtIP-depleted cells, and measured the levels of laser-induced R-loops by the live cell imaging method. Here also we found that with Senataxin expression, the recruitment of RNaseH in the CtIP-depleted cells is reduced to the levels observed in cells expressing wild-type CtIP (Figure 4D). Similar to the CPT survival assay results, we found that the PCF11 was not able to rescue CtIP deficiency for reduction of R-loop levels after laser micro-irradiation.

Previous work on CtIP in vitro identified mutants that exhibit lower levels of endonuclease activity on flap structures in comparison to the wild-type protein (Makharashvili et al., 2014; Wang et al., 2014). Here we used the N289A/H290A (NA/HA) mutant allele also containing shRNA-resistant mutations to complement CtIP-depleted cells and found that this mutant failed to reduce the increased RNaseH recruitment to damage sites that occurs in CtIP-deficient cells (Figure 4E, Figure 4—figure supplement 1). Thus the nuclease activity of CtIP appears to play a role in DNA damage recognition and/or processing that helps to prevent R-loop accumulation in human cells.

The accumulation of R-loops in CtIP deficient cells is dependent on transcription

To further test the role of active transcription in R-loop accumulation, we pre-treated cells with 5,6-dichloro-1-beta-D-ribofuranosylbenzimidazole (DRB), a RNA polymerase II inhibitor, and found that inhibition of transcription rescues the R-loop accumulation phenotype caused by CtIP deficiency (Figure 4F). As overexpression of Senataxin reduces R-loop formation in CtIP-depleted cells after DNA damage, we expected that depletion of this enzyme would have the opposite effect. Indeed, U2OS cells depleted of Senataxin also exhibit increased R-loop formation after laser-induced DNA damage (Figure 4G, Figure 4—figure supplement 1), consistent with previous observations of DNA damage sensitivity in Senataxin mutant cells (Suraweera et al., 2007; Lavin et al., 2013).

The XPG protein, a component of nucleotide excision repair (Fagbemi et al., 2011), has been shown to be important in the resolution of R-loops (Sollier et al., 2014). As a comparison to CtIP, we also assessed whether the deficiency of this protein would also lead to high R-loop levels after DNA damage. As expected, we observed that the XPG deficient cells accumulate more R-loops after laser induced DNA breaks in comparison to wild-type cells (Figure 4G, S2G). Interestingly, however, concurrent depletion of both CtIP and XPG showed R-loops at levels comparable to wild-type untreated cells (Figure 4H). This result suggests that R-loops do not form efficiently in the absence of both CtIP and XPG, or that they are not recognized efficiently by the RNaseHD10R-E48R-mCherry protein in the absence of both CtIP and XPG.

R-loop accumulation in CtIP-depleted cells without exogenous damage

Considering that deletion of the gene encoding CtIP is cell-lethal even in the absence of exogenous damage (Polato et al., 2014; Chen et al., 2005), we also hypothesized that R-loops might accumulate in CtIP-depleted cells under normal growth conditions. To address this question, we again used the RNaseHD10R-E48R-mCherry sensor but in this case monitored its accumulation in undamaged cells by fluorescence activated cell sorting (FACS), using a modified technique reported previously with a fragment of RNaseH fused to GFP (Bhatia et al., 2014a). Using this procedure, unbound RNaseHD10R-E48R-mCherry protein is removed from the nucleoplasm by detergent extraction, while protein bound to chromatin is retained. This analysis showed a statistically significant increase in RNaseHD10R-E48R-mCherry fluorescence intensity in CtIP-depleted U2OS cells in all cell cycle phases (Figure 5A). Analysis of mCherry alone in these cells showed no differences with CtIP depletion (Figure 4—figure supplement 2). This was also observed in XPG-depleted cells, consistent with the observed effects of both XPG and CtIP with laser damage as shown in Figure 4. Similarly, we examined R-loop accumulation in CtIP-depleted cells complemented with the nuclease-deficient form of CtIP (N289A/H290A, NA/HA, Figure 4—figure supplement 2) and found the levels of RNaseHD10R-E48R-mCherry fluorescence intensity identical to that of CtIP-depleted cells (Figure 5B), suggesting that the nuclease activity of CtIP is necessary for R-loop resolution even in cells that are not exposed to exogenous damage.

Figure 5 with 1 supplement see all
CtIP depletion affects R-loop accumulation and transcription in human cells.

(A) DNA-RNA hybrids were quantified in undamaged U2OS cells by monitoring chromatin-bound RNaseHD10R-E48R-mCherry by FACS. 10,000 cells were counted in each of 3 biological replicates; error bars represent S.D. * and ** denote p < 0.05 or 0.01, respectively in Student's two-tailed T test with comparisons as indicated. (B) RNA/DNA hybrids were quantified in undamaged, CtIP-depleted U2OS cells complemented with either vector only, eGFP-CtIP(wt), or nuclease-deficient eGFP-CtIP(NA/HA) as in (A). 10,000 cells were counted in each of 3 biological replicates; error bars represent S. D. **** denotes p < 0.0001 using Student's two-tailed T test with comparisons as indicated. (C) S9.6 antibody was used to monitor RNA-DNA hybrids in wild-type or CtIP-depleted U2OS cells. Anti-Nucleolin was used as a marker for the nucleolus. (D) Quantification of S9.6 antibody signal in wild-type, CtIP-depleted, XPG-depleted, Senataxin-depleted, or double CtIP/XPG-depleted U2OS cells as indicated. Signal overlapping the nucleolin signal was excluded from the analysis; n > 50, Error bars represent S.E.M. *, **, and **** denote p < 0.05, 0.01, and 0.0001, respectively, using Student's two-tailed T test with comparisons as indicated. (E) Quantification of S9.6 antibody signal in wild-type, CtIP-depleted, or CtIP-depleted plus RNaseH overexpression in U2OS cells as in (D). (F) Wild-type or CtIP-depleted U2OS cells were exposed to CPT (5 µM) or were untreated before harvesting of cellular mRNA. Analysis of transcripts by RNA-seq and hierarchical clustering of transcripts from 21,412 genes is shown as a heat map (red for over-expressed, black for unchanged expression, and green for under-expressed genes) in comparison to wild-type undamaged cells (see Supplementary file 3). (G) Statistical comparisons of overlap between the top 100 differentially expressed genes as ranked by DESeq differential expression p-value and DRIPc-seq peaks from GEO dataset GSE70189. Randomly picked genes were compared to this dataset (‘randomized control’) with the average of 35.56% and standard deviation 4.76% (estimated from 1000 simulations). Genes with significant differences between wild-type and CtIP-depleted cells were identified in the absence of DNA damage (‘WT vs CtIP shRNA (-CPT’)) as well as with CPT treatment (‘WT vs CtIP shRNA (+CPT’)) and were compared with the DRIPc-seq dataset. All three values are above the 99% confidence intervals for the null hypothesis that the genes showing the most evidence of differential expression overlapped the peak regions at the same rate as randomly selected genes.

https://doi.org/10.7554/eLife.42733.010

To confirm these results with a different technique, we also utilized the S9.6 antibody, which recognizes RNA-DNA hybrids and has been widely used as a probe for R-loops in cells (Santos-Pereira and Aguilera, 2015; Boguslawski et al., 1986; García-Rubio et al., 2018). We used immunofluorescence signal from S9.6 antibody in control as well as CtIP-depleted, XPG-depleted, and Senataxin-depleted U2OS cells and quantified the level of signal per cell. As this antibody also recognizes the components of nucleoli, the S9.6 signal that colocalized with these organelles was subtracted from the total signal, and the result was normalized by the area of the nucleus. We found that undamaged CtIP-depleted or XPG-depleted cells have significantly more R-loops than their wild-type counterparts (Figure 5C,D). These findings suggest that CtIP is responsible for the prevention and/or resolution of R-loops, in normally growing cells as well as in cells exposed to DNA damage. We also observed that concurrent depletion of CtIP and XPG resulted in a lower level of R-loop accumulation (Figure 5D), similar to the result with laser-induced damage (Figure 4H). This observation of lower RNA-DNA hybrids in the absence of both nucleases is thus not specific to laser damage or to the sensor used for R-loop detection.

Global patterns of transcription are altered with CtIP depletion

CtIP was originally identified as a binding partner of C-terminal Binding Protein (CtBP), a transcriptional co-regulator (Schaeper et al., 1998), and also binds directly to Rb and the tumor suppressor BRCA1 which also has been widely reported to affect transcription and R-loop formation (Monteiro et al., 1996; Scully et al., 1997; Takaoka and Miki, 2018; Yu et al., 1998; Hatchi et al., 2015). Considering our results with CtIP and R-loop accumulation, we asked whether depletion of CtIP has global effects on transcription patterns by analyzing mRNA using RNA-seq. We performed this analysis on U2OS cells expressing control or CtIP-specific shRNA and examined both CPT-treated and untreated conditions. RNA levels were quantified for 30,769 transcripts. CtIP depletion was found to alter 5013 (~16%) of these transcripts, with both increases (2,578) and decreases (2,435) observed relative to the control cells. Unsupervised hierarchical clustering was used to analyze the transcripts (Figure 5E) (Supplementary file 3). We found that there are transcriptional changes associated with CPT exposure in U2OS cells: 1285 transcripts were upregulated upon CPT treatment, and 1158 transcripts were downregulated. Interestingly, a comparison of the genes affected by CPT exposure to a previous dataset of genes showing R-loop accumulation indicates an overlap significantly higher than would be predicted by chance (Figure 5F). Over 60% of the genes affected by CPT (either up or down) overlap with R-loop prone regions of the genome (Ginno et al., 2012) (see ‘WT only, - vs +CPT’, Figure 5F), whereas less than 40% overlap with DNA-RNA immunoprecipitation (DRIP) positive genes occurs with a randomized control. A similar analysis of the gene set identified in CtIP-depleted cells compared to normal cells also indicates a higher than expected overlap (~50%), suggesting that depletion of CtIP has effects on transcription that are correlated with R-loop-prone regions of the genome.

Quantitation of RNA-DNA hybrids in CtIP-depleted cells

To investigate the role of CtIP in R-loop accumulation at specific loci, we first generated an inducible genomic cassette containing a mouse class switch region (Sγ3) that has previously been shown to accumulate R-loops (Huang et al., 2006). We performed DRIP with the S9.6 antibody followed by quantitative PCR for this locus in U2OS cells and found that the levels of R-loops increase with doxycycline-induced transcription, even in wild-type cells (Figure 6A). The DRIP signal was removed by RNaseH treatment, confirming the specificity of the S9.6 antibody. A much larger increase in R-loops was found in CtIP-depleted cells, however, while the overall levels of transcripts are similar in both cases (Figure 6A, Figure 6—figure supplement 1).

Figure 6 with 3 supplements see all
CtIP depletion induces accumulation of R-loops in human cells.

(A) RNA/DNA hybrids were quantified by DRIP-qPCR in U2OS cells containing a stably integrated, doxycycline-inducible transgene containing murine Sγ3 repeats. R-loop accumulation was measured by immunoprecipitation with the S9.6 antibody and qPCR for the Sγ3 region in the absence or presence of transcription (-/+Dox) in wild-type or CtIP-depleted cells; n > 6, error bars represent S.E.M. (B) Quantification of RNA/DNA hybrids in U2OS cells at endogenous loci using DRIP-qPCR. Levels of hybrids were measured at the ß-actin gene, with CtIP or XPG depletion, and with RNaseH overexpression in cells, as indicated; n > 3, error bars represent S. D. (C), (D), (E). DRIP-qPCR of sites in the RPL13A gene are shown with CtIP or XPG depletion and RNaseH overexpression in cells as indicated. In (F), CtIP-depleted cells were complemented with wild-type eGFP-CtIP or nuclease-deficient NA/HA mutant. (G) Senataxin ChIP was performed in cells containing the doxycycline-inducible transgene containing murine Sγ3 repeats. Levels of SETX occupancy were quantified in the presence or absence of doxycycline and with CtIP depletion as indicated and are represented as fold changes relative to wild-type cells in the absence of dox. n = 3, error bars represent standard deviation. * and ** denote p < 0.05 or 0.01, respectively, using Student's two-tailed T test with comparisons as indicated.

https://doi.org/10.7554/eLife.42733.012

We then examined several endogenous loci that have previously been reported to be prone to R-loop formation (Bhatia et al., 2014b; Hatchi et al., 2015). The β-actin gene has been reported to accumulate R-loops, particularly at the G-rich ‘pause’ sequences downstream of the coding region (Hatchi et al., 2015; Skourti-Stathaki et al., 2014). We observed higher levels of RNA-DNA hybrids at these regions in CtIP-depleted cells in the absence of exogenous DNA damage, which could be reduced to wild-type levels by overexpression of wild-type RNaseH (Figure 6B). We also tested XPG-depleted cells and observed an even higher level of R-loops under these conditions (Figure 6C). Similar results were observed on the UBF and CD30 genes (Figure 6—figure supplements 2 and 3), which we tested because levels of transcription are significantly lower in CtIP-depleted cells (Supplementary file 3, Figure 5—figure supplement 1). We also examined RPL13A, a gene that has been identified as a region prone to R-loop formation (Bhatia et al., 2014b; García-Rubio et al., 2018). We tested three locations throughout the body of the RPL13A gene and found significantly higher levels of R-loops in CtIP-depleted cells which were reduced by overexpression of RNaseH in cells (Figure 6D) or by treatment of genomic DNA with RNaseH in vitro prior to the immunoprecipitation (Figure 6—figure supplement 3). We also observed high levels of R-loops at this gene in XPG-depleted cells compared to wild-type (Figure 6E). Lastly, the nuclease-deficient NA/HA allele of CtIP was expressed in CtIP-depleted cells, and R-loops were found to be approximately 1.5 to 2-fold higher in these cells in comparison to cells expressing the wild-type allele, similar to our observations in uncomplemented cells (Figure 6F).

Senataxin has been shown to localize at sites of transcription-replication conflicts and to travel with replication forks (Alzu et al., 2012).Here we asked whether Senataxin is recruited to R-loops in the absence of CtIP or XPG and found that depletion of either factor increases Senataxin occupancy at the inducible (Sγ3) locus (Figure 6G) by 3 to 5-fold, similar to our observations of Sen1 in yeast.

CtIP depletion leads to fewer DNA breaks after CPT treatment

Our results suggest that the CtIP and XPG nucleases help to either prevent R-loop formation in the genome or to resolve R-loops once they are formed. Since CtIP and XPG are both specific for 5ʹ flaps, we considered a model in which CtIP and XPG process 5ʹ flaps present in an R-loop structure (Figure 7). We hypothesize that this ssDNA cleavage event would result in extension and stabilization of the RNA-DNA hybrid, because the release of tension in one DNA strand would prevent spontaneous extrusion of the RNA. This conversion of the nascent lesion into an extended structure would also generate access for helicases to recognize and remove the RNA strand from the DNA. It is also possible that nuclease processing could convert the pre-lesion into double-strand breaks.

Proposed model of R-loop processing.

Polymerase stalling at sites of nicks, topoisomerase adducts (TopI adduct shown here on non-template strand), or other lesions generates a nascent R-loop structure (RNA shown in red). Cleavage of this nascent structure at one of 2 exposed 5ʹ flaps by nucleases, suggested in this work to be CtIP or XPG, can generate a stabilized, extended RNA-DNA hybrid because of the release of torsional constraint in the DNA template. Senataxin (or other helicases) preferentially access the RNA-DNA hybrid in this stabilized intermediate and remove the RNA, promoting reannealing of the displaced non-template strand and single-strand DNA repair. In this hypothetical model we do not know if one or both strands are cut, the timing or regulation of RNA polymerase removal, or the exact regulation of Senataxin activity at the lesion. A theoretical, alternative pathway of Sae2/CtIP-independent R-loop removal involving Senataxin is shown at right.

https://doi.org/10.7554/eLife.42733.016

One prediction of this model is that CtIP and XPG-depleted cells would exhibit fewer single-strand DNA breaks compared to normal cells, even though they exhibit higher levels of R-loops. To test this idea, we created DNA damage with CPT and measured single-strand DNA breaks with an alkaline comet assay. We found that exposure to CPT generated a marked increase in DNA breaks, and that transcription promotes these breaks, as pretreatment with DRB reduced the levels of breaks by ~75% in wild-type cells (Figure 8A). CtIP depletion led to a significant reduction in the accumulation of DNA breaks after CPT treatment, consistent with the proposed model that CtIP can facilitate the conversion of stalled transcription associated DNA lesions into DNA breaks.

CtIP and its nuclease activity promote ssDNA break formation.

(A) DNA breaks were quantified in wild-type and CtIP-depleted U2OS cells by alkaline comet assay. Cells were untreated (DMSO) or exposed to 5 µM CPT for 1 hr, with DRB (20 µM) or aphidicolin (2 µg/mL) pretreatment as indicated. Olive moments were calculated by analyzing at least 100 comets for each sample; error bars represent S.E.M. (B) Quantification of ssDNA breaks by alkaline comet assay was performed in wild-type, CtIP-depleted, XPG-depleted, or CtIP/XPG-depleted U2OS cells as in (A). (C) Quantification of ssDNA breaks by alkaline comet assay was performed in wild-type or CtIP-depleted U2OS cells complemented with wild-type eGFP-CtIP or nuclease-deficient NA/HA mutant CtIP as in (A). (D) A schematic representation of Ligation-mediated (LM)-PCR assay (top). Primer extension with a biotinylated primer (in red) from genomic DNA produces a double-stranded DNA end that is isolated with streptavidin and amplified by ligation-mediated PCR (asymmetric duplex and nested primers are presented in blue and green, respectively). LM-PCR assay measuring DNA breaks on the bottom strand of the RPL13A gene (bottom). DNA single-strand breaks were measured by LM-PCR at the endogenous RPL13A locus in wild-type or CtIP-depleted cells; n = 6, error bars represent S.E.M. * and **** denote p < 0.05 or 0.0001, respectively, using Student's two-tailed T test with comparisons as indicated.

https://doi.org/10.7554/eLife.42733.017

Next, we assessed the levels of single-strand DNA breaks in cells depleted for XPG, or for XPG and CtIP concurrently. In cells depleted for XPG there are fewer breaks after CPT treatment, and in cells depleted for both proteins, we observed no increase in breaks at all with CPT exposure (Figure 8B). This result does suggest that XPG and CtIP perform a function at transcription-associated lesions that results in an increase in single-strand breaks, likely their common function in promoting cleavage of 5ʹ flaps. To test this, we also examined breaks by comet assay in cells expressing the nuclease-deficient NA/HA CtIP mutant and found that in this case also, there was a large reduction in breaks formed with CPT exposure, very similar to the uncomplemented cells (Figure 8C).

To further validate this result at a specific locus in the genome, we returned to the RPL13A gene, where we observed high levels of R-loops in cells lacking CtIP using DRIP-qPCR (Figure 6). Here we used a modified LM-PCR assay (Hatchi et al., 2015) to measure single-strand DNA breaks in the genome. Primer extension from a sequence within the RPL13A locus converts any single-strand breaks present into single-ended double-strand breaks, then ligation-mediated PCR followed by qPCR quantitates the levels of these single-ended breaks (Figure 8D). Using this procedure, we did observe spontaneous single-strand breaks on the template strand of the RPL13A gene, and the level of breaks was reduced by 40% to 50% with depletion of CtIP, again consistent with the observation that single-strand breaks are reduced in cells lacking CtIP.

Discussion

In this study we demonstrate a functional relationship between the Sae2/CtIP enzyme and transcription-related DNA damage in eukaryotic cells, showing that the damage sensitivity of cells lacking Sae2/CtIP can be rescued by either Sen1/Senataxin or RNaseH overexpression. We further provide evidence for accumulation of stalled RNA polymerase complexes and RNA-DNA hybrids in cells deficient in Sae2/CtIP, with these lesions located at sites of highly expressed genes. These results suggest that Sae2/CtIP is not only a double-strand break resection factor, but also functions at transcription-associated lesions in eukaryotic cells.

In S. cerevisiae, the temperature-sensitive sen1-1 mutant exhibits synthetic lethality in combination with DNA repair mutants mre11, rad50, sgs1, and rad52, indicating a requirement for homologous recombination in the absence of SEN1 function (Mischo et al., 2011). Consistent with these results, we observe a synthetic sensitivity of sen1-1 with sae2 for survival of CPT and MMS exposure, similar to the sensitivity of sae2 rnh1 rnh201 strains. Conversely, overexpression of SEN1, RNH1, or PCF11 partially rescues sae2Δ survival of these DNA damaging agents.

From sen1 separation of function mutants we conclude that the helicase activity of Sen1 is important for the effect on survival of sae2Δ strains to DNA damage. Since we also observe stalling of RNA polymerase in sae2Δ strains, particularly with CPT treatment, one possible explanation is that Sae2 promotes the processing or resolution of transcription complexes stalled by Top1 conjugates and that SEN1 overexpression rescues survival in this context because of its known activities in removing RNA-DNA hybrids. Our observations that RNH1 overexpression has effects similar to SEN1 indicate that the removal of the ribonucleotides from DNA is an important aspect of the suppression. Considering that we observe Sen1 at sites of transcription-related lesions in sae2Δ strains, it is conceivable that Sen1 acts in a parallel pathway to that of Sae2, and overexpression of this pathway promotes RNA removal and thus survival (Figure 7). Alternatively, it is possible that Sen1 plays a role downstream of Sae2 and that in the absence of Sae2 function, Sen1 catalytic activity is less efficient even though its recruitment to damage sites appears to be unimpeded.

In human cells, overexpression of Senataxin also complements CtIP-depleted cells for CPT survival and for accumulation of R-loops at sites of laser-induced DNA damage. The extent of this suppression is remarkable and suggests that R-loops are a limiting factor in the recovery of CtIP-depleted cells following DNA damage. In mammalian cells, loss of CtIP is lethal whereas yeast strains lacking SAE2 have no growth deficit in the absence of DNA damage (McKee and Kleckner, 1997; Prinz et al., 1997; Chen et al., 2005; Makharashvili and Paull, 2015). This could be related to our observation that CtIP-depleted human cells exhibit higher levels of spontaneous R-loops than wild-type cells, even in the absence of exogenous damage, whereas sae2 null yeast strains only show RNA polymerase II pausing and R-loop accumulation with damage treatment.

CtIP and Sae2 exhibit an intrinsic endonuclease activity that is specific for 5ʹ flap structures and can be genetically separated from its ability to stimulate the nuclease of activity of Mre11 (Makharashvili et al., 2014; Wang et al., 2014; Arora et al., 2017). In human cells we observed that a CtIP mutant deficient in endonuclease activity failed to rescue CtIP-depleted cells for reduction of R-loops at laser damage sites or at genomic loci, thus we conclude that the action of CtIP at sites of stalled transcription involves its nuclease activity. Since we also show in this work that R-loop formation in CtIP-depleted cells resembles that of cells depleted of XPG, an endonuclease that also acts in nucleotide excision repair, it is possible that both enzymes target 5ʹ flap structures, of which there are at least two present in every R-loop structure (see model in Figure 7). Evidence for a DNA cleavage event induced by CtIP or XPG in response to CPT or other transcription stalling lesions comes from our analysis of CPT-treated cells using alkaline comet assays, and also by locus-specific quantitation of single-strand breaks. These results clearly show that there are fewer single-strand breaks after DNA damage in the absence of CtIP or XPG, even though the levels of R-loops in these cells are much higher. We do not know if there is a specificity for either template or non-template ssDNA breaks for these enzymes, but we do observe a reduction in template strand breaks at the RPL13A locus with depletion of CtIP.

Although R-loops as measured by RNaseH-binding and S9.6 antibody immunoprecipitation are significantly higher in CtIP or XPG-depleted cells, depletion of both factors simultaneously shows a very different result: R-loop levels similar to wild-type cells. We observed this phenomenon in untreated cells, in cells treated with CPT, and in cells with laser-induced DNA damage. To explain this finding we propose that, in the absence of both CtIP and XPG, unprocessed nascent R-loops and/or stalled RNA polymerase complexes accumulate (Figure 7). We propose that, due to the topological constraints on R-loop formation, these nascent R-loop structures are small and are not efficiently recognized by either the S9.6 antibody or by RNase H. We know that there are toxic lesions present in cells depleted of both CtIP and XPG since the survival of cells depleted for both factors is very poor (Figure 4—figure supplement 1). Alternatively, it is possible that the transcriptional patterns change in cells depleted of both CtiP and XPG and that R-loops are much lower in this mutant for this reason. We cannot exclude this possibility with the data currently available, but it is certainly testable in future experiments.

The idea that a nascent R-loop is topologically constrained and relatively inaccessible in the absence of strand breaks is consistent with previous work showing that a nick in the non-template strand greatly improves the efficiency of stable R-loop formation, because the non-template strand then does not compete with the RNA for hybridization to the template strand (Roy et al., 2010; Aguilera and Gómez-González, 2017). Here we postulate that transient stabilization of an RNA-DNA duplex could initiate R-loop formation but that extensive spreading and stabilization of the hybrid would require either secondary structure formation in the non-template strand or cleavage of one of the DNA strands, as previously shown (Roy et al., 2010). We propose that cleavage of one of the DNA strands, although seemingly detrimental in its stabilization of the RNA-DNA hybrid, likely facilitates removal of the hybrid by transcription-associated helicases such as Senataxin and/or Aquarius. Biochemical characterization of the helicase domain of yeast Sen1 showed that the enzyme requires single-stranded DNA adjacent to the hybrid for efficient loading prior to unwinding of the annealed RNA (Martin-Tumasz and Brow, 2015). This type of structure is not available in an R-loop in a topologically closed system without cleavage of a DNA strand or active unwinding of the DNA duplex adjacent to the RNA-DNA hybrid. In addition, a recent study found that treatment of chromatin with low levels of the single-strand DNA-specific S1 nuclease greatly improves the yield of R-loops immunoprecipitated by the S9.6 antibody (Wahba et al., 2016), consistent with this hypothesis.

There are also alternative hypotheses about the nature of the initiating lesion at genomic sites that require Sae2/CtIP. One possibility is that double-strand breaks form at sites of transcription-replication collisions, since we know that R-loops greatly increase the level of genomic instability at locations where they accumulate, and double-strand breaks have been implicated in these events (Richard and Manley, 2017; Wickramasinghe and Venkitaraman, 2016). Recent work demonstrates that R-loops form in human cells at DNA sites adjacent to induced double-strand breaks and that the Senataxin enzyme promotes their removal as well as Rad51 recruitment and homologous recombination (Cohen et al., 2018). In addition, a subset of R-loops in yeast were shown to induce Rad52-bound double-strand breaks, with the RNA-DNA hybrid located on one side of the break and resected DNA on the other (Costantino and Koshland, 2018). It is conceivable that CtIP and XPG promote the activity of Senataxin at such lesions, removing R-loops to promote resection. Lastly, double-strand breaks have been shown in some contexts to accompany high levels of transcriptional activity and appear to facilitate gene expression (Madabhushi et al., 2015); in this case TopII was implicated in formation of the breaks, but it is not clear if processing of the breaks occurs at these sites or is important for cell survival.

It is also possible that the initiating lesion is simply a stalled RNA polymerase, and that processing of this structure to create single-strand breaks first generates a transient R-loop as described above, but ultimately promotes the release of the polymerase and prevents the formation of stable, extensive R-loops. This idea that the polymerase is still present in the initiating lesion is supported by our data in yeast showing increased occupancy of RNAPII in sae2Δ strains that is reduced by Sen1 overexpression. PCF11 also reduces the sensitivity of sae2Δ strains to DNA damaging agents, and PCF11 is known for its activities in promoting transcription termination, although it also promotes Sen1 recruitment (Grzechnik et al., 2015).

In conclusion, we have presented evidence supporting a role for Sae2/CtIP in processing of transcription-related DNA lesions and show that release of R-loops from the genome is a limiting factor for the survival of Sae2/CtIP-deficient cells following DNA damage. This is perhaps related to the fact that CtIP was first identified through its association with the transcription regulator CtBP (Schaeper et al., 1998), and also interacts directly with the tumor suppressor BRCA1, which associates with transcription-related complexes (Makharashvili and Paull, 2015; Yu et al., 1998Chinnadurai, 2006). BRCA1 itself has been shown to localize to a subset of transcription termination regions and to regulate levels of RNA-DNA hybrids in human cells (Hatchi et al., 2015; Hill et al., 2014). In addition, XPG was recently found to be present in a complex with BRCA1 that is important for cellular responses to DNA damage that is separate from its roles in excision repair (Trego et al., 2016). Further studies will need to address whether the roles of CtIP and BRCA1 at transcription-associated lesions are functionally interdependent and whether Senataxin can also rescue BRCA1-deficient cells in the same manner as CtIP-depleted cells. Lastly, CtIP has been shown to have important repair functions in G1 phase cells (Barton et al., 2014; Biehs et al., 2017; Helmink et al., 2011; Quennet et al., 2011; Yun and Hiom, 2009); it will be important to determine if the R-loop processing functions indicated here play a role in the repair of transcription-associated damage even outside of S phase and whether this accounts for any of the essential functions of CtIP in mammals.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain
background (yeast)
yeast strains see supplementary file 1
Cell line (human)U2OSATCC
Cell line (human)HEK-293TATCC
Cell line (human)U2OS T-RexTM Flp-inJeff ParvinU2OS Flp-inInvitrogen tet-on system
Transfected
construct (human)
pTP3146this studyGFP-CtIPsee Materials and methods
Transfected construct (human)pTP3663this studyFlag-Bio-CtIPsee Materials and methods
Transfected construct (human)pTP3665this studyFlag-Bio-CtIP(N289A/H290A)see Materials
and methods
Transfected construct (human)pTP3531this studyC-term of Senataxin in pcDNA5/FRT/TOsee Materials
and methods
Transfected construct (human)pTP4195this studyPCF11 in pcDNA5/FRT/TOsee Materials and methods
Transfected construct (E. Coli)pTP3492this studywild-type RNaseH-mCherry in pcDNA5/FRT/TOsee Materials
and methods
Transfected constructpTP3494this studymCherry only in pcDNA5/FRT/TOsee Materials
and methods
Transfected construct (E. Coli)pTP3493this studyRNaseHI-D10R-E48R in pcDNA5/FRT/TOsee Materials and methods
Transfected construct (E. Coli)pTP3660this studyRNaseHI-D10R-
E48R in lentivirus vector
see Materials and methods
Transfected constructpRSITEP--U6Tet-(sh)-EF1-TetRep-2A-shRNA-CtIPCellectainducible shRNA for CtIPsee Materials and methods
Transfected constructpTP3703this studyinducible shRNA for XPGsee Materials
 and methods
Transfected constructpTP3677this studyinducible shRNA for SETXsee Materials
 and methods
Transfected constructpTP4195this studySγ3 sequence in pcDNA5/FRT/TOsee Materials
 and methods
Otherprimers see supplementary file 4

S. cerevisiae strains and expression constructs

For yeast strains see supplementary file 1. Genomic deletions were made with standard lithium chloride transformations and integrations (Adams et al., 1997) and were verified by PCR. Full-length SEN1, SSU72, and RTT103 were cloned into the 2μ plasmid pRS425 (Christianson et al., 1992) by fusion PCR to create pTP3500, pTP3249, and pTP3498, respectively. A pRS425 derivative containing PCF11 was a gift from Steve Hanes. Mutations in SEN1 were made in pTP3500 by Quikchange mutagenesis (Stratagene). The sen1-1 strain and corresponding wild-type strain were gifts from Nicholas Proudfoot. The HTB-tagged Rpb2 and Sen1 strains were gifts from Jeff Corden. The rnh1 rnh201 mutant strain was a gift from David Tollervey. A high-copy vector containing the wild-type SAE2 gene with a 2xFLAG tag in pRS425 (61)‘FLAG-SAE2/2μ’ was a gift from John Petrini, and was used for the SAE2 ChIP experiment.

Yeast camptothecin survival assay

Cells were grown to exponential phase (OD 0.5–0.6) and synchronized using alpha-factor for 3 hr at 30°C. Half of the cells were kept in alpha factor (G1), while the other half were washed and resuspended in fresh media (S). Previous studies have shown that all the cells enter S phase 30 min after the removal of alpha factor (Fu et al., 2014). Therefore 30 min after the release into fresh media, both G1 and S samples were treated with either 100 µM CPT or DMSO for two hours for an acute drug dose. At the end of the treatment, cells were washed and appropriate dilutions were plated on YPDA +glucose plates to obtain single colonies. Single colonies were counted after two days and survival efficiency was calculated as the number of colonies on the ‘+CPT’ plates divided by the number of colonies on the ‘no treatment’ plates. For thiolutin treatment, 15 min after the release into fresh media both G1 and S phase cells were treated with either DMSO or thiolutin (2.5 μg/mL final concentration). After another 15 min CPT or DMSO was added to the media at indicated concentration.

Chromatin immunoprecipitation in yeast

Sae2: Yeast cells containing a FLAG-Sae2 expression cassette on a high copy number 2μ plasmid were grown to exponential phase in 2 L of appropriate minimal media to OD600 = 0.5–0.6. The cells were centrifuged and resuspended in 50 ml fresh media (concentrated 40-fold). Yeast mating pheromone alpha-factor was added to final concentration of 10 μM and cells were synchronized for 4 hr at 30°C. Half of the cells were kept in alpha factor (G1), while the other half were washed and resuspended in fresh media (S). After the wash, both G1 and S phase cells were further divided into two and treated with 100 μM camptothecin or DMSO for 50 min. At the end of the drug treatment cells were crosslinked by addition of formaldehyde (1% final concentration) at RT for 25 min, followed by glycine (125 mM final concentration) at RT for 5–10 min. The cells were harvested, washed with water and flash frozen until further processing. Thus 2L of starting culture was divided into four samples per strain with approximately 500 OD cells per sample.

Each cell pellet was resuspended in 400 μl lysis buffer (50 mM HEPES, 150 mM NaCl, 1 mM EDTA, 1 mM DTT, 10% glycerol, 0.1% NP40, and protease inhibitors (Pierce # A32955; 1 tablet per 10 ml) and lysed using a bead beater (3 cycles of 45 s) in the presence of 400 μl 0.5 mm zirconia beads. The beads were washed with 2 × 500 μl of lysis buffer to collect a total of 1.5 ml cell extract. Sonication was performed with a Branson Digital Sonifier (5 cycles of 1 min each, with 10 s on, 10 s off at 28% amplitude). The cells were kept on ice for 5 min in between each cycle. The extract was cleared with high-speed centrifugation at 4°C for 30 min. A small sample was treated with proteinase K and RNaseA and separated by agarose gel to check for sonication efficiency (DNA size should be between 100–250 bp). The lysate was diluted to 10 ml with the lysis buffer. A 500 μl aliquot of the lysate was saved as the ‘Input’ sample. 50 μg Sigma FLAG-M2 antibody and 300 μl Pierce Protein A/G magnetic beads (prewashed with lysis buffer) were added to the cleared lysate. The cells were rotated at 4°C overnight. The following day, the beads were separated and washed 3 times each with wash-buffer 1 (25 mM Tris pH 8, 1 mM EDTA, 150 mM NaCl, 1% Triton, 100 μM camptothecin or DMSO equivalent), wash buffer 2 (25 mM Tris pH = 8, 1 mM EDTA, 500 mM NaCl, 1% Triton), wash buffer 3 (10 mM Tris pH 8, 1 mM EDTA, 1% Triton, 500 mM LiCl, 0.5% NP40) and wash buffer 4 (25 mM Tris pH 8, 1 mM EDTA, 1% Triton, 150 mM NaCl). 500 μl elution buffer (wash buffer 4 + 3X FLAG peptide) was added to the beads and kept shaking at 4°C for 2 hr. The beads were eluted with 100 μl elution buffer (wash buffer 4 + 2% SDS) and incubated at 65°C for 30 min. A second elution was done with 100 μl elution buffer similarly and combined for 150 μl total elution. The final elution and the Input sample (supplemented to 2% final SDS) were reverse cross-linked at 65°C overnight. Next day, all samples were diluted to SDS <0.5% and treated with 20 μg RNase A at 37°C 2 hr followed by 40 μg of proteinase K at 37°C 2 hr. The DNA was purified by phenol chloroform extractions followed by ethanol precipitation and stored at −20°C until further processing.

The DNA samples were gel purified to obtain a size range of 50–200 bp. The sequencing libraries were prepared for each sample using NEBNext DNA Library prep kit for Illumina (E6040S) and were sequenced and analyzed at the UT Austin GSAF. The bam files and bed files were visualized using Integrated Genome Viewer (iGV) and compared with saccer3 reference genome. Primary data is available at the NCBI GEO website under GSE122782.

RPB2: Yeast cells containing a His6-Tev-Biotin (HTB)-tagged RPB2 allele in the genome were used for this experiment. Cell pellets were prepared, lysed and sonicated similar to Sae2 ChIP, except the following lysis buffer was used - 25 mM Tris pH 7.5, 150 mM NaCl, 1 mM EDTA, 1 mM DTT, 10% glycerol, 0.1% NP40, 0.1% SDS, 1% Triton, 200 mM PMSF supplemented with protease inhibitors (Pierce # A32955; 1 tablet per 10 ml). After sonication the lysate was divided into three parts - 10% for Input, 45% for Rpb2 IP and 45% for mock IP. The IP was done with streptavidin linked M280 magnetic beads (Invitrogen) overnight and sheep anti-mouse M280 magnetic beads (Invitrogen) were used for the mock. The next day the beads were separated and washed 3 times with the following buffers - 1 (25mM Tris pH 7.5, 150 mM NaCl, 1 mM EDTA, 1% Triton, 0.1% SDS), 2 (25 mM Tris pH 7.5, 500 mM NaCl, 1 mM EDTA, 1% Triton, 0.1% SDS), 3 (10 mM Tris pH 8, 500 mM LiCl, 1 mM EDTA, 1% Triton, 0.5% NP40), and 4 (10mM Tris pH 8, 1 mM EDTA). For each wash, the beads were rotated for 5 min at RT. The fold enrichment over Input at different genomic loci was calculated using SYBR-Green based quantitative PCR. Samples were tested at various dilution factors to optimize a dilution factor for a CT value in the linear range. Then percentages of DNA enrichment of IP over the Input were calculated by using the following equation:

(100%*2^(CT(input)-CT(IP)-log(dilution_factor,2) - 100%*2^(CT(input)-CT(Mock IP)-log(dilution_factor,2)).

Then relative fold of enrichment was calculated by normalizing the percentage of DNA enrichment of IP of each group to WT cells without CPT treatment.

SEN1: Yeast cells containing a His6-Tev-Biotin (HTB)-tagged SEN1 allele in the genome were prepared, lysed and sonicated similar to RPB2 ChIP except that all samples were prepared with CPT exposure (100 μM camptothecin or DMSO for 50 min). The IP was performed with streptavidin linked M280 magnetic beads (Invitrogen). The fold enrichment over Input at different genomic loci was calculated using SYBR-Green based quantitative PCR. Samples were tested at various dilution factors to optimize a dilution factor for a CT value in the linear range. Then percentages of DNA enrichment of IP over the Input were calculated by using the following equation: (100%*2^(CT(input)-CT(IP)-log(dilution_factor,2)). The relative fold of enrichment was calculated by normalizing the percentage of DNA enrichment of IP of each group to WT cells.

DNA-RNA ImmunoPrecipitation (DRIP) in yeast

Yeast cells were grown as described for the Sae2 ChIP experiment, except there were no G2 cell samples and no formaldehyde crosslinking was done. DRIP was performed as previously described (Boguslawski et al., 1986); a detailed protocol is available on request. Briefly, 150–200 μg genomic DNA isolated using the Qiagen Genomic DNA kit (500G) was treated with S1 nuclease and precipitated in 130 μl TE. The DNA was sonicated using a Covaris sonicator, precipitated, and resuspended in 50 μl of nuclease-free water. Half of the sample was treated with RNaseH in vitro (Thermo Rnase H, 5 units per 10 μg DNA), overnight at 65°C. Then 350 μl of FA buffer (1% Triton X-100, 0.1% sodium deoxycholate, 0.1% SDS, 50 mM HEPES, 150 mM NaCl, 1 mM EDTA) was added to each DNA sample, and incubated for 90 min with 5 μg of S9.6 antibody prebound to magnetic protein A beads. Beads were then washed and the DNA eluted as described above. %RNA–DNA hybrid amounts were quantified using Sybr-Green based quantitative PCRs on DNA samples from DRIP and Input DNA. Q-PCR reactions were performed on ViiA7 Real-Time PCR System (ABI) under standard thermal cycling conditions for 40 cycles. Results were analyzed with ViiA7 software (ABI). For each sample, fold enrichment over Input was calculated by the following equation: Fold enrichment over input = 2^(CtInput - Log(dilution factor,2) - CtDRIP)

Primer sequences used in this study were adapted from (Alzu et al., 2012; Grzechnik et al., 2015; El Hage et al., 2014) and are listed in Supplementary file 4. A mock IP with empty beads was done for each sample to control for non-specific binding and enrichment was calculated in the same way as the DRIP sample.

Statistical analysis of Sae2-ChIP-transcription overlap

For each sample, overlap between peaks identified from ChIP-seq data and the top 10% of highly transcribed genes in yeast (supplementary file 2) (Nagalakshmi et al., 2008; Pelechano et al., 2010; Miura et al., 2008) was assessed using Bedtools (Quinlan and Hall, 2010) and the fraction of peaks for which an overlap was detected was recorded. Also for each sample a background null distribution of overlap rates was estimated by repeatedly sampling a random set of coding sequences equal in number to those in the top 10% list from the Saccharomyces cerevisiae genome (equivalent to selection of top ORFs after random permutation) and then locating overlaps using bedtools. By comparing the overlap fraction to the estimated null distribution, we constructed 99% confidence intervals for the permutation test p-values (Ernst, 2004) of the null hypothesis that the overlap between ChIP-seq peaks and the top 10% of highly transcribed genes was equal to the rate at which the peaks overlapped randomly chosen coding sequences.

Mammalian cell culture: Human U2OS and HEK-293T cells were grown and maintained in tetracycline-free DMEM containing 10% FBS media in a humidified 37°C incubator in the presence of 5% CO2. All cell lines were treated and maintained in plasmocin (InVivoGen) to ensure no mycoplasma contamination.

Mammalian expression constructs

Invitrogen Gateway pENTR223 donor vector for hSenataxin(∆1–1850) was obtained from DNASU (#HsCD00505781), and cloned into pcDNA5/FRT/TO (ThermoFisher) vector to make pTP3531. shRNA CtIP was custom-made by Cellecta (pRSITEP--U6Tet-(sh)-EF1-TetRep-2A-shRNA-CtIP) and includes the shRNA expression cassette 5ʹ-GAGCAGACCTTTCTTAGTATAGTTAATATTCATAGCTATACTGAGAAAGG

TCTGCTCTTTT-3 ʹ. Dox-inducible elements were removed from pRSITEP--U6Tet-(sh)-EF1-TetRep-2A-shRNA-CtIP shRNA CtIP(-Dox) (pTP3914) using Q5 Site-Directed Mutagenesis (NEB, #E0554S). The N-terminal fusion of eGFP with CtIP (eGFP-CtIP) ORF was amplified from pC1-eGFP-CtIP (a generous gift from Steven Jackson), and cloned into pcDNA5/FRT/TO to make pTP3146. The A206K mutation in eGFP was made to prevent eGFP dimerization, and shRNA resistance mutations introduced to generate pTP3148. pcDNA5-flag-bio-CtIP(wt) (containing N-terminal Flag and biotinylation signal sequences) (pTP3663) was made by Q5 Site-Directed Mutagenesis to remove eGFP, and insert Flag and biotinylation signal sequences. pcDNA5-flag-bio-CtIP(N289A/H290A) (pTP3665) was made using QuikChange II Site-Directed Mutagenesis (Agilent Technologies). shRNA SETX1 (pRSITEP--U6Tet-(sh)-EF1-TetRep-2A-HYGRO) (pTP3677) and shRNA XPG (pRSITEP--U6Tet-(sh)-EF1-TetRep-2A-HYGRO) (pTP3703) were made from the pRSITEP--U6Tet-(sh)-EF1-TetRep-2A-shRNA-CtIP construct (Cellecta) using Q5 Site-Directed Mutagenesis, with the shRNA cassettes 5ʹ-GCCAGATCGTATACAATTATAGTTAATATTCATAGCTATAATTGTATACGATCTGGCTTTT-3 ʹ and 5ʹ-GAACGCACCTGCTGCTGTAGAGTTAATATTCATAGCTCTACAGCAGCAGGTGCGTTCTTTT-3 ʹ, respectively. pcDNA5 with with wild-type RnaseHI (rnhA from E. coli) containing an NLS and fused to mCherry (pTP3492) was generated from pcDNA5/FRT/TO (Invitrogen) and pICE-RNaseHI-mCherry (Addgene 60365, gift from Patrick Calsou). pcDNA5 with NLS-mCherry (pTP3494) was generated from pcDNA5/FRT/TO (invitrogen) and pICE-mCherry (Addgene # 60364). pcDNA5-RNaseHI-D10R-E48R-NLS-mCherry (pTP3493) was cloned using pcDNA5/FRO/TO and pICE-RNaseHID10R-E48R-NLS-mCherry (a gift from Patrick Calsou, Addgene # 60367 (Britton et al., 2014)). pLenti-PGK-RNaseHID10R-E48R-NLS-mCherry (pTP3660) was cloned using pLenti PGK GFP Blast (w510-5) which was a gift from Eric Campeau and Paul Kaufman (Addgene plasmid #19069 [Campeau et al., 2009]) and the RNaseHID10R-E48R-NLS-mCherry fragment from pICE-RNaseHID10R-E48R-NLS-mCherry. pBluescript-Sγ3 × 12 (pTW-121) was a generous gift from Michael Lieber. pcDNA5/FRT/TO-Sγ3 × 12 (pTP4195) was cloned using pcDNA5/FRT/TO and the Sγ3 region from pTW-121. pcDNA5/FRT/TO-hPCF11 (pTP4195) was cloned using pcDNA5/FRT/TO and the hPCF11 ORF containing plasmid, obtained from Kazusa (ORK06290). All constructs and mutations were confirmed by DNA sequencing. Details of plasmid construction available upon request.

Clonogenic survival assays

U2OS cells were harvested by trypsinization (0.25% trypsin; Life Technologies) and counted using Scepter (Millipore Sigma). 1,500 cells were seeded per 10 cm cell culture dish, and were allowed to adhere to the bottom of the plate for 36 hr. For experiments with tet-inducible CtIP shRNA, all cells were exposed to doxycycline (1 µg/mL) during seeding and gene depletion and/or over-expression and throughout the experimental course. After 36 hours cells were treated CPT for 1 hr, the CPT-containing media was replaced with fresh media, and cell recovery was allowed for 10 days. Colonies were stained with crystal violet (0.05% in 20% ethanol), destained with water, and counted using a scanner and Image J.

RNaseHD10R-E48R-mCherry Laser Micro-irradiation

U2OS cells were seeded in glass bottom petri dishes (35 × 10 mm, 22 mm glass, WillCo-dish, HBST-3522), and grown in DMEM/10% FBS media in the presence of 1 µg/mL doxycycline. After 36 hr, media was replaced with media containing 10 µM BrdU. After an additional 36 hr, laser micro-irradiation was performed with an inverted confocal microscope (FV1000; Olympus) equipped with a CO2 module and a 37°C heating chamber. A preselected spot within the nucleus was microirradiated with 20 iterations of a 405 nm laser with 100% power to generate localized DNA damage. Then, time-lapse images were acquired using a red laser at 1 min time intervals for 10 min. The fluorescence intensity of mCherry signal at the laser microirradiated sites was measured using the microscope’s software. Data collected from >10 cells were normalized to their initial intensity and plotted against time.

RNaseHD10R-E48R-mCherry FACS

U2OS cells were grown in DMEM/10% FBS media in the presence of 1 µg/mL doxycyclin in 10 cm dishes. After 3 days, the cells were harvested by trypsinization, rinsed in 5 mL cold PBS with Ca2+ (0.9 mM) and Mg2+ (0.5 mM), and centrifuged at 1000 g for 3 min. Unbound RNaseHD10R-E48R-mCherry was extracted with 1 mL Triton X-100 buffer (0.5% Triton X-100, 20 mM Hepes-KOH (pH 7.9), 50 mM NaCl, 3 mM MgCl2, 300 mM Sucrose) at 4°C for exactly 2 min and at 1300 g for 3 min. Cells were then rinsed twice in PBS at RT and fixed in 3.7% paraformaldehyde in PBS for 10 min at RT, rinsed twice in PBS at RT again, and stained with FxCycleTM FarRed stain (200 nM in PBS with 100 µg/mL RNaseA). Cells were kept in the staining solution at 4°C protected from light. The samples were analyzed in a flow cytometer without washing, using 633/5 nm excitation and emission collected in a 660/20 band pass or equivalent.

S9.6 immunostaining

U2OS cells were seeded into 8-well Nunc Lab-Tek II Chamber Slides (Nalge Nunc International, #154534) 48 hr before experiments. Prior to immunostaining, cells were washed with PBS, and preextracted with incubation in CSK buffer (10 mM PIPES, pH 7.0, 100 mM NaCl, 300 mM sucrose, and 3 mM MgCl2, 0.7% Triton X-100) twice for 3 min at room temperature. After preextraction, cells were washed with PBS and fixed with 2% paraformaldehyde for 10 min. Cells were then permeabilized for 5 min with PBS/0.2% Triton X-100, washed with PBS, and blocked with PBS/0.1% Tween 20 (PBS-T) containing 5% BSA. For immunostaining cells were incubated with primary antibodies (S9.6 and nucleolin) in PBS/5% BSA overnight, then washed with PBS-T and incubated with appropriate secondary antibodies coupled to Alexa Fluor 488 or 594 fluorophores (Life Technologies) in PBS-T/5% BSA. After washes in PBS-T and PBS, coverslips were incubated 30 min with 2 µg/ml DAPI in PBS. After washes in PBS, coverslips were rinsed with water and mounted on glass slides using ProLong Gold (Life Technologies).

DNA-RNA ImmunoPrecipitation (DRIP) in mammalian cells

U2OS cells (one 150 mm dish per biological replicate) were harvested by trypsinization (0.25% trypsin; Life Technologies) and pelleted at 1,000 g for 5 min in 15 mL conical tubes. Cell pellets were washed with PBS and divided for RNA, DRIP or LM-PCR harvests. Cell pellets for DRIP were resuspended in 5 mL of PBS supplemented with 0.5% SDS, and digested with 2 mg of Proteinase K (GoldBio) at 37°C overnight. Cell lysates were then extracted once with 1 vol of equilibrated phenol pH 8 and twice with 1 vol of chloroform. DNA was precipitated with 1 vol of isopropanol, and spun down at 6,500 g for 15 min. The DNA pellet was transferred to a 1.7 mL eppendorf tube, washed with 1 mL of 70% ethanol, and rehydrated in 0.1x TE (1 mM Tris-HCl pH 8.0, 0.1 mM EDTA). Nucleic acids were digested using a restriction enzyme cocktail (20 units each of EcoRI, HindIII, BsrGI, XbaI) (New England Biolabs) overnight at 37°C in 1x NEBuffer 2.1. DNA concentration was measured using Qubit dsDNA HS kit (Thermo). For experiments with RNaseH treatment in vitro, RNaseH (Thermo) was added at a concentration of 5 units per 10 µg DNA and incubated overnight at 37°C. 10 µg of digested nucleic acids were then diluted in 1 mL final DRIP buffer (10 mM sodium phosphate, 140 mM sodium chloride, 0.05% Triton X-100) and 100 µg of S9.6 antibody (purified from ATCC HB-8730) and incubated at 4°C overnight. This and all wash steps were performed on a rotisserie mixer. 30 µL of Pierce Protein A/G Magnetic Beads (Fisher Scientific, 88803) was added and incubated for additional 2 hr, followed by washing three times with 1 mL of 1x IP buffer for 10 min at room temperature with constant rotation. After the final wash, the agarose slurry was resuspended in 100 µL of TE + 0.5% SDS 1 mg of Proteinase K for >1 hr at 37°C. 10 µL of 7.5 M Ammonium Acetate, 1 µg of glycogen, and 400 µL of 100% ice-cold Ethanol were added to the digested DRIP samples, and kept at −20°C for at least 2 hr (to overnight) to precipitate the immuno-precipitated material. The pellet was collected by centrifugation in a microcentrifuge at maximum speed for 30 min at 4°C, washed with cold 70% ethanol, air-dried, and resuspended in 100 µL of 0.1x TE. We used 10 µL reactions with PowerUp sybr green master mix (Applied Biosystems) for qPCR amplification of genomic loci (see Supplementary file 4). Reactions were incubated with the following program on a Viia 7 System cycler (Life Technologies): 50°C 2 min, 95°C 10 min, 40 cycles of 95°C 15 s, 64°C 1 min, followed by a melt curve: 95°C 15 s, 60°C 1 min, 0.05 °C/sec to 95°C 15 s. For each DRIP sample, linear range of amplification was identified by testing a wide range of dilutions. Fold enrichment for a given locus was calculated using the 2-ΔΔCT method (Schmittgen and Livak, 2008), and then normalizing the samples to the measurements of the wild-type results.

RT-qPCR

U2OS cells (one 150 mm dish per biological replicate) were harvested by trypsinization (0.25% trypsin; Life Technologies) and pelleted at 1,000 g for 5 min in 15 mL conical tubes. Cell pellets were washed with PBS (Life Technologies) and divided for RNA, DRIP or LM-PCR harvests. RNA was either purified and retro-transcribed using RNA purification (Qiagen) and SuperScript IV Reverse Transcriptase (Thermo #8090050) kits, respectively, or using Fast Cells-to-CT kit (Thermo #4399003). qPCR was done using the same settings as those for DRIP-qPCR and LM-PCR methods, and GAPDH used as a reference gene.

mRNA-seq

U2OS cells (one 150 mm dish per biological replicate) were harvested by trypsinization and pelleted at 1,000 RCF for 5 min in 15 mL Falcon tubes. mRNA was purified using Qiagen RNA purification kit, and mRNA was isolated using AMPure XP kit (Beckman Coulter, #A63880). mRNA-seq libraries were prepared with the NEBNext Multiplex Small RNA Library Prep Set for Illumina (#E7300S) according to manufacturer instructions. The library sequencing and analysis were done at New York Genome Center.

Statistical analysis of mRNA-seq DRIP data overlap

For each statistical comparison, overlap between the top 100 genes as ranked by DESeq differential expression p-value and DRIPc-seq peaks from GEO dataset GSE70189 (Sanz 2016) was assessed using bedtools (Quinlan and Hall, 2010). For each comparison, we calculated the percentage of the top 100 genes for which such an overlap was found. These percentages were compared to a null distribution for overlap rates estimated using a permutation testing approach (Ernst, 2004) in which we repeatedly selected 100 genes at random from the list of all genes tested by DESeq (equivalent to selection of top 100 genes after randomly permuting DESeq p-values) and applied bedtools to calculate the DRIPc-seq overlap rate in the same manner. Using this approach we estimated 99% confidence intervals for the permutation test p-values of the null hypothesis that the genes showing the most evidence of differential expression overlapped the peak regions at the same rate as randomly selected genes.

Senataxin ChIP-qPCR

U2OS cells (one 150 mm dish per biological replicate) were crosslinked by addition of formaldehyde (1% final concentration) at RT for 15 min, followed by glycine (125 mM final concentration) at RT for 5 min. Cells were washed twice with cold PBS and harvested by scraping. Then cells were pelleted at 3,000 rpm for 30 min in 15 mL Falcon tubes. Each cell pellet was resuspended in 2 mL of RIPA buffer (50 mM Tris pH8, 150 mM NaCl, 2 mM EDTA, 0.1% SDS, 0.5% Sodium Deoxycholate, 1% NP40, and protease inhibitors (Pierce # A32955; 1 tablet per 10 mL)) and sonicated with a Bioruptor sonicator for 15–30 min at high power 10 s on and 10 s off. The extract was cleared with 13,000 rpm centrifugation at 4°C for 30 s and the supernatant was transferred to new tube. A small sample was treated with 1% SDS, 100 mM NaHCO3 and RNaseA and purified by Qiagen PCR purification kit to check DNA concentration with NanoDrop 2000 (Thermofisher). The chromatin was diluted to 50 μg/mL with RIPA buffer. A 50 μL aliquot of the lysate was saved as the ‘Input’ sample, and 1 mL of the lysate was used per immunoprecipitation sample. 2 μg of anti-SETX antibody (Novus Biologicals, NB100-57542) was added to all immunoprecipitation samples except the beads-only control and immunoprecipitated overnight with rotation at 4°C. 20 µL of Pierce Protein A/G Magnetic Beads (Fisher Scientific) was added and incubated for additional 2 hr, followed by washing 3 times each with wash buffer 1 (20 mM Tris pH8, 2 mM EDTA, 150 mM NaCl, 1% Triton, 0.1% SDS), wash buffer 2 (20 mM Tris pH8, 2 mM EDTA, 500 mM NaCl, 1% Triton, 0.1% SDS), wash buffer 3 (10 mM Tris pH8, 1 mM EDTA, 1% Sodium Deoxycholate, 250 mM LiCl, 1% NP40) and TE buffer (10 mM Tris pH8, 0.1 mM EDTA). 125 μl elution buffer (1% SDS, 100 mM NaHCO3) was added to the beads and kept shaking at 30°C for 30 min. The beads were then pelleted and the supernatant was transferred into fresh tube. The tube containing the supernatant was kept shaking overnight at 65°C. The DNA samples were purified (Qiagen PCR purification kit) and eluted with 50 μl of water (heated at 50°C and incubated for 30 min on column before spinning).

We used 10 µl reactions with PowerUp sybr green master mix (Applied Biosystems) for qPCR amplification of genomic loci (see Supplementary file 4). Reactions were incubated with the following program on a Viia 7 System (Life Technologies): 50°C 2 min, 95°C 10 min, 40 cycles of 95°C 15 s, 64°C 1 min, followed by a melt curve: 95°C 15 s, 60°C 1 min, 0.05 °C/second to 95°C 15 s. For each ChIP sample, linear range of amplification was identified by testing a wide range of dilutions. Fold enrichment for a given locus was calculated using the 2-ΔΔCT method (Schmittgen and Livak, 2008), and then normalizing the samples to the measurements of the control.

Ligation-mediated PCR (LM-PCR)

U2OS cells (one 150 mm dish per biological replicate) were harvested by trypsinization and pelleted at 1,000 g for 5 min in 15 mL conical tubes. Cell pellets were washed with PBS and divided for RNA, DRIP or LM-PCR harvests. Genomic DNA (gDNA) was purified using genomic DNA preparation kit (Zymo Research Quick-gDNA MiniPrep - Capped column, Genesee Scientific, 11-317AC) and gDNA concentration was determined using Nanodrop. 50 µL primer extension mix contained: 5 µL of 10X polymerase buffer (NEB, supplied with Deepvent(-Exo) enzyme), 4 µL MgSO4 (100 mM), 1 µL of Deepvent(-Exo) (NEB), 1 µL NTP mix (0.5 mM each final), 0.5 µL biotinylated primers (stock concentration 100 µM), and 1 µg of gDNA. Primer extension was done in a thermocycler in one round of primer extension: 15 min at 95°C, 30 s at 60°C, 5 min at 72°C. Control solution was made by dilution of 1 µg genomic DNA in 0.1x TE. Primer extension products were ligated to the phosphorylated asymmetric adaptor duplex overnight (oligonucleotides were phosphorylated with T4 polynucleotide kinase at 37°C for 3–4 hr, purified with a nucleotide removal kit (Qiagen), and annealed with boiling and slow cooling in the presence of 0.1 M NaCl). Ligation reactions were mixed with 30 µL of KilobaseBinder (Invitrogen) magnetic beads prepared according to the manufacturer’s protocol, total volume was adjusted to 100 µL, and incubated with genomic DNA samples overnight. Washes were performed on a magnetic stand: 3 × 10 min washing with wash buffer (50 mM Tris, pH 8, 0.1% (wt/vol) SDS and 150 mM NaCl), then 10 min washing with 0.1x TE. After the 0.1x TE wash, the beads were resuspended in 100 µL of 0.1x TE and 10 µL used for nested PCR. Nested PCR reaction contained: 5 µL of 10X polymerase buffer (NEB, supplied with Deepvent(-Exo) enzme), 4 µL MgSO4 (100 mM), 1 µL of Deepvent(-Exo), 1 µL NTP mix (0.5 mM each final), 1 µL each nested primers (stock concentration 100 µM), and 10 µL of beads. Nested PCR was done in a thermocycle with the following amplification steps: 1) one step of total denaturation: 15 min at 95°C; 2) 15 steps of amplification: 30 s at 95°C 30 s at 60°C, 5 min at 72°C; and 3) one step of extension: 5 min at 72°C. Nested reactions were diluted 50-fold in 0.1x TE, and serial dilutions were prepared to determine linear range of amplification. Fold enrichment for a given locus was calculated using the comparative Ct method, and then normalizing the samples to the measurements of the wild-type results.

Comet assay

U2OS cells were grown in DMEM/10% FBS media in the presence of 1 µg/mL doxycyclin in 6-well plates at a very sparse seeding density. After 3 days, the cells were treated with DNA damaging agents, harvested by trypsinization, and rinsed in 1 mL cold PBS. Olive moments of damaged DNA were measured using OxiSelect Comet Assay Kit (3-Well Slides) (Cellbiolabs, #STA-350).

References

  1. 1
    Methods in Yeast Genetics
    1. A Adams
    2. DE Gottschling
    3. C Kaiser
    (1997)
    Cold Spring Harbor Laboratory Press.
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20
  21. 21
  22. 22
  23. 23
  24. 24
  25. 25
  26. 26
  27. 27
  28. 28
  29. 29
  30. 30
  31. 31
  32. 32
  33. 33
  34. 34
  35. 35
    Detection of DNA-RNA Hybrids in Vivo. in Genome Instability
    1. M García-Rubio
    2. S Barroso
    3. A Aguilera
    (2018)
    M Muzi-Falconi, G. W Brown, editors. New York: Springer.
  36. 36
  37. 37
  38. 38
  39. 39
  40. 40
  41. 41
  42. 42
  43. 43
  44. 44
  45. 45
  46. 46
  47. 47
  48. 48
  49. 49
  50. 50
  51. 51
  52. 52
  53. 53
  54. 54
    A general method for identifying recessive diploid-specific mutations in Saccharomyces cerevisiae, its application to the isolation of mutants blocked at intermediate stages of meiotic prophase and characterization of a new gene SAE2
    1. AH McKee
    2. N Kleckner
    (1997)
    Genetics 146:797–816.
  55. 55
  56. 56
  57. 57
  58. 58
  59. 59
  60. 60
  61. 61
  62. 62
  63. 63
  64. 64
  65. 65
  66. 66
  67. 67
  68. 68
  69. 69
  70. 70
    Isolation of COM1, a new gene required to complete meiotic double-strand break-induced recombination in Saccharomyces cerevisiae
    1. S Prinz
    2. A Amon
    3. F Klein
    (1997)
    Genetics 146:781–795.
  71. 71
  72. 72
  73. 73
  74. 74
  75. 75
  76. 76
  77. 77
  78. 78
  79. 79
  80. 80
  81. 81
  82. 82
  83. 83
  84. 84
  85. 85
  86. 86
  87. 87
  88. 88
  89. 89
  90. 90
  91. 91
  92. 92
  93. 93
  94. 94
  95. 95
  96. 96
  97. 97
  98. 98
  99. 99
  100. 100
  101. 101
  102. 102
  103. 103
  104. 104

Decision letter

  1. Andrés Aguilera
    Reviewing Editor; CABIMER, Universidad de Sevilla, Spain
  2. Jessica K Tyler
    Senior Editor; Weill Cornell Medicine, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

[Editors’ note: a previous version of this study was rejected after peer review, but the authors submitted for reconsideration. The first decision letter after peer review is shown below.]

Thank you for submitting your work entitled "Sae2/CtIP prevents R-loop accumulation in eukaryotic cells" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife at this moment. We believe that this is very interesting work with exciting results, but it needs further analysis to support the model. However, we would be happy to consider a resubmission of your work, if you can appropriately respond to the reviewers.

As I said, this is an interesting study performed in yeast and human cells to show that CtIP is involved in resolving R-loops in conjunction with XPG. By first observing the ability of Sen1 DNA-RNA helicase, involved in transcription termination, to suppress some of the phenotypes of sae2∆ mutants such as CPT sensitivity and R-loop accumulation in the rDNA, authors conclude that yeast Sae2 is important for R-loop removal. They go on to show that Sae2 is found at sites of high transcription, especially upon treatment with CPT in S phase, and that its deletion leads to transcription-dependent damage sensitivity and Pol II stalling following CPT. Notably, most of these findings also apply for CtIP function in human cells. CtIP depletion triggers sensitivity to CPT that is rescued by Senataxin (the Sen1 human ortholog) overexpression. They find that RNA-DNA hybrids accumulate upon CTIP-loss or XPG-loss at laser-induced damage, based on binding of an mCherry-RNaseH sensor. Moreover, CtIP depletion decreases ssDNA break, suggesting that, as XPG, CtIP contributes to R-loop dissolution by generating a ssDNA break promoting the activity of senataxin and other hybrids helicases. The authors show that CtIP and XPG reduce breaks formed by CPT using both comet assays and LM-PCR. The most puzzling data came from combining both XPG and CtIP depletion, since, although their co-depletion completely abolishes the generation of an ssDNA break, no R-loop accumulate in these conditions. The authors interpret these data, as a lack of R-loop extension in these conditions, that would make them undetectable. Together, these studies lead the authors to propose that XPG and CtIP work in a redundant manner to process R-loops by generating a break at the R-loop site and allowing access of SETX to the hybrids for hybrid resolution. They propose a model by which CtIP would promote cleavage of Flap structures as a step to resolve R-loops.

The work is very interesting and exciting and provides an intriguing model and important function of CTIP to understand. However, additional results are needed to test the model and rule out other possibilities. Several experiments require additional control; all studies with S9.6 should provide the control with RNaseH treatment in vitro to show that the signal is removed (S9.6 also recognizes dsRNA and data must assure that the signal detected corresponds to RNA-DNA hybrid). Although authors use Sen1 to remove R-loops, the data suggest that the terminator function of Sen1 has a role in the suppression of the CPT sensitivity and by extension the R-loops. In addition, the yeast data do not clearly support that RNAPII transcription is the major cause of R-loops. The authors are unable to show hybrids in RNAPII genes, but only in rDNA regions. Of particular note, the authors did not sufficiently establish the proposed order of events which place CtIP and XPG upstream of SETX. Is CtIP or XPG needed for Sen1/SETX to bind the DNA at the sites of hybrid formation, tested using the RNaseH sensor and ChIP assays? This would be one prediction of the model if nuclease processing is needed to generate access for Sen1/SETX. Could indeed the authors rule out that SETX and CtIP are not simply acting to reduce the same hybrid structures (albeit in different ways)? In summary, as it stands the authors need more data to substantiate their conclusions.

Reviewer #1:

This is an interesting study performed in yeast and human cells to show that CtIP is involved in resolving R-loops. By first observing the ability of Sen1 DNA-RNA helicase to suppress some of the phenotypes of sae2∆ mutants such as CPT sensitivity and R-loops detected by a specific antibody, authors conclude that yeast Sae2 is important for R-loop removal. The study is extended to human cells, in which using a parallel approach the authors conclude that CtIP have similar role. In this case, they use laser micro-irradiation and siXPG cells, which allow the authors to propose a model by which CtIP would be able to cleave Flap structures as a step to resolve R-loops. This is a new and a priori unexpected involvement of a DSB processing factor in R-loop removal that merits being considered for publication. However, the study has a number of issues that need to be resolved before it can be published. There are three important points that need to be solved first, apart from the essential experiments suggested below.

- All studies with S9.6, except one in Figure 6A, did not provide the control with RNase H1 to show that the signal is removed. It is known that S9.6 also recognizes dsRNA and it is not possible to make conclusions with this antibody without removing the signal with RNase H1.

- Although authors use Sen1 to remove R-loops, the data suggest that the terminator function of Sen1 has a role in the suppression of the CPT sensitivity and by extension the R-loops. It is necessary to show that RNH1 overexpression, not just Sen1/SETX also suppresses the CPT phenotype in yeast and that of micro-irradiated human cells.

- Authors propose that CtIP/Sae2 may have a new FLAP endonucleolytic function similar to XPG. This conclusion is based on the similar phenotypes observed for CtIP and XPG-depleted cells. However, a similar phenotype may be produced by different mechanisms, and R-loop dynamics may respond to many different factors. The in vivo data showing that in the double depletion in human cells they have equal amount of R-loops than the simple is inconsistent with a model implying that an ssDNA nick (as that caused by S1 in vitro experiment) stabilizes R-loops. The in vivo data do not seem to support the model proposed since if CtIP is not able to cleaves the FLAP structure, R-loops would not be stabilized. In this context, the S1 experiment is really confusing and unnecessary in this study (the Lieber lab already showed in the past that a nick in the DNA increases the accumulation of R-loops).

- Provided the know function of CtIP in DSB resection and the relevance of transcription-replication collisions as a way to produce stalled and collapsed forks and considering the possibility that it could also lead to fork reversal generating a one-ended DSB-like structure susceptible of being resected by CtIP to restart the fork, it may be possible that the inability of CtIP to act at broken or reversal replication forks stalled in front of an R-loop lead to an accumulation of these hybrids as structures causing the lethality in CPT or microirradiation and Sae2/CtIP cells. Consequently, it is necessary to show that in vitro CtIP has the suggested activity. The assay done with S1 should indeed be performed with CtIP.

In Figure 1, authors should show overexpression of RNaseH to demonstrate that R-loops are the cause of CPT sensitivity in sae2∆ strain.

Since the CPT sensitivity phenotype is observed in S-phase, it would be important to address if Sen1 and RNaseH1 rescue sae2∆ sensitivity to HU. Could it be transcription/replication collisions not R-loop dependent?

A DRIP-qPCR analysis of some of the genes with increased Sae2 recruitment in the ChIP-seq to validate the data.

In Figure 1E, the control DRIP samples with RNaseH1 treatment is not shown.

No statistical analysis is supplied for any of the yeast tables. This is essential in Figure 3A, where authors claim that o/e SEN1 reduces RNA Pol II accumulation. Again, an RNaseH1 o/e should be included.

In Figure 4A, authors should show overexpression of RNaseH as a way to demonstrate that R-loops are the cause of CPT sensitivity in cells depleted of CtIP.

Immunofluorescences in Figure 5C should have RNase H -treated cells as control. Image contrast could be improved and also show the channels separately.

How do authors explain the reduction on R-loops compare to siC levels when both nucleases CtIP and XPG are missing? This is odd.

Regarding the ssDNA breaks assay, due to the CtIP role in resection it is expected to have less breaks after DNA damage. Authors could perform the assay in a background known to increase R-loops, such as sen1 or rnh1 rnh2 and see if CtIP depletion reduces the R-loop-dependent DNA breaks.

The yeast data do not seem to support that RNAPII transcription is the major cause of R-loops. The authors are unable to show hybrids in RNAPII genes, but only in rDNA regions. Indeed, it makes sense from the data that CPT, that it is the rDNA region, in which the Tollervey lab has shown the relevance of Top1 to prevent R-loop formation, where the major intermediate leading to lethality may accumulate after CPT. Is there any data showing an involvement of Sen1 in RNAPI transcription termination? This needs to be considered, since at the end it is not really clear which function of Sen1 is able to suppress the sensitivity to CPT of sae2∆ cells.

The enrichment of Sae2 at 176 sites of transcription in S phase may not necessarily related with R-loops. Authors do not show whether such enrichment is reduced by RNase H overexpression. At least should be done by DRIP-qPCR to validate the data using RNase H.

In the genome-wide analysis, the fact that RNAPII is found at high levels at sites previously described to from R-loops does not implies that R-loops are accumulated in sae2∆ strains. It is required to reduce the signal by overexpressing RNH1. Overexpression of Sen1 produces a reduction in signal, but this may be due to the terminator function of Sen1. For this reason, authors need to revert the phenotype with a protein not involved in termination, but just in R-loop removal, such as RNH1.

I am not sure what the results of Figure 4B really says. If CPT causes breaks, it should not be surprising that CtIP increases the sensitivity. Provided the impact of transcription in collisions or increase in damage by other ways, the action of DRB should not be surprising. However, the reduction of the sensitivity phenotype is very small. Results could be repeated using another inhibitor of transcription such as α-amanitin.

In Figure 5 it is necessary to show that all signals are reduced by RNase H.

Reviewer #2:

In this manuscript, Makharashvili et al., report a novel function for Sae2/CtIP in both yeast and human cells: They propose that this endonuclease, known to promote resection during DSB repair, also contributes in R-loops (DNA-RNA hybrids) dissolution, in conjunction with XPG. First, they found that yeast sen1, an RNA-DNA helicase involved in transcription termination, as well as transcription inhibitors, rescue the CPT sensitivity of sae2 deficient strains. They further report that Sae2 binds to highly transcribed genes following exposure to CPT in S phase, that it correlates with accumulation (pausing) of RNA Polymerase II at these positions in CPT treated cells, and that R-loops accumulate in Sae2 deficient strain (at the rDNA locus). Notably, most of these findings also apply for CtIP function in human cells: CtIP depletion triggers sensitivity to CPT that is rescued by Senataxin (the Sen1 human ortholog) overexpression and R-loops accumulate in CtIP-depleted cells, as they do in XPG-depleted cells, as previously reported. Moreover, CtIP depletion decreases ssDNA break, suggesting that, as XPG, CtIP contributes to R-loop dissolution by generating a ssDNA break promoting the activity of senataxin and other hybrids helicases. All these data identify Sae2/CtIP as a key regulator of R-loops stability on yeast and human genome. The most puzzling data came from combining both XPG and CtIP depletion, since, although their co depletion completely abolishes the generation of an ssDNA break, no R-loop accumulate in these conditions. The authors interpret these data, as a lack of R-loop extension in these conditions, that would make them undetectable.

Given the threat of R-loop on genome stability that has been clearly described recently, identifying the mechanisms that function to regulate their occurrence on the genome is of prime interest. Additionally, the model presented here is very interesting and exciting. Yet I feel that (i) the model would be more convincing if the same loci were analyzed across the Figures, (see main point 1 below) and (ii) some key experiment are lacking to fully support the model (see main point 2).

For the yeast part, the authors need to show that indeed, R-loops accumulates at sites that recruit sae2 upon CPT treatment. They show Figure 2E that they do accumulate on rDNA, but to be consistent with Figure 2C, and Figure 3A-B and to demonstrate convincingly the relationship at specific loci between Sae2 and R-loops, the authors need to report the accumulation of R-loops at ENO1, ADH2, FBA1, as well as SNR13, SNR5. Additionally, the authors need to extend their Sae2-flag ChIP-seq data analysis more specifically by comparing their data with DRIP-seq yeast genome profiles (see my detailed points on Figure 2).

For the mammalian cells part, the fact that codepletion of XPG and CtIP shows no R-loops accumulation but deficient ssDNA breakage is really puzzling. The authors propose that the hybrids still accumulate in these conditions but are not detectable using their assay (S9.6 and mutated cherry RNAseH). The author needs to demonstrate that this is the case. Indeed, that CtIP depletion rescues R-loop accumulation in XPG-depleted cells may also indicate that CtIP lies downstream XPG mediated-ssDNA cleavage, hence challenging their model. I realize this may be difficult to assess, but this is an important piece of data that is lacking to support their current model; maybe the authors could try at one locus non denaturing sodium bisulfite treatment to detect ssDNA (as in Ginno et al., 2012 or Loomis et al., 2014)?

Figure 1: Sen 1 also rescues viability upon CPT in mre 11 deficient strain. Can the author comment and integrate the MRX complex in their R-loop processing model?

Figure 2: The ChIP-seq data should be more described, and a full supplemental Figure should be provided. Do the 45 peaks also overlap with the 176 peaks in presence of CPT? If yes, can we see some examples on browser? Can the author show a scatter plot where for each gene, the transcription level is plotted against the CPT-treated enrichment of Sae2 (normalized against gene length)? The author could also retrieve RNA Pol II mapping and perform the same analysis. Another very common way to show this type of data, would be to separate the yeast genes based on their expression level and show that Sae2 binding is statistically higher for the highly expressed genes subset compared to the low expressed set of genes. Finally, Sae2 binding in S phase upon CPT should be compared to DRIP-seq data from the Koshland lab (Wahba et al., 2016). Given that the authors show R-loop accumulation at rDNA, can they also report the change of Sae2 recruitment upon CPT on rDNA from their Sae2 ChIP-seq? Can we also see the snapshot for PDC1, SNR13, SNR5 for Sae2 distribution in CPT treated samples?

Figure 3: "We did not observe CPT induced RNA Pol II pausing at PDC1". It seems from the Figure that the author can actually see some Rbp2 increase (Figure 3B).

Figure 5: In their expression study, is there some overlap between genes modified following CPT treatment and genes modified after CtIP depletion? Can the author directly show the DRIP-seq count on the different gene subsets (WT -vs +CPT, WTvsCtiP -CPT and WT vs CtIP + CPT) compared to random genes (together with p values)?

Figure 6: Part of the Figure 6B, can the author show the R-loop level by DRIP qPCR (only at the b-actin gene) upon XPG and CtIP depletion?

Figure 8: the assay presented Figure 8D is very nice. Could the author also perform XPG only and CtIP/XPG depletion to further validate that indeed ssDNA breakage is absent in these conditions?

Reviewer #3:

In this manuscript, the role of Sae2/CTIP in R-loop accumulation and processing is explored both in yeast and mammalian cells. Motivated by understanding the unexpected sensitivity of Sae2/CTIP-deficient cells to CPT-induced 3'-ssDNA lesions, Paull and colleagues explored the role of transcriptional regulation in survival of Sae2-deficient cells. Upon finding that SEN1 expression rescues this sensitivity and that its loss enhances sensitivity, they go on to show that Sae2 is found at sites of high transcription, especially upon treatment with CPT, and that its deletion leads to transcription-dependent damage sensitivity and Pol II stalling following CPT. Similarly, they find in mammalian cells that sensitivity due to CTIP loss can be rescued by SETX expression and that RNA-DNA hybrids accumulate upon CTIP-loss or XPG-loss at laser-induced damage, based on binding of an mCherry-RNaseH sensor. Hybrids are also elevated in the absence of damage and these nucleases both at genes know to form R-loops and R-loop inducible sites. Finally, the authors show that CtIP and XPG reduce breaks formed by CPT using both comet assays and LM-PCR. Together, these studies lead the authors to propose that XPG and CtIP work in a redundant manner to process R-loops by generating a break at the R-loop site and allowing access of SETX to the hybrids for hybrid resolution.

While this is an intriguing model and important function of CTIP to understand, I think that the model is somewhat premature at this point and additional results are needed to test the model and rule out other possibilities. Several experiments require additional controls as well. Of particular note, I don't think the authors have sufficiently established the proposed order of events which place CtIP and XPG upstream of SETX. Is CtIP or XPG needed for Sen1/SETX to bind the DNA at the sites of hybrid formation, tested using the RNaseH sensor and ChIP assays? This would be one prediction of the model if nuclease processing is needed to generate access for Sen1/SETX. Also, can the authors rule out that SETX and CtIP are not simply acting to reduce the same hybrid structures (albeit in different ways)? As it stands the authors need more data to substantiate their conclusions.

Where does the CPT-induced break fit into the authors' model? The break induced by CtIP/XPG would be in addition to this CPT-induced break. This is omitted from Figures and models and a somewhat confusing point.

Figure 2: As a specificity control the authors should test whether Sae2 binding by ChIP is blocked by transcription inhibition.

Figure 2: Since the DRIP did not work well in yeast, it would be helpful to show that Sae2 binding by ChIP is rescued by overexpression of RNaseH or Sen1 in yeast cells. Similarly, they could ask if RNaseH overexpression rescues CPT effects on survival.

Figure 3: The authors need to analyze several other genes that are not expressed or expressed at lower levels to show specificity of the effect of CtIP loss at highly expressed genes. Right now they examine two genes, PDC1 and NRD1 as negative controls (if I understand this correctly) and Pol II binding is actually elevated at the first site.

Figure 4: Does RNaseH overexpression rescue viability of CTIP deletion? Also, please comment why in Figure 4 hybrids increase with DRB treatment in WT cells?

Figure 4, Figure 5 and Figure 6: Is the nuclease activity of XPG required for any of the observed effects? Testing this in at least one of the assays would be helpful.

Figure 5D: Does RNaseH expression in vivo and RNaseH treatment in vitro reduce the increased hybrid signal (which is actually very weak). This is an important control.

Figure 5E/F: What is the rationale for both increases and decreases in transcription overlapping with site of hybrid formation? I don't understand the implications of the RNA-seq data. Also, Figure 5F is missing in the Figure, making these data difficult to evaluate.

Figure 5: What is the impact of CtIP and XPG loss, or loss of both, on the cell cycle. Are breaks or hybrid levels reduced due to alterations in cell cycle progression (e.g. failure to enter S phase) or accumulation in G2. It seems in WT cells hybrids are naturally higher in G2 and if breaks depend on S phase entry changes in cell cycle could affect the interpretation.

Figure 6: Why are there no more breaks upon addition of CPT? Shouldn't the CPT itself lead to break formation even without the action of XPG and CtIP? Also, alkaline comet is not specific for SSB detection – these could be DSBs. I suggest the authors use caution in the way they present these data.

The idea that the R-loops are too small to be detected when both XPG and CtIP are lost is not well supported. Isn't it possible that there is no R-loop under these conditions and that RNAPII has simply stalled and is the toxic lesion? Can RNaseH expression rescue sensitivity due to loss of both XPG and CtIP? That is one test of this idea. Or can evidence for a smaller R-loops be obtained using bisulfite sequencing. Minimally I think other models should be considered.

[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]

Thank you for submitting your article "Sae2/CtIP prevents R-loop accumulation in eukaryotic cells" for consideration by eLife. Your article has been reviewed by the same three peer reviewers that revised the first submission, and the evaluation has been overseen by the same Reviewing Editor and Jessica Tyler as the Senior Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

Makharashvili et al., report a novel function for Sae2/CtIP in both yeast and human cells, and propose that Sae2/CtIP, known to promote resection during DSB repair, also contributes in R-loop (DNA-RNA hybrids) dissolution, in conjunction with XPG. In this revised version, the authors have addressed to a reasonable extent my main points. More specifically they are now consistent throughout the manuscript, and report Sae2 binding and R-loop accumulation in Sae2 deleted strain at the same loci. They have also now changed their discussion to take more hypotheses into account. They have also largely controlled their data by performing RNAseH treatment to validate their results obtained with S9.6 antibody. This manuscript is a significantly improved version of the previous one. Results are now clearer and convincing. However, the key conclusion of their model that CtIP cleaves the loop needs further support and clarification before acceptance.

Essential revisions:

The results on which the model proposed rely on CPT-treated cells (i.e. Figure 2A-E, Figure 4A-C, Figure 5F and Figure 8) (CPT creates ssDNA breaks with Top1-cc) or cells upon laser-induced breaks (i.e. Figure 4D-H). So, the experimental conditions used implies to start with a genotoxic-induced break. It is still therefore unclear why CtIP would be required for an additional break. Indeed, authors were not able to show the proposed activity of CtIP in vitro. Authors would need to show the action of CtIP in untreated cells (no CPT, no laser irradiation), with no break, to support their model that demands that CtIP cleaves the loop. The known action of the Sae2/CtIP nuclease activity on DNA resection as a requirement to remove the RNA-DNA hybrid accumulated at a break would make much more sense and fit better with the combined effect with XPG. Therefore, either authors provide new data with untreated cells to support their model as such or alternatively include in their model the breaks caused by CPT/laser irradiation to explain the role of CtIP under such conditions.

https://doi.org/10.7554/eLife.42733.030

Author response

[Editors’ note: the author responses to the first round of peer review follow.]

As I said, this is an interesting study performed in yeast and human cells to show that CtIP is involved in resolving R-loops in conjunction with XPG. By first observing the ability of Sen1 DNA-RNA helicase, involved in transcription termination, to suppress some of the phenotypes of sae2∆ mutants such as CPT sensitivity and R-loop accumulation in the rDNA, authors conclude that yeast Sae2 is important for R-loop removal. They go on to show that Sae2 is found at sites of high transcription, especially upon treatment with CPT in S phase, and that its deletion leads to transcription-dependent damage sensitivity and Pol II stalling following CPT. Notably, most of these findings also apply for CtIP function in human cells. CtIP depletion triggers sensitivity to CPT that is rescued by Senataxin (the Sen1 human ortholog) overexpression. They find that RNA-DNA hybrids accumulate upon CTIP-loss or XPG-loss at laser-induced damage, based on binding of an mCherry-RNaseH sensor. Moreover, CtIP depletion decreases ssDNA break, suggesting that, as XPG, CtIP contributes to R-loop dissolution by generating a ssDNA break promoting the activity of senataxin and other hybrids helicases. The authors show that CtIP and XPG reduce breaks formed by CPT using both comet assays and LM-PCR. The most puzzling data came from combining both XPG and CtIP depletion, since, although their co-depletion completely abolishes the generation of an ssDNA break, no R-loop accumulate in these conditions. The authors interpret these data, as a lack of R-loop extension in these conditions, that would make them undetectable. Together, these studies lead the authors to propose that XPG and CtIP work in a redundant manner to process R-loops by generating a break at the R-loop site and allowing access of SETX to the hybrids for hybrid resolution. They propose a model by which CtIP would promote cleavage of Flap structures as a step to resolve R-loops.

The work is very interesting and exciting and provides an intriguing model and important function of CTIP to understand. However, additional results are needed to test the model and rule out other possibilities. Several experiments require additional control; all studies with S9.6 should provide the control with RNaseH treatment in vitro to show that the signal is removed (S9.6 also recognizes dsRNA and data must assure that the signal detected corresponds to RNA-DNA hybrid). Although authors use Sen1 to remove R-loops, the data suggest that the terminator function of Sen1 has a role in the suppression of the CPT sensitivity and by extension the R-loops. In addition, the yeast data do not clearly support that RNAPII transcription is the major cause of R-loops. The authors are unable to show hybrids in RNAPII genes, but only in rDNA regions. Of particular note, the authors did not sufficiently establish the proposed order of events which place CtIP and XPG upstream of SETX. Is CtIP or XPG needed for Sen1/SETX to bind the DNA at the sites of hybrid formation, tested using the RNaseH sensor and ChIP assays? This would be one prediction of the model if nuclease processing is needed to generate access for Sen1/SETX. Could indeed the authors rule out that SETX and CtIP are not simply acting to reduce the same hybrid structures (albeit in different ways)? In summary, as it stands the authors need more data to substantiate their conclusions.

Thank you for the in-depth comments. From the summary we received, it seems that the major issues have to do with: (1) confirmation of the specificity of S9.6 immunoprecipitations, (2) demonstration of the ability of RNaseH suppression in addition to SEN1/Senataxin suppression of CtIP depletion phenotypes, (3) demonstration of R-loops at RNAPII genes in yeast, and (4) further investigation and validation of the ideas in our proposed model. We have performed several additional experiments to address these points, as discussed below. We think the manuscript is significantly improved with these revisions and additions to the data. We have also revised our thinking about the model and have incorporated some alternative scenarios into the discussion in the main text. We address these four main questions first and then answer the reviewer questions below.

1) RNaseH in vitro treatment for validation of S9.6 IPs:

We repeated the S9.6 DRIP-qPCR experiment using pre-treatment with RNaseH in vitro as a control. These results, shown in Figure 6C, and Figure 6—Figure supplement 3 that the S9.6 signal is in fact due to RNA-DNA hybrids as it is eliminated by RNaseH.

2) Another suggestion of the reviewers was to show RNaseH suppression of phenotypes in yeast and in human cells, which would confirm the R-loop-related role of SEN1/SETX.

Galactose-induced overexpression of RNH1 also suppresses the sensitivity of Δsae2 yeast cells to camptothecin and to MMS, as shown in Figure 1.

We also performed this experiment in human cells by overexpressing RNaseH in cells depleted of CtIP. We found that this treatment also reduces R-loops in CtIP-depleted cells, as measured by DRIP-qPCR. This result is now shown in Figure 6B and D.

3) Is RNAPII transcription the cause of R-loop accumulation in sae2∆ yeast cells? To answer this question we re-visited DRIP experiments in yeast. We observed a statistically significant increase in R-loops at highly transcribed loci in sae2∆ cells, as in Figure 2E (ADH1, ENO2, FBA1).

4) To address whether the proposed model of SEN1/SETX recruitment to transcription sites via Sae2/CtIP is correct.

We decided to determine if SEN1 and SETX recruitment to relevant sites in both yeast and human cells is Sae2/CtIP-dependent. In yeast, we used an HTB-tagged SEN1 strain and examined recruitment to several of the loci where we observed high levels of Sae2 protein and also R-loop accumulation. This experiment shows that SEN1 is actually present at higher levels than in wild-type strains (these isolations were all done in S phase with CPT treatment) (Figure 3C).

In human cells we performed ChIP-qPCR experiments to determine if endogenous Senataxin is present at sites of R-loop accumulation. We used our inducible Sγ3 locus for these experiments since we are able to control the transcription at this site. Similar to the experiment in yeast, we found that Senataxin occupancy is actually higher in CtIP-depleted cells than in wild-type, and that this is dependent on active transcription (Figure 6H). It was also higher with XPG depletion but the p value for this comparison was 0.06.

We conclude from this that the recruitment of SEN1/SETX protein is not impaired, yet there seems to be a significant dysfunction of the enzyme since levels of R-loops are high and RNAPII is found to be stalled at these sites. One possibility is that SEN1/SETX recruitment to the site is mediated by association with the polymerase or other factors, yet the enzyme is not able to access the R-loop efficiently because of a problem with the structure of the DNA at the locus (our initial model). It is also possible that Sae2/CtIP is in a separate, parallel pathway to SEN1/SETX and that SEN1 overexpression (or RNaseH overexpression) helps in sae2∆ or CtIP-depleted cells because this alternate pathway is augmented by the increased removal of RNA-DNA hybrids. We now present both of these models in the main text and in Figure 7.

Reviewer #1:

This is an interesting study performed in yeast and human cells to show that CtIP is involved in resolving R-loops. By first observing the ability of Sen1 DNA-RNA helicase to suppress some of the phenotypes of sae2∆ mutants such as CPT sensitivity and R-loops detected by a specific antibody, authors conclude that yeast Sae2 is important for R-loop removal. The study is extended to human cells, in which using a parallel approach the authors conclude that CtIP have similar role. In this case, they use laser micro-irradiation and siXPG cells, which allow the authors to propose a model by which CtIP would be able to cleave Flap structures as a step to resolve R-loops. This is a new and a priori unexpected involvement of a DSB processing factor in R-loop removal that merits being considered for publication. However, the study has a number of issues that need to be resolved before it can be published. There are three important points that need to be solved first, apart from the essential experiments suggested below.

1) All studies with S9.6, except one in Figure 6A, did not provide the control with RNase H1 to show that the signal is removed. It is known that S9.6 also recognizes dsRNA and it is not possible to make conclusions with this antibody without removing the signal with RNase H1.

We have repeated the DRIP-qPCR experiments and performed RNaseH treatment of the samples before the IP (shown in Figure 6A and Figure 6—Figure supplement 3), showing that the signal is specific to RNA-DNA hybrids.

- Although authors use Sen1 to remove R-loops, the data suggest that the terminator function of Sen1 has a role in the suppression of the CPT sensitivity and by extension the R-loops. It is necessary to show that RNH1 overexpression, not just Sen1/SETX also suppresses the CPT phenotype in yeast and that of micro-irradiated human cells.

See Figure 1 and Figure 6B,D.

- Authors propose that CtIP/Sae2 may have a new FLAP endonucleolytic function similar to XPG. This conclusion is based on the similar phenotypes observed for CtIP and XPG-depleted cells. However, a similar phenotype may be produced by different mechanisms, and R-loop dynamics may respond to many different factors. The in vivo data showing that in the double depletion in human cells they have equal amount of R-loops than the simple is inconsistent with a model implying that an ssDNA nick (as that caused by S1 in vitro experiment) stabilizes R-loops. The in vivo data do not seem to support the model proposed since if CtIP is not able to cleaves the FLAP structure, R-loops would not be stabilized. In this context, the S1 experiment is really confusing and unnecessary in this study (the Lieber lab already showed in the past that a nick in the DNA increases the accumulation of R-loops).

We find that the double depletion of both CtIP and XPG generates a very low level of R-loops, similar to wild-type cells, whereas each single depletion shows high R-loops. So, the double depletion is not equivalent to either of the single depletions. To explain this, we propose that extensive R-loops are not being formed in the double depletion cells because of a lack of single-strand processing. The Lieber laboratory showed previously that a nick in either strand strongly promotes stabilization of R-loops, so our hypothesis is consistent with this idea. We agree that we don't need to show the nick inducing R-loops since this was published previously.

The model is simply a diagrammatic set of working hypotheses that we are using to frame questions around this data; we are certainly not claiming to have proven everything in the model, and the discussion is modified now to better reflect this view. We know that CtIP and XPG are not completely redundant because we see obvious R-loop accumulation in the absence of either factor. We are working toward understanding the differences between their activities using purified components, but this is beyond the scope of the work being considered here.

- Provided the know function of CtIP in DSB resection and the relevance of transcription-replication collisions as a way to produce stalled and collapsed forks and considering the possibility that it could also lead to fork reversal generating a one-ended DSB-like structure susceptible of being resected by CtIP to restart the fork, it may be possible that the inability of CtIP to act at broken or reversal replication forks stalled in front of an R-loop lead to an accumulation of these hybrids as structures causing the lethality in CPT or microirradiation and Sae2/CtIP cells. Consequently, it is necessary to show that in vitro CtIP has the suggested activity. The assay done with S1 should indeed be performed with CtIP.

We have made R-loops in vitro using prokaryotic and phage RNA polymerases but have not observed significant levels of processing of these structures. Considering the known association between CtIP and human transcription-associated complexes though, perhaps it is not surprising that a reconstitution with heterologous polymerase would not work here.

It is certainly possible that some of the consequences of CtIP depletion involve fork reversal. We now have alleles of CtIP that can separate the function of CtIP in canonical DSB processing from the nuclease-related function, so we are in the process of testing these.

In Figure 1, authors should show overexpression of RNaseH to demonstrate that R-loops are the cause of CPT sensitivity in sae2∆ strain.

As shown in Figure 1, we do observe suppression of CPT and MMS sensitivity by RNH1 in a ∆sae2 strain. We also show that RNaseH overexpression in human U2OS cells reduces R-loops in CtIP-depleted cells (Figure 6B,D).

Since the CPT sensitivity phenotype is observed in S-phase, it would be important to address if Sen1 and RNaseH1 rescue sae2∆ sensitivity to HU. Could it be transcription/replication collisions not R-loop dependent?

We tested the HU sensitivity of sae2 strains to hydroxyurea with either RNH1 or SEN1 overexpression and found no evidence for suppression of sensitivity under these conditions (Author response image 1). Stalling of replication forks, although toxic in a sae2 background, does not appear to be related to R-loop removal.

Author response image 1
Overexpression of RNH1 or SEN1 does not suppress the sensitivity of Δsae2 strains to hydroxyurea (HU) exposure.

(A). RNH1 was induced from the GAL1 promoter on a CEN plasmid in Δsae2 compared to Δsae2 with vector only. Viability with or without HU (100 mM) was assessed at 48 hours or 72 hours as indicated. All plates contain galactose. (B). SEN1 was overexpressed from a CEN plasmid inΔsae2 compared to Δsae2 with vector only. Viability with or without CPT (5 μg/ml) was assessed at 48 or 72 hours as indicated on glucose-containing media.

https://doi.org/10.7554/eLife.42733.024

A DRIP-qPCR analysis of some of the genes with increased Sae2 recruitment in the ChIP-seq to validate the data.

See point #3 above, and Figure 2E.

In Figure 1E, the control DRIP samples with RNaseH1 treatment is not shown.

We show in vitro treatment of samples with RNaseH in Figure 2E as well as in Figure 6A and Figure 6—Figure supplement 3. Figure 1 doesn't contain any DRIP experiments.

No statistical analysis is supplied for any of the yeast tables. This is essential in Figure 3A, where authors claim that o/e SEN1 reduces RNA Pol II accumulation. Again, an RNaseH1 o/e should be included.

p values have been added to Figure 3. We do not have RNaseH1 overexpression in this case but the fact that RNH1 overexpression rescues growth of Δsae2 cells to CPT and MMS (Figure 1) shows that the role of RNA removal is critical.

In Figure 4A, authors should show overexpression of RNaseH as a way to demonstrate that R-loops are the cause of CPT sensitivity in cells depleted of CtIP.

We now show this in Figure 1 in yeast as well as in Figure 6 in human cells.

Immunofluorescences in Figure 5C should have RNase H -treated cells as control. Image contrast could be improved and also show the channels separately.

We expressed RNaseH in cells with CtIP depletion, as shown in Author response image 2 and in Figure 5. Expression of RNaseH reduced levels of RNA-DNA hybrids recognized by S9.6.

Author response image 2
CtIP, XPG, or Senataxin-depleted cells exhibit higher levels of RNA-DNA hybrids.

(A) Human U2OS cells expressing shRNA specific for CtIP with or without RNaseH expression as indicated were analyzed using immunofluorescence with S9.6 antibody and with antinucleolin antibody which stains the nucleoli. S9.6 signal overlapping with nucleolin signal was substracted from the total signal and the data was normalized to the size of the nucleus. (B) Quantification of >50 cells from each cell line was performed. Error bars represent S.E.M. **** denotes p < 0.0001 using Student's two-tailed T test with comparisons as indicated.

https://doi.org/10.7554/eLife.42733.025

How do authors explain the reduction on R-loops compare to siC levels when both nucleases CtIP and XPG are missing? This is odd.

The idea is that nicks in DNA promote the extension and stabilization of R-loops. This has been shown in vitro by Lieber and colleagues and we have confirmed this result (previously shown in one of the supplementary Figures). In the absence of a single-strand break, RNA-DNA hybrids are extremely constrained topologically, and the region of the RNA-DNA hybrid is likely to be inaccessible because of the presence of the non-template strand of DNA. So, we are proposing that, in the absence of strand breaks, there is a nascent structure that is not efficiently recognized by S9.6 or RNaseH but yet is toxic to cells and needs to be removed. We speculate that this could be a small R-loop or a paused polymerase associated with a small R-loop but do not know exactly what this structure is.

Regarding the ssDNA breaks assay, due to the CtIP role in resection it is expected to have less breaks after DNA damage. Authors could perform the assay in a background known to increase R-loops, such as sen1 or rnh1 rnh2 and see if CtIP depletion reduces the R-loop-dependent DNA breaks.

Actually, we would expect more breaks in the absence of CtIP if its role is primarily in double-strand break repair because presumably there would be more unresolved breaks. In the manuscript we are using an alkaline comet assay which measures single-strand breaks, and here we always observe fewer in the absence of CtIP. Resection of double-strand breaks would not be expected to change the total number of single-strand breaks. Unfortunately, we do not have any method to measure single-strand breaks in yeast as the reviewer suggests. In human cells we have measured single-strand breaks in XPG-depleted cells (which have higher R-loops), and in this context, removal of CtIP also lowers the number of single-strand breaks (Figure 8B).

The yeast data do not seem to support that RNAPII transcription is the major cause of R-loops. The authors are unable to show hybrids in RNAPII genes, but only in rDNA regions. Indeed, it makes sense from the data that CPT, that it is the rDNA region, in which the Tollervey lab has shown the relevance of Top1 to prevent R-loop formation, where the major intermediate leading to lethality may accumulate after CPT. Is there any data showing an involvement of Sen1 in RNAPI transcription termination? This needs to be considered, since at the end it is not really clear which function of Sen1 is able to suppress the sensitivity to CPT of sae2∆ cells.

See point #3 above. We do now show higher levels of R-loops at RNAPII genes in sae2∆ strains with DNA damage. Sen1 is definitely involved in transcription termination, of non-coding RNAs as well as a subset of RNAPII-transcribed protein coding genes (13). We are not trying to eliminate termination as part of the possible mechanism here; in fact, we also show in Figure 1 the ability of PCF11 to partially suppress sae2 DNA damage sensitivity, and PCF11 is primarily known as a transcription termination factor (4). PCF11 also promotes the association of SEN1 with RNAPII however, and both sen1 and pcf11 mutations in yeast induce higher R-loops (4). It is also important to point out that SEN1 promotes transcription termination by removal of nascent RNA made by RNA Pol I as well as by RNA Pol II (5), although we removed the rDNA data here is favor of the RNAPII data.

The enrichment of Sae2 at 176 sites of transcription in S phase may not necessarily related with R-loops. Authors do not show whether such enrichment is reduced by RNase H overexpression. At least should be done by DRIP-qPCR to validate the data using RNase H.

We now show that the sites we isolated with high Sae2 occupancy do have higher R-loops in sae2∆ strains, and we show RNaseH treatment of the S9.6 IPs eliminates the signal. We also show that RNH1 expression reduces the sensitivity of sae2∆ strains to both CPT and MMS, and we show that RNaseH overexpression in human cells reduces levels of R-loops in CtIP-depleted cells. We are pretty darn sure that these sites have R-loops. We are not saying that Sae2/CtIP is going to these sites because there are R-loops there, but that Sae2/CtIP goes to sites where high transcription is happening, and that in the absence of Sae2/CtIP, there are R-loops.

In the genome-wide analysis, the fact that RNAPII is found at high levels at sites previously described to from R-loops does not implies that R-loops are accumulated in sae2∆ strains. It is required to reduce the signal by overexpressing RNH1. Overexpression of Sen1 produces a reduction in signal, but this may be due to the terminator function of Sen1. For this reason, authors need to revert the phenotype with a protein not involved in termination, but just in R-loop removal, such as RNH1.

Overexpression of RNH1 does suppress the phenotype of Δsae2 strains to both CPT and MMS (see Figure 1), and overexpression of wild-type RNaseH reduces levels of R-loops in CtIP-depleted human cells. Also, we found that the sen1-R302W allele rescues Δsae2 DNA damage sensitivity similar to wild-type SEN1. This mutation has been reported to abrogate the terminator function of SEN1 by blocking interaction of SEN1 with Rpb1 (6), suggesting that the terminator function of SEN1 is not critical (Figure 1A). In contrast, mutation of the helicase domain does reduce the ability of SEN1 to suppress the phenotype, and a combination of this mutation with a Δsae2 deletion generates extreme DNA damage sensitivity (Figure 1C).

I am not sure what the results of Figure 4B really says. If CPT causes breaks, it should not be surprising that CtIP increases the sensitivity. Provided the impact of transcription in collisions or increase in damage by other ways, the action of DRB should not be surprising. However, the reduction of the sensitivity phenotype is very small. Results could be repeated using another inhibitor of transcription such as α-amanitin.

The CPT sensitivity assay in Figure 4B shows partial suppression of the sensitivity observed in CtIP-depleted cells by DRB treatment. The fact that we see partial restoration is expected because the transcription-associated role of CtIP that we are describing in this work is only part of its diverse biological functions, which also include promoting the nuclease activity of Mre11 at double-strand break sites. We would not expect transcription inhibition to necessarily affect this aspect of its function if the double-strand break is the critical lesion. We also previously tested α-amanitin but we found it was too toxic in this type of assay.

In Figure 5 it is necessary to show that all signals are reduced by RNase H.

See point #1 above.

Reviewer #2:

In this manuscript, Makharashvili et al., report a novel function for Sae2/CtIP in both yeast and human cells: They propose that this endonuclease, known to promote resection during DSB repair, also contributes in R-loops (DNA-RNA hybrids) dissolution, in conjunction with XPG. First, they found that yeast sen1, an RNA-DNA helicase involved in transcription termination, as well as transcription inhibitors, rescue the CPT sensitivity of sae2 deficient strains. They further report that Sae2 binds to highly transcribed genes following exposure to CPT in S phase, that it correlates with accumulation (pausing) of RNA Polymerase II at these positions in CPT treated cells, and that R-loops accumulate in Sae2 deficient strain (at the rDNA locus). Notably, most of these findings also apply for CtIP function in human cells: CtIP depletion triggers sensitivity to CPT that is rescued by Senataxin (the Sen1 human ortholog) overexpression and R-loops accumulate in CtIP-depleted cells, as they do in XPG-depleted cells, as previously reported. Moreover, CtIP depletion decreases ssDNA break, suggesting that, as XPG, CtIP contributes to R-loop dissolution by generating a ssDNA break promoting the activity of senataxin and other hybrids helicases. All these data identify Sae2/CtIP as a key regulator of R-loops stability on yeast and human genome. The most puzzling data came from combining both XPG and CtIP depletion, since, although their co depletion completely abolishes the generation of an ssDNA break, no R-loop accumulate in these conditions. The authors interpret these data, as a lack of R-loop extension in these conditions, that would make them undetectable.

Given the threat of R-loop on genome stability that has been clearly described recently, identifying the mechanisms that function to regulate their occurrence on the genome is of prime interest. Additionally, the model presented here is very interesting and exciting. Yet I feel that (i) the model would be more convincing if the same loci were analyzed across the Figures, (see main point 1 below) and (ii) some key experiment are lacking to fully support the model (see main point 2).

For the yeast part, the authors need to show that indeed, R-loops accumulates at sites that recruit sae2 upon CPT treatment. They show Figure 2E that they do accumulate on rDNA, but to be consistent with Figure 2C, and Figure 3A-B and to demonstrate convincingly the relationship at specific loci between Sae2 and R-loops, the authors need to report the accumulation of R-loops at ENO1, ADH2, FBA1, as well as SNR13, SNR5. Additionally, the authors need to extend their Sae2-flag ChIP-seq data analysis more specifically by comparing their data with DRIP-seq yeast genome profiles (see my detailed points on Figure 2).

See point #3 above, and Figure 2E. Comparison to DRIPseq data sets is discussed below.

For the mammalian cells part, the fact that codepletion of XPG and CtIP shows no R-loops accumulation but deficient ssDNA breakage is really puzzling. The authors propose that the hybrids still accumulate in these conditions but are not detectable using their assay (S9.6 and mutated cherry RNAseH). The author need to demonstrate that this is the case. Indeed, that CtIP depletion rescues R-loop accumulation in XPG-depleted cells may also indicate that CtIP lies downstream XPG mediated-ssDNA cleavage, hence challenging their model. I realize this may be difficult to assess, but this is an important piece of data that is lacking to support their current model; maybe the authors could try at one locus non denaturing sodium bisulfite treatment to detect ssDNA (as in Ginno et al., 2012 or Loomis et al., 2014)?

Much more detailed analysis is required to determine exactly what the nature of the initiating lesion is. We know there is some type of lesion, since removal of both factors results in very high sensitivity to DNA damage. We do not think the data is consistent with CtIP creating a toxic intermediate downstream of XPG action because if this were the case, CtIP depletion would rescue the sensitivity of XPG-depleted cells and this is not the case. We propose that the lesion is a nascent R-loop but it could also be simply a stalled polymerase, if secondary structure in DNA were exposed in the stalled complex. Certainly, the nature of the lesion is of interest to us, and we are working on reconstituting this in vitro, but determining this conclusively is likely the topic of an entire subsequent study.

Figure 1: Sen 1 also rescues viability upon CPT in mre 11 deficient strain. Can the author comment and integrate the MRX complex in their R-loop processing model?

We are working on that but do not have enough data to speculate on what the role of MRX(N) is in R-loop processing.

Figure 2: The ChIP-seq data should be more described, and a full supplemental Figure should be provided. Do the 45 peaks also overlap with the 176 peaks in presence of CPT? If yes, can we see some examples on browser? Can the author show a scatter plot where for each gene, the transcription level is plotted against the CPT-treated enrichment of Sae2 (normalized against gene length)? The author could also retrieve RNA Pol II mapping and perform the same analysis. Another very common way to show this type of data, would be to separate the yeast genes based on their expression level and show that Sae2 binding is statistically higher for the highly expressed genes subset compared to the low expressed set of genes.

This is what we did in Figure 2D. We look at the overlap between the sites where Sae2 is bound in S phase with CPT and compare them to the top 10% of transcribed genes (ranked by expression level) versus the same number of randomly chosen genes. The comparison with the randomly chosen genes is done 1000 times, which generates a distribution. Only in the case of S phase plus CPT is there a statistically significant difference between the overlap with the top 10% of genes and the overlap with the randomly selected genes. More detailed information about the confidence intervals for the transcription analysis is now shown in Supplementary file 1. This shows that the p value for the S+CPT immunoprecipitation overlapping with the top 10% of transcribed genes is <.0053, whereas the analysis of the S phase sample with no DNA damage yield a p value <.757. We have not done in-depth analysis of transcription levels versus Sae2 enrichment because the transcription levels we are using are from published RNA-seq data, not the S phase or S phase plus CPT cells that we are using here, which would be preferable. We are working on doing this in mammalian cells with CtIP ChIP but this is still in progress.

With respect to the comparison between the S phase peaks and the S plus CPT peaks, there are relatively few peaks that overlap. A browser view of a few of these overlapping genes is shown in Author response image 3.

Author response image 3
Browser view of Sae2-ChIP at the GPR1, TBS1, and SAM2 genes in sae2Δ cells expressing Flag-Sae2, in S phase with CPT exposure compared to S phase with no DNA damage.

Reads from the immunoprecipitated sample are shown (IP) in comparison to control immunoprecipitations performed in the absence of Flag antibody (bead control, BC).

https://doi.org/10.7554/eLife.42733.026

Finally, Sae2 binding in S phase upon CPT should be compared to DRIP-seq data from the Koshland lab (Wahba et al., 2016).

9 of 45 Sae2 peaks in S phase (20%) and 36 of 176 Sae2 peaks in S phase with CPT (20%) overlap with the DRIP peaks in wild-type cells from Wahba et al., 2016. This is now stated in the text.

Given that the authors show R-loop accumulation at rDNA, can they also report the change of Sae2 recruitment upon CPT on rDNA from their Sae2 ChIP-seq? Can we also see the snapshot for PDC1, SNR13, SNR5 for Sae2 distribution in CPT treated samples?

There is substantial recruitment of Sae2 to the rDNA, which increases with CPT exposure, and we do observe Sae2 at PDC1 (Author response image 4), but there is no Sae2 detected at SNR5 or SNR13, possibly because these are non-coding RNA genes and are very short. We are not including this though as we have removed the rDNA DRIP data in favor of the more relevant RNAPII loci.

Author response image 4
Browser views of Sae2-ChIP at the rDNA locus and the PDC1 locus on ch.XII in sae2Δ cells expressing Flag-Sae2, in S phase with CPT exposure compared to S phase with no DNA damage.
https://doi.org/10.7554/eLife.42733.027

Figure 3: "We did not observe CPT induced RNA Pol II pausing at PDC1". It seems from the Figure that the author can actually see some Rbp2 increase (Figure 3B).

We corrected the description in the text.

Figure 5: In their expression study, is there some overlap between genes modified following CPT treatment and genes modified after CtIP depletion? Can the author directly show the DRIP-seq count on the different gene subsets (WT -vs +CPT, WTvsCtiP -CPT and WT vs CtIP + CPT) compared to random genes (together with p values)?

We did not do DRIP-seq. We did RNA-seq and compared the locations of genes with differences in gene expression depending on CtIP status and CPT exposure to previously published DRIPseq data (Figure 5F). This analysis showed that the genes affected by CtIP loss are overrepresented in the DRIP-seq dataset (p<0.0052 for the comparison between – /+ CtIP and the genes identified by DRIPseq). The 99% confidence intervals have been added to the supplementary file as well as cited in the text.

Figure 6: Part of the Figure 6B, can the author show the R-loop level by DRIP qPCR (only at the b-actin gene) upon XPG and CtIP depletion?

We were not able to do this with the large number of experiments requested.

Figure 8: The assay presented Figure 8D is very nice. Could the author also perform XPG only and CtIP/XPG depletion to further validate that indeed ssDNA breakage is absent in these conditions?

We would like to do this but had to prioritize other experiments based on the summary of the reviews.

Reviewer #3:

In this manuscript, the role of Sae2/CTIP in R-loop accumulation and processing is explored both in yeast and mammalian cells. Motivated by understanding the unexpected sensitivity of Sae2/CTIP-deficient cells to CPT-induced 3'-ssDNA lesions, Paull and colleagues explored the role of transcriptional regulation in survival of Sae2-deficient cells. Upon finding that SEN1 expression rescues this sensitivity and that its loss enhances sensitivity, they go on to show that Sae2 is found at sites of high transcription, especially upon treatment with CPT, and that its deletion leads to transcription-dependent damage sensitivity and Pol II stalling following CPT. Similarly, they find in mammalian cells that sensitivity due to CTIP loss can be rescued by SETX expression and that RNA-DNA hybrids accumulate upon CTIP-loss or XPG-loss at laser-induced damage, based on binding of an mCherry-RNaseH sensor. Hybrids are also elevated in the absence of damage and these nucleases both at genes know to form R-loops and R-loop inducible sites. Finally, the authors show that CtIP and XPG reduce breaks formed by CPT using both comet assays and LM-PCR. Together, these studies lead the authors to propose that XPG and CtIP work in a redundant manner to process R-loops by generating a break at the R-loop site and allowing access of SETX to the hybrids for hybrid resolution.

While this is an intriguing model and important function of CTIP to understand, I think that the model is somewhat premature at this point and additional results are needed to test the model and rule out other possibilities. Several experiments require additional controls as well. Of particular note, I don't think the authors have sufficiently established the proposed order of events which place CtIP and XPG upstream of SETX. Is CtIP or XPG needed for Sen1/SETX to bind the DNA at the sites of hybrid formation, tested using the RNaseH sensor and ChIP assays? This would be one prediction of the model if nuclease processing is needed to generate access for Sen1/SETX.

As discussed in point #4 above, we agree that this is an important issue and we measured SEN1 recruitment as well as SETX recruitment in yeast and human cells, respectively. We do not find support for the idea that Sae2/CtIP recruits SEN1/SETX, although we do think it is possible that Sae2/CtIP creates an intermediate that is necessary for its function. We also consider other models, as discussed in the main text.

Also, can the authors rule out that SETX and CtIP are not simply acting to reduce the same hybrid structures (albeit in different ways)? As it stands the authors need more data to substantiate their conclusions.

In the case of CtIP, we are considering the fact that all of our evidence points toward a role for the nuclease activity in promoting removal of the R-loop, and the nuclease is clearly specific for a 5ʹ flap. We have not worked with XPG in vitro but the literature shows that it also is specific for a 5ʹ flap. If these activities are working at the site of an R-loop, there is no obvious way for either enzyme independently or both together to completely remove a hybrid. So, we have postulated in our working model that SETX is acting downstream of one or both of the nucleases, since it is known to be present at sites of hybrids and to play important roles in removing hybrids. Since there is substantial evidence for R-loops forming at DSB sites (9) and for DSBs occurring at sites of R-loops (10), we are also considering the possibility that an intermediate in this pathway is a DSB (see discussion in main text).

It is also worth noting that the striking phenotype we observe with depletion of both CtIP and XPG does suggest that these are two of the major players in this process. We are not excluding the possibility that other enzymes may also be acting here though, and we consider the model to be just the best set of working hypotheses we have with the current set of data.

Where does the CPT-induced break fit into the authors' model? The break induced by CtIP/XPG would be in addition to this CPT-induced break. This is omitted from Figures and models and a somewhat confusing point.

Although we do use CPT extensively in the manuscript, the phenomenon of SEN1/SETX-induced recovery of Sae2 or CtIP-deficient cells also occurs with other forms of DNA damage including MMS and laser-induced damage. The ssDNA break formed by the Top1 adduct is not shown in the model for simplicity.

Figure 2: As a specificity control the authors should test whether Sae2 binding by ChIP is blocked by transcription inhibition. Figure 2: Since the DRIP did not work well in yeast, it would be helpful to show that Sae2 binding by ChIP is rescued by overexpression of RNaseH or Sen1 in yeast cells. Similarly, they could ask if RNaseH overexpression rescues CPT effects on survival.

We were able to work out the technical issues with DRIP in yeast and found that there are elevated R-loops at sites of high transcription and high Sae2 occupancy with DNA damage in S phase (see point # 3). We also find that the survival of sae2 strains to CPT or MMS is promoted by overexpression of RNH1 (see Figure 1).

Figure 3: The authors need to analyze several other genes that are not expressed or expressed at lower levels to show specificity of the effect of CtIP loss at highly expressed genes. Right now they examine two genes, PDC1 and NRD1 as negative controls (if I understand this correctly) and Pol II binding is actually elevated at the first site.

We are not suggesting that Sae2 is at all highly-transcribed genes; there are many locations in the genome where transcription is high, yet we do not see Sae2 at these sites. NRD1 serves as a negative control here, where we see neither Sae2 nor accumulation of RNAPII.

Figure 4: Does RNaseH overexpression rescue viability of CTIP deletion? Also, please comment why in Figure 4 hybrids increase with DRB treatment in WT cells?

See point #2. The difference between wild-type untreated and wild-type with DRB is not statistically significant and are within the range we normally observe for wildtype cells.

Figure 4, Figure 5 and Figure 6: Is the nuclease activity of XPG required for any of the observed effects? Testing this in at least one of the assays would be helpful.

We do not have the reagents to express recombinant XPG in human cells. It is interesting that XPG was reported to associate with BRCA1, which also binds directly to CtIP, and to participate in some way in homologous recombination (11). We would like to know if that role and the role we are examining in this study require the nuclease activity; however, these authors reported that it is not possible to reconstitute the function of XPG with respect to homologous recombination using a transgene or overexpression so at this point we have not attempted this. It is worth trying in the future though.

Figure 5D: Does RNaseH expression in vivo and RNaseH treatment in vitro reduce the increased hybrid signal (which is actually very weak). This is an important control.

See point #1 above.

Figure 5E/F: What is the rationale for both increases and decreases in transcription overlapping with site of hybrid formation? I don't understand the implications of the RNA-seq data. Also, Figure 5F is missing in the Figure, making these data difficult to evaluate.

RNA-DNA hybrids and DNA breaks can cause both increases as well as decreases in transcription (12). Figure 5F does not appear to be missing.

Figure 5: What is the impact of CtIP and XPG loss, or loss of both, on the cell cycle. Are breaks or hybrid levels reduced due to alterations in cell cycle progression (e.g. failure to enter S phase) or accumulation in G2. It seems in WT cells hybrids are naturally higher in G2 and if breaks depend on S phase entry changes in cell cycle could affect the interpretation.

We have measured cell cycle progression in CtIP-depleted, XPG-depleted, and double-depleted cells and find that is not significantly different from wild-type (data not shown). We are not removing 100% of either of these factors, which may explain why we do not observe drastic changes in cell growth or cell cycle progression (Figure 4—Figure supplement 1 and Figure 4—Figure supplement 2).

Figure 6: Why are there no more breaks upon addition of CPT? Shouldn't the CPT itself lead to break formation even without the action of XPG and CtIP? Also, alkaline comet is not specific for SSB detection – these could be DSBs. I suggest the authors use caution in the way they present these data.

There are significantly more ssDNA breaks observed with CPT treatment in wild-type cells. We are showing the single-strand breaks here because we see an obvious change with DNA damage treatment and with the status of CtIP and XPG, whereas the neutral comet assay shows comparatively few breaks under the conditions used in these experiments. It is true that DSBs would also be evident in an alkaline comet assay but if this was the origin of the signal, they would be evident also in the neutral assay.

The idea that the R-loops are too small to be detected when both XPG and CtIP are lost is not well supported. Isn't it possible that there is no R-loop under these conditions and that RNAPII has simply stalled and is the toxic lesion?

Yes, this is possible. See discussion of this issue in the main text.

Can RNaseH expression rescue sensitivity due to loss of both XPG and CtIP? That is one test of this idea. Or can evidence for a smaller R-loops be obtained using bisulfite sequencing. Minimally I think other models should be considered.

We have not done RNaseH rescue of XPG+CtIP depletion. We discuss other scenarios in the main text.

[Editors' note: the author responses to the re-review follow.]

Summary:

Makharashvili et al., report a novel function for Sae2/CtIP in both yeast and human cells, and propose that Sae2/CtIP, known to promote resection during DSB repair, also contributes in R-loop (DNA-RNA hybrids) dissolution, in conjunction with XPG. In this revised version, the authors have addressed to a reasonable extent my main points. More specifically they are now consistent throughout the manuscript, and report Sae2 binding and R-loop accumulation in Sae2 deleted strain at the same loci. They have also now changed their discussion to take more hypotheses into account. They have also largely controlled their data by performing RNAseH treatment to validate their results obtained with S9.6 antibody. This manuscript is a significantly improved version of the previous one. Results are now clearer and convincing. However, the key conclusion of their model that CtIP cleaves the loop needs further support and clarification before acceptance.

Essential revisions:

The results on which the model proposed rely on CPT-treated cells (i.e. Figure 2A-E, Figure 4A-C, Figure 5F and Figure 8) (CPT creates ssDNA breaks with Top1-cc) or cells upon laser-induced breaks (i.e. Figure 4D-H). So, the experimental conditions used implies to start with a genotoxic-induced break. It is still therefore unclear why CtIP would be required for an additional break. Indeed, authors were not able to show the proposed activity of CtIP in vitro. Authors would need to show the action of CtIP in untreated cells (no CPT, no laser irradiation), with no break, to support their model that demands that CtIP cleaves the loop. The known action of the Sae2/CtIP nuclease activity on DNA resection as a requirement to remove the RNA-DNA hybrid accumulated at a break would make much more sense and fit better with the combined effect with XPG. Therefore, either authors provide new data with untreated cells to support their model as such or alternatively include in their model the breaks caused by CPT/laser irradiation to explain the role of CtIP under such conditions.

In the current version of the manuscript, we show that CtIP depletion in untreated cells generates accumulation of R-loops (as measured by mCherry-RnaseH FACS, Figure 5A, B and by S9.6 in Figure 5C,D,E). Figure 5B specifically shows the effect of the nuclease-deficient mutant in untreated cells. Also, our quantification of ssDNA breaks at the RPL13A locus in Figure 8D is in untreated cells.

The reviewers request that existing (or exogenously induced) DNA breaks be incorporated into the model, since some of our assays utilize agents that induce breaks and under these conditions, we observe an effect of Sae2/CtIP that relates to transcription-induced DNA damage.

We have incorporated a block with an adjacent nick into a revised version of the model in Figure 7. This version also shows the nucleic acids in a manner that is closer to the most recent structures of the elongating RNA polymerase holoenzyme (Ehara et al., 2017).

References:

H. Ehara et al., Structure of the complete elongation complex of RNA polymerase II with basal factors. Science. 357, 921–924 (2017).

https://doi.org/10.7554/eLife.42733.031

Article and author information

Author details

  1. Nodar Makharashvili

    1. Howard Hughes Medical Institute, The University of Texas at Austin, Austin, United states
    2. Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    No competing interests declared
  2. Sucheta Arora

    1. Howard Hughes Medical Institute, The University of Texas at Austin, Austin, United states
    2. Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Investigation, Methodology, Writing—review and editing
    Contributed equally with
    Yizhi Yin
    Competing interests
    No competing interests declared
  3. Yizhi Yin

    1. Howard Hughes Medical Institute, The University of Texas at Austin, Austin, United states
    2. Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Investigation, Methodology, Writing—review and editing
    Contributed equally with
    Sucheta Arora
    Competing interests
    No competing interests declared
  4. Qiong Fu

    Gastrointestinal Malignancy Section, Thoracic and Gastrointestinal Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Conceptualization, Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  5. Xuemei Wen

    Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  6. Ji-Hoon Lee

    Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7387-935X
  7. Chung-Hsuan Kao

    Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  8. Justin WC Leung

    Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, United States
    Contribution
    Investigation, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  9. Kyle M Miller

    Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Supervision, Validation, Writing—review and editing
    Competing interests
    No competing interests declared
  10. Tanya T Paull

    1. Howard Hughes Medical Institute, The University of Texas at Austin, Austin, United states
    2. Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Writing—original draft, Project administration, Writing—review and editing
    For correspondence
    tpaull@utexas.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2991-651X

Funding

Cancer Prevention and Research Institute of Texas (RP160667)

  • Nodar Makharashvili
  • Yizhi Yin

Howard Hughes Medical Institute

  • Sucheta Arora
  • Qiong Fu
  • Xuemei Wen
  • Ji-Hoon Lee
  • Chung-Hsuan Kao
  • Tanya T Paull

National Cancer Institute (K22CA204354)

  • Justin WC Leung

National Cancer Institute (R01CA198279)

  • Kyle M Miller

National Cancer Institute (RO1CA201268)

  • Kyle M Miller

American Cancer Society (RSG-16-042-01-DMC)

  • Kyle M Miller

Cancer Prevention and Research Institute of Texas (RP160667)

  • Tanya T Paull

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

Work in the TTP laboratory is supported in part by the Cancer Prevention and Research Institute of Texas (RP160667). The KMM laboratory is supported by the NIH National Cancer Institute (R01CA198279 and RO1CA201268) and the American Cancer Society (RSG-16-042-01-DMC). The work of Justin Leung is supported by the NIH National Cancer Institute (K22CA204354). We thank Steve Hanes, Nicholas Proudfoot, Jeff Corden, John Petrini, Hannah Klein, Lorraine Symington, Jim Haber, Michael Lieber, Steve Jackson, Patrick Calsou, Eric Campeau, and Paul Kaufman for reagents including yeast strains and plasmids.

Senior Editor

  1. Jessica K Tyler, Weill Cornell Medicine, United States

Reviewing Editor

  1. Andrés Aguilera, CABIMER, Universidad de Sevilla, Spain

Publication history

  1. Received: October 11, 2018
  2. Accepted: November 30, 2018
  3. Accepted Manuscript published: December 7, 2018 (version 1)
  4. Version of Record published: December 17, 2018 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 1,231
    Page views
  • 241
    Downloads
  • 1
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Chromosomes and Gene Expression
    2. Stem Cells and Regenerative Medicine
    Jeroen Witteveldt et al.
    Research Article Updated
    1. Chromosomes and Gene Expression
    2. Structural Biology and Molecular Biophysics
    David Trombley McSwiggen et al.
    Research Article Updated