Topoisomerase 1-dependent R-loop deficiency drives accelerated replication and genomic instability

Article Topoisomerase 1-dependent R-loop deficiency drives accelerated replication and genomic instability Graphical abstract Highlights dIncreased TOP1 expression by mutated RAS reduces R loops dLow R-loop levels promote accelerated replication and DNA damage dTOP1 restoration or mild replication inhibition rescue DNA acceleration and damage dHigh TOP1 expression is associated with replication mutagenesis in cancer Authors Dan Sarni, Sonia Barroso, Alon Shtrikman, Michal Irony-Tur Sinai, Yifat S. Oren, Andre ´s Aguilera, Batsheva Kerem Correspondence [email protected] In brief TOP1 deficiency increases R loops driving replication stress characterized by slow replication and DNA damage. Sarni et al. reveal that HRAS increases TOP1 and reduces R loops, causing accelerated replication and DNA damage, highlighting the importance of TOP1 equilibrium in regulating R-loop homeostasis to ensure faithful replication and genome integrity. Sarni et al., 2022, Cell Reports 40, 111397 September 27, 2022 ª2022 The Author(s). https://doi.org/10.1016/j.celrep.2022.111397 ll Article Topoisomerase 1-dependent R-loop deficiency drives accelerated replication and genomic instability Dan Sarni, 1 Sonia Barroso, 2 Alon Shtrikman, 1 Michal Irony-Tur Sinai, 1 Yifat S. Oren, 1 Andre ´s Aguilera, 2 and Batsheva Kerem 1,3, * 1 Department of Genetics, The Life Sciences Institute, The Hebrew University, Jerusalem 91904, Israel 2 Department of Genome Biology, Andalusian Center of Molecular Biology and Regenerative Medicine CABIMER, Seville Universidad de Sevilla-CSIC-Universidad Pablo de Olavide, Seville, Spain 3 Lead contact *Correspondence: batsheva[email protected] https://doi.org/10.1016/j.celrep.2022.111397 SUMMARY DNA replication is a complex process tightly regulated to ensure faithful genome duplication, and its perturbation leads to DNA damage and genomic instability. Replication stress is commonly associated with slow and stalled replication forks. Recently, accelerated replication has emerged as a non-canonical form of replication stress. However, the molecular basis underlying fork acceleration is largely unknown. Here, we show that mutated HRAS activation leads to increased topoisomerase 1 (TOP1) expression, causing aberrant replication fork acceleration and DNA damage by decreasing RNA-DNA hybrids or R-loops. In these cells, restoration of TOP1 expression or mild replication inhibition rescues the perturbed replication and reduces DNA damage. Furthermore, TOP1 or RNaseH1 overexpression induces accelerated replication and DNA damage, highlighting the importance of TOP1 equilibrium in regulating R-loop homeostasis to ensure faithful DNA replication and genome integrity. Altogether, our results dissect a mechanism of oncogene-induced DNA damage by aberrant replication fork acceleration. INTRODUCTION DNA replication is a complex process that is tightly regulated to ensure faithful duplication of the genome. Various factors are involved in regulating replication, including origin licensing and firing, replication elongation rate, and termination (Conti et al., 2007;Fragkos et al., 2015). Under conditions that slow or stall replication fork progression (defined as replication stress), dormant origins are activated to allow completion of DNA synthesis to maintain genome integrity (Courbet et al., 2008;Ge et al., 2007). However, insufficient compensation of the perturbed DNA replication may lead to genome instability (Gaillard et al., 2015;Zeman and Cimprich, 2014). Several factors lead to replication stress, among them nucleotide deficiency, accumulation of RNA-DNA hybrids and DNA lesions (Gaillard et al., 2015;Zeman and Cimprich, 2014), all of which result in perturbed replication dynamics and increased genomic instability. Genomic instability is a hallmark of cancer and a driver of tumorigenesis (Hanahan and Weinberg, 2011;Negrini et al., 2010). Aberrant activation of oncogenes and tumor suppressor genes induces replication stress, leading to accumulation of DNA damage and an increased tumorigenicity potential (Bartkova et al., 2006;Bester et al., 2011;Dominguez-Sola et al., 2007;Galanos et al., 2016;Di Micco et al., 2006). This stress is characterized by slow replication rate, fork stalling, activation of dormant origins, and even re-replication. However, several studies have found accelerated replication rates following alterations in expression of various genes including overexpression (OE) of the oncogene Spi-1 (Rimmele et al., 2010) and the cancer-associated gene ISG15 (Raso et al., 2020), downregulation of mRNA biogenesis genes involved in mRNA processing and export (Bhatia et al., 2014;Domı ´nguez-Sa ´nchez et al., 2011; Salas-Armenteros et al., 2017), depletion of origin-firing factors (Sedlackova et al., 2020;Zhong et al., 2013), and inhibition of poly(ADP-ribose) polymerase (PARP) (Maya-Mendoza et al., 2018;Sugimura et al., 2008). In most of these studies, accelerated replication was accompanied by DNA damage. However, whether the accelerated replication rate induces DNA damage, per se, and the molecular mechanism(s) underlying fork acceleration are largely unknown. Here, we show that activation of the mutated HRAS (RAS) oncogene in pre-senescent cells increases topoisomerase 1 (TOP1) levels, leading to replication fork acceleration and DNA damage by decreasing R-loop levels. Restoration of TOP1 expression or mild replication inhibition in RAS-expressing cells restores normal R-loop levels, rescues the perturbed replication, and reduces DNA damage. We further show that OE of TOP1 causes aberrant replication fork acceleration and DNA damage, similar to the effect of TOP1 increase by RAS. Degradation of Rloops by OE of RNaseH1, independent of TOP1 OE, also Cell Reports 40, 111397, September 27, 2022 ª2022 The Author(s). 1 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ll OPEN ACCESS AB CD EG I FHJ (legend on next page) 2Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS accelerates DNA replication and generates DNA damage. These results highlight the important role of TOP1 in maintaining genome stability by controlling R-loop homeostasis, enabling tight regulation of DNA replication fork progression. Additionally, high TOP1 expression in tumors is associated with replicationinduced mutations, suggesting that TOP1-induced accelerated replication may promote mutagenesis. Altogether, the results of our study reveal a novel mechanism of oncogene-induced DNA damage induced by aberrant replication fork acceleration. RESULTS RAS expression induces replication acceleration in presenescent cells RAS proteins (HRAS, KRAS, NRAS) are members of a GTP-binding protein family (Pylayeva-Gupta et al., 2011), regulating numerous cellular processes including cell-cycle progression (Downward, 2003). Mutated RAS expression induces genomic instability leading to senescence, an antitumor cell-cycle arrest state (Denko et al., 1994;Saavedra et al., 2000;Yang et al., 2013). However, cells escaping this proliferation inhibition drive tumorigenesis (Halazonetis et al., 2008). Therefore, we first investigated the effect of RAS on DNA replication dynamics in pre-senescent cells. For this, immortalized human foreskin fibroblasts were retrovirally infected with an inducible ER: HRAS-G12V vector (RAS). RAS selective expression following 4-hydroxytamoxifen (4-OHT) supplementation was verified by western blot (Figures 1A and S1A). Following RAS activation, cells entered a hyperproliferative phase, as indicated by increased population doubling and IdU incorporation already at day 2 (Figures S1B–S1D). This was followed by a decline in the proliferative potential until proliferation ceased by day 10, when cells entered senescence, as indicated by reduced population doublings, reduced IdU incorporation, and increased senescence associated b-gal activity (Figures S1B–S1F). Hence, the effect of RAS activation on replication dynamics and genome stability was investigated in pre-senescence RAS-expressing cells up to 5 days following RAS induction. We then analyzed the effect of RAS activation on replication dynamics using DNA combing, which enables replication analysis of single DNA molecules (Figure 1B). The analysis showed a remarkable increase in the mean replication rate on both days 2 and 5, following RAS activation (Figure 1C). Similar results were obtained in another cell line of fetal human lung fibroblasts, WI-38 (Figures S1G and S1I). Previous studies have shown that slowed replication is correlated with an increased number of activated origins (Courbet et al., 2008;Ge et al., 2007). Therefore, we investigated origin activation in RAS-expressing cells. Analysis of the mean replication fork distance showed a significant increase on both days 2 and day 5 following RAS activation (Figure S1H). Similar results were obtained in WI-38 cells (Figure S1J). These results indicate that in pre-senescent RAS-expressing cells, there was a significant increase in the rate of replication along with a decrease in local origin activation. Fork stalling induced by replication stress manifests as asymmetrical progression of sister forks emanating from the same origin (Conti et al., 2007). In order to further characterize the accelerated replication rate following RAS expression, we compared the progression of left and right outgoing sister replication forks. The analysis showed no significant decrease in fork symmetry following RAS expression on both days 2 and 5 compared with control cells (Figure 1D), indicating no increase in fork stalling. Similar results were obtained in WI-38 cells (Figure S1K). Altogether, these results indicate a non-classical form of aberrant replication dynamics in pre-senescent RAS-expressing cells, exhibited by accelerated replication and decreased origin activation. This aberrant acceleration was observed both in the hyperproliferative phase (day 2) and shortly before cells senesce (day 5). RAS leads to accelerated replication-induced DNA damage Slow replication rate, induced by oncogenes, including mutated RAS OE, generates DNA damage and activates damage response pathways (Abulaiti et al., 2006;Aird et al., 2013;Kotsantis et al., 2016;Macheret and Halazonetis, 2015). In order to determine whether RAS-induced fork acceleration causes DNA damage, we examined cellular DNA damage response markers known also to be induced under replication stress (Ewald et al., 2007). We first analyzed DNA damage by co-localization of phosphorylated H2AX (gH2AX) and 53BP1 foci. The Figure 1. RAS expression leads to increased replication rate and DNA damage (A) Protein levels of HRAS and GAPDH in FSE-hTert cells with (+) or without () ER:RAS infection and 5 day 4-OHT treatment, as indicated. (B) Scheme of the protocol and exemplary images of DNA combing. (C) Fork rate (kb/min) in control and RAS-expressing cells for 2 or 5 days; at least 240 fibers per condition were analyzed. (D) Sister fork symmetry in control and RAS-expressing cells for 2 or 5 days; at least 100 fibers per condition were analyzed. Dashed green line indicates asymmetry ratio threshold. (C and D) Red lines indicate medians, and means are indicated. Data for RAS day 2 are the summary of 2 independent experiments; data for RAS day 5 are the summary of 4 independent experiments. Mann-Whitney rank-sum test. (E and F) Co-localization of gH2AX (red) and 53BP1 (green) foci in control and RAS-expressing cells for the indicated time points (days). Representative images (E), and percentage of cells with indicated number of co-localized gH2AX and 53BP1 foci per nucleus (F); at least 380 nuclei per condition were analyzed. Data are the summary of three independent experiments. p values were calculated compared with control (Ctrl) by one-way ANOVA. (G and H) 53BP1 NBs (green) in G1-phase (cyclin A negative, red) cells, as indicated in (A). Representative images (G), and percentage of cells with indicated number of NBs per nucleus (H); at least 85 nuclei per condition were analyzed. Only NBs >1 mm in diameter were scored. p values were calculated compared with RAS. Data are representative of three independent experiments with similar results. (I) An exemplary image of a metaphase spread in RAS cells; red arrow indicates a break. (J) Quantification of chromosomal aberrations detected in metaphase spreads of RAS cells (n = 120) or Ctrl cells (n = 155). Data are from two independent experiments, and means ±SEM are shown. ns, non-significant; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Scale bars, 10 mm. Cell Reports 40, 111397, September 27, 2022 3 Article ll OPEN ACCESS analysis showed a significant increase in DNA damage already on day 2 post RAS activation (Figures 1E and 1F), when aberrant accelerated replication is already found (Figure 1C). Interestingly, the levels of DNA damage markers increased in these cells over time (Figures 1E and 1F), implying that the accumulation of unrepaired damage may lead to cell-cycle arrest (Bartkova et al., 2006;Halazonetis et al., 2008;Di Micco et al., 2006). Next, we investigated whether the observed damage is associated with replication stress, known to induce DNA lesions that manifest as nuclear bodies (NBs) of 53BP1 in the G1 phase of the next cell cycle (Lukas et al., 2011). Analysis of 53BP1 NBs (>1 mmin diameter) in G1-phase cells (cyclin A negative) showed a significant increase in NB formation in RAS-expressing cells compared with control cells (Figures 1G and 1H). In contrast to large 53BP1 NBs, small 53BP1 foci were reported to form at double-strand breaks (DBSs) irrespectively of replication stress (Palmerola et al., 2022;Schultz et al., 2000). Interestingly, analysis of small 53BP1 foci (<1 mm in diameter) in G1 cells showed an increase in foci formation in RAS-expressing cells (Figures S2A and S2B), suggesting that RAS induced both replicative and non-replicative DNA damage. Furthermore, we found in RAS-expressing cells a significant increase in gH2AX, a DNA damage marker also induced upon replication stress (Figures S2C and S2D) (Ewald et al., 2007). Next, we analyzed whether RAS activation leads to the expression of fragile sites, hotspots of genomic instability. These sites are sensitive to replication stress conditions, as they fail to complete DNA replication, leaving underreplicated regions that manifest as chromosomal breaks in metaphase chromosomes (Glover et al., 1984;Miron et al., 2015). Metaphase spread analysis showed a significant increase in chromosomal fragility in RAS-expressing cells (Figures 1I and 1J), implying that the replication perturbation induced by RAS generates replication-induced genomic instability. We then tested CHK1 phosphorylation, a hallmark of the replication stress response (Zeman and Cimprich, 2014). A significant increase in CHK1 phosphorylation was found in RAS-expressing cells (Figures S2E and S2F). Overall, these results suggest that the RAS-induced DNA damage is associated with aberrant acceleration of DNA replication. Reducing the accelerated replication fork progression rescues the DNA damage phenotype We next investigated whether accelerated replication could be the cause for DNA damage in RAS-expressing pre-senescent cells. For this, we treated RAS-cells with hydroxyurea (HU), an inhibitor of replication fork progression, to slow the accelerated replication and analyzed its effect on DNA damage. HU inhibits the ribonucleotide reductase (RNR), thus reducing the deoxyribonucleotide pool, resulting in reduced replication rates in a dose-dependent manner (Ge and Blow, 2010;Skoog and Nordenskjo ¨ld, 1971;Te ´cher et al., 2016). Whereas high doses of HU (R1 mM) lead to fork arrest, low doses (%0.1 mM) decelerate replication fork rate (Koundrioukoff et al., 2013;Te ´cher et al., 2016). Therefore, we used relatively low HU concentrations and analyzed their effect on the replication dynamics. Cells expressing RAS for 5 days were treated with 0.001–0.1 mM HU for 48 h prior to the analysis, which allowed the cells to go through at least one cell cycle under inhibitory conditions (Figure 2A). Flow cytometry analysis showed no significant change in the cell-cycle progression, indicating that HU treatment did not arrest cell proliferation (Figures S3A and S3B). DNA combing analysis revealed that mild replication inhibition of RAS cells with 0.01 mM HU resulted in a dramatic fork deceleration compared with non-treated RAS cells (Figure 2B). The mean rate in these HU-treated RAS cells showed no significant difference compared with control cells, indicating restoration of replication fork rate (Figure 2B). This HU concentration also led to a reduction in the fork distance in RAS-expressing cells to the normal distance observed in the control cells (Figure 2C). Finally, 0.01 mM HU treatment did not induce sister fork asymmetry in RAS-expressing cells, indicating that this low HU concentration did not induce fork stalling (Figure 2D). These results indicate that mild replication inhibition in RAS-expressing cells rescued the perturbed DNA replication, resulting in the restoration of normal replication dynamics. Next, we investigated whether the replication rate restoration affected RAS-induced DNA damage. For this, cells were treated with 0.01 mM HU for 48 h prior to DNA damage analysis by immunofluorescence detection of co-localized gH2AX and 53BP1 foci. Mild HU treatment in control cells did not lead to DNA damage induction (Figure S3C). However, 0.01 mM HU treatment led to a significant decrease in the number of RASinduced damage foci compared with non-treated RAS-expressing cells (Figures 2E and 2F). It is worth noting that the highest HU concentration (0.1 mM) used decreased dramatically the replication rate even when compared with control cells (Figure 2B) and led to increased DNA damage compared with non-treated RASexpressing cells (Figures 2E and 2F). A considerably lower dose of HU (0.001 mM) had a limited, non-significant effect on the replication rate (Figure 2B) and, as expected, had no significant effect on DNA damage formation compared with RAS-expressing cells not treated with HU (Figures 2E and 2F). Altogether these results indicate that restoration of the accelerated replication rate dramatically reduced the DNA damage in RAS-expressing cells. We further investigated the effect of replication restoration on DNA damage by examining the effect of aphidicolin (APH), another replication inhibitor, which inhibits DNA polymerases a,d, and εand decreases fork progression in a dose-dependent manner (Cheng and Kuchta, 1993;Ikegami et al., 1978). RAS-expressing cells were treated with relatively low APH concentrations for 48 h prior to replication dynamics and DNA damage analyses. Flow cytometry analysis showed no significant change in cell-cycle progression, indicating that like HU, APH treatment did not arrest cell proliferation (Figures S3A and S3B). Co-localization analysis of gH2AX and 53BP1 foci revealed that a low dose of 0.01 mM APH significantly decreased the number of damage foci in RAS-expressing cells compared with non-treated RAS cells (Figures S3D and S3E), while it had no effect on the level of the damage markers in control cells (Figure S3C). Furthermore, similar to the effect of various HU concentrations, a very low dose of APH (0.001 mM) did not have a significant effect on DNA damage in RAS-expressing cells compared with non-treated RAS-expressing cells (Figure S3E); by contrast, a high dose of 0.1 mM APH induced DNA damage (Figure S3E). Finally, we investigated whether the DNA damage rescue by 4Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS the 0.01 mM APH treatment was associated with replication restoration. As expected, DNA combing analysis showed restoration of the replication dynamics by the APH treatment (Figures S3F–S3H), altogether suggesting that accelerated replication generates DNA damage. Excess TOP1 causes accelerated replication rate and DNA damage in RAS-expressing cells To explore the molecular mechanism/s underlying the accelerated replication in RAS cells, we examined the differences in gene expression after mutated RAS activation. For this, we performed RNA sequencing (RNA-seq) analysis on control and RAS-expressing cells at two time points, at 2 and 4 days post RAS activation, when cells are proliferating. Principal-compoAB CD EF Figure 2. Mild replication inhibition restores normal replication dynamics and rescues DNA damage (A) Scheme of the protocol. Replication and damage analysis in RAS cells ±HU treatment, as indicated. (B–D) DNA combing analysis of Ctrl and RAS cells ± HU treatment, as indicated. (B) Fork rate (kb/min); at least 300 fibers per condition were analyzed. (C) Fork distance (kb); at least 150 forks per condition were analyzed. (D) Sister fork symmetry; at least 110 forks per condition were analyzed. Means are indicated, and red lines indicate medians. p values were calculated compared with Ctrl by one-way ANOVA. Data are the summary of two independent experiments. (D) Dashed green line indicates asymmetry ratio threshold. (E and F) Co-localization of gH2AX (red) and 53BP1 (green) foci, as indicated in (B). Representative images (E), and percentage of cells with indicated number of foci per nucleus (F); at least 190 nuclei per condition were analyzed. Data are representative of two independent experiments with similar results. p values were calculated compared with RAS cells by Mann Whitney rank-sum test. ns, nonsignificant; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Scale bars, 10 mm. nent analysis showed that the expression profiles of RAS cells clustered together and were distinguishable from control cells (Figure S4A). After RAS activation, >1,700 genes were differentially expressed, with an estimated false discovery rate (FDR) of <5% and a fold change >2-fold (Figure S4B). Gene Ontology (GO) annotation analysis of the upregulated genes following RAS activation (shared at both time points, 282 genes) showed enrichment for signaling and developmental processes (Figure S4C). Among the shared downregulated genes (568 genes) in RAS cells, GO annotation analysis identified enrichment of anatomical and developmental processes (Figure S4C). DNA replication was not found among the GO annotations significantly enriched after RAS activation. Therefore, we next focused on individual DNA replication annotated genes (GO: 0006260) to identify specific differentially expressed genes in RAS compared with control cells, which could lead to dysregulation of the replication process. Previously, deregulation of origin firing factors such as CDC7,ORC1,MCM4, MCM6,Treslin, and MTBP have been shown to lead to an increased replication rate in various organisms (Flach et al., 2014;Maya-Mendoza et al., 2018;Sedlackova et al., 2020; Zhong et al., 2013). However, our analysis showed no significant change in the expression level of any of these genes or other origin licensing or firing genes (Figure 3A; Table S1), suggesting that in our system, the accelerated replication rate was not the result of a decreased origin usage. Cell Reports 40, 111397, September 27, 2022 5 Article ll OPEN ACCESS AB D C EF GH I J Figure 3. Increased TOP1 expression causes accelerated DNA replication and DNA damage (A) Expressed DNA replication annotated genes (GO: 0006260, n = 258) ranked according to the RAS/Ctrl fold change. Light blue, genes previously associated with accelerated replication; red, TOP1. (B) Protein levels of TOP1 and Tubulin in Ctrl and RAS cells, as indicated. (legend continued on next page) 6Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS Analysis of replication annotated genes identified only five genes upregulated by at least 2-fold following RAS activation: E2F7,EREG,EGFR,HMGA1, and TOP1 (Figures 3A; Table S1). Interestingly, TOP1 downregulation was reported to reduce replication fork rate and induce DNA damage (Promonet et al., 2020;Tuduri et al., 2009). TOP1 is an essential protein in mammalian cells that resolves DNA torsional stress induced during replication and transcription (Pommier, 2006;Pommier et al., 2016). Therefore, we set to investigate the role of elevated TOP1 in regulation of accelerated DNA replication. First, we validated the increased level of TOP1 in RAS cells by western blot and qRT-PCR (Figures 3B and S5A). We then explored the relevance of TOP1 OE for cancer. Analysis of The Cancer Genome Atlas (TCGA) datasets revealed a 2-fold increase in TOP1 in 9/33 cancer types, as found in our RASinduced system (Figure S5B). Interestingly, the expression of NRAS is also significantly increased in all 9 cancer types (Figure S5B). We further identified that TOP1 and NRAS expression was positively correlated in 8/9 cancer types (Figure S5C), further supporting the possible link between RAS activation and TOP1 OE. It is worth noting that in cancers, the expression of each RAS family gene member is not necessarily correlated with each other, potentially due to their redundant function (Stephens et al., 2017). Indeed, our TCGA analysis showed no significant change in the expression of KRAS or HRAS in most of the 9 cancer types in which TOP1 and NRAS are increased (Figure S5B), thus suggesting that each RAS member may increase TOP1 expression. We then looked for possible transcription factors that can bind the promoter of TOP1 and contribute to its increased expression in four separate transcription factor binding databases, ChIP Enrichment Analysis (CHEA), Encyclopedia of DNA Elements (ENCODE), MotipMap, and TRANSFAC, and found one transcription factor shared between all four databases, MYC (Figure S5D; Table S2). Interestingly, the expression of MYC is significantly increased in 7/9 TCGA cancer types in which TOP1 is increased (Figure S5B). Accordingly, in our RAS-expressing cells MYC was overexpressed compared with control cells (Figure S5E). These results are in agreement with previous studies showing that RAS upregulates the expression of MYC (Kerkhoff et al., 1998) and enhances MYC protein stability (Sears et al., 1999). Furthermore, a recent report found that MYC recruits TOP1 to actively transcribed genes and stimulates its activity (Das et al., 2022), thus supporting the hypothesis that OE of RAS increases the expression and activity of MYC, which subsequently contributes to the activation of TOP1 transcription and to its activity at transcribed genes. To explore the effect of excess TOP1 levels on replication dynamics and DNA damage, we first restored normal TOP1 level in RAS-expressing cells by moderate downregulation of TOP1 using low concentrations of two independent small interfering RNAs (siRNAs) (Figures 3C and 3D). We then examined the effect of TOP1 restoration on replication dynamics. The analysis showed that TOP1 restoration significantly reduced the replication rate in siTOP1-treated RAS-expressing cells compared with control siRNA-treated RAS cells (Figure 3E), which was indistinguishable from the rate of the control cells, indicating complete restoration of a normal replication rate (Figure 3E). TOP1 restoration also significantly reduced the fork distance in siTOP1treated RAS cells compared with control siRNA-treated RAS cells (Figure S6A), indicating restoration of the replication dynamics. Finally, TOP1 restoration did not affect sister fork symmetry (Figure S6B). Downregulation of TOP1 in control cells using the same low concentrations of siTOP1 led to significant reduction in replication rate and fork distance compared with treatment with a control siRNA (Figures S6C–S6E), in agreement with previous results (Promonet et al., 2020;Tuduri et al., 2009). Furthermore, downregulation of TOP1 in control cells significantly reduced the sister forks symmetry ratio (Figure S6F) and increased DNA damage (Figure S6G), suggesting that deficit in TOP1 leads to classical replication stress, whereas excess TOP1 drives a non-canonical form of replication stress characterized by fork acceleration. We further investigated the effect of TOP1 restoration on RASinduced DNA damage. Analysis of gH2AX foci showed a significant decrease in damage foci following TOP1 downregulation in RAS cells compared with control siRNA-treated RAS cells (Figure 3F), indicating that restoration of TOP1 to the normal level of control cells rescues DNA damage. Altogether, these results suggest that regulated TOP expression1 is crucial since both increased and decreased TOP1 levels are deleterious to cells. Reduced TOP1-dependent R-loops promote accelerated replication and DNA damage To test our hypothesis that excess TOP1 accelerates replication rate leading to DNA damage, we overexpressed TOP1 in HEK293 cells, in which RAS expression was not affected (Figure 3G), and analyzed its effect on replication dynamics. TOP1 OE significantly increased the mean replication rate (Figure 3H) and, accordingly, increased the fork distance (Figure S6H). Fork (C) Protein levels of TOP1 and GAPDH in Ctrl and RAS cells treated with two independent siRNAs against TOP1 (siTOP1-1 and siTOP1-2) or non-targeting siRNA (siCtrl), as indicated. (D) qRT-PCR of TOP1 normalized to GAPDH in RAS cells treated with siTOP1, as indicated. The values are averaged fold change (mean ±SEM, n = 2) relative to Ctrl (non-RAS) cells treated with siCtrl. (E) Fork rate (kb/min) of cells, as indicated in (C); at least 270 fibers per condition were analyzed. Means are indicated, and red lines indicate medians. p values were calculated by one-way ANOVA. Data are the summary of two independent experiments. (F) Percentage of cells with the indicated number of gH2AX foci in cells, as indicated in (C); at least 1,000 nuclei per condition were analyzed. p values were calculated compared with siCtrl RAS cells. Data are representative of three independent experiments. (G) Protein levels of endogenous TOP1 (TOP1), ectopic TOP1 (TOP1-GFP), RAS, and GAPDH in HEK-293 cells transfected with a control GFP vector (Ctrl) or with TOP1-GFP (TOP1), as indicated. (H) Fork rate (kb/min) of HEK-293 cells, as indicated in (G); at least 400 fibers per condition were analyzed. (I and J) 53BP1 (green) foci in HEK-293 cells, as indicated in (G). Representative images (I). Percentage of cells with indicated number of foci (J). At least 300 nuclei were analyzed. Data are representative of two independent experiments. ns, non-significant; ****p < 0.0001. Scale bars, 10 mm. Cell Reports 40, 111397, September 27, 2022 7 Article ll OPEN ACCESS AC BD EF Figure 4. Elevated TOP1 reduces R-loop accumulation (A and B) RNA-DNA hybrids in HEK-293 cells transfected with a control GFP vector (Ctrl) or with TOP1-GFP (TOP1), treated with (+) RNase III and with (+) or without () RNaseH1, as indicated. Representative images of RNA-DNA antibody (S9.6, red), nucleolin (green), and DAPI (blue) staining (A). Mean nuclear fluorescence intensity of RNA-DNA hybrid antibody (S9.6) after nucleolar signal removal (B). At least 600 nuclei were analyzed. Data are summary of two independent experiments. (C and D) RNA-DNA hybrids in ER:RAS FSE hTert cells with (RAS) or without (Ctrl) 4-OHT treatment treated with RNaseIII and RNaseH1, as indicated. Representative images, staining as in (A) (C). Mean nuclear fluorescence intensity of RNA-DNA hybrids (S9.6 antibody) after nucleolar signal removal in Ctrl and RASexpressing cells for 2 or 5 days (D). (legend continued on next page) 8Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS Another possible factor is the use of different cellular systems with different genetic backgrounds. It is well established that there is accumulation of genetic changes during cell culturing of cancer cell lines, leading to variations in gene-expression patterns that may differently affect the replication dynamics and DNA damage (Ben-David et al., 2018;Kim et al., 2017;Weissbein et al., 2014). Altogether, the plasticity of RAS-induced replication stress found in different studies suggests that the genetic background of oncogenic cells may affect the phenotype and hence should be reflected in the treatment for patients with cancer. Altogether, our results indicate that TOP1 is a crucial factor for genome integrity, by tightly regulating replication dynamics. This further highlights the importance of TOP1-dependent R-loop homeostasis in replication regulation, as unbalanced levels alter replication dynamics and promote genomic instability (Figure S8C). These results are highly important for understanding early events leading to cancer development, as different mechanisms may underlie the oncogene-induced replication perturbation driving genomic instability. They reveal the complex nature of oncogene-induced replication stress, which should be taken into consideration when replication inhibitors are considered as a therapeutic tool for cancer (Keller et al., 2022). STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: dKEY RESOURCES TABLE dRESOURCE AVAILABILITY BLead contact BMaterials availability BData and code availability dEXPERIMENTAL MODEL AND SUBJECT DETAILS BCell Culture BPlasmids dMETHOD DETAILS BReplication dynamics using DNA combing BImmunofluorescence staining BMetaphase chromosome preparation and fragile site analysis BWestern blot analysis BPopulation doublings BRNA sequencing analysis BGene correlation analysis in GEPIA BRNA analysis BsiRNA BCell cycle analysis BDRIP-qPCR BAlkaline gel electrophoresis BMutation analysis BViability assay dQUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. celrep.2022.111397. ACKNOWLEDGMENTS This research was supported by grants from the Israel Science Foundation (grant nos. 176/11 and 1284/18), the Israeli Centers of Research Excellence (I-CORE), and Gene Regulation in Complex Human Disease, Center No. 41/ 11, and by the ISF-NSFC joint program (grant no. 2535/16) to B.K. and by grants from the Agencia Estatal de Investigacio ´n from the Spanish Ministry of Science and Innovation (PID2019-104270GB-I00/BMC), the European Research Council (ERC2014 AdG669898 TARLOOP), the European Union (FEDER), and the Foundation ‘‘Vencer el Cancer’’ to A.A. The authors thank Dr. Naomi Melamed-Book for her assistance in confocal microscopy and the Mantoux Bioinformatics Institute of the Nancy and Stephen Grand Israel National Center for Personalized Medicine, Weizmann Institute of Science, for assistance in deep sequencing and bioinformatics analysis. The authors thank the members of the Kerem lab for thoughtful discussions and advice. AUTHOR CONTRIBUTIONS Conceptualization, D.S. and B.K.; methodology, D.S., A.A., and B.K.; investigation, D.S., S.B., A.S., M.I.-T.S., Y.S.O., A.A., and B.K.; visualization, D.S. and B.K.; writing – original draft, D.S. and B.K.; writing – review & editing, D.S., M.I.-T.S., A.A., and B.K.; funding acquisition, A.A. and B.K. DECLARATION OF INTERESTS The authors declare no competing interests. Received: March 5, 2022 Revised: June 26, 2022 Accepted: August 31, 2022 Published: September 27, 2022 REFERENCES Abulaiti, A., Fikaris, A.J., Tsygankova, O.M., and Meinkoth, J.L. (2006). Ras induces chromosome instability and abrogation of the DNA damage response. Cancer Res. 66, 10505–10512. https://doi.org/10.1158/0008-5472.CAN-062351. Aird, K.M., Zhang, G., Li, H., Tu, Z., Bitler, B.G., Garipov, A., Wu, H., Wei, Z., Wagner, S.N., Herlyn, M., et al. (2013). Suppression of nucleotide metabolism underlies the establishment and maintenance of oncogene-induced senescence. 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Cell Biol. 201, 373–383. https://doi.org/10.1083/jcb.201208060. 18 Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS STAR+METHODS KEY RESOURCES TABLE REAGENT or RESOURCE SOURCE IDENTIFIER Antibodies Mouse anti-BrdU BD Biosciences Cat# 347580; AB_10015219 Goat anti-mouse Alexa Fluor 488 Invitrogen Cat# A11001; AB_2534069 Rat anti-BrdU Abcam Cat# ab6326; AB_305426 Goat anti-rat Alexa Fluor 594 Invitrogen Cat# A11007; AB_10561522 Mouse anti-ssDNA Millipore Cat# MAB3034; AB_11212688 Donkey anti-mouse Alexa Fluor 647 Invitrogen Cat# A31571; AB_162542 Mouse anti-phosphorylated H2AX (Ser 139) Millipore Cat# 05-636; AB_309864 Rabbit anti-53BP1 Bethyl Laboratories Cat# A300-272A; AB_185520 Mouse anti-cyclin A2 Abcam Cat# ab16726; AB_302478 Mouse anti-S9.6 Kerafast Cat# ENH001; AB_2687463 Rabbit anti-nucleolin Abcam Cat# ab22758; AB_776878 Donkey anti-rabbit Alexa Fluor 488 Abcam Cat# ab150065; AB_2860569 Goat anti-mouse Alexa Fluor 555 Invitrogen Cat# A21422; AB_2535844 Rabbit anti-HRAS Santa Cruz Cat# sc-520; AB_631670 Mouse anti-Chk1 Cell Signaling Cat# 2360S Rabbit anti-phosphorylated chk1 (S345) Cell Signaling Cat# 2348S Rabbit anti-GAPDH Cell Signaling Cat# 2118S Mouse anti-beta Catenin BD Biosciences Cat# 610153; AB_397554 Mouse anti-Tubulin Sigma Cat# T5168; AB_477579 Mouse anti-beta Actin Santa Cruz Cat# sc-69879; AB_1119529 Rabbit anti-Topoisomerase 1 Abcam Cat# ab109374; AB_10861978 Rabbit anti-RNaseH1 Abcam Cat# ab229078 Mouse anti-TDP1 Santa Cruz Cat# sc-365674; AB_10847225 Mouse anti-SRSF1 Santa Cruz Cat# sc-33652; AB_628248 Donkey anti-rabbit HRP Jackson ImmunoResearch Cat# 711-035-152; AB_10015282 Donkey anti-mouse HRP Jackson ImmunoResearch Cat# 715-035-150; AB_2340770 Chemicals, peptides, and recombinant proteins 4-hydroxytamoxifen (4-OHT) Sigma Cat# H7904 Guanosine Sigma Cat# G6752 Uridine Sigma Cat# U3750 Cytidine Sigma Cat# C4654 Adenosine Sigma Cat# A9251 Aphidicolin (APH) Sigma Cat# A0781 Hydroxyurea (HU) Sigma Cat# H8627 IdU Sigma Cat# I7125 CldU Sigma Cat# C6891 RNase III New England Biolabs Cat# MO245S RNaseH1 New England Biolabs Cat# MO297L VECTASHILED Antifade mounting medium with DAPI Vector Laboratories Cat# H-1200 Colcemid Biological Industries Cat# 12-004-1D EZ-ECL SARTORUS Cat# 20500120 Oligofectamine Invitrogen Cat# 12252-011 Lipofectamine 2000 Invitrogen Cat# 11668-027 RNase A Sigma Cat# R6513 (Continued on next page) Cell Reports 40, 111397, September 27, 2022 e1 Article ll OPEN ACCESS RESOURCE AVAILABILITY Lead contact Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Batsheva Kerem ([email protected]). Continued REAGENT or RESOURCE SOURCE IDENTIFIER RNaseH2 Dr. Andrew Jackson N/A Proteinase K Sigma Cat# P2308 SYBER Gold Invitrogen Cat# S11494 Camptothecin (CPT) Sigma Cat# C9911 Critical commercial assays Fiber-Prep kit Genomic Vision Cat# EXTR-001 Fiber-Comb kit Genomic Vision Cat# MSC-001 Crystal violet assay kit Abcam Cat# ab121855 Deposited data Raw and analyzed RNA-seq data This paper GSE168738 Experimental models: Cell lines FSE hTert Dr. Yehuda Tzfati N/A WI-38 hTert Dr. Amir Eden N/A HEK-293 Dr. Michal Goldberg N/A Oligonucleotides PCR GAPDH Fwd: TGAGCTTGACAAAGTGGTCG Hy Labs N/A PCR GAPDH Rev: GGCTCTCCAGAACATCATCC Hy Labs N/A PCR POLR2A Fwd: TGCGCACCATCAAGAGAGTC Hy Labs N/A PCR POLR2A Rev: CTCCGTCACAGACATTCGCTT Hy Labs N/A PCR TOP1 Fwd: CCCTGTACTTCATCGACAAGC Hy Labs N/A PCR TOP1 Rev: CCACAGTGTCCGCTGTTTC Hy Labs N/A siTOP1-1: GCACAUCAAUCUACACCCA Dharmacon Cat# S0-2605017G siTOP1-2: CGAAGAAGGUAGUAGAGUC Dharmacon Cat# S0-2605017G siSRSF1-1: UUCGGAUGUCUGGAGGUAAGUUACC Invitrogen Cat# HSS109654 siSRSF1-2: GGACAUUGAGGACGUGUUCUACAAA Invitrogen Cat# HSS109655 siCtrl: UGGUUUACAUGUCGACUAA Dharmacon Cat# D-001810-01-20 DRIP RPL13A Fwd: GCTTCCAGCACAGGACAGGTAT This paper N/A DRIP RPL13A Rev: CACCCACTACCCGAGTTCAAG This paper N/A DRIP PRKG1 Fwd: TGTATTCTAACCAGACCTCCTAAATTGG This paper N/A DRIP PRKG1 Rev: AGTGGTCAGTGGCCTTTTGG This paper N/A DRIP SAV1 Fwd: CTGTGTCCTCACCCAAATCTCAT This paper N/A DRIP SAV1 Rev: CCAGGTCCCTCCCTTGATACA This paper N/A Recombinant DNA ER:RAS pLNC Dr. Juan Carlos Acosta N/A pEF1-GFP-TOP1 Dr. Tasuku Honjo N/A pEGFP-RNaseH1 Dr. Robert Crouch N/A pGFP-TDP1 Dr. Fritz Boege N/A pEF1-GFP Dr. Tasuku Honjo N/A Software and algorithms ImageJ Schneider et al., 2012 https://imagej.nih.gov/ij/ Prism 8.3.0 GraphPad https://www.graphpad.com/ RStudio RStudio Team https://www.rstudio.com/ e2 Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS Materials availability This study did not generate new unique reagents. Data and code availability dAll RNA-seq data were deposited at GEO and are publicly available as of the date of publication. Accession number is listed in the key resources table. dThis paper does not report original code. dAny additional information required to reanalyze the data reported in this paper is available from the lead contact. EXPERIMENTAL MODEL AND SUBJECT DETAILS Cell Culture Male human foreskin fibroblasts, FSE-hTert cells; female lung fibroblasts, WI38-hTert; and HEK-293 cells originating from a female fetus were grown in DMEM supplemented with 10% fetal bovine serum, 100,000 U l -1 penicillin and 100 mg L 1 streptomycin. ER:RAS activation was induced by supplementing the growth media with 200 mM of 4-hydroxytamoxifen (4-OHT). Nucleoside supplementation was achieved by supplementing the growth media with 50 mM of A, U, C and G each for 48 h prior to fixation. Aphidicolin and hydroxyurea treatments were performed in growth media with indicated concentrations for 48 h prior to fixation. Plasmids For ER:RAS infection, Phoenix retroviral packaging cells were transiently transfected with ER:RAS pLNC vector plasmids (kindly provided by Dr. J.C Acosta). Cells were infected three times with the Phoenix cell supernatant, containing replication-defective viruses. Infected FSE and WI38 cells were selected using 400 mgmL 1 G418 for the next 10 days. For TOP1-GFP transfection, HEK-293 cells were transiently transfected with pEGFP-TOP1 or with a control pEF1-GFP vector (kindly provided by Dr. Tasuku Honjo). Transfected cells were FACS sorted 24 h post transfection and 24 h later GFP positive cells were analyzed. For GFP-RNaseH1 transfection, HEK293 cells were transiently transfected with pEGFP-RNaseH1 vector (kindly provided by Dr. Robert Crouch) or with a control pEF1-GFP vector. Transfected cells were FACS sorted 24 h post transfection and 48 h later GFP positive cells were analyzed. For GFP-TDP1 transfection, HRK-293 cells were transiently transfected with pGFP-TDP1 vector (kindly provided by Dr. Fritz Boege) or with a control pEF1-GFP vector. Transfected cells were FACS sorted 24 h post transfection and 48 h later GFP positive cells were analyzed. METHOD DETAILS Replication dynamics using DNA combing Molecular combing is a process whereby single DNA molecules (hundreds of Kbs) are stretched on a silanized glass surface (COV002, Genomic vision) (Bensimon et al., 1994). In general, unsynchronized cells were labeled for 30 min by medium containing 100 mM of the thymidine analog iododeoxyuridine (IdU). At the end of the first labeling period, the cells were washed twice with a warm medium and pulse labeled once more for 30 min with a medium containing 100 mM chlorodepxyuridine (CldU) and then washed with cold PBS and harvested. Genomic DNA was extracted using Fiber-Prep kit (EXTR-001, Genomic Vision), combed using the Fiber-Comb (MSC-001, Genomic Vision) and analyzed as previously described (Herrick and Bensimon, 1999). The primary antibody for fluorescence detection of IdU was mouse anti-BrdU (Becton Dickinson), and the secondary antibody was goat anti-mouse Alexa Fluor 488 (Invitrogen). The primary antibody for fluorescence detection of CldU was rat anti-CldU (Novus Biologicals). The secondary antibody was goat anti-rat Alexa Fluor 594 (Invitrogen). The primary antibody for fluorescence detection of ssDNA was mouse anti-ssDNA (Millipore). The secondary antibody was donkey anti-mouse Alexa Fluor 647 (Invitrogen). The length of the replication signals and the fork distances were measured in micrometers and converted to kilo bases according to a constant and sequence-independent stretching factor (1mm = 2kb), as previously reported (Herrick and Bensimon, 1999). Fork symmetry is expressed as the ratio of the shorter to the longer distance covered during the IdU pulse, for each pair of sister replication forks. Images were analyzed double blindly using Fiji (Schindelin et al., 2012). Immunofluorescence staining Cells were fixed in 4% formaldehyde/PBS for 10 min, permeabilized with 0.5% Triton/PBS for 10 min, and blocked with 10% fetal bovine serum/PBS for 1-3 h. The primary antibodies used were mouse anti-phosphorylated H2AX (Millipore, 1:100), rabbit anti53BP1 (Bethyl Laborartories, 1:100), mouse anti-cyclin A2 (Abcam, 1:100) and mouse anti-BrdU (Becton Dickinson, 1:25). For RNA-DNA hybrid detection, cells were washed with cold PBS and incubated with pre-fixation buffer solution (0.5% Triton X-100, 20mM Hepes-KOH pH 7.9, 50mM NaCl, 3mM MgCl 2 , and 300mM Sucrose). After pre-fixation buffer was removed, cells were fixed with 100% ice-cold methanol for 8 min. Then, all cells were treated with RNaseIII (New England Biolabs, MO245S) according to the manufacture instructions for 30 min in 37c. Washed once with PBS and treated with RNaseH1 (New England Biolabs, MO297L) according to the manufacture instructions for 30 min in 37c. PBS washed and incubated in blocking solution 2% BSA/PBS overnight. Cell Reports 40, 111397, September 27, 2022 e3 Article ll OPEN ACCESS S9.6 antibody (kindly provided by Dr. Rachel Eiges) was used, 1:500, rabbit anti nucleolin was use at 1:1000 (Abcam). Secondary antibodies added were anti–mouse Alexa Fluor 488 (Invitrogen), anti-rabbit Alexa Fluor 488 (Abcam), anti-mouse Alexa Fluor 555 (Invitrogen). DNA was counterstained with mounting medium for fluorescence with DAPI (Vector Laboratories). For focus information analysis images were taken with the FV-1200 confocal microscope (Olympus, Japan), with a 60X/1.42 oil immersion objective. Multiple dyes sequential scanning mode was used in order to avoid emission bleed-through. For focus and fluorescent intensity analysis the Hermes WiScan system (Idea Bio-Medical, Israel) was used. All images were analyzed double blindly using Fiji (Schindelin et al., 2012). Metaphase chromosome preparation and fragile site analysis Cells were treated with 100 ng mL 1 colcemid (Invitrogen) for 15–40 min, collected by trypsinization, treated with hypotonic solution at 37C for 30 min and fixed with multiple changes of methanol:acetic acid 3:1. Fixed cells were kept at 20c until analysis. For analysis of total gaps and breaks chromosomes were stained with propidium-iodide and analyzed double blindly using Fiji (Schindelin et al., 2012). Western blot analysis 8-12% polyacrylamide gels were used for protein separation and detection. The gels were transferred to a nitrocellulose membrane, and antibody hybridization and chemiluminescence (ECL) were performed according to standard procedures. The primary antibodies used in these analyses were rabbit anti-H-RAS (Santa Cruz, 1:1,000), mouse anti-CHK1 (Cell signaling, 1:500), rabbit antiphosphorylated CHK1 (Cell Signaling, 1:200), rabbit anti-GAPDH (Cell Signaling, 1:1,000), mouse anti-b-catenin (BD-Biosciences, 1:2,500), mouse anti-Tubulin (Sigma, 1:50,000), mouse antib-Actin (Santa Cruz, 1:2,000), rabbit anti-TOP1 (Abcam, 1:10,000), rabbit anti-RNaseH1 (Abcam, 1:1,000), mouse anti-TDP1(Santa Cruz, 1:500), and mouse anti SRSF1 (Santa Cruz, 1:50). HRP-conjugated anti-rabbit and anti-mouse secondary antibodies was obtained from Jackson Immunoresearch Laboratories (711-035-152, 1:5,000). Population doublings Cells were grown in media as indicated in the ’Cell Culture’ section. Initial seeding concentration of cells was 10,000 per well. Cells were trypsinized and counted. Population doublings (PD) was measured according to the following formula: Xb is the number of cells at the beginning of incubation and Xe is the number of cell at the final count (Greenwood et al., 2004). RNA sequencing analysis Sequencing libraries were prepared using the Illumina TruSeq mRNA kit, and sequenced (60 bp, single reads) on a single lane of Illumina HiSeq 2500 V4 instrument, to a depth of 27 million reads per sample. Reads were aligned to the hg19 genome (UCSC, downloaded from iGenomes) using TopHat (v2.0.10) (Kim et al., 2013). HTSeq-count (version 0.6.1p1) (Anders et al., 2015) was used to count reads on gene exons (UCSC Annotation from March 9, 2012). Differential expression analysis was performed using DESeq2 (1.6.3) (Love et al., 2014) with betaPrior set to False. Gene set enrichment analysis was performed using WebGestalt (Wang et al., 2013). Gene correlation analysis in GEPIA The online database Gene Expression Profiling Interactive Analysis (GEPIA) (Tang et al., 2017) was used to explore TOP1, NRAS, KRAS, HRAS and MYC expression levels in cancer. GEPIA is an interactive tool for analyzing RNA-seq expression data from 9,736 tumors and 8,587 normal samples from the TCGA and GTEx projects. GEPIA was used to generate TOP1, NRAS, KRAS, HRAS and MYC expression plots in normal and tumor samples and gene expression correlation analysis in tumor samples. RNA analysis Total RNA was extracted using the RNeasy Mini Kit extraction kit (QIAGEN). RNA-less and reverse transcriptase-less reactions were used as controls. cDNA synthesis was performed using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems). Real-time PCR was subsequently performed in ABI 7500 using a Power SYBR green PCR master Mix (Applied Biosystems). The expression level was normalized to the transcript levels of GAPDH. Specific primers for these PCRs were designed using the Primer Express software: GAPDH: Fwd, TGAGCTTGACAAAGTGGTCG; Rev, GGCTCTCCAGAACATCATCC, POLR2A: Fwd, TGCGCACCA TCAAGAGAGTC; Rev, CTCCGTCACAGACATTCGCTT, TOP1: Fwd, CCCTGTACTTCATCGACAAGC; Rev, CCACAGTGTCCGC TGTTTC. siRNA siRNA against TOP1 (TOP1-1: 50-GCACAUCAAUCUACACCCA-30and TOP1-2: 50-CGAAGAAGGUAGUAGAGUC-30) and a control, non-targeting siRNA (Ctrl: 50-UGGUUUACAUGUCGACUAA-30) were purchased from Dharmacon. Cells were transfected with 40nM control siRNA and 20nM siRNA against TOP1, using Oligofectamine (Thermo-Fisher). Cells were analyzed 48 h after transfection. siRNA against SRSF1 (Invitrogen HSS109654 and HSS109655). Cells were transfected with 40mM siRNA, using oligofectamie. e4 Cell Reports 40, 111397, September 27, 2022 Article ll OPEN ACCESS Cell cycle analysis Cells were harvested and the pellet resuspended in 0.5mL cold PBS and fixed in 4.5mL 100% chilled methanol and kept at 20C. Prior to FACS analysis, methanol residues were washed and cells were resuspended in PBS containing 0.2mg/ml RNase for 30 min. Cells were stained with 50mg/ml propidium iodide and the DNA content was analyzed by flow cytometry (BD FACSAria III). DRIP-qPCR DRIP-qPCR was carried out essentially as previously described (Garcı ´a-Rubio et al., 2018) in FSE hTERT ER:RAS cells after 48 h of 200 nM 4-OHT treatment. Briefly, DNA–RNA hybrids were immunoprecipitated using the S9.6 antibody from gently extracted and enzymatically digested DNA, treated or not with RNase H. Quantitative PCR was performed at the indicated regions of RPL13A, PRKG1 and SAV1 genes with the corresponding primers listed below. Means and SEM from at least four independent experiments were calculated. Alkaline gel electrophoresis To determine the presence of excess genome-embedded ribonucleotides in nuclear DNA, alkaline gel electrophoresis of RNaseH2treated genomic DNA was performed as previously described (Reijns et al., 2022). MEF RNaseH2B +/+ and RNaseH2B / were used as controls (Reijns et al., 2012). Total nucleic acids were isolated from pellets from 1 million cells by incubation in ice-cold buffer (20mM TRIs-HCl ph7.5, 75mM NacCl, 50 mM EDTA) with 200 mgmL 1 proteinase K (Sigma) for 10 min on ice, followed by addition of N-lauroylsarcosine sodium salt to a final concentration of 1%. Nucleic acids were extracted using phenol-chloroform, then isopropanol-precipitated and dissolved in nuclease-free water. For alkaline gel electrophoresis, 500 ng of total nucleic acids was incubated with 1pmol of purified recombinant RNaseH2 (kindly provided by Dr. Martin Reijns and Prof. Andrew Jackson, (Reijns et al., 2011)) and 0.25 mg of RNaseA (Sigma) for 30 min at 37c in 100 mL reaction buffer (60 mM KCl, 39mM Tris-HCl pH 8.0, 1.5 mM MgCl 2 , 0.01% Triton X-100). Nucleic acids were ethanol-precipitated, dissolved in nuclease-free water and 250 ng was separated on 0.7% agarose gels in 50 mM NaOH, 1 mM EDTA. After overnight electrophoresis the gel was neutralized in 0.7 M Tris-HCl pH 8.0, 1.5 M NaCl and stained with SYBER Gold (Invitrogen). Images were taken with ChemiDoc Bio-Rad, and densitometry plots were generated using ImageJ (Schindelin et al., 2012). Mutation analysis Expression and mutational data were collected from ICGC data portal (ref). Briefly, TOP1 expression in normal (healthy) samples was used to determine TOP1 expression profile; such that expression > 2SD of the mean were considered high-TOP1 and samples within the range ±2SD of the mean were considered normal-TOP1. Then, tumor samples were divided into 2 groups according to their TOP1 expression profile (normal or high). Indel and SBS count per sample were compared between normaland high-TOP1. Indel and SBS profiles in normal-TOP1, high-TOP1 and high-normal (subtracted) were calculated based on the relative percentage of each mutation type per sample. The relative contribution of indel and SBS signatures to the mutational profiles was performed using YASPA package for R (H€ ubschmann et al., 2021). Viability assay Control and RAS-expressing cells for 3 days were seeded in 96 wells, and treated with camptothecin (CPT, Sigma) 0.0001-1 mM for 3 days. Cristal Violet staining assay was performed according to manufacturer’s instructions (Abcam, ab232855). Briefly, Cells were washed with a washing solution and then stained with Crystal Violet for 20 min in RTc. Staining solution was removed, and cells were washed four times with washing solution, followed by incubation with solubilization solution for 20 min in RTc. O.D was measured by Synergy H1 plate reader. QUANTIFICATION AND STATISTICAL ANALYSIS All data analysis was performed using Excel, GraphPad Prism 8.3.0 for Windows, GraphPad Software, La Jolla California USA (www. graphpad.com) or R project for Statistical Computing (htpp://www.r-project.com). For comparisons of replication dynamics, Immunofluorescence staining, metaphase spreads analyses, and SA-bgal activity student t-test, one-way ANOVA and Mann-Whitney rank-sum test were performed, as indicated. Numbers of repeats are indicated in the figure legends. RPL13A Fwd GCTTCCAGCACAGGACAGGTAT RPL13A Rev CACCCACTACCCGAGTTCAAG PRKG1 Fwd TGTATTCTAACCAGACCTCCTAAATTGG PRKG1 Rev AGTGGTCAGTGGCCTTTTGG SAV1 Fwd CTGTGTCCTCACCCAAATCTCAT SAV1 Rev CCAGGTCCCTCCCTTGATACA Cell Reports 40, 111397, September 27, 2022 e5 Article ll OPEN ACCESS