Replication fork stalling at DNA lesions is driven by competition between damage bypass pathways

Replication fork stalling at DNA lesions is driven by competition between damage bypass pathways | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Replication fork stalling at DNA lesions is driven by competition between damage bypass pathways Amir Aharoni, Amit Cohen, Daniel Dovrat, Wiktoria Kabza, Elizabeth Colby, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8353672/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Replication fork stalling or slowdown is a hallmark of replication stress and can lead to DNA damage-induced fork collapse and genetic instability. Stalled replication forks must be stabilized to enable damage processing, yet the connection between fork stalling and lesion bypass remains poorly understood. To explore this relationship, we developed a real-time system to monitor the replicative bypass of locus-specific abasic sites in individual live yeast cells. Using this approach, we find that delays in replisome progression through the DNA lesions arise from fork-associated activity of DNA damage bypass factors rather than from the lesions themselves. Specifically, replication delays are linked to competition between translesion synthesis and recombination-mediated bypass. Our work highlights the complex interplay between fork stalling and damage processing, demonstrating how pathway choice impacts cell survival. Biological sciences/Molecular biology/DNA replication/Translesion synthesis Biological sciences/Molecular biology/DNA damage and repair/DNA damage response DNA damage bypass DNA replication translesion synthesis template switching salvage recombination daughter-strand gap ubiquitin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Genome maintenance systems ensure faithful transmission of a cell’s genetic information to the next generation in face of DNA damage and replication stress 1 . They comprise DNA damage signaling systems, DNA repair pathways responsible for the removal of lesions, and replication-associated DNA damage tolerance (DDT) mechanisms ensuring complete and accurate genome duplication 2 . Although many of the factors and molecular mechanisms contributing to these protective pathways have been characterized in detail, we are only beginning to understand their dynamic interplay in the context of a live cell. Systems for the site-specific analysis of DNA transactions have been instrumental for elucidating mechanisms of genome maintenance. For example, sequence-specific endonucleases have served to unravel the choreography of DNA double-strand break (DSB) repair 3 . Similarly, responses to replication fork blockage have been revealed using sequence-specific DNA-binding proteins 4 – 6 . Importantly, these approaches combine the advantages of single-cell strategies, i.e., the option of gaining real-time insight into the dynamics of key players via fluorescence microscopy, with those of bulk techniques such as next-generation sequencing, which provide quantitative data on a genome-wide scale. However, most insults to the genome have not been amenable to such tools, as they usually arise randomly scattered across the genome and their chemical nature tends to be heterogeneous. By developing a system to monitor the replicative processing of DNA polymerase-stalling lesions in a defined genomic locus, we have now gained insight into the dynamic regulation of DDT in real time. DDT promotes the bypass of lesions by effectively postponing their removal until after replication of the damaged region 7 , 8 . It operates either via mutagenic translesion synthesis (TLS) by specialized DNA polymerases capable of replicating damaged DNA or via an error-free template switching (TS) mechanism that utilizes the undamaged sister chromatid for homologous recombination (HR). In eukaryotes, TLS and TS are controlled by the mono- and polyubiquitylation of the replication factor PCNA 9 , 10 , respectively. In the absence of PCNA ubiquitylation, HR-mediated lesion processing is still possible via an alternative pathway known as salvage recombination (SR) 11 . There is good evidence that DDT can act in association with the replisome, i.e., “on the fly”, but also – via re-priming of the replisome downstream of the damaged region – in a postreplicative manner after passage of the replication fork 12 – 14 . However, we still know little about the extent of replication fork stalling at DNA lesions and how it is connected to the choice between the DDT pathways, the timing of their activation relative to replisome movement, and their effects on cell viability. We now present a tool that is based on the introduction of site-specific abasic or apurinic/apyrimidinic (AP) sites, which are among the most common spontaneous DNA lesions, arising thousands of times per day in eukaryotic cells 15 . They are formed by spontaneous hydrolysis of the N-glycosidic bond or via active removal of damaged or mismatched bases by DNA glycosylases in the context of base excision repair (BER) 15 , 16 . If left unrepaired, AP sites and their byproducts impede replisome progression, and their bypass in vitro and in vivo has been shown to involve DDT 17 , 18 . Here, using a CRISPR-based targeting approach, we enzymatically introduce AP sites into an early-replicating region of the budding yeast genome. Via a reporter system based on two fluorescently marked repressor arrays surrounding the damaged region 19 , we monitor the effects of AP sites on the replication kinetics of this locus and their processing via TLS, TS and SR in real time. Application of this system provides high-resolution, quantitative insight into the temporal and spatial organization of DNA damage bypass. By measuring fork stalling and differentiating between TLS and HR-mediated bypass on a single-cell level, we found that the bypass of AP sites is associated with a marked delay in replication fork progression. Importantly, this delay is not caused by the inability of the replisome to move across lesions but rather by a competition between TLS and TS factors at the replication fork. We uncover common features between TS and SR, such as extended fork stalling and the emergence and resolution of a daughter-strand gap closely behind the fork. Overall, this approach reveals the choreography of AP site bypass, laying the practical and conceptual foundation for future studies of the dynamic regulation of the DNA replication stress response. Results Design of a real-time monitoring system for the replicative bypass of AP sites Establishment of an experimental system for the real-time monitoring of locus-specific DNA damage bypass (Fig. 1 A) necessitates a critical set of design principles. First, it requires the introduction of replication-stalling lesions that are physiological substrates of DDT. Second, the lesions need to be introduced into a defined genomic target region whose replication can be monitored in real time. Finally, lesions should be inducible in a controlled manner that is coordinated with genome replication and affords control over the damage load. To fulfill the first criterium, we made use of a mutant human uracil DNA glycosylase, UDG Y147A (here called UDG*). This enzyme had been reported to excise thymine from single-stranded (ss) or double-stranded (ds) DNA 20 (Fig. 1 A). The resulting AP sites are known to interfere strongly with replication. In vitro , the concerted activities of replicative DNA polymerase δ and TLS polymerase ζ are required to replicate an AP site-containing template 18 . In budding yeast, AP sites introduced randomly into the genome are processed by mutagenic ubiquitin-dependent TLS involving polymerases ζ and Rev1 17 . Thus, AP sites are common physiological targets of DDT. For the second criterium – the ability to target UDG* to a specific genomic region – we fused the protein to catalytically inactive Cas9 (dCas9). A synthetic CRISPR array ( SCA ) containing multiple target sequences for dCas9-UDG* was designed for integration into the desired locus, and the dCas9-UDG* construct was combined with an expression cassette for a matching guide RNA (gRNA, Fig. 1 A). To follow replication of the damaged or undamaged SCA in real time, we employed a live-cell imaging-based approach that we recently developed for S. cerevisiae 19 . Here, replication is monitored by tracking the intensity changes of two fluorescently labeled arrays ( lacO 128 and tetO 128 ) inserted in the vicinity of an early-replicating origin, ARS413 , by time-lapse microscopy (Fig. 1 A). Measuring the interval between the duplication times of each fluorescent reporter during the cell cycle allows us to infer the progression of single replisomes through the genomic region between the reporters 19 . Importantly, the region is predominantly replicated with defined directionality from the neighboring ARS413 as the downstream origin, ARS414 , is located far from tetO (see map and explanation in Supplementary Fig. 1A ). We previously applied this approach to measure replisome progression through G4-containing sequences 21 , 22 or actively transcribing genes 23 , observing replication slowdown in various mutant strains. For monitoring DDT, the SCA is now inserted between the lacO and tetO reporters. The third criterium, control over lesion induction and damage load, was implemented by placing the dCas9-UDG* sequence under the control of an estradiol-inducible promoter 24 and equipping the protein with an auxin-inducible degron tag (AID) 25 . These features allow for transient induction of AP sites in G1-arrested cells and subsequent removal of the enzyme before release into S phase, without the need to exchange the growth medium ( Fig. 1BC ). Thus, the number of AP sites in the SCA that will be encountered in the following round of replication can be tuned by means of the duration of dCas9-UDG* induction or by varying the number of gRNA target sequence repeats (n) in the SCA n ( SCA 8 , SCA 16 , or SCA 64 ). Premature repair of the AP sites or unwanted processing into strand breaks is minimized by using an apn1Δ mutant, deficient in the major BER-specific AP endonuclease 15 . As the default strain background for this study, this mutant is therefore designated as “ WT* ”. Validation of site-specific AP site induction To validate gRNA-mediated recruitment of the Cas9 construct to the SCAs , we first induced catalytically active Cas9 during G1 and monitored the appearance of DSBs by means of a separation between the lacO and tetO reporters ( Supplementary Fig. 1B ). We observed successful gRNA-dependent DSB induction in all three SCAs against a low background in the absence of Cas9 ( Supplementary Fig. 1C ). This indicates efficient recruitment of Cas9 to the SCA in most cells. Next, we optimized the induction and depletion times of dCas9-UDG* during G1. The protein appears within 30 min of estradiol addition and reaches near complete degradation within 60 min of auxin treatment (Fig. 1 B). Based on these properties, we settled on a 2 h induction period, followed by a 1 h degradation phase in G1-arrested cells. To confirm the specific introduction of AP sites within the SCA following dCas9-UDG* expression, we analyzed isolated genomic DNA via G enome-wide L igation of 3’- O H E nds in combination with next-generation Seq uencing (GLOE-Seq) 26 . This technique localizes strand breaks with nucleotide precision, and in vitro pre-treatment of the DNA with a lesion-specific endonuclease further permits the detection of various base lesions. To analyze and quantify AP sites, we therefore combined the protocol with APE1 pre-treatment and used the signals from a partial digestion of the genomic DNA with a rare-cutting restriction enzyme, Not I, for standardization and absolute quantification 27 . Consistent with selective UDG* activity, GLOE-Seq analysis of genomic DNA isolated from SCA 16 WT* cells after dCas9-UDG* induction in G1 phase showed a marked enrichment of signals on both strands in and around the SCA compared to a control strain lacking the gRNA (Fig. 2 A). Importantly, GLOE-Seq without APE1 pre-treatment yielded much lower signals, indicating that most AP sites introduced by dCas9-UDG* do not give rise to strand breaks. As expected from using the T-specific UDG* enzyme, comparison of nucleotide frequencies among the GLOE-Seq signals revealed an enrichment of T in SCA 16 far beyond its relative representation in the sequence specifically in APE1-treated samples of strains containing the gRNA (Fig. 2 B). On a genome-wide level, enrichment of T was much less pronounced, indicating that dCas9-UDG* preferentially targets the SCA over non-specific regions. Absolute quantification revealed an average of ca. 0.6 AP sites within SCA 16 (Fig. 2 C), corresponding to a lesion density of approximately 0.9 kbp − 1 compared to less than 0.3 kbp − 1 in the rest of the genome. While our method does not differentiate between isolated and clustered or closely spaced lesions 26 , this suggests that approximately 50% of all SCA 16 cells experienced at least one AP site in the target region, assuming a Poisson distribution. AP sites introduced by dCas9-UDG* are successfully bypassed in S phase As a final validation step, we examined by live-cell imaging and bulk viability assays whether the replisome originating from ARS413 can bypass the damaged SCA (Fig. 1 A). To this end, we released cells into S phase after transient G1 induction of dCas9-UDG* (Fig. 1 B) and examined replication through the damaged SCA by monitoring the duplication of the lacO and tetO arrays surrounding the AP sites. A complete blockage of replication at the AP sites should result in failure to replicate the downstream tetO during the 3 h experiment in a substantial number of cells. However, microscopy analysis revealed no increase in such cell population following dCas9-UDG* induction ( Supplementary Fig. 2A ). The possibility of replication of tetO from the neighboring (downstream) ARS414 was deemed unlikely because 88% of cells replicated tetO with replication times of up to 30 min (∆t, defined as the time interval for lacO to tetO mid-array duplication) ( Supplementary Fig. 2B ), while use of ARS414 would – based on the distance ( Supplementary Fig. 1A ) – result in replication of the tetO ~ 40 min following lacO replication. Moreover, replication times were not significantly affected by deletion of ARS414 , confirming the intended replication directionality ( Supplementary Fig. 2B ). Extensive DSB formation during SCA replication was excluded by quantification of the co-localization between lacO and tetO , which indicated a separation of the reporters in less than 7% of all cells ( Supplementary Fig. 2C ). To assess the success of AP site bypass in a bulk experiment, we quantified the viability of WT* cells after transient dCas9-UDG* induction for 2 h. We found that more than 85% of cells containing SCA 64 survived the treatment and were able to form colonies ( Supplementary Fig. 2D ). Taken together, these data imply that the overall damage load induced by our system can be successfully bypassed in cells with an intact DDT system in the absence of BER. Therefore, the system was deemed suitable for an in vivo analysis of DDT under close-to-realistic conditions. AP sites in the replication template delay replisome progression Having validated the selective activity of dCas9-UDG* (Fig. 2 ), we measured how varying loads of AP sites would affect replication progression. In our system, transient stalling or slowdown of replication is detected by an increase in the replication time relative to unperturbed replication 21 , 22 . We found that induction of dCas9-UDG* significantly delayed replication through the SCAs , while unselective activation of the enzyme in the absence of gRNA had no effect on the replication of SCA 64 (Fig. 3 A). Moreover, replication delay in the absence of APN1 ( WT* ) was not reduced compared to BER-positive ( WT ) cells, suggesting that the AP sites themselves, rather than BER intermediates, are the leading cause of replication slowdown ( Supplementary Fig. 2E ). To examine whether the observed replication delay was a direct consequence of replisome stalling or slowdown by the AP sites or an indirect effect of DNA damage checkpoint activation, we measured replication in checkpoint-deficient rad9Δ cells in the WT* background. We found that the rad9Δ mutation suppressed the replication delay following dCas9-UDG* induction only to a minor extent ( Supplementary Fig. 2E ), indicating that checkpoint activation contributes little to the slowdown. Overall, these results show that AP sites in the replication template significantly impede replisome progression, thus allowing us to examine the interplay between fork stalling and the activation of the different DDT pathways. AP site bypass can proceed with or without the formation of extended stretches of ssDNA We had previously shown that the ssDNA-binding Replication Protein A (RPA) complex is required for recruitment of the ubiquitin protein ligase (E3) Rad18 to mediate PCNA ubiquitylation 28 and can serve as a proxy for postreplicative damage bypass 14 . We therefore quantified the signal of GFP-labeled Rfa1 associated with the bypass of AP sites during the cell cycle, focusing on bright foci that co-localized with the lacO and tetO reporters ( Supplementary Fig. 3 ) and persisted for more than 12 minutes (min, see methods for criteria justification). Using these criteria, we observed co-localizing RPA foci following dCas9-UDG* induction in nearly 30% of the SCA 64 cells, corresponding to a ~ 3-fold increase relative to uninduced conditions or to unselective dCas9 induction without gRNA ( Fig. 3 B). A similar fraction of RPA-positive cells following dCas9-UDG* induction was observed in the SCA 16 strain, whereas in the SCA 8 strain, a smaller fraction of these cells was observed (Fig. 3 B). Interestingly, RPA-positive SCA 64 and SCA 16 cells exhibited significantly more severe delays in replication through the array than cells without foci, although both sub-populations were delayed relative to undamaged cells in all SCA strains (Fig. 3 C). This indicates that lesions are present and can impede replisome progression even when they do not give rise to strong RPA foci. These data suggest that AP site bypass proceeds via at least two different modes, one of them accompanied by severe fork stalling or slowdown and the formation of extended stretches of ssDNA. Moreover, the RPA-associated mode becomes more prominent with increasing damage loads. RPA foci reflect postreplicative daughter-strand gaps Alignment of the lacO and tetO replication profiles 23 can reveal the timing of an event, e.g., the binding of a specific protein, relative to replisome progression through the intervening region for a given cell population (Fig. 4 A). Using this analysis in the RPA-positive cell population, we found that RPA foci intensity gradually increased during replisome progression through SCA 64 and reached its maximum after duplication of the downstream tetO reporter (Fig. 4 A and Supplementary Fig. 4A ). To validate that RPA foci formation was coupled to replisome progression through the AP sites, we also analyzed cells containing the SCA 64 integrated further distal to ARS413 between lacO and tetO . In these SCA 64 -distal cells, the midpoint of RPA foci formation was shifted to a later time relative to the midpoint measured in SCA 64 -proximal cells, in accordance with the altered location of the SCA 64 ( Supplementary Fig. 4BC and Supplementary Table 1 ). In addition, deletion of EXO1 , encoding a nuclease responsible for expanding postreplicative daughter-strand gaps in preparation for HR-mediated repair 29 , 30 , delayed the timing of RPA foci increase relative to WT* cells ( Supplementary Fig. 4D ). These experiments confirm that RPA foci represent daughter-strand gaps and are driven by replisome progression through the AP sites. They also demonstrate that RPA is predominantly recruited in a postreplicative manner, consistent with our previous observation of the kinetics of RPA foci induced by the alkylating agent methyl methanesulfonate (MMS) 14 . We therefore interpret the RPA foci as postreplicative daughter-strand gaps, resulting from the resumption of replication downstream of the lesions. Daughter-strand gap dynamics reveal three distinct response modes Clustering of individual RPA-positive cells according to their foci patterns during the cell cycle revealed two distinct sub-populations exhibiting RPA accumulation at different times relative to replisome progression through the AP sites (Fig. 4 B). In one sub-population, termed “early-RPA”, foci intensity reached its midpoint when the replisome had progressed ~ 5.9 kbp beyond the SCA 64 , followed by a resolution after replication of tetO (Fig. 4 C and Supplementary Table 1 ). Notably, the GFP fluorescence patterns of individual early-RPA cells indicated that both foci formation and resolution were rapid reactions ( Supplementary Fig. 4E ). This population experienced a severe replication delay through the different SCAs (Fig. 4 D). In another sub-population, termed “late-RPA”, the intensities of the foci grew more gradually ( Supplementary Fig. 4E ), reached their midpoint much later, when the replisome was ~ 31.5 kbp beyond the SCA 64 , and plateaued toward the end of the observation period (Fig. 4 E and Supplementary Table 1 ). This population experienced no significant replication delay over the RPA-negative cells (Fig. 4 D). An additional, heterogeneous group of cells was identified without clearly defined RPA dynamics and with no replication delay ( Supplementary Fig. 5AB ). Early- and late-RPA populations were present in roughly equal proportions among the SCA 8 , SCA 16 or SCA 64 RPA-positive cells ( Supplementary Fig. 5C ), and their relative timing was similar in the three SCA strains ( Supplementary Fig. 5D and Supplementary Table 1 ). These results suggest that this divergent response to AP sites is robust and largely independent of the number of lesions and the region across which they are spread. Finally, we monitored the timing of anaphase among the different sub-populations as a measure of viability within the time frame of observation. Surprisingly, late-RPA cells were dramatically less successful in completing the cell cycle than early-RPA cells, and these were, in turn, less successful than the RPA-negative population, of which more than 90% passed through mitosis. Failure of RPA-positive cells to undergo anaphase increased with increasing length of the SCA (Fig. 4 F and Supplementary Table 2 ). Overall, these results show that cells have a choice between at least three distinct modes of AP site processing. The first involves efficient and successful bypass with a relatively minor slowdown of replication, no detectable RPA foci, and little impact on viability (RPA-negative cells). The second is a replication-associated response characterized by a severe delay in replisome progression through the AP sites, a daughter-strand gap arising transiently and closely behind the moving fork, and an increased risk of failure to complete the cell cycle in a timely manner (early-RPA cells). The third is characterized by a relatively minor slowdown of replication, the gradual formation of a persistent daughter-strand gap after the replication fork has passed the AP sites, and strongly reduced viability as measured by anaphase events (late-RPA cells). TS delays fork progression and is activated shortly after replisome passage To link the dynamics of RPA foci to the various DDT mechanisms, we examined a set of mutants specifically targeting the individual sub-pathways. Deletion of UBC13 , encoding the ubiquitin-conjugating enzyme (E2) responsible for PCNA polyubiquitylation, selectively inactivates the TS pathway. Microscopy analysis of ubc13Δ cells revealed a complete suppression of the lesion-induced replication delays ( Fig. 5 A and Supplementary Fig. 6A) , indicating that the observed replication fork stalling requires PCNA polyubiquitylation. Moreover, the overall fraction of RPA-positive cells and specifically the early-RPA population were severely depleted in ubc13Δ mutants, and the appearance of RPA foci was considerably delayed ( Fig. 5BC , Supplementary Fig. 6BC and Supplementary Table 1) . This suggests that the early-RPA pattern, accompanied by a strong replication delay (Fig. 4 C), represents AP site bypass by the TS pathway controlled by PCNA polyubiquitylation. Deletion of RAD18 , which completely abolishes PCNA ubiquitylation and compromises both TS and TLS, largely mirrored the results obtained with ubc13Δ mutants (Fig. 5 A B and Supplementary Fig. 6A-C ). As TS is thought to proceed via sister-chromatid recombination, we also monitored the appearance of HR intermediates via an internally GFP-tagged, functional RAD51 allele 31 . The strong increase of Rad51 foci that colocalize with lacO and tetO following dCas9-UDG* induction and their dependence on UBC13 ( Supplementary Fig. 6D ) confirmed the importance of HR for the TS pathway. Interestingly, while in a WT* background the percentages of Rad51-positive and RPA-positive cells were similar (30–35%), deletion of UBC13 caused a much stronger reduction in Rad51 compared to RPA positive cells ( Supplementary Fig. 6D ). This suggests that in WT * cells, most Rad51 foci represent TS events. Considering that HR involves a cooperation of RPA with Rad51, it also implies that in ubc13Δ mutants, a sizable fraction of daughter-strand gaps does not undergo HR and may therefore represent unsuccessful attempts at gap repair. Like TS, SR is activated closely behind the replisome Via its association with SUMOylated PCNA in S phase 32 , 33 , the antirecombinogenic helicase Srs2 was shown to suppress HR by preventing the formation of the recombinogenic Rad51 filament 34 , 35 . Deletion of SRS2 in DDT-deficient cells therefore rescues viability by activating SR 32,33 . Nevertheless, srs2Δ single mutants exhibit a damage sensitivity comparable to ubc13Δ mutants 36 . To characterize the contributions of Srs2, we examined the effects of deleting the gene in WT* and rad18Δ cells. In the srs2Δ single mutant, the fraction of RPA-positive cells and – even more so – of cells with Rad51 foci increased dramatically ( Supplementary Fig. 6D ), consistent with the activation of HR. Moreover, RPA foci intensities were higher in srs2Δ relative to WT * cells ( Supplementary Fig. 6E ). Surprisingly, however, replication kinetics was reminiscent of ubc13Δ mutants, with little replisome delay (Fig. 5 A, Supplementary Fig. 6A ) but a strong delay in the appearance and inefficient resolution of RPA or Rad51 foci ( Supplementary Fig. 6F and Supplementary Table 1 ). Taken together, these data suggest that in a TS-competent background, Srs2 contributes to fork stalling and promotes early gap repair while preventing late – and likely inefficient – recombination. Specific activation of the SR pathway was examined in a rad18Δ srs2Δ double mutant. As expected, deletion of SRS2 partially suppressed the damage sensitivity of rad18Δ in our strain background ( Supplementary Fig. 6G ). Microscopy analysis of rad18Δ srs2Δ cells revealed a WT *-like replication delay following dCas9-UDG* induction and an almost 2-fold increase in the early-RPA population relative to the rad18Δ or srs2Δ single mutants ( Fig. 5AB, Supplementary Fig. 6A-C ). Compared to WT * cells, the early-RPA foci emerged even earlier in the double mutant ( Supplementary Fig. 6H ). Overall, these results indicate that the SR pathway, activated in the absence of both PCNA ubiquitylation and the anti-recombinase Srs2, exhibits similar characteristics to the TS pathway, promoting HR bypass closely behind replication forks and characterized by significant fork stalling or slowdown. TLS does not involve large daughter-strand gaps and competes with HR-dependent DDT Bypass of AP sites not involving extended daughter-strand gaps may reflect TLS. We therefore examined the importance of this pathway using single TLS polymerase deletions ( rad30Δ, rev1Δ , rev3Δ ) as well as a triple deletion ( tlsΔ ). Consistent with a positive contribution of TLS to DDT in RPA-negative cells, completion of anaphase in this population was decreased in rad30Δ , rev1Δ , and rev3Δ single mutants (Fig. 6 A). Surprisingly, however, the tlsΔ mutation restored the viability of the RPA-negative cells, possibly suggesting a dominant negative effect of the remaining TLS polymerases in the single deletions. Bulk colony formation experiments were in excellent agreement with the microscopy analysis, further validating the importance of TLS for cell viability following dCas9-UDG* induction (Fig. 6 B). Notably, loss of TLS polymerases suppressed the damage-dependent replication delays in the RPA-negative cells and in the total induced populations ( Supplementary Fig. 7AB ). Taken together, these results indicate the importance of TLS polymerase activity for AP site bypass in cells that do not develop an extended daughter-strand gap. When we compared RPA foci populations in the TLS mutants, we found no major changes, except for a mild increase of RPA positive in the rad30Δ mutant ( Supplementary Fig. 7CD ). Interestingly, however, the early-RPA foci, corresponding to TS events, peaked at an even earlier time point in rad30Δ and tlsΔ compared to WT* cells (Fig. 6 C and Supplementary Table 1 ), suggesting that TS-associated daughter-strand gap expansion occurs earlier in these mutants. In addition, we found a partial suppression of the replication delay in the early-RPA cells of rad30Δ, rev1Δ and tlsΔ and in the late-RPA population of tlsΔ , relative to the respective WT* populations ( Fig. 6DE ). These results show that the presence of TLS polymerases slows down HR-mediated bypass of AP sites. Moreover, anaphase analysis revealed that most TLS deletions improved viability of the early and late-RPA cells relative to the respective WT* populations, with a maximal increase observed in the tlsΔ mutant (Fig. 6 A and Supplementary Table 2 ). Thus, it seems that the TLS polymerases interfere with AP site bypass via TS, not only by delaying daughter-strand gap expansion but also by interfering with successful completion of the cell cycle. Surprisingly, the deletion of REV3 alone abolished cell cycle completion in the late-RPA cells (Fig. 6 A), possibly suggesting a contribution of polymerase ζ to gap filling late in the cell cycle. Overall, these results highlight the importance of TLS for the viability of cells that do not develop a daughter-strand gap, but they also indicate competition between TLS polymerases and the TS-mediated bypass that leads to a delay in daughter-strand gap expansion, replication progression, and reduced viability. Discussion In this study, we describe a real-time monitoring system for the replicative bypass of AP sites in a defined genomic locus in live yeast cells. Application to a range of genetic backgrounds has allowed us to disentangle the choreography of DNA damage bypass, revealing the extent of fork stalling and its association with different pathways, the sequence of events, the hierarchy of bypass pathways acting at or behind the replication fork, and the implications for successful completion of the cell cycle. Based on the overall delay in replisome passage and the dynamics of ssDNA around the damaged region, we identified two cell populations exhibiting distinct bypass patterns that correlate well with the major DDT pathways: TLS, TS, and SR. The largest discernable population, characterized by minor replisome delay and the absence of substantial stretches of ssDNA (RPA-negative cells), is dominated by TLS. Judging by the rate of anaphase completion (Fig. 4 F), this mode of DDT is associated with the highest success rates. Consistent with their dependence on HR, cells engaging in TS or SR exhibit RPA foci (Figs. 3 – 4 ). These pathways are accompanied by a major replisome delay with a daughter-strand gap forming less than 6 kbp behind the replisome (early-RPA) and operate with moderate efficiency. We identified a third RPA-positive population exhibiting minor replisome delay, generating a daughter-strand gap more than 30 kbp behind the replisome (late-RPA), with low success rates. The model shown in Fig. 7 summarizes our findings in the context of DDT pathway choice and illustrates replisome stalling as a conditional event initiated by the competitive actions of damage processing factors. TLS polymerases promote AP site bypass but interfere with HR-dependent pathways The involvement of TLS polymerases in DDT has been studied extensively, with evidence for both fork-associated (“on the fly”) and postreplicative action 37 . Our analysis shows that TLS mediates AP site bypass without detectable RPA foci, implying either polymerase switching during replisome passage or the filling of a small and transient daughter-strand gap. The notion that replisome delay is more pronounced in the presence of the TLS polymerases than in their absence ( Supplementary Fig. 7AB ) suggests that at least some of the bypass events are slow and occur directly at the fork. Moreover, our assay probably underestimates the TLS-associated replication delay due to the presence of RPA-negative cells that did not experience a lesion. Fork-associated TLS of cyclobutene pyrimidine dimers, mediated by polymerase η (Rad30), has also been observed recently 38 . Consistent with previous reports implying a concerted action of multiple polymerases in the insertion and extension of nucleotides opposite AP sites 18 , 39 , we found reduced viability in all the single TLS polymerase mutants ( Fig. 6AB ). Surprisingly, however, combined deletion of all three TLS genes restored viability, suggesting that other polymerases, probably independent of PCNA ubiquitylation, can mediate efficient AP site bypass in their absence. Indeed, a biochemical study revealed that polymerase ε can bypass AP sites with relatively high efficiency in vitro 40 . Interestingly, the replisome delay conferred by the TLS polymerases affects not only RPA-negative cells, but also those undergoing HR-mediated gap repair. Moreover, in these cells, abolishing TLS enhances viability (Fig. 6 A), suggesting that TLS interferes with HR-mediated bypass. The acceleration of daughter-strand gap expansion in TLS-deficient cells ( rad30Δ and tlsΔ ) and the increase in the fraction of RPA-negative cells likely undergoing TLS upon deletion of UBC13 can be interpreted as a competition of polymerase η with the PCNA polyubiquitylation machinery for access to monoubiquitylated PCNA, the common intermediate of TLS and TS 41 , or with the downstream events initiated by the polyubiquitin chain. Competition between TS and TLS by polymerase ζ and Rev1 behind the fork was also reported in the bypass of (6 − 4) photoproducts and bulky adducts 38 . In the case of polymerase ζ, the loss of viability upon REV3 deletion (Fig. 6 A) indicates a potential collaboration between this TLS polymerase and the SR machinery. In fact, a contribution of polymerase ζ to HR is consistent with previous findings showing that REV3 is responsible for high mutagenesis during DSB repair in yeast 42 . TS and SR delay the replisome but accelerate daughter-strand gap expansion and enable gap filling Despite the identification of a growing number of regulatory factors 30 , 43 – 46 , the mechanism of TS initiation, its activation relative to the replisome, its consequences for replication fork stalling, and its relationship to SR are still poorly understood 7 , 8 , 11 , 47 . Both TS and SR are thought to be active in S and G2/M phase, based on the appearance of characteristic X-shaped HR intermediates on two-dimensional gels 30 , 46 , 48 , but there are no data about their relative timing other than the assumption that SR is a pathway of last resort that becomes relevant if TLS and TS fail. TS is thought to occur mainly in a postreplicative manner 13 , 14 , although impacts on fork progression have been noted 49 . Our analysis shows that during the bypass of AP sites, the TS pathway is accompanied by a pronounced replisome delay, followed by the early appearance of an RPA focus. We interpret this as a slow repriming reaction, giving rise to a daughter-strand gap that is then rapidly expanded. Despite the absence of PCNA polyubiquitylation, the SR pathway appears to operate with similar kinetics. Our results also imply that a delay of gap expansion prevents efficient recombination-mediated gap repair. This suggests that both TS and SR, by accelerating gap expansion, ensure recombination closely behind the replication fork, when sister chromatids are still closely aligned 45 , and chromatin is potentially not fully matured. As noted above, the TS-associated delay in replisome progression is consistent with competition between PCNA polyubiquitylation enzymes and TLS polymerases. Interestingly, activation of SR is associated with a similar replisome delay in a DDT-deficient background where competition with TLS polymerases should not apply. Whether the delay in this situation reflects the lack of an alternative processing pathway or a coordination with ubiquitin-independent HR factors remains to be determined. Postreplicative bypass pathways are chosen at or close to the stalled replication fork Perhaps the most surprising finding emerging from our kinetic analysis of RPA foci is the observation that the two HR-mediated pathways, TS and SR, although both operating in a postreplicative fashion, originate from a decision that is made at or close to the site of replisome stalling. The notion that replisomes experience a pronounced delay in TS or SR cells implies that there is a limited window of opportunity at the replication fork to engage in PCNA polyubiquitylation and activate TS or, in the absence of the ubiquitylation, SR. The underlying choice may be influenced by several factors, such as the load and distribution of lesions or the persistence of PCNA itself at the fork. Loss of PCNA from the stalled primer-template junction might thus prevent timely activation of TS, for example by Elg1-mediated unloading 44 or if the PCNA-polymerase complex releases the primer terminus and is “dragged along” with the moving replisome. Such events might result in a daughter-strand gap that is expanded slowly and is unsuitable for efficient repair. Our results indicate an approximately equal population of cells undergoing TS versus cells accumulating unresolved daughter-strand gaps later in the cell cycle, in a genetic background where the only DNA repair defect is an inactivation of BER to stabilize AP sites (Figs. 4 – 5 and Supplementary Fig. 5 ). This suggests that a significant proportion of cells with unresolved gaps accumulates during replication through AP sites even in cells capable of PCNA ubiquitylation. These cells may elicit checkpoint activation, leading to cell cycle arrest and reduced capacity to complete anaphase. Nevertheless, we cannot exclude that TS can also be activated at an unexpanded gap later during the cell cycle, for example, by reloading of PCNA. In fact, we and others previously showed that ubiquitin-dependent DDT can be deferred to G2/M phase by restricting the expression of the relevant E3s 12 , 13 . Likewise, it is possible that some TS events proceed too rapidly to yield a measurable RPA focus, especially when TLS is not competing. Such events might contribute to the enhanced survival of RPA-negative cells in the tlsΔ background. Despite the detailed insight that our system of inducible AP sites provides into the kinetics of DDT, several open questions remain to be addressed in future studies. These pertain to the distribution of AP sites between the leading and lagging strand templates and the respective consequences for DDT. The dCas9-UDG* construct exhibits little strand bias (Fig. 2 A). Yet, lesions on the lagging strand template would not be expected to stall the replisome, although they might give rise to daughter-strand gaps 50 , 51 . Our replisome progression data, therefore, appear to reflect predominantly the effects of leading strand stalling. Future studies inducing strand-specific lesions will be needed to tease apart the fate of leading- versus lagging-strand damage. One major limitation is our current lack of information about the exact nature of the lesions at the time they are encountered by the replisome. Although we showed that most cells do not experience strand breaks in the apn1Δ background, AP sites are reactive structures that can also result in DNA-protein crosslinks 16 . Moreover, we cannot exclude clusters of closely spaced AP sites resulting from extended residence of dCas9-UDG* at the SCA , as GLOE-Seq does not distinguish these from isolated AP sites 26 . Such clusters would likely aggravate replisome stalling compared to single lesions and may affect the balance between the DDT pathways. Regarding the relative contributions of DDT pathways, our analysis has highlighted important properties of each mechanism, but it may over- or underestimate their frequencies. For example, we cannot distinguish TLS from potentially very rapid TS events among the RPA-negative cells. Considering that REV1 expression peaks in the G2/M phase 52 , our analysis, focusing on an early-replicating region, may underestimate the contribution of this TLS polymerase to AP site bypass. Finally, we cannot assign a defined pathway to the sub-population of RPA-positive cells whose RPA pattern does not fall into either the “early” or the “late” category (defined as “others”). A transition between pathways, e.g. a participation of TLS polymerases at an extended daughter-strand gap, may account for some of these events. Our experimental system, with its ability to differentiate between TS and SR, paves the way to a better understanding of replicative damage processing. It will enable us to determine what factors dictate the choice between alternative pathways, elucidate the respective mechanisms of daughter-strand gap expansion, and identify the factors contributing to gap filling in either pathway. Its real-time approach is highly complementary to other set-ups designed to observe DDT. For example, episomal or integrated plasmids carrying single, defined lesions 53 – 56 have given ample information about the efficiency and accuracy of DDT, but they do not provide kinetic information. In vitro reconstitution of DNA replication on damaged templates has revealed valuable time-resolved insight into TLS and repriming on a population level 51 but is not well suited for analyzing pathway choices in a complex cellular environment. The same holds true for single-molecule measurements with purified components 57 . The single-cell strategy described here enables us to monitor the timing of damage bypass with respect to replisome position, and to disentangle the direct effects of fork progression through damaged regions from global cellular effects such as cell cycle arrest and checkpoint signaling. Expansion to other types of DNA damage, e.g. base deamination or ssDNA breaks, will be possible via the choice of Cas9 variants 58 – 60 , and the monitoring of additional key HR factors such as Rad52, or Rad54 61 , is expected to increase the utility of this system for revealing the kinetics of recombination-mediated lesion bypass. Methods Plasmid construction Plasmids pAC-Cas9-27 and pAC-Cas9-28 containing Cas9 under the control of the GAL10 promoter, with and without a gRNA, respectively, were constructed using a pRS306 plasmid as a backbone ( Supplementary Table 3 ). The Cas9 gene was fused to the AID* tag 25 followed by a CYC1 terminator. A guide RNA (gRNA) cassette targeting a sequence derived from the hygromycin resistance cassette (GACCTGATGCAGCTCTCGGA) 62 or a Stu I site (empty control) was cloned to target the Cas9 to the Synthetic CRISPR Arrays ( SCAs , see below). Plasmids pAC-dCas9-53 and pAC-dCas9-54 encoding dCas9-UDG* were generated by amplifying the Uracil DNA Glycosylase (UDG) gene deleted of the first 84 amino acids from human cDNA and introducing the T174A mutation via overlapping primers 20 . The resulting UDG* was cloned in frame to the 5’ end of Cas9 containing the D10A and H840A point mutations, containing an AID* tag, yielding a catalytically inactive dCas9-UDG*. The dCas9-UDG* was fused to a CYC1 terminator, an additional C-terminal AID* tag followed by a 9×FLAG tag and the gRNA ( Supplementary Table 3 ). For incorporating GFP at the N-terminal region of Rfa1, the pAG25-sfGFP-RFA1-gRNA plasmid was constructed by cloning an RFA1 sequence, recoded to avoid Cas9-mediated digestion, and an N-terminal sfGFP fusion amplified from pAG25-sfGFP-RFA1 (kindly provided by the Schuldiner lab, Weizmann Institute, Israel). To allow sfGFP-RFA1 genomic integration, the pCAS3-RFA1-g1-2 plasmid was generated from the previously described pCAS2 plasmid 62 by introducing two gRNA sequences targeting the N-terminal region of native Rfa1 (AGGTACGATAATCCCACCGG and AGCAGTGTTCAACTTTCGAG) ( Supplementary Table 3 ). SCAs consisting of 8, 16 or 64 repeats of the gRNA target sequence (described above) with 20 bp random sequences between the repeats, were obtained from BioBasic. Arrays with the 16 or 64 repeats were inserted into a pUC origin plasmid to generate the pDD-SCA plasmids containing homology regions at the 5’ and 3’ ends to enable genomic integration ( Supplementary Table 3 ). The SCA 8 was amplified from the SCA 16 plasmid, appending sequences for integration between the lacO/tetO arrays by HR. All plasmid constructions were performed using Gibson Assembly according to the manufacturer’s instructions. The resulting constructs were validated by polymerase chain reaction (PCR) and confirmed through Sanger sequencing. Strain generation Saccharomyces cerevisiae strains for replication measurements were generated using the W1588 MATa background, expressing nuclear LacI-HaloTag and TetR-tdTomato fusion proteins 23 . The strains contain non-repetitive lacO 128 and tetO 128 arrays located at chrIV:332960 and chrIV:352560, respectively, near the autonomously replicating sequence (ARS) 413, with an inter-array distance of ~ 25.5 kb. The SCAs were inserted into the genome between the lacO and tetO arrays into chrIV:340385 or chrIV:352558 locations using a two-step integration process 62 . First, a yeast-selectable marker ( natMX6 antibiotic resistance gene) was integrated into the genome by HR. The marker was then replaced with a linearized pDD-SCA plasmid, co-transformed with the pCAS2-NAT plasmid to facilitate SCA integration 62 . For generating the apn1∆ strains, the APN1 coding region was replaced through HR with either hphMX or kanMX antibiotic resistance cassettes, using primers with 100 bp homology to the target genomic region. The antibiotic resistance markers were later deleted from the genome using a two-step integration process with a short oligonucleotide cassette, as previously described 62 . All other knockout strains ( Supplementary Table 4 ) were generated in the background of apn1∆ ( WT* ) by replacing the coding regions via HR with antibiotic resistance cassettes ( natMX6 or kanMX ), or with the HIS3MX6 auxotrophic cassette. Integration was validated using internal and external primers specific to the genomic region of the deleted genes. To facilitate estradiol-mediated Cas9 induction, GEM plasmids for the expression of Estradiol receptor (EstR) fused to Gal4 binding domain and transcription activation domain (TAD) (kindly provided by the Pasero lab) 63 were linearized and integrated into the TRP1 or AUR1 loci by HR. All plasmids for Cas9 integration were linearized using Xcm I and integrated into the ura3-1 locus. The Oryza sativa TIR1 gene was integrated at the ADE1 locus to enable auxin-induced degradation of Cas9. For RPA tagging, sfGFP was incorporated at the N-terminus of Rfa1 by co-transforming the pAG25-sfGFP-RFA1 gRNA-resistant plasmid along with CRISPR/Cas9-mediated HR using the pAC-Rfa1-pCAS3-g1-2 system. For RAD51 tagging, iGFP was PCR-amplified from a strain containing RAD51 -iGFP 31 , followed by incorporation into the RAD51 locus of the microscopy strains. Integration was enabled by co-transformation of the iGFP together with a CRISPR/Cas9 plasmid targeting the RAD51 gene 31 . Positive colonies were verified by PCR followed by microscopy analysis. The strain and plasmid for RAD51-iGFP generation were a kind gift from Angela Taddei. Western blots Western blotting was performed to monitor Cas9 induction and degradation. Protein extraction was carried out as previously described 25 . Briefly, 2 OD 600 units of exponentially growing yeast cells were harvested at three time points: before estradiol induction, 2 h after estradiol induction, and 1 h after degradation with IAA. The cell pellet was resuspended in 500 µl of doubly distilled water and mixed with 75 µl of 1.85 M NaOH/7.5% β-mercaptoethanol. After 15 min of incubation, 75 µl of 55% TCA was added to the mixture, followed by centrifugation. The resulting pellet was resuspended in 40 µl of high-urea protein loading buffer (8 M urea, 5% SDS, 200 mM Tris-HCl, 1 mM EDTA, and 0.1% bromophenol blue pH 6.8), boiled at 65°C and spun down. For analysis, 8 µl of the protein supernatants were loaded onto a 10% precast SDS-PAGE gel (Bio-Rad) and separated by electrophoresis. Proteins were transferred to a nitrocellulose membrane using the Trans-Blot Turbo system (Bio-Rad) according to manufacturer’s protocol. Membranes were blocked with PBST (PBS containing 0.1% Tween 20) supplemented with 5% skim milk for 1 h, followed by three 5 min washes with PBST. Cas9 was detected using a primary mouse anti-Cas9 antibody (1:2,000, Cell Signaling Technology) in PBST + 1% skim milk for 1 h, followed by incubation with a secondary goat anti-mouse antibody (1:10,000, Jackson ImmunoResearch) conjugated to horseradish peroxidase (HRP). The membrane was washed three times with PBST, and Cas9 was visualized using the EZ-ECL chemiluminescence detection kit (Thermo Fisher) according to the manufacturer’s instructions. Pgk1 was detected as a loading control using a primary mouse anti-Pgk1 antibody (1:50,00, Santa Cruz Biotechnology) and a secondary goat anti-mouse HRP-conjugated antibody (1:10,000, Jackson ImmunoResearch). Isolation of genomic DNA For mapping of AP sites and strand breaks, genomic DNA (gDNA) was extracted from yeast cultures treated according to the scheme shown in Fig. 1 B before release into S phase. Cultures of 600 ml were treated with sodium azide (0.1% final concentration) and EDTA (20 mM final concentration), mixed thoroughly, and incubated on ice at 4°C for 15 min. Cells were pelleted by centrifugation at 2,000× g for 5 min at room temperature. Pellets were washed with 30 ml of ice-cold PBS containing 5 mM EDTA, followed by another centrifugation step under the same conditions at 4°C. Cells were then resuspended in 4 ml of Y1 buffer (1 M sorbitol, 100 mM EDTA pH 8.0) containing 14 mM β-mercaptoethanol and treated with 4 mg of Zymolyase 100T at 30°C until spheroplasting exceeded 90%. Spheroplasts were pelleted at 2,000× g for 2 min, washed once with 4 ml of Y1 buffer lacking β-mercaptoethanol, and gently resuspended in 7 ml of TEN buffer (50 mM Tris HCl pH 8.0, 50 mM EDTA, 100 mM NaCl) containing 1.5% Sarkosyl without vortexing. Subsequently, 4 mg of Proteinase K was added, and samples were gently mixed by inversion. Lysates were incubated for 1 h at 37°C, with gentle mixing every 10–15 min. Samples were then centrifuged at 3,000 rpm for 15 min at room temperature, the supernatants were transferred to 15 ml Falcon tubes, and their volumes were adjusted to 8.2 ml using TEN buffer containing 1.5% Sarkosyl. To establish a CsCl gradient, 8.6 g of CsCl 2 were added, and the solutions were incubated at 30°C until the CsCl 2 was fully dissolved. 15 µl of Hoechst 33342 (10 mg/ml) were added to each sample. Samples were transferred to OptiSeal tubes, balanced to 1 mg, and centrifuged in a VTi 65.1 rotor using an Optima XE-100 ultracentrifuge at 50,000 rpm for 20 h at 20° C. Following ultracentrifugation, gDNA was extracted using 1.6 mm needles and transferred to 15 ml Falcon tubes, yielding an approximate volume of 3 ml per sample. DNA was purified by three extractions with an equal volume of 80% isopropanol, followed by centrifugation at 1,500 rpm for 3 min at room temperature. Ethanol (100%) was then added to a final concentration of 50%, and the solutions were gently mixed by inversion. At this stage, DNA often appeared as a cloudy or jelly-like substance rather than a precipitate. The liquid supernatants were carefully removed, and the DNA was washed 1–2 times with 70% ethanol, promoting dehydration into a solid pellet. After air drying, 100 µl of 0.25× IDTE (Integrated DNA Technologies) buffer was added, and the tubes were left overnight at 4°C to promote dissolution. DNA concentrations were determined using a Qubit fluorometer, and samples were stored at 4°C. Mapping of AP sites via GLOE-Seq GLOE-Seq was performed in two independent replicates largely as previously described 26 , 64 , with minor modifications, including APE1 pre-digestion to convert AP sites to nicks and absolute quantification by means of partial Not I digestion of the gDNA 27 . Oligonucleotides are listed in Supplementary Table 5 . Not I digestion To achieve 50% Not I digestion, 5 µg of gDNA per sample were digested with Not I-HF (New England Biolabs) to completion and combined with 5 µg of undigested gDNA. The digestion was stopped by adding EDTA to 25 mM, followed by a 10-min incubation at room temperature. DNA was purified using 100 µl of SPRI beads (HighPrep PCR from Biozol), which were washed twice with 1 ml of 80% ethanol, air-dried, and the DNA was eluted in 100 µl of nuclease-free water. DNA concentrations were determined using a Qubit fluorometer. The efficiency of Not I digestion was assessed by qPCR using undigested gDNA as control. The qPCR assay targeted selected Not I sites in the S. cerevisiae genome: chromosome I (ID#5773/5774), chromosome II (ID#5775/5776), chromosome IV (ID#5805/5806), chromosome XII (ID#5809/5810), and a control region without Not I site on chromosome III (ID#3331/3332). Three technical replicates were performed per condition. Amplification in untreated and Not I-digested samples was compared using the ΔΔC T method 65 . Final cutting efficiency was calculated as the mean efficiency of all four Not I-targeted sites on chromosomes I, II, IV, and XII. APE1 treatment Following Not I digestion, each sample was split into two equal portions, one of which was treated with 4 U/µg of APE1 (New England Biolabs) in 1× NEBuffer 4 at 37°C for 1 h, followed by heat inactivation at 65°C for 20 min. The other portion was incubated under identical conditions but without APE1. Both samples were then dephosphorylated using 1 U/µg of antarctic phosphatase (New England Biolabs), with incubation at 37°C for 1 h. DNA was purified using SPRI beads at a 1:1 volume ratio, washed twice with 80% ethanol, air‑dried, and eluted in nuclease‑free water. DNA concentration was subsequently determined by using a Qubit fluorometer. Preparation of GLOE-Seq libraries Libraries were prepared as described 64 , using biotinylated proximal adaptor (ID ID#3989/3899) for capturing of 3’-OH ends, extension primer (ID#3790) for second strand synthesis, and distal GLOE-Seq adaptor (and ID#3791/7060). Library amplification was carried out for 10 cycles using primers P5 and P7 (Illumina), followed by two rounds of purification using SPRI beads. To assess adaptor ligation efficiency and library quality, 1 µL of the final product was analyzed on an Agilent High Sensitivity D5000 ScreenTape, confirming a size range of approximately 250–530 bp. The concentrations of the libraries were determined using a Qubit fluorometer with reagents specific to dsDNA, and samples were pooled to a final concentration of 4 nM for sequencing on an Illumina NextSeq 2000 sequencer. GLOE-Seq data analysis The S. cerevisiae reference genome (sacCer3) was modified to include SCA 16 for strains 1566 and 1607 on chromosome IV. Additionally, chromosome XI was modified to reflect the deletion of APN1 . For all analyses, mitochondrial DNA and the Not I sites were excluded. GLOE-Seq data were processed using GLOE-Pipe 64 . Initial trimming of paired-end reads was performed using Cutadapt (v. 4.0) 66 , followed by alignment to the strain-specific reference genome using Bowtie2 (v. 2.4.5) 67 . BAM files were first filtered to select only the mapped R1 reads, and then they were converted into BED files using SAMtools (v. 1.10) 68 and BEDtools (v. 2.27.1) 69 . These BED files were utilized to identify 3’-OH ends in the indirect mode as part of the GLOE-Pipe, to count the number of reads assigned to the Not I sites, and to calculate nucleotide frequency both within the SCA and across the entire genome. The BED files were further converted into normalized BigWig files, which were then split into plus (FWD) and minus (REV) strands for visualization in a genome browser, using bamCoverage from deepTools (v. 3.5.1) 70 . These BigWig files were used to illustrate the profile within SCA 16 and surrounding regions by utilizing computeMatrix and plotProfile from deepTools. Absolute Quantification For each sample, the absolute number of strand breaks or AP sites was quantified using Not I signals as a standard essentially as described 27 . Briefly, GLOE-Seq data were used to determine the mean number of mapped reads per Not I site over all Not I sites. This value was divided by the mean cutting efficiency as determined by qPCR for each sample (see above). The resulting factor, α, was used for calculating the absolute numbers of 3’-OH ends within SCA 16 and within the rest of the nuclear genome ( N SCA16 and N genome ) from the total number of mapped reads in these regions ( R SCA16 and R genome ): N = R /α. Viability assays Spot assays Yeast strains were grown to exponential phase, diluted to an OD 600 of 1, and 10-fold serial dilutions (5 µl each of OD 600 of 1, 0.1, 0.001, 0.0001) were spotted onto plates of YPD with or without 0.002% of MMS (Sigma). Strains were grown for two days at 30°C and imaged using MiniBIS Pro (DNR Bio-Imaging Systems). Bulk viability assays WT* and TLS KO strains were grown overnight in synthetic complete (SC) medium containing 4% glucose at 30°C. Cultures were diluted to an OD 600 of 0.2 and arrested in G1 phase by the addition of 10 µg/ml of α-factor (GenScript) for 1 h. Estradiol (500 nM, Sigma-Aldrich) was then added to induce dCas9-UDG* expression, and the cultures were incubated for an additional 2 h. Uninduced controls were prepared without estradiol. To degrade dCas9-UDG*, 1 mM indole-3-acetic acid (IAA, Thermo Fisher) was added 1 h before plating. Cells were then diluted (10 − 4 ) and plated on YPD plates containing 1 mM IAA in four replicates. The number of colonies for each strain was counted using ImageJ software, and the percentage of survival, calculated by [(colony number * dilution factor (10 4 ))\ (OD * 10 7 ) * 100], was normalized to uninduced survival levels. SDs were calculated using Excel. Microscopy Yeast cells were grown overnight in SC medium containing 4% glucose at 30°C. Cultures were diluted to an OD 600 of 0.2, and SiR-HALO dye was added to a final concentration of 800 nM 22,23 . To arrest cells in the G1 phase, 10 µg/ml of α-factor (GenScript) was added, and cultures were incubated for 1 h. Estradiol (500 nM, Sigma-Aldrich) was then added to induce dCas9-UDG* expression, and the cultures were incubated for an additional 2 h. Uninduced controls were prepared without estradiol. To degrade dCas9-UDG*, 1 mM IAA (Thermo Fisher) was added 1 h before imaging. For microscopy, cells were immobilized in slide chambers (Ibidi) precoated with 2 mg/ml concanavalin A (Sigma). Before imaging, cells were washed thoroughly with a warm SC medium containing 4% glucose and 1 mM IAA to remove residual α-factor and SiR-HALO dye. Live-cell imaging was conducted using a Cell-Discoverer 7 inverted wide-field microscope (Zeiss) equipped with a Colibri 7 LED light source. Imaging was performed at 30°C, with a 50× water immersion objective (NA = 1.2). Time-lapse imaging was carried out at 1 min intervals over a 3 h period in 3D, capturing 8 z-sections spaced 0.8 µm apart. Fluorescence signals from LacI-Halo-SiR, TetR-tdTomato, and GFP-RPA or Rad51-GFP were visualized using 650 nm, 561 nm, and 488 nm excitation wavelengths, respectively. Quantification and statistical analysis Time-lapse imaging data were collected using ZEN 3.0 software and analyzed with a custom Python-based computational pipeline (AutoCRAT, see below) to measure replication fork progression, essentially as previously described 22 , 23 . The pipeline identifies, tracks, and quantifies fluorescence signals from LacI-Halo-SiR, TetR-tdTomato, and RPA-GFP foci in individual cells. At least 120 cells were analyzed and merged for each strain across 2–5 independent experiments. Replication time data was statistically analyzed using Monte Carlo resampling with 1,000,000 iterations. Swarm plots were generated using the Seaborn package in Python to visualize replication timing distributions. Error bars in bulk viability analysis (Fig. 6 B) were calculated after merging two independent experiments containing three technical repeats and represent standard deviation from the mean. DSB data statistics ( Supplementary Fig. 1D and 2C ) was analyzed from three independent repeats using a t-test and the standard deviation from the mean is presented. GFP-RPA analysis was performed using a custom computational pipeline designed to identify and quantify GFP-RPA foci that co-localize with the lacO and tetO arrays, normalize their signals to the replication time of the arrays, and average the normalized RPA profiles of all cells. Thresholds for RPA foci intensity (65 AFU) and time duration (12 min) were set following visual inspection of the dynamics of colocalization and calculation of enrichment of RPA-positive cells between induced and uninduced strains. The outputs included replication-normalized signal averaging plots (see Fig. 4 A) and heatmap profiles (see Fig. 4 B). Cells were then categorized into sub-populations based on predefined manually validated thresholds. RPA-positive cells were defined as having co-localized GFP foci with a total fluorescence intensity > 65 arbitrary units for > 12 consecutive min. Within this population, early-RPA cells were defined by average normalized intensities of 0.3, and < 0.4 during the replication-normalized time windows [-0.5, 0], [0.6, 1.6] and [2.2, 3], respectively. Late-RPA cells were defined by average normalized intensities < 0.35, 0.3 during the same time windows. RAD51-positive cells were defined as having co-localized GFP foci with a total fluorescence intensity of > 105 arbitrary units for > 12 consecutive min. To ensure consistent sub-population definitions, all microscopy experiments in all strains were performed under identical illumination conditions, and all data analysis was performed using identical thresholds. DSB analysis was performed by counting total live cells in the imaging field and identifying cells with DSBs following G1 synchronization, 2 h of Cas9 induction and release into the cell cycle. DSB-positive cells were defined as those exhibiting LacI-Halo-SiR and TetR-tdTomato foci separated by more than 1 µm 23 , identified using automated image analysis throughout a 3 h experiment. Statistical differences were validated using a Z-test. Viability analysis was performed by manually identifying anaphase timing in replicating cells. Cells were classified as viable if the anaphase event occurred within 80 mins of tetO array replication. Cells were excluded from anaphase analysis if tetO duplication took place less than 80 mins before the end of the experiment. Data and Code Availability The sequence datasets generated and analyzed during this study are available in the Gene Expression Omnibus repository, https://www.ncbi.nlm.nih.gov/geo , under accession number GEO: GSE301837. Reviewer access: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE301837 Reviewer token: ojujwwuitzsbvmb The code used for image analysis of all microscopy experiments performed in this study is available in GitHub repository. The main repository for AutoCRAT: https://github.com/dovratd/AutoCRAT The repository for accessory scripts: https://github.com/dovratd/AutoCRAT-accessory-scripts Declarations Acknowledgements We thank the Aharoni lab members for useful comments throughout the project, Giuseppe Petrosino and the Genomics and Bioinformatics Core Facilities at IMB for support with GLOE-Seq, and Marta Garbacz for helpful input at early stages. Work in the Aharoni laboratory is supported by the Israeli Science Foundation (ISF) grant number 707/21, the Binational Science Foundation (BSF-NSF) grant number 2021737, BSF grant number 2023164, and Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant numbers 552129721 and 548574498. In the Ulrich lab, the project was funded by DFG grant numbers 548574498 and 393547839 – SFB 1361. Author Contributions Conceptualization, A.A. and H.D.U.; Methodology, A.C., D.D., N.Z., E.R.C. and L.S.B.; Investigation & Data Analysis, A.C., D.D., W.K., N.Z., H.D.U. and A.A.; Writing, A.A. and H.D.U; Funding Acquisition, A.A. and H.D.U.; Resources, A.C. and D.D.; Supervision, A.A. and H.D.U. Competing interests The authors declare no competing interests. References Jackson SP, Bartek J (2009) The DNA-damage response in human biology and disease. 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Nucleic Acids Res 42 Additional Declarations There is NO Competing Interest. Supplementary Files CohenetalAPsites2025SINCV3.docx SUPPLEMENTARY INFO Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:47:31","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":206676,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/b1089398871e26c877bcf0ac.html"},{"id":99601569,"identity":"8613f73c-5b1c-49f5-aced-6912a8e1af0f","added_by":"auto","created_at":"2026-01-06 10:47:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":401253,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA system for the real-time monitoring of replication fork progression through locus-specific AP sites\u003c/strong\u003e. (\u003cstrong\u003eA\u003c/strong\u003e) Schematic illustration of the system. AP sites are introduced by transient expression of dCas9-UDG* during G1, followed by auxin-induced degradation and release into S phase. Replication fork progression and RPA accumulation are measured simultaneously in S and G2 phase by monitoring the duplication of the fluorescently labeled \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003earrays and colocalization of GFP-labeled Rfa1 (see \u003cstrong\u003eFig. S3A\u003c/strong\u003e for representative images). (\u003cstrong\u003eB\u003c/strong\u003e) Experimental protocol for the induction and degradation of dCas9-UDG* during G1. (\u003cstrong\u003eC\u003c/strong\u003e) Western blots showing dCas9-UDG* levels during induction and degradation. Pgk1 serves as a loading control.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/28da3654b1f04800b2ed772a.png"},{"id":99601572,"identity":"b5b77132-71fe-4f85-b0d7-bff13c9df24c","added_by":"auto","created_at":"2026-01-06 10:47:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":514481,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003edCas9-UDG* generates AP sites preferentially in the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSCA\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) AP sites are introduced at \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e in both strands in a gRNA-specific manner and without causing substantial strand breakage. Genome browser views of GLOE-Seq signals in \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e and its surrounding genomic region, prepared from \u003cem\u003eWT*\u003c/em\u003e samples after dCas9-UDG* induction in G1, with or without gRNA and \u003cem\u003ein vitro\u003c/em\u003e APE1 pre-treatment. (\u003cstrong\u003eB\u003c/strong\u003e) dCas9-UDG* generates GLOE-Seq signals preferentially at T in \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e. Nucleotide frequencies in GLOE-Seq signals are plotted in comparison to the percentages present in the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e sequence and the rest of the nuclear genome. (\u003cstrong\u003eC\u003c/strong\u003e) Absolute numbers of AP sites (+APE1) or strand breaks (-APE1) in \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e and the rest of the nuclear genome, quantified by standardization to a partial \u003cem\u003eNot\u003c/em\u003eI digest.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/e5f990f1bcc2089f232b4fe5.png"},{"id":99601570,"identity":"61538804-ee28-4a49-a438-3aab17fb40c8","added_by":"auto","created_at":"2026-01-06 10:47:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":320586,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLocus-specific AP sites impede replisome progression. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Different loads of AP sites, introduced by dCas9-UDG*, lead to replication delays. Replication times through \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e, or \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e are shown in the presence or absence (for \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e) of gRNA in \u003cem\u003eWT*\u003c/em\u003e cells with (I) or without (U) dCas9-UDG* induction. Replication through \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e after induction of dCas9-UDG* in the absence of gRNA serves as a control for nonspecific damage. (\u003cstrong\u003eB\u003c/strong\u003e) Induction of AP sites enhances the percentage of RPA-positive cells. The percentage of cells with a colocalized RPA focus was quantified relative to the total number of cells\u003cstrong\u003e \u003c/strong\u003efor which replication was recorded in \u003cem\u003eWT* \u003c/em\u003estrains harboring\u003cem\u003e SCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e, SCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e, \u003c/em\u003eor\u003cem\u003e SCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e with uninduced (U) or induced (I) dCas9-UDG*. A \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e\u003csub\u003e \u003c/sub\u003estrain without gRNA served as a control for nonspecific damage. (\u003cstrong\u003eC\u003c/strong\u003e) Formation of extended stretches of ssDNA is associated with prolonged replisome delay. Replication times of uninduced (U) or induced (I) cells with (+) or without (-) RPA foci are shown for \u003cem\u003eWT*\u003c/em\u003e strains containing \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e, or \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/7a5f392200f1f1b3fd7c41e1.png"},{"id":99601574,"identity":"54b7b113-cc0e-49c3-8c01-8310ce675afe","added_by":"auto","created_at":"2026-01-06 10:47:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":691145,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe timing of daughter-strand gap formation defines two distinct response modes. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eRPA foci, marking daughter-strand gaps,\u003cstrong\u003e \u003c/strong\u003eare\u003cstrong\u003e \u003c/strong\u003eformed following replisome passage through the AP sites.\u003cstrong\u003e \u003c/strong\u003eThe normalized fluorescence intensity of RPA, \u003cem\u003elacO \u003c/em\u003eand \u003cem\u003etetO \u003c/em\u003efoci, monitored during AP site replication, is averaged over all RPA-positive cells, and the time axis is normalized to the replication time in each cell. Shaded areas represent the standard error of the mean. The dashed black curve represents a fit of RPA foci intensities to a sigmoidal function. The relative location of the AP sites (0.35) and the midpoint of GFP fluorescence intensity (0.63) are indicated as dashed grey and green lines, respectively. (\u003cstrong\u003eB\u003c/strong\u003e) A heatmap of RPA foci dynamics in individual cells, aligned to panel A, reveals two major sub-populations exhibiting early (top) or late (bottom) RPA foci relative to replisome position. (\u003cstrong\u003eC\u003c/strong\u003e) RPA foci in the early-RPA sub-population arise close to the replisome and are rapidly resolved (midpoint: 0.63). (\u003cstrong\u003eD\u003c/strong\u003e) Early-RPA cells exhibit a pronounced replication delay. Replication times are shown for RPA-negative (-), early- (E) or late- (L) RPA cells containing \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e, or \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e (see also \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eFig. 5\u003c/strong\u003e). (\u003cstrong\u003eE\u003c/strong\u003e) RPA foci in the late-RPA sub-population arise far from the replisome and are not resolved (midpoint: 1.54). (\u003cstrong\u003eF\u003c/strong\u003e) Early-RPA cells exhibit a higher probability of reaching anaphase relative to late-RPA cells but a lower probability than RPA-negative cells (see also \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/882d647aab3aa0fd184e3e44.png"},{"id":99601576,"identity":"35034583-d70f-45f8-b13c-bf12ce91a14b","added_by":"auto","created_at":"2026-01-06 10:47:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":363065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTS and SR are associated with strong replisome delay and early daughter-strand gap formation. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eReplication delay at the AP sites is suppressed in \u003cem\u003eubc13Δ\u003c/em\u003e, \u003cem\u003erad18Δ\u003c/em\u003e, and \u003cem\u003esrs2Δ \u003c/em\u003ebut is restored in \u003cem\u003erad18Δ\u003c/em\u003e \u003cem\u003esrs2Δ\u003c/em\u003e double mutant. Replication times of RPA-positive (+) and -negative (-) cells are shown. (\u003cstrong\u003eB\u003c/strong\u003e) Early-RPA cells decrease in frequency in \u003cem\u003eubc13Δ\u003c/em\u003e, \u003cem\u003erad18Δ\u003c/em\u003e, and \u003cem\u003esrs2Δ\u003c/em\u003e but the frequency is restored in \u003cem\u003erad18Δ\u003c/em\u003e \u003cem\u003esrs2Δ\u003c/em\u003edouble mutant. Shown is the percentage of RPA-positive cells with late, early, or no clear pattern (other) of RPA foci. For additional analysis of the mutant strains, see \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eFig. 6\u003c/strong\u003e. (\u003cstrong\u003eC\u003c/strong\u003e) RPA foci formation is delayed in \u003cem\u003eubc13Δ \u003c/em\u003e(midpoint: 1.24) \u003cem\u003eversus\u003c/em\u003e \u003cem\u003eWT*\u003c/em\u003e cells (midpoint: 0.63, see \u003cstrong\u003eFig. 4A\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/78cf0394058e41c802832ffe.png"},{"id":99601578,"identity":"9d5f7466-90e3-41f5-9728-0b9d7d63118c","added_by":"auto","created_at":"2026-01-06 10:47:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":605368,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTLS polymerases affect cell viability, the timing of daughter-strand gap formation, and replisome progression. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eInactivating individual TLS polymerases interferes with anaphase in the RPA-negative (-) population but promotes anaphase of early- (E) and late- (L) RPA populations (except for \u003cem\u003erev3Δ\u003c/em\u003e late-RPA cells).\u003cstrong\u003e \u003c/strong\u003eValues are normalized to the respective uninduced populations (\u003cem\u003eWT*\u003c/em\u003e values from \u003cstrong\u003eFig. 4F\u003c/strong\u003e). (\u003cstrong\u003eB\u003c/strong\u003e) Induction of dCas9-UDG* reduces bulk viability of individual TLS mutants relative to the \u003cem\u003eWT*\u003c/em\u003e strain. Viability is measured by colony formation and normalized to the respective uninduced conditions. (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eDeletion of \u003cem\u003eRAD30\u003c/em\u003e accelerates\u003cstrong\u003e \u003c/strong\u003ethe formation of RPA foci after fork passage through the AP sites.\u003cstrong\u003e \u003c/strong\u003eRPA foci dynamics is shown during AP site replication in\u003cem\u003e WT* \u003c/em\u003eearly-RPA cells\u003cem\u003e \u003c/em\u003e(top, midpoint: 0.63, see \u003cstrong\u003eFig. 4C\u003c/strong\u003e) and \u003cem\u003erad30Δ\u003c/em\u003e (bottom, midpoint: 0.5). Dashed lines mark the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e position and the RPA midpoints. (\u003cstrong\u003eD-E\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eInterfering with TLS\u003cstrong\u003e \u003c/strong\u003epartially suppresses the dCas9-UDG*-induced replication delay.\u003cstrong\u003e \u003c/strong\u003eReplication times are shown for early- (\u003cstrong\u003eD\u003c/strong\u003e) and late- (\u003cstrong\u003eE\u003c/strong\u003e) RPA cells in \u003cem\u003eWT*\u003c/em\u003e and TLS mutants. For additional analysis of the mutant strains, see \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eFig. 8\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/dbd67bcd9a6226947ea67e81.png"},{"id":99601583,"identity":"9f149c41-a6c1-48e0-9b46-f9f5d3cd8773","added_by":"auto","created_at":"2026-01-06 10:47:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":530667,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA dynamic model for DNA damage bypass. \u003c/strong\u003eThe cartoon highlights the decision points and kinetics of the major DDT pathways upon encounter of the replisome with AP sites. (\u003cstrong\u003eA\u003c/strong\u003e) If PCNA is not ubiquitylated (top), the replisome proceeds with little delay, but the resulting daughter-strand gap undergoes slow expansion (late-RPA), leading to unresolved gaps far behind the replication fork. A temporary uncoupling of the DNA polymerase from the replicative helicase allows for association of RPA and subsequent PCNA monoubiquitylation (middle). Recruitment of a TLS polymerase can promote efficient lesion bypass at the fork (\u003cstrong\u003eTLS\u003c/strong\u003e) without emergence of a larger stretch of ssDNA (RPA-negative). Alternatively, PCNA is polyubiquitylated (bottom), which is associated with a delay in replisome progression, largely due to competition with TLS polymerases. PCNA polyubiquitylation promotes rapid gap expansion upon repriming of the replisome (early-RPA) and HR-mediated resolution of the gap close to the replication fork (\u003cstrong\u003eTS\u003c/strong\u003e). (\u003cstrong\u003eB\u003c/strong\u003e) In the absence of PCNA ubiquitylation (\u003cem\u003erad18Δ\u003c/em\u003e), deletion of \u003cem\u003eSRS2\u003c/em\u003e restores the replisome delay and allows for rapid gap expansion, followed by gap repair close to the fork via the \u003cstrong\u003eSR\u003c/strong\u003e pathway. (SUMO: brown ball; ubiquitin: black balls).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/94b0eedaf6e72627a1fe66f7.png"},{"id":99804252,"identity":"45aa0494-dff1-4f1f-81b8-ff636db98912","added_by":"auto","created_at":"2026-01-08 14:12:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5615994,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/019b0568-6d7e-4419-a9a3-721d2bb980ce.pdf"},{"id":99793042,"identity":"623c4153-11de-403c-b987-438c8861ee69","added_by":"auto","created_at":"2026-01-08 13:30:55","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3416068,"visible":true,"origin":"","legend":"SUPPLEMENTARY INFO","description":"","filename":"CohenetalAPsites2025SINCV3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8353672/v1/9bd1be92298d58f2de08e429.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Replication fork stalling at DNA lesions is driven by competition between damage bypass pathways","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGenome maintenance systems ensure faithful transmission of a cell\u0026rsquo;s genetic information to the next generation in face of DNA damage and replication stress\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. They comprise DNA damage signaling systems, DNA repair pathways responsible for the removal of lesions, and replication-associated DNA damage tolerance (DDT) mechanisms ensuring complete and accurate genome duplication\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Although many of the factors and molecular mechanisms contributing to these protective pathways have been characterized in detail, we are only beginning to understand their dynamic interplay in the context of a live cell.\u003c/p\u003e \u003cp\u003eSystems for the site-specific analysis of DNA transactions have been instrumental for elucidating mechanisms of genome maintenance. For example, sequence-specific endonucleases have served to unravel the choreography of DNA double-strand break (DSB) repair\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Similarly, responses to replication fork blockage have been revealed using sequence-specific DNA-binding proteins\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Importantly, these approaches combine the advantages of single-cell strategies, i.e., the option of gaining real-time insight into the dynamics of key players via fluorescence microscopy, with those of bulk techniques such as next-generation sequencing, which provide quantitative data on a genome-wide scale. However, most insults to the genome have not been amenable to such tools, as they usually arise randomly scattered across the genome and their chemical nature tends to be heterogeneous.\u003c/p\u003e \u003cp\u003eBy developing a system to monitor the replicative processing of DNA polymerase-stalling lesions in a defined genomic locus, we have now gained insight into the dynamic regulation of DDT in real time. DDT promotes the bypass of lesions by effectively postponing their removal until after replication of the damaged region\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. It operates either via mutagenic translesion synthesis (TLS) by specialized DNA polymerases capable of replicating damaged DNA or via an error-free template switching (TS) mechanism that utilizes the undamaged sister chromatid for homologous recombination (HR). In eukaryotes, TLS and TS are controlled by the mono- and polyubiquitylation of the replication factor PCNA\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, respectively. In the absence of PCNA ubiquitylation, HR-mediated lesion processing is still possible via an alternative pathway known as salvage recombination (SR)\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. There is good evidence that DDT can act in association with the replisome, i.e., \u0026ldquo;on the fly\u0026rdquo;, but also \u0026ndash; via re-priming of the replisome downstream of the damaged region \u0026ndash; in a postreplicative manner after passage of the replication fork\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, we still know little about the extent of replication fork stalling at DNA lesions and how it is connected to the choice between the DDT pathways, the timing of their activation relative to replisome movement, and their effects on cell viability.\u003c/p\u003e \u003cp\u003eWe now present a tool that is based on the introduction of site-specific abasic or apurinic/apyrimidinic (AP) sites, which are among the most common spontaneous DNA lesions, arising thousands of times per day in eukaryotic cells\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. They are formed by spontaneous hydrolysis of the N-glycosidic bond or via active removal of damaged or mismatched bases by DNA glycosylases in the context of base excision repair (BER)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. If left unrepaired, AP sites and their byproducts impede replisome progression, and their bypass \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e has been shown to involve DDT\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Here, using a CRISPR-based targeting approach, we enzymatically introduce AP sites into an early-replicating region of the budding yeast genome. Via a reporter system based on two fluorescently marked repressor arrays surrounding the damaged region\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, we monitor the effects of AP sites on the replication kinetics of this locus and their processing via TLS, TS and SR in real time.\u003c/p\u003e \u003cp\u003eApplication of this system provides high-resolution, quantitative insight into the temporal and spatial organization of DNA damage bypass. By measuring fork stalling and differentiating between TLS and HR-mediated bypass on a single-cell level, we found that the bypass of AP sites is associated with a marked delay in replication fork progression. Importantly, this delay is not caused by the inability of the replisome to move across lesions but rather by a competition between TLS and TS factors at the replication fork. We uncover common features between TS and SR, such as extended fork stalling and the emergence and resolution of a daughter-strand gap closely behind the fork. Overall, this approach reveals the choreography of AP site bypass, laying the practical and conceptual foundation for future studies of the dynamic regulation of the DNA replication stress response.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign of a real-time monitoring system for the replicative bypass of AP sites\u003c/h2\u003e \u003cp\u003eEstablishment of an experimental system for the real-time monitoring of locus-specific DNA damage bypass (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) necessitates a critical set of design principles. First, it requires the introduction of replication-stalling lesions that are physiological substrates of DDT. Second, the lesions need to be introduced into a defined genomic target region whose replication can be monitored in real time. Finally, lesions should be inducible in a controlled manner that is coordinated with genome replication and affords control over the damage load.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo fulfill the first criterium, we made use of a mutant human uracil DNA glycosylase, UDG\u003csup\u003eY147A\u003c/sup\u003e (here called UDG*). This enzyme had been reported to excise thymine from single-stranded (ss) or double-stranded (ds) DNA\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The resulting AP sites are known to interfere strongly with replication. \u003cem\u003eIn vitro\u003c/em\u003e, the concerted activities of replicative DNA polymerase δ and TLS polymerase ζ are required to replicate an AP site-containing template\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In budding yeast, AP sites introduced randomly into the genome are processed by mutagenic ubiquitin-dependent TLS involving polymerases ζ and Rev1\u003csup\u003e17\u003c/sup\u003e. Thus, AP sites are common physiological targets of DDT.\u003c/p\u003e \u003cp\u003eFor the second criterium \u0026ndash; the ability to target UDG* to a specific genomic region \u0026ndash; we fused the protein to catalytically inactive Cas9 (dCas9). A synthetic CRISPR array (\u003cem\u003eSCA\u003c/em\u003e) containing multiple target sequences for dCas9-UDG* was designed for integration into the desired locus, and the dCas9-UDG* construct was combined with an expression cassette for a matching guide RNA (gRNA, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eTo follow replication of the damaged or undamaged \u003cem\u003eSCA\u003c/em\u003e in real time, we employed a live-cell imaging-based approach that we recently developed for \u003cem\u003eS. cerevisiae\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Here, replication is monitored by tracking the intensity changes of two fluorescently labeled arrays (\u003cem\u003elacO\u003c/em\u003e\u003csub\u003e\u003cem\u003e128\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003etetO\u003c/em\u003e\u003csub\u003e\u003cem\u003e128\u003c/em\u003e\u003c/sub\u003e) inserted in the vicinity of an early-replicating origin, \u003cem\u003eARS413\u003c/em\u003e, by time-lapse microscopy (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Measuring the interval between the duplication times of each fluorescent reporter during the cell cycle allows us to infer the progression of single replisomes through the genomic region between the reporters\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Importantly, the region is predominantly replicated with defined directionality from the neighboring \u003cem\u003eARS413\u003c/em\u003e as the downstream origin, \u003cem\u003eARS414\u003c/em\u003e, is located far from \u003cem\u003etetO\u003c/em\u003e (see map and explanation in \u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e). We previously applied this approach to measure replisome progression through G4-containing sequences\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e or actively transcribing genes\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, observing replication slowdown in various mutant strains. For monitoring DDT, the \u003cem\u003eSCA\u003c/em\u003e is now inserted between the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e reporters.\u003c/p\u003e \u003cp\u003eThe third criterium, control over lesion induction and damage load, was implemented by placing the dCas9-UDG* sequence under the control of an estradiol-inducible promoter\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e and equipping the protein with an auxin-inducible degron tag (AID)\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. These features allow for transient induction of AP sites in G1-arrested cells and subsequent removal of the enzyme before release into S phase, without the need to exchange the growth medium (\u003cb\u003eFig.\u0026nbsp;1BC\u003c/b\u003e). Thus, the number of AP sites in the \u003cem\u003eSCA\u003c/em\u003e that will be encountered in the following round of replication can be tuned by means of the duration of dCas9-UDG* induction or by varying the number of gRNA target sequence repeats (n) in the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e (\u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e, or \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e). Premature repair of the AP sites or unwanted processing into strand breaks is minimized by using an \u003cem\u003eapn1Δ\u003c/em\u003e mutant, deficient in the major BER-specific AP endonuclease\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. As the default strain background for this study, this mutant is therefore designated as \u0026ldquo;\u003cem\u003eWT*\u003c/em\u003e\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eValidation of site-specific AP site induction\u003c/h3\u003e\n\u003cp\u003eTo validate gRNA-mediated recruitment of the Cas9 construct to the \u003cem\u003eSCAs\u003c/em\u003e, we first induced catalytically active Cas9 during G1 and monitored the appearance of DSBs by means of a separation between the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e reporters (\u003cb\u003eSupplementary Fig.\u0026nbsp;1B\u003c/b\u003e). We observed successful gRNA-dependent DSB induction in all three \u003cem\u003eSCAs\u003c/em\u003e against a low background in the absence of Cas9 (\u003cb\u003eSupplementary Fig.\u0026nbsp;1C\u003c/b\u003e). This indicates efficient recruitment of Cas9 to the \u003cem\u003eSCA\u003c/em\u003e in most cells. Next, we optimized the induction and depletion times of dCas9-UDG* during G1. The protein appears within 30 min of estradiol addition and reaches near complete degradation within 60 min of auxin treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Based on these properties, we settled on a 2 h induction period, followed by a 1 h degradation phase in G1-arrested cells.\u003c/p\u003e \u003cp\u003eTo confirm the specific introduction of AP sites within the \u003cem\u003eSCA\u003c/em\u003e following dCas9-UDG* expression, we analyzed isolated genomic DNA via \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eG\u003c/span\u003eenome-wide \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eL\u003c/span\u003eigation of 3\u0026rsquo;-\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eO\u003c/span\u003eH \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eE\u003c/span\u003ends in combination with next-generation \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSeq\u003c/span\u003euencing (GLOE-Seq)\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. This technique localizes strand breaks with nucleotide precision, and \u003cem\u003ein vitro\u003c/em\u003e pre-treatment of the DNA with a lesion-specific endonuclease further permits the detection of various base lesions. To analyze and quantify AP sites, we therefore combined the protocol with APE1 pre-treatment and used the signals from a partial digestion of the genomic DNA with a rare-cutting restriction enzyme, \u003cem\u003eNot\u003c/em\u003eI, for standardization and absolute quantification\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsistent with selective UDG* activity, GLOE-Seq analysis of genomic DNA isolated from \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e \u003cem\u003eWT*\u003c/em\u003e cells after dCas9-UDG* induction in G1 phase showed a marked enrichment of signals on both strands in and around the \u003cem\u003eSCA\u003c/em\u003e compared to a control strain lacking the gRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Importantly, GLOE-Seq without APE1 pre-treatment yielded much lower signals, indicating that most AP sites introduced by dCas9-UDG* do not give rise to strand breaks. As expected from using the T-specific UDG* enzyme, comparison of nucleotide frequencies among the GLOE-Seq signals revealed an enrichment of T in \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e far beyond its relative representation in the sequence specifically in APE1-treated samples of strains containing the gRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). On a genome-wide level, enrichment of T was much less pronounced, indicating that dCas9-UDG* preferentially targets the \u003cem\u003eSCA\u003c/em\u003e over non-specific regions. Absolute quantification revealed an average of ca. 0.6 AP sites within \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), corresponding to a lesion density of approximately 0.9 kbp\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compared to less than 0.3 kbp\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the rest of the genome. While our method does not differentiate between isolated and clustered or closely spaced lesions\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, this suggests that approximately 50% of all \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e cells experienced at least one AP site in the target region, assuming a Poisson distribution.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eAP sites introduced by dCas9-UDG* are successfully bypassed in S phase\u003c/h3\u003e\n\u003cp\u003eAs a final validation step, we examined by live-cell imaging and bulk viability assays whether the replisome originating from \u003cem\u003eARS413\u003c/em\u003e can bypass the damaged \u003cem\u003eSCA\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). To this end, we released cells into S phase after transient G1 induction of dCas9-UDG* (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) and examined replication through the damaged \u003cem\u003eSCA\u003c/em\u003e by monitoring the duplication of the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e arrays surrounding the AP sites. A complete blockage of replication at the AP sites should result in failure to replicate the downstream \u003cem\u003etetO\u003c/em\u003e during the 3 h experiment in a substantial number of cells. However, microscopy analysis revealed no increase in such cell population following dCas9-UDG* induction (\u003cb\u003eSupplementary Fig.\u0026nbsp;2A\u003c/b\u003e). The possibility of replication of \u003cem\u003etetO\u003c/em\u003e from the neighboring (downstream) \u003cem\u003eARS414\u003c/em\u003e was deemed unlikely because 88% of cells replicated \u003cem\u003etetO\u003c/em\u003e with replication times of up to 30 min (∆t, defined as the time interval for \u003cem\u003elacO\u003c/em\u003e to \u003cem\u003etetO\u003c/em\u003e mid-array duplication) (\u003cb\u003eSupplementary Fig.\u0026nbsp;2B\u003c/b\u003e), while use of \u003cem\u003eARS414\u003c/em\u003e would \u0026ndash; based on the distance (\u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e) \u0026ndash; result in replication of the \u003cem\u003etetO\u003c/em\u003e\u0026thinsp;~\u0026thinsp;40 min following \u003cem\u003elacO\u003c/em\u003e replication. Moreover, replication times were not significantly affected by deletion of \u003cem\u003eARS414\u003c/em\u003e, confirming the intended replication directionality (\u003cb\u003eSupplementary Fig.\u0026nbsp;2B\u003c/b\u003e). Extensive DSB formation during \u003cem\u003eSCA\u003c/em\u003e replication was excluded by quantification of the co-localization between \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e, which indicated a separation of the reporters in less than 7% of all cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;2C\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eTo assess the success of AP site bypass in a bulk experiment, we quantified the viability of \u003cem\u003eWT*\u003c/em\u003e cells after transient dCas9-UDG* induction for 2 h. We found that more than 85% of cells containing \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e survived the treatment and were able to form colonies (\u003cb\u003eSupplementary Fig.\u0026nbsp;2D\u003c/b\u003e). Taken together, these data imply that the overall damage load induced by our system can be successfully bypassed in cells with an intact DDT system in the absence of BER. Therefore, the system was deemed suitable for an \u003cem\u003ein vivo\u003c/em\u003e analysis of DDT under close-to-realistic conditions.\u003c/p\u003e\n\u003ch3\u003eAP sites in the replication template delay replisome progression\u003c/h3\u003e\n\u003cp\u003eHaving validated the selective activity of dCas9-UDG* (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), we measured how varying loads of AP sites would affect replication progression. In our system, transient stalling or slowdown of replication is detected by an increase in the replication time relative to unperturbed replication\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. We found that induction of dCas9-UDG* significantly delayed replication through the \u003cem\u003eSCAs\u003c/em\u003e, while unselective activation of the enzyme in the absence of gRNA had no effect on the replication of \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Moreover, replication delay in the absence of \u003cem\u003eAPN1\u003c/em\u003e (\u003cem\u003eWT*\u003c/em\u003e) was not reduced compared to BER-positive (\u003cem\u003eWT\u003c/em\u003e) cells, suggesting that the AP sites themselves, rather than BER intermediates, are the leading cause of replication slowdown (\u003cb\u003eSupplementary Fig.\u0026nbsp;2E\u003c/b\u003e). To examine whether the observed replication delay was a direct consequence of replisome stalling or slowdown by the AP sites or an indirect effect of DNA damage checkpoint activation, we measured replication in checkpoint-deficient \u003cem\u003erad9Δ\u003c/em\u003e cells in the \u003cem\u003eWT*\u003c/em\u003e background. We found that the \u003cem\u003erad9Δ\u003c/em\u003e mutation suppressed the replication delay following dCas9-UDG* induction only to a minor extent (\u003cb\u003eSupplementary Fig.\u0026nbsp;2E\u003c/b\u003e), indicating that checkpoint activation contributes little to the slowdown.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOverall, these results show that AP sites in the replication template significantly impede replisome progression, thus allowing us to examine the interplay between fork stalling and the activation of the different DDT pathways.\u003c/p\u003e\n\u003ch3\u003eAP site bypass can proceed with or without the formation of extended stretches of ssDNA\u003c/h3\u003e\n\u003cp\u003eWe had previously shown that the ssDNA-binding Replication Protein A (RPA) complex is required for recruitment of the ubiquitin protein ligase (E3) Rad18 to mediate PCNA ubiquitylation\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and can serve as a proxy for postreplicative damage bypass\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. We therefore quantified the signal of GFP-labeled Rfa1 associated with the bypass of AP sites during the cell cycle, focusing on bright foci that co-localized with the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e reporters (\u003cb\u003eSupplementary Fig.\u0026nbsp;3\u003c/b\u003e) and persisted for more than 12 minutes (min, see methods for criteria justification). Using these criteria, we observed co-localizing RPA foci following dCas9-UDG* induction in nearly 30% of the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e cells, corresponding to a\u0026thinsp;~\u0026thinsp;3-fold increase relative to uninduced conditions or to unselective dCas9 induction without gRNA \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). A similar fraction of RPA-positive cells following dCas9-UDG* induction was observed in the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e strain, whereas in the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e strain, a smaller fraction of these cells was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Interestingly, RPA-positive \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e cells exhibited significantly more severe delays in replication through the array than cells without foci, although both sub-populations were delayed relative to undamaged cells in all \u003cem\u003eSCA\u003c/em\u003e strains (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). This indicates that lesions are present and can impede replisome progression even when they do not give rise to strong RPA foci. These data suggest that AP site bypass proceeds via at least two different modes, one of them accompanied by severe fork stalling or slowdown and the formation of extended stretches of ssDNA. Moreover, the RPA-associated mode becomes more prominent with increasing damage loads.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRPA foci reflect postreplicative daughter-strand gaps\u003c/h2\u003e \u003cp\u003eAlignment of the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e replication profiles\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e can reveal the timing of an event, e.g., the binding of a specific protein, relative to replisome progression through the intervening region for a given cell population (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Using this analysis in the RPA-positive cell population, we found that RPA foci intensity gradually increased during replisome progression through \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e and reached its maximum after duplication of the downstream \u003cem\u003etetO\u003c/em\u003e reporter (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cb\u003eSupplementary Fig.\u0026nbsp;4A\u003c/b\u003e). To validate that RPA foci formation was coupled to replisome progression through the AP sites, we also analyzed cells containing the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e integrated further distal to \u003cem\u003eARS413\u003c/em\u003e between \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e. In these \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e-distal cells, the midpoint of RPA foci formation was shifted to a later time relative to the midpoint measured in \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e-proximal cells, in accordance with the altered location of the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;4BC\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). In addition, deletion of \u003cem\u003eEXO1\u003c/em\u003e, encoding a nuclease responsible for expanding postreplicative daughter-strand gaps in preparation for HR-mediated repair\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, delayed the timing of RPA foci increase relative to \u003cem\u003eWT*\u003c/em\u003e cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;4D\u003c/b\u003e). These experiments confirm that RPA foci represent daughter-strand gaps and are driven by replisome progression through the AP sites. They also demonstrate that RPA is predominantly recruited in a postreplicative manner, consistent with our previous observation of the kinetics of RPA foci induced by the alkylating agent methyl methanesulfonate (MMS)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. We therefore interpret the RPA foci as postreplicative daughter-strand gaps, resulting from the resumption of replication downstream of the lesions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDaughter-strand gap dynamics reveal three distinct response modes\u003c/h3\u003e\n\u003cp\u003eClustering of individual RPA-positive cells according to their foci patterns during the cell cycle revealed two distinct sub-populations exhibiting RPA accumulation at different times relative to replisome progression through the AP sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In one sub-population, termed \u0026ldquo;early-RPA\u0026rdquo;, foci intensity reached its midpoint when the replisome had progressed\u0026thinsp;~\u0026thinsp;5.9 kbp beyond the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e, followed by a resolution after replication of \u003cem\u003etetO\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). Notably, the GFP fluorescence patterns of individual early-RPA cells indicated that both foci formation and resolution were rapid reactions (\u003cb\u003eSupplementary Fig.\u0026nbsp;4E\u003c/b\u003e). This population experienced a severe replication delay through the different \u003cem\u003eSCAs\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). In another sub-population, termed \u0026ldquo;late-RPA\u0026rdquo;, the intensities of the foci grew more gradually (\u003cb\u003eSupplementary Fig.\u0026nbsp;4E\u003c/b\u003e), reached their midpoint much later, when the replisome was ~\u0026thinsp;31.5 kbp beyond the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e, and plateaued toward the end of the observation period (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). This population experienced no significant replication delay over the RPA-negative cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). An additional, heterogeneous group of cells was identified without clearly defined RPA dynamics and with no replication delay (\u003cb\u003eSupplementary Fig.\u0026nbsp;5AB\u003c/b\u003e). Early- and late-RPA populations were present in roughly equal proportions among the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e or \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e64\u003c/em\u003e\u003c/sub\u003e RPA-positive cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;5C\u003c/b\u003e), and their relative timing was similar in the three \u003cem\u003eSCA\u003c/em\u003e strains (\u003cb\u003eSupplementary Fig.\u0026nbsp;5D\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). These results suggest that this divergent response to AP sites is robust and largely independent of the number of lesions and the region across which they are spread. Finally, we monitored the timing of anaphase among the different sub-populations as a measure of viability within the time frame of observation. Surprisingly, late-RPA cells were dramatically less successful in completing the cell cycle than early-RPA cells, and these were, in turn, less successful than the RPA-negative population, of which more than 90% passed through mitosis. Failure of RPA-positive cells to undergo anaphase increased with increasing length of the \u003cem\u003eSCA\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF and \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eOverall, these results show that cells have a choice between at least three distinct modes of AP site processing. The first involves efficient and successful bypass with a relatively minor slowdown of replication, no detectable RPA foci, and little impact on viability (RPA-negative cells). The second is a replication-associated response characterized by a severe delay in replisome progression through the AP sites, a daughter-strand gap arising transiently and closely behind the moving fork, and an increased risk of failure to complete the cell cycle in a timely manner (early-RPA cells). The third is characterized by a relatively minor slowdown of replication, the gradual formation of a persistent daughter-strand gap after the replication fork has passed the AP sites, and strongly reduced viability as measured by anaphase events (late-RPA cells).\u003c/p\u003e\n\u003ch3\u003eTS delays fork progression and is activated shortly after replisome passage\u003c/h3\u003e\n\u003cp\u003eTo link the dynamics of RPA foci to the various DDT mechanisms, we examined a set of mutants specifically targeting the individual sub-pathways. Deletion of \u003cem\u003eUBC13\u003c/em\u003e, encoding the ubiquitin-conjugating enzyme (E2) responsible for PCNA polyubiquitylation, selectively inactivates the TS pathway. Microscopy analysis of \u003cem\u003eubc13Δ\u003c/em\u003e cells revealed a complete suppression of the lesion-induced replication delays \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cb\u003eSupplementary Fig.\u0026nbsp;6A)\u003c/b\u003e, indicating that the observed replication fork stalling requires PCNA polyubiquitylation. Moreover, the overall fraction of RPA-positive cells and specifically the early-RPA population were severely depleted in \u003cem\u003eubc13Δ\u003c/em\u003e mutants, and the appearance of RPA foci was considerably delayed (\u003cb\u003eFig.\u0026nbsp;5BC\u003c/b\u003e, \u003cb\u003eSupplementary Fig.\u0026nbsp;6BC\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;1)\u003c/b\u003e. This suggests that the early-RPA pattern, accompanied by a strong replication delay (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), represents AP site bypass by the TS pathway controlled by PCNA polyubiquitylation. Deletion of \u003cem\u003eRAD18\u003c/em\u003e, which completely abolishes PCNA ubiquitylation and compromises both TS and TLS, largely mirrored the results obtained with \u003cem\u003eubc13Δ\u003c/em\u003e mutants (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003eB\u003c/b\u003e and \u003cb\u003eSupplementary Fig.\u0026nbsp;6A-C\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs TS is thought to proceed via sister-chromatid recombination, we also monitored the appearance of HR intermediates via an internally GFP-tagged, functional \u003cem\u003eRAD51\u003c/em\u003e allele\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The strong increase of Rad51 foci that colocalize with \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e following dCas9-UDG* induction and their dependence on \u003cem\u003eUBC13\u003c/em\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;6D\u003c/b\u003e) confirmed the importance of HR for the TS pathway. Interestingly, while in a \u003cem\u003eWT*\u003c/em\u003e background the percentages of Rad51-positive and RPA-positive cells were similar (30\u0026ndash;35%), deletion of \u003cem\u003eUBC13\u003c/em\u003e caused a much stronger reduction in Rad51 compared to RPA positive cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;6D\u003c/b\u003e). This suggests that in \u003cem\u003eWT\u003c/em\u003e* cells, most Rad51 foci represent TS events. Considering that HR involves a cooperation of RPA with Rad51, it also implies that in \u003cem\u003eubc13Δ\u003c/em\u003e mutants, a sizable fraction of daughter-strand gaps does not undergo HR and may therefore represent unsuccessful attempts at gap repair.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLike TS, SR is activated closely behind the replisome\u003c/h2\u003e \u003cp\u003eVia its association with SUMOylated PCNA in S phase\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, the antirecombinogenic helicase Srs2 was shown to suppress HR by preventing the formation of the recombinogenic Rad51 filament\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Deletion of \u003cem\u003eSRS2\u003c/em\u003e in DDT-deficient cells therefore rescues viability by activating SR\u003csup\u003e32,33\u003c/sup\u003e. Nevertheless, \u003cem\u003esrs2Δ\u003c/em\u003e single mutants exhibit a damage sensitivity comparable to \u003cem\u003eubc13Δ\u003c/em\u003e mutants\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. To characterize the contributions of Srs2, we examined the effects of deleting the gene in \u003cem\u003eWT*\u003c/em\u003e and \u003cem\u003erad18Δ\u003c/em\u003e cells. In the \u003cem\u003esrs2Δ\u003c/em\u003e single mutant, the fraction of RPA-positive cells and \u0026ndash; even more so \u0026ndash; of cells with Rad51 foci increased dramatically (\u003cb\u003eSupplementary Fig.\u0026nbsp;6D\u003c/b\u003e), consistent with the activation of HR. Moreover, RPA foci intensities were higher in \u003cem\u003esrs2Δ\u003c/em\u003e relative to \u003cem\u003eWT\u003c/em\u003e* cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;6E\u003c/b\u003e). Surprisingly, however, replication kinetics was reminiscent of \u003cem\u003eubc13Δ\u003c/em\u003e mutants, with little replisome delay (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, \u003cb\u003eSupplementary Fig.\u0026nbsp;6A\u003c/b\u003e) but a strong delay in the appearance and inefficient resolution of RPA or Rad51 foci (\u003cb\u003eSupplementary Fig.\u0026nbsp;6F\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). Taken together, these data suggest that in a TS-competent background, Srs2 contributes to fork stalling and promotes early gap repair while preventing late \u0026ndash; and likely inefficient \u0026ndash; recombination.\u003c/p\u003e \u003cp\u003eSpecific activation of the SR pathway was examined in a \u003cem\u003erad18Δ srs2Δ\u003c/em\u003e double mutant. As expected, deletion of \u003cem\u003eSRS2\u003c/em\u003e partially suppressed the damage sensitivity of \u003cem\u003erad18Δ\u003c/em\u003e in our strain background (\u003cb\u003eSupplementary Fig.\u0026nbsp;6G\u003c/b\u003e). Microscopy analysis of \u003cem\u003erad18Δ srs2Δ\u003c/em\u003e cells revealed a \u003cem\u003eWT\u003c/em\u003e*-like replication delay following dCas9-UDG* induction and an almost 2-fold increase in the early-RPA population relative to the \u003cem\u003erad18Δ\u003c/em\u003e or \u003cem\u003esrs2Δ\u003c/em\u003e single mutants (\u003cb\u003eFig.\u0026nbsp;5AB, Supplementary Fig.\u0026nbsp;6A-C\u003c/b\u003e). Compared to \u003cem\u003eWT\u003c/em\u003e* cells, the early-RPA foci emerged even earlier in the double mutant (\u003cb\u003eSupplementary Fig.\u0026nbsp;6H\u003c/b\u003e). Overall, these results indicate that the SR pathway, activated in the absence of both PCNA ubiquitylation and the anti-recombinase Srs2, exhibits similar characteristics to the TS pathway, promoting HR bypass closely behind replication forks and characterized by significant fork stalling or slowdown.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTLS does not involve large daughter-strand gaps and competes with HR-dependent DDT\u003c/h2\u003e \u003cp\u003eBypass of AP sites not involving extended daughter-strand gaps may reflect TLS. We therefore examined the importance of this pathway using single TLS polymerase deletions (\u003cem\u003erad30Δ, rev1Δ\u003c/em\u003e, \u003cem\u003erev3Δ\u003c/em\u003e) as well as a triple deletion (\u003cem\u003etlsΔ\u003c/em\u003e). Consistent with a positive contribution of TLS to DDT in RPA-negative cells, completion of anaphase in this population was decreased in \u003cem\u003erad30Δ\u003c/em\u003e, \u003cem\u003erev1Δ\u003c/em\u003e, and \u003cem\u003erev3Δ\u003c/em\u003e single mutants (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Surprisingly, however, the \u003cem\u003etlsΔ\u003c/em\u003e mutation restored the viability of the RPA-negative cells, possibly suggesting a dominant negative effect of the remaining TLS polymerases in the single deletions. Bulk colony formation experiments were in excellent agreement with the microscopy analysis, further validating the importance of TLS for cell viability following dCas9-UDG* induction (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Notably, loss of TLS polymerases suppressed the damage-dependent replication delays in the RPA-negative cells and in the total induced populations (\u003cb\u003eSupplementary Fig.\u0026nbsp;7AB\u003c/b\u003e). Taken together, these results indicate the importance of TLS polymerase activity for AP site bypass in cells that do not develop an extended daughter-strand gap.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWhen we compared RPA foci populations in the TLS mutants, we found no major changes, except for a mild increase of RPA positive in the \u003cem\u003erad30Δ\u003c/em\u003e mutant (\u003cb\u003eSupplementary Fig.\u0026nbsp;7CD\u003c/b\u003e). Interestingly, however, the early-RPA foci, corresponding to TS events, peaked at an even earlier time point in \u003cem\u003erad30Δ\u003c/em\u003e and \u003cem\u003etlsΔ\u003c/em\u003e compared to \u003cem\u003eWT*\u003c/em\u003e cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e), suggesting that TS-associated daughter-strand gap expansion occurs earlier in these mutants. In addition, we found a partial suppression of the replication delay in the early-RPA cells of \u003cem\u003erad30Δ, rev1Δ\u003c/em\u003e and \u003cem\u003etlsΔ\u003c/em\u003e and in the late-RPA population of \u003cem\u003etlsΔ\u003c/em\u003e, relative to the respective \u003cem\u003eWT*\u003c/em\u003e populations (\u003cb\u003eFig.\u0026nbsp;6DE\u003c/b\u003e). These results show that the presence of TLS polymerases slows down HR-mediated bypass of AP sites. Moreover, anaphase analysis revealed that most TLS deletions improved viability of the early and late-RPA cells relative to the respective \u003cem\u003eWT*\u003c/em\u003e populations, with a maximal increase observed in the \u003cem\u003etlsΔ\u003c/em\u003e mutant (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). Thus, it seems that the TLS polymerases interfere with AP site bypass via TS, not only by delaying daughter-strand gap expansion but also by interfering with successful completion of the cell cycle. Surprisingly, the deletion of \u003cem\u003eREV3\u003c/em\u003e alone abolished cell cycle completion in the late-RPA cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), possibly suggesting a contribution of polymerase ζ to gap filling late in the cell cycle.\u003c/p\u003e \u003cp\u003eOverall, these results highlight the importance of TLS for the viability of cells that do not develop a daughter-strand gap, but they also indicate competition between TLS polymerases and the TS-mediated bypass that leads to a delay in daughter-strand gap expansion, replication progression, and reduced viability.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we describe a real-time monitoring system for the replicative bypass of AP sites in a defined genomic locus in live yeast cells. Application to a range of genetic backgrounds has allowed us to disentangle the choreography of DNA damage bypass, revealing the extent of fork stalling and its association with different pathways, the sequence of events, the hierarchy of bypass pathways acting at or behind the replication fork, and the implications for successful completion of the cell cycle.\u003c/p\u003e \u003cp\u003eBased on the overall delay in replisome passage and the dynamics of ssDNA around the damaged region, we identified two cell populations exhibiting distinct bypass patterns that correlate well with the major DDT pathways: TLS, TS, and SR. The largest discernable population, characterized by minor replisome delay and the absence of substantial stretches of ssDNA (RPA-negative cells), is dominated by TLS. Judging by the rate of anaphase completion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), this mode of DDT is associated with the highest success rates. Consistent with their dependence on HR, cells engaging in TS or SR exhibit RPA foci (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e–\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These pathways are accompanied by a major replisome delay with a daughter-strand gap forming less than 6 kbp behind the replisome (early-RPA) and operate with moderate efficiency. We identified a third RPA-positive population exhibiting minor replisome delay, generating a daughter-strand gap more than 30 kbp behind the replisome (late-RPA), with low success rates. The model shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e summarizes our findings in the context of DDT pathway choice and illustrates replisome stalling as a conditional event initiated by the competitive actions of damage processing factors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTLS polymerases promote AP site bypass but interfere with HR-dependent pathways\u003c/h2\u003e \u003cp\u003eThe involvement of TLS polymerases in DDT has been studied extensively, with evidence for both fork-associated (“on the fly”) and postreplicative action\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Our analysis shows that TLS mediates AP site bypass without detectable RPA foci, implying either polymerase switching during replisome passage or the filling of a small and transient daughter-strand gap. The notion that replisome delay is more pronounced in the presence of the TLS polymerases than in their absence (\u003cb\u003eSupplementary Fig.\u0026nbsp;7AB\u003c/b\u003e) suggests that at least some of the bypass events are slow and occur directly at the fork. Moreover, our assay probably underestimates the TLS-associated replication delay due to the presence of RPA-negative cells that did not experience a lesion. Fork-associated TLS of cyclobutene pyrimidine dimers, mediated by polymerase η (Rad30), has also been observed recently\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsistent with previous reports implying a concerted action of multiple polymerases in the insertion and extension of nucleotides opposite AP sites\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, we found reduced viability in all the single TLS polymerase mutants (\u003cb\u003eFig.\u0026nbsp;6AB\u003c/b\u003e). Surprisingly, however, combined deletion of all three TLS genes restored viability, suggesting that other polymerases, probably independent of PCNA ubiquitylation, can mediate efficient AP site bypass in their absence. Indeed, a biochemical study revealed that polymerase ε can bypass AP sites with relatively high efficiency \u003cem\u003ein vitro\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInterestingly, the replisome delay conferred by the TLS polymerases affects not only RPA-negative cells, but also those undergoing HR-mediated gap repair. Moreover, in these cells, abolishing TLS enhances viability (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), suggesting that TLS interferes with HR-mediated bypass. The acceleration of daughter-strand gap expansion in TLS-deficient cells (\u003cem\u003erad30Δ\u003c/em\u003e and \u003cem\u003etlsΔ\u003c/em\u003e) and the increase in the fraction of RPA-negative cells likely undergoing TLS upon deletion of \u003cem\u003eUBC13\u003c/em\u003e can be interpreted as a competition of polymerase η with the PCNA polyubiquitylation machinery for access to monoubiquitylated PCNA, the common intermediate of TLS and TS\u003csup\u003e41\u003c/sup\u003e, or with the downstream events initiated by the polyubiquitin chain. Competition between TS and TLS by polymerase ζ and Rev1 behind the fork was also reported in the bypass of (6 − 4) photoproducts and bulky adducts\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In the case of polymerase ζ, the loss of viability upon \u003cem\u003eREV3\u003c/em\u003e deletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA) indicates a potential collaboration between this TLS polymerase and the SR machinery. In fact, a contribution of polymerase ζ to HR is consistent with previous findings showing that \u003cem\u003eREV3\u003c/em\u003e is responsible for high mutagenesis during DSB repair in yeast\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eTS and SR delay the replisome but accelerate daughter-strand gap expansion and enable gap filling\u003c/h2\u003e \u003cp\u003eDespite the identification of a growing number of regulatory factors\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan additionalcitationids=\"CR44 CR45\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e–\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, the mechanism of TS initiation, its activation relative to the replisome, its consequences for replication fork stalling, and its relationship to SR are still poorly understood\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Both TS and SR are thought to be active in S and G2/M phase, based on the appearance of characteristic X-shaped HR intermediates on two-dimensional gels\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, but there are no data about their relative timing other than the assumption that SR is a pathway of last resort that becomes relevant if TLS and TS fail. TS is thought to occur mainly in a postreplicative manner\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, although impacts on fork progression have been noted\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur analysis shows that during the bypass of AP sites, the TS pathway is accompanied by a pronounced replisome delay, followed by the early appearance of an RPA focus. We interpret this as a slow repriming reaction, giving rise to a daughter-strand gap that is then rapidly expanded. Despite the absence of PCNA polyubiquitylation, the SR pathway appears to operate with similar kinetics. Our results also imply that a delay of gap expansion prevents efficient recombination-mediated gap repair. This suggests that both TS and SR, by accelerating gap expansion, ensure recombination closely behind the replication fork, when sister chromatids are still closely aligned\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, and chromatin is potentially not fully matured. As noted above, the TS-associated delay in replisome progression is consistent with competition between PCNA polyubiquitylation enzymes and TLS polymerases. Interestingly, activation of SR is associated with a similar replisome delay in a DDT-deficient background where competition with TLS polymerases should not apply. Whether the delay in this situation reflects the lack of an alternative processing pathway or a coordination with ubiquitin-independent HR factors remains to be determined.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePostreplicative bypass pathways are chosen at or close to the stalled replication fork\u003c/h2\u003e \u003cp\u003ePerhaps the most surprising finding emerging from our kinetic analysis of RPA foci is the observation that the two HR-mediated pathways, TS and SR, although both operating in a postreplicative fashion, originate from a decision that is made at or close to the site of replisome stalling. The notion that replisomes experience a pronounced delay in TS or SR cells implies that there is a limited window of opportunity at the replication fork to engage in PCNA polyubiquitylation and activate TS or, in the absence of the ubiquitylation, SR. The underlying choice may be influenced by several factors, such as the load and distribution of lesions or the persistence of PCNA itself at the fork. Loss of PCNA from the stalled primer-template junction might thus prevent timely activation of TS, for example by Elg1-mediated unloading\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e or if the PCNA-polymerase complex releases the primer terminus and is “dragged along” with the moving replisome. Such events might result in a daughter-strand gap that is expanded slowly and is unsuitable for efficient repair.\u003c/p\u003e \u003cp\u003eOur results indicate an approximately equal population of cells undergoing TS versus cells accumulating unresolved daughter-strand gaps later in the cell cycle, in a genetic background where the only DNA repair defect is an inactivation of BER to stabilize AP sites (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e–\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cb\u003eSupplementary Fig.\u0026nbsp;5\u003c/b\u003e). This suggests that a significant proportion of cells with unresolved gaps accumulates during replication through AP sites even in cells capable of PCNA ubiquitylation. These cells may elicit checkpoint activation, leading to cell cycle arrest and reduced capacity to complete anaphase. Nevertheless, we cannot exclude that TS can also be activated at an unexpanded gap later during the cell cycle, for example, by reloading of PCNA. In fact, we and others previously showed that ubiquitin-dependent DDT can be deferred to G2/M phase by restricting the expression of the relevant E3s\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Likewise, it is possible that some TS events proceed too rapidly to yield a measurable RPA focus, especially when TLS is not competing. Such events might contribute to the enhanced survival of RPA-negative cells in the \u003cem\u003etlsΔ\u003c/em\u003e background.\u003c/p\u003e \u003cp\u003eDespite the detailed insight that our system of inducible AP sites provides into the kinetics of DDT, several open questions remain to be addressed in future studies. These pertain to the distribution of AP sites between the leading and lagging strand templates and the respective consequences for DDT. The dCas9-UDG* construct exhibits little strand bias (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Yet, lesions on the lagging strand template would not be expected to stall the replisome, although they might give rise to daughter-strand gaps\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Our replisome progression data, therefore, appear to reflect predominantly the effects of leading strand stalling. Future studies inducing strand-specific lesions will be needed to tease apart the fate of leading- \u003cem\u003eversus\u003c/em\u003e lagging-strand damage.\u003c/p\u003e \u003cp\u003eOne major limitation is our current lack of information about the exact nature of the lesions at the time they are encountered by the replisome. Although we showed that most cells do not experience strand breaks in the \u003cem\u003eapn1Δ\u003c/em\u003e background, AP sites are reactive structures that can also result in DNA-protein crosslinks\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Moreover, we cannot exclude clusters of closely spaced AP sites resulting from extended residence of dCas9-UDG* at the \u003cem\u003eSCA\u003c/em\u003e, as GLOE-Seq does not distinguish these from isolated AP sites\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Such clusters would likely aggravate replisome stalling compared to single lesions and may affect the balance between the DDT pathways.\u003c/p\u003e \u003cp\u003eRegarding the relative contributions of DDT pathways, our analysis has highlighted important properties of each mechanism, but it may over- or underestimate their frequencies. For example, we cannot distinguish TLS from potentially very rapid TS events among the RPA-negative cells. Considering that \u003cem\u003eREV1\u003c/em\u003e expression peaks in the G2/M phase\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e, our analysis, focusing on an early-replicating region, may underestimate the contribution of this TLS polymerase to AP site bypass. Finally, we cannot assign a defined pathway to the sub-population of RPA-positive cells whose RPA pattern does not fall into either the “early” or the “late” category (defined as “others”). A transition between pathways, e.g. a participation of TLS polymerases at an extended daughter-strand gap, may account for some of these events.\u003c/p\u003e \u003cp\u003eOur experimental system, with its ability to differentiate between TS and SR, paves the way to a better understanding of replicative damage processing. It will enable us to determine what factors dictate the choice between alternative pathways, elucidate the respective mechanisms of daughter-strand gap expansion, and identify the factors contributing to gap filling in either pathway. Its real-time approach is highly complementary to other set-ups designed to observe DDT. For example, episomal or integrated plasmids carrying single, defined lesions\u003csup\u003e\u003cspan additionalcitationids=\"CR54 CR55\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e–\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e have given ample information about the efficiency and accuracy of DDT, but they do not provide kinetic information. \u003cem\u003eIn vitro\u003c/em\u003e reconstitution of DNA replication on damaged templates has revealed valuable time-resolved insight into TLS and repriming on a population level\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e but is not well suited for analyzing pathway choices in a complex cellular environment. The same holds true for single-molecule measurements with purified components\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe single-cell strategy described here enables us to monitor the timing of damage bypass with respect to replisome position, and to disentangle the direct effects of fork progression through damaged regions from global cellular effects such as cell cycle arrest and checkpoint signaling. Expansion to other types of DNA damage, e.g. base deamination or ssDNA breaks, will be possible via the choice of Cas9 variants\u003csup\u003e\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e–\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, and the monitoring of additional key HR factors such as Rad52, or Rad54\u003csup\u003e61\u003c/sup\u003e, is expected to increase the utility of this system for revealing the kinetics of recombination-mediated lesion bypass.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003cdiv id=\"Sec28\" class=\"Section4\"\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Methods","content":"\u003ch2\u003ePlasmid construction\u003c/h2\u003e\u003cp\u003ePlasmids pAC-Cas9-27 and pAC-Cas9-28 containing Cas9 under the control of the \u003cem\u003eGAL10\u003c/em\u003e promoter, with and without a gRNA, respectively, were constructed using a pRS306 plasmid as a backbone (\u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e). The Cas9 gene was fused to the AID* tag\u003csup\u003e25\u003c/sup\u003e followed by a \u003cem\u003eCYC1\u003c/em\u003e terminator. A guide RNA (gRNA) cassette targeting a sequence derived from the hygromycin resistance cassette (GACCTGATGCAGCTCTCGGA)\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e or a \u003cem\u003eStu\u003c/em\u003eI site (empty control) was cloned to target the Cas9 to the Synthetic CRISPR Arrays (\u003cem\u003eSCAs\u003c/em\u003e, see below). Plasmids pAC-dCas9-53 and pAC-dCas9-54 encoding dCas9-UDG* were generated by amplifying the Uracil DNA Glycosylase (UDG) gene deleted of the first 84 amino acids from human cDNA and introducing the T174A mutation via overlapping primers\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The resulting UDG* was cloned in frame to the 5’ end of Cas9 containing the D10A and H840A point mutations, containing an AID* tag, yielding a catalytically inactive dCas9-UDG*. The dCas9-UDG* was fused to a \u003cem\u003eCYC1\u003c/em\u003e terminator, an additional C-terminal AID* tag followed by a 9×FLAG tag and the gRNA (\u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e). For incorporating GFP at the N-terminal region of Rfa1, the pAG25-sfGFP-RFA1-gRNA plasmid was constructed by cloning an \u003cem\u003eRFA1\u003c/em\u003e sequence, recoded to avoid Cas9-mediated digestion, and an N-terminal sfGFP fusion amplified from pAG25-sfGFP-RFA1 (kindly provided by the Schuldiner lab, Weizmann Institute, Israel). To allow sfGFP-RFA1 genomic integration, the pCAS3-RFA1-g1-2 plasmid was generated from the previously described pCAS2 plasmid\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e by introducing two gRNA sequences targeting the N-terminal region of native Rfa1 (AGGTACGATAATCCCACCGG and AGCAGTGTTCAACTTTCGAG) (\u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e). \u003cem\u003eSCAs\u003c/em\u003e consisting of 8, 16 or 64 repeats of the gRNA target sequence (described above) with 20 bp random sequences between the repeats, were obtained from BioBasic. Arrays with the 16 or 64 repeats were inserted into a pUC origin plasmid to generate the pDD-SCA plasmids containing homology regions at the 5’ and 3’ ends to enable genomic integration (\u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e). The \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e8\u003c/em\u003e\u003c/sub\u003e was amplified from the \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e plasmid, appending sequences for integration between the lacO/tetO arrays by HR. All plasmid constructions were performed using Gibson Assembly according to the manufacturer’s instructions. The resulting constructs were validated by polymerase chain reaction (PCR) and confirmed through Sanger sequencing.\u003c/p\u003e\u003ch2\u003eStrain generation\u003c/h2\u003e\u003cp\u003e \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e strains for replication measurements were generated using the W1588 \u003cem\u003eMATa\u003c/em\u003e background, expressing nuclear LacI-HaloTag and TetR-tdTomato fusion proteins\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The strains contain non-repetitive \u003cem\u003elacO\u003c/em\u003e\u003csub\u003e\u003cem\u003e128\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003etetO\u003c/em\u003e\u003csub\u003e\u003cem\u003e128\u003c/em\u003e\u003c/sub\u003e arrays located at chrIV:332960 and chrIV:352560, respectively, near the autonomously replicating sequence (ARS) 413, with an inter-array distance of ~ 25.5 kb. The \u003cem\u003eSCAs\u003c/em\u003e were inserted into the genome between the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e arrays into chrIV:340385 or chrIV:352558 locations using a two-step integration process\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. First, a yeast-selectable marker (\u003cem\u003enatMX6\u003c/em\u003e antibiotic resistance gene) was integrated into the genome by HR. The marker was then replaced with a linearized pDD-SCA plasmid, co-transformed with the pCAS2-NAT plasmid to facilitate \u003cem\u003eSCA\u003c/em\u003e integration\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. For generating the \u003cem\u003eapn1∆\u003c/em\u003e strains, the \u003cem\u003eAPN1\u003c/em\u003e coding region was replaced through HR with either \u003cem\u003ehphMX\u003c/em\u003e or \u003cem\u003ekanMX\u003c/em\u003e antibiotic resistance cassettes, using primers with 100 bp homology to the target genomic region. The antibiotic resistance markers were later deleted from the genome using a two-step integration process with a short oligonucleotide cassette, as previously described\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. All other knockout strains (\u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e) were generated in the background of \u003cem\u003eapn1∆\u003c/em\u003e (\u003cem\u003eWT*\u003c/em\u003e) by replacing the coding regions via HR with antibiotic resistance cassettes (\u003cem\u003enatMX6\u003c/em\u003e or \u003cem\u003ekanMX\u003c/em\u003e), or with the \u003cem\u003eHIS3MX6\u003c/em\u003e auxotrophic cassette. Integration was validated using internal and external primers specific to the genomic region of the deleted genes. To facilitate estradiol-mediated Cas9 induction, GEM plasmids for the expression of Estradiol receptor (EstR) fused to Gal4 binding domain and transcription activation domain (TAD) (kindly provided by the Pasero lab)\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e were linearized and integrated into the \u003cem\u003eTRP1\u003c/em\u003e or \u003cem\u003eAUR1\u003c/em\u003e loci by HR. All plasmids for Cas9 integration were linearized using \u003cem\u003eXcm\u003c/em\u003eI and integrated into the \u003cem\u003eura3-1\u003c/em\u003e locus. The \u003cem\u003eOryza sativa TIR1\u003c/em\u003e gene was integrated at the \u003cem\u003eADE1\u003c/em\u003e locus to enable auxin-induced degradation of Cas9. For RPA tagging, sfGFP was incorporated at the N-terminus of Rfa1 by co-transforming the pAG25-sfGFP-RFA1 gRNA-resistant plasmid along with CRISPR/Cas9-mediated HR using the pAC-Rfa1-pCAS3-g1-2 system. For \u003cem\u003eRAD51\u003c/em\u003e tagging, iGFP was PCR-amplified from a strain containing \u003cem\u003eRAD51\u003c/em\u003e-iGFP\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, followed by incorporation into the \u003cem\u003eRAD51\u003c/em\u003e locus of the microscopy strains. Integration was enabled by co-transformation of the iGFP together with a CRISPR/Cas9 plasmid targeting the \u003cem\u003eRAD51\u003c/em\u003e gene\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Positive colonies were verified by PCR followed by microscopy analysis. The strain and plasmid for RAD51-iGFP generation were a kind gift from Angela Taddei.\u003c/p\u003e\u003ch2\u003eWestern blots\u003c/h2\u003e\u003cp\u003eWestern blotting was performed to monitor Cas9 induction and degradation. Protein extraction was carried out as previously described\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Briefly, 2 OD\u003csub\u003e600\u003c/sub\u003e units of exponentially growing yeast cells were harvested at three time points: before estradiol induction, 2 h after estradiol induction, and 1 h after degradation with IAA. The cell pellet was resuspended in 500 µl of doubly distilled water and mixed with 75 µl of 1.85 M NaOH/7.5% β-mercaptoethanol. After 15 min of incubation, 75 µl of 55% TCA was added to the mixture, followed by centrifugation. The resulting pellet was resuspended in 40 µl of high-urea protein loading buffer (8 M urea, 5% SDS, 200 mM Tris-HCl, 1 mM EDTA, and 0.1% bromophenol blue pH 6.8), boiled at 65°C and spun down. For analysis, 8 µl of the protein supernatants were loaded onto a 10% precast SDS-PAGE gel (Bio-Rad) and separated by electrophoresis. Proteins were transferred to a nitrocellulose membrane using the Trans-Blot Turbo system (Bio-Rad) according to manufacturer’s protocol. Membranes were blocked with PBST (PBS containing 0.1% Tween 20) supplemented with 5% skim milk for 1 h, followed by three 5 min washes with PBST. Cas9 was detected using a primary mouse anti-Cas9 antibody (1:2,000, Cell Signaling Technology) in PBST + 1% skim milk for 1 h, followed by incubation with a secondary goat anti-mouse antibody (1:10,000, Jackson ImmunoResearch) conjugated to horseradish peroxidase (HRP). The membrane was washed three times with PBST, and Cas9 was visualized using the EZ-ECL chemiluminescence detection kit (Thermo Fisher) according to the manufacturer’s instructions. Pgk1 was detected as a loading control using a primary mouse anti-Pgk1 antibody (1:50,00, Santa Cruz Biotechnology) and a secondary goat anti-mouse HRP-conjugated antibody (1:10,000, Jackson ImmunoResearch).\u003c/p\u003e\u003ch2\u003eIsolation of genomic DNA\u003c/h2\u003e\u003cp\u003eFor mapping of AP sites and strand breaks, genomic DNA (gDNA) was extracted from yeast cultures treated according to the scheme shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB before release into S phase. Cultures of 600 ml were treated with sodium azide (0.1% final concentration) and EDTA (20 mM final concentration), mixed thoroughly, and incubated on ice at 4°C for 15 min. Cells were pelleted by centrifugation at 2,000×\u003cem\u003eg\u003c/em\u003e for 5 min at room temperature. Pellets were washed with 30 ml of ice-cold PBS containing 5 mM EDTA, followed by another centrifugation step under the same conditions at 4°C.\u003c/p\u003e\u003cp\u003eCells were then resuspended in 4 ml of Y1 buffer (1 M sorbitol, 100 mM EDTA pH 8.0) containing 14 mM β-mercaptoethanol and treated with 4 mg of Zymolyase 100T at 30°C until spheroplasting exceeded 90%. Spheroplasts were pelleted at 2,000×\u003cem\u003eg\u003c/em\u003e for 2 min, washed once with 4 ml of Y1 buffer lacking β-mercaptoethanol, and gently resuspended in 7 ml of TEN buffer (50 mM Tris HCl pH 8.0, 50 mM EDTA, 100 mM NaCl) containing 1.5% Sarkosyl without vortexing. Subsequently, 4 mg of Proteinase K was added, and samples were gently mixed by inversion. Lysates were incubated for 1 h at 37°C, with gentle mixing every 10–15 min. Samples were then centrifuged at 3,000 rpm for 15 min at room temperature, the supernatants were transferred to 15 ml Falcon tubes, and their volumes were adjusted to 8.2 ml using TEN buffer containing 1.5% Sarkosyl. To establish a CsCl gradient, 8.6 g of CsCl\u003csub\u003e2\u003c/sub\u003e were added, and the solutions were incubated at 30°C until the CsCl\u003csub\u003e2\u003c/sub\u003e was fully dissolved. 15 µl of Hoechst 33342 (10 mg/ml) were added to each sample. Samples were transferred to OptiSeal tubes, balanced to 1 mg, and centrifuged in a VTi 65.1 rotor using an Optima XE-100 ultracentrifuge at 50,000 rpm for 20 h at 20° C.\u003c/p\u003e\u003cp\u003eFollowing ultracentrifugation, gDNA was extracted using 1.6 mm needles and transferred to 15 ml Falcon tubes, yielding an approximate volume of 3 ml per sample. DNA was purified by three extractions with an equal volume of 80% isopropanol, followed by centrifugation at 1,500 rpm for 3 min at room temperature. Ethanol (100%) was then added to a final concentration of 50%, and the solutions were gently mixed by inversion. At this stage, DNA often appeared as a cloudy or jelly-like substance rather than a precipitate. The liquid supernatants were carefully removed, and the DNA was washed 1–2 times with 70% ethanol, promoting dehydration into a solid pellet. After air drying, 100 µl of 0.25× IDTE (Integrated DNA Technologies) buffer was added, and the tubes were left overnight at 4°C to promote dissolution. DNA concentrations were determined using a Qubit fluorometer, and samples were stored at 4°C.\u003c/p\u003e\u003ch2\u003eMapping of AP sites via GLOE-Seq\u003c/h2\u003e\u003cp\u003eGLOE-Seq was performed in two independent replicates largely as previously described\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e, with minor modifications, including APE1 pre-digestion to convert AP sites to nicks and absolute quantification by means of partial \u003cem\u003eNot\u003c/em\u003eI digestion of the gDNA\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Oligonucleotides are listed in \u003cb\u003eSupplementary Table\u0026nbsp;5\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e \u003cb\u003eNot\u003c/b\u003e \u003cb\u003eI\u003c/b\u003e \u003cb\u003edigestion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo achieve 50% \u003cem\u003eNot\u003c/em\u003eI digestion, 5 µg of gDNA per sample were digested with \u003cem\u003eNot\u003c/em\u003eI-HF (New England Biolabs) to completion and combined with 5 µg of undigested gDNA. The digestion was stopped by adding EDTA to 25 mM, followed by a 10-min incubation at room temperature. DNA was purified using 100 µl of SPRI beads (HighPrep PCR from Biozol), which were washed twice with 1 ml of 80% ethanol, air-dried, and the DNA was eluted in 100 µl of nuclease-free water. DNA concentrations were determined using a Qubit fluorometer. The efficiency of \u003cem\u003eNot\u003c/em\u003eI digestion was assessed by qPCR using undigested gDNA as control. The qPCR assay targeted selected \u003cem\u003eNot\u003c/em\u003eI sites in the \u003cem\u003eS. cerevisiae\u003c/em\u003e genome: chromosome I (ID#5773/5774), chromosome II (ID#5775/5776), chromosome IV (ID#5805/5806), chromosome XII (ID#5809/5810), and a control region without \u003cem\u003eNot\u003c/em\u003eI site on chromosome III (ID#3331/3332). Three technical replicates were performed per condition. Amplification in untreated and \u003cem\u003eNot\u003c/em\u003eI-digested samples was compared using the ΔΔC\u003csub\u003eT\u003c/sub\u003e method \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Final cutting efficiency was calculated as the mean efficiency of all four \u003cem\u003eNot\u003c/em\u003eI-targeted sites on chromosomes I, II, IV, and XII.\u003c/p\u003e\u003ch2\u003eAPE1 treatment\u003c/h2\u003e\u003cp\u003eFollowing \u003cem\u003eNot\u003c/em\u003eI digestion, each sample was split into two equal portions, one of which was treated with 4 U/µg of APE1 (New England Biolabs) in 1× NEBuffer 4 at 37°C for 1 h, followed by heat inactivation at 65°C for 20 min. The other portion was incubated under identical conditions but without APE1. Both samples were then dephosphorylated using 1 U/µg of antarctic phosphatase (New England Biolabs), with incubation at 37°C for 1 h. DNA was purified using SPRI beads at a 1:1 volume ratio, washed twice with 80% ethanol, air‑dried, and eluted in nuclease‑free water. DNA concentration was subsequently determined by using a Qubit fluorometer.\u003c/p\u003e\u003ch2\u003ePreparation of GLOE-Seq libraries\u003c/h2\u003e\u003cp\u003eLibraries were prepared as described\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e, using biotinylated proximal adaptor (ID ID#3989/3899) for capturing of 3’-OH ends, extension primer (ID#3790) for second strand synthesis, and distal GLOE-Seq adaptor (and ID#3791/7060). Library amplification was carried out for 10 cycles using primers P5 and P7 (Illumina), followed by two rounds of purification using SPRI beads. To assess adaptor ligation efficiency and library quality, 1 µL of the final product was analyzed on an Agilent High Sensitivity D5000 ScreenTape, confirming a size range of approximately 250–530 bp. The concentrations of the libraries were determined using a Qubit fluorometer with reagents specific to dsDNA, and samples were pooled to a final concentration of 4 nM for sequencing on an Illumina NextSeq 2000 sequencer.\u003c/p\u003e\u003ch2\u003eGLOE-Seq data analysis\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003eS. cerevisiae\u003c/em\u003e reference genome (sacCer3) was modified to include \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e for strains 1566 and 1607 on chromosome IV. Additionally, chromosome XI was modified to reflect the deletion of \u003cem\u003eAPN1\u003c/em\u003e. For all analyses, mitochondrial DNA and the \u003cem\u003eNot\u003c/em\u003eI sites were excluded.\u003c/p\u003e\u003cp\u003eGLOE-Seq data were processed using GLOE-Pipe\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. Initial trimming of paired-end reads was performed using Cutadapt (v. 4.0)\u003csup\u003e66\u003c/sup\u003e, followed by alignment to the strain-specific reference genome using Bowtie2 (v. 2.4.5)\u003csup\u003e67\u003c/sup\u003e. BAM files were first filtered to select only the mapped R1 reads, and then they were converted into BED files using SAMtools (v. 1.10)\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e and BEDtools (v. 2.27.1)\u003csup\u003e69\u003c/sup\u003e. These BED files were utilized to identify 3’-OH ends in the indirect mode as part of the GLOE-Pipe, to count the number of reads assigned to the \u003cem\u003eNot\u003c/em\u003eI sites, and to calculate nucleotide frequency both within the \u003cem\u003eSCA\u003c/em\u003e and across the entire genome. The BED files were further converted into normalized BigWig files, which were then split into plus (FWD) and minus (REV) strands for visualization in a genome browser, using bamCoverage from deepTools (v. 3.5.1)\u003csup\u003e70\u003c/sup\u003e. These BigWig files were used to illustrate the profile within \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e and surrounding regions by utilizing computeMatrix and plotProfile from deepTools.\u003c/p\u003e\u003ch2\u003eAbsolute Quantification\u003c/h2\u003e\u003cp\u003eFor each sample, the absolute number of strand breaks or AP sites was quantified using \u003cem\u003eNot\u003c/em\u003eI signals as a standard essentially as described\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Briefly, GLOE-Seq data were used to determine the mean number of mapped reads per \u003cem\u003eNot\u003c/em\u003eI site over all \u003cem\u003eNot\u003c/em\u003eI sites. This value was divided by the mean cutting efficiency as determined by qPCR for each sample (see above). The resulting factor, α, was used for calculating the absolute numbers of 3’-OH ends within \u003cem\u003eSCA\u003c/em\u003e\u003csub\u003e\u003cem\u003e16\u003c/em\u003e\u003c/sub\u003e and within the rest of the nuclear genome (\u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003eSCA16\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003egenome\u003c/em\u003e\u003c/sub\u003e) from the total number of mapped reads in these regions (\u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003eSCA16\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003egenome\u003c/em\u003e\u003c/sub\u003e): \u003cem\u003eN\u003c/em\u003e = \u003cem\u003eR\u003c/em\u003e/α.\u003c/p\u003e\u003ch2\u003eViability assays\u003c/h2\u003e\u003ch2\u003eSpot assays\u003c/h2\u003e\u003cp\u003eYeast strains were grown to exponential phase, diluted to an OD\u003csub\u003e600\u003c/sub\u003e of 1, and 10-fold serial dilutions (5 µl each of OD\u003csub\u003e600\u003c/sub\u003e of 1, 0.1, 0.001, 0.0001) were spotted onto plates of YPD with or without 0.002% of MMS (Sigma). Strains were grown for two days at 30°C and imaged using MiniBIS Pro (DNR Bio-Imaging Systems).\u003c/p\u003e\u003ch2\u003eBulk viability assays\u003c/h2\u003e\u003cp\u003e \u003cem\u003eWT*\u003c/em\u003e and TLS KO strains were grown overnight in synthetic complete (SC) medium containing 4% glucose at 30°C. Cultures were diluted to an OD\u003csub\u003e600\u003c/sub\u003e of 0.2 and arrested in G1 phase by the addition of 10 µg/ml of α-factor (GenScript) for 1 h. Estradiol (500 nM, Sigma-Aldrich) was then added to induce dCas9-UDG* expression, and the cultures were incubated for an additional 2 h. Uninduced controls were prepared without estradiol. To degrade dCas9-UDG*, 1 mM indole-3-acetic acid (IAA, Thermo Fisher) was added 1 h before plating. Cells were then diluted (10\u003csup\u003e− 4\u003c/sup\u003e) and plated on YPD plates containing 1 mM IAA in four replicates. The number of colonies for each strain was counted using ImageJ software, and the percentage of survival, calculated by [(colony number * dilution factor (10\u003csup\u003e4\u003c/sup\u003e))\\ (OD * 10\u003csup\u003e7\u003c/sup\u003e) * 100], was normalized to uninduced survival levels. SDs were calculated using Excel.\u003c/p\u003e\n\u003ch3\u003eMicroscopy\u003c/h3\u003e\n\u003cp\u003eYeast cells were grown overnight in SC medium containing 4% glucose at 30\u0026deg;C. Cultures were diluted to an OD\u003csub\u003e600\u003c/sub\u003e of 0.2, and SiR-HALO dye was added to a final concentration of 800 nM\u003csup\u003e22,23\u003c/sup\u003e. To arrest cells in the G1 phase, 10 \u0026micro;g/ml of α-factor (GenScript) was added, and cultures were incubated for 1 h. Estradiol (500 nM, Sigma-Aldrich) was then added to induce dCas9-UDG* expression, and the cultures were incubated for an additional 2 h. Uninduced controls were prepared without estradiol. To degrade dCas9-UDG*, 1 mM IAA (Thermo Fisher) was added 1 h before imaging. For microscopy, cells were immobilized in slide chambers (Ibidi) precoated with 2 mg/ml concanavalin A (Sigma). Before imaging, cells were washed thoroughly with a warm SC medium containing 4% glucose and 1 mM IAA to remove residual α-factor and SiR-HALO dye. Live-cell imaging was conducted using a Cell-Discoverer 7 inverted wide-field microscope (Zeiss) equipped with a Colibri 7 LED light source. Imaging was performed at 30\u0026deg;C, with a 50\u0026times; water immersion objective (NA\u0026thinsp;=\u0026thinsp;1.2). Time-lapse imaging was carried out at 1 min intervals over a 3 h period in 3D, capturing 8 z-sections spaced 0.8 \u0026micro;m apart. Fluorescence signals from LacI-Halo-SiR, TetR-tdTomato, and GFP-RPA or Rad51-GFP were visualized using 650 nm, 561 nm, and 488 nm excitation wavelengths, respectively.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eQuantification and statistical analysis\u003c/h2\u003e \u003cp\u003eTime-lapse imaging data were collected using ZEN 3.0 software and analyzed with a custom Python-based computational pipeline (AutoCRAT, see below) to measure replication fork progression, essentially as previously described\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The pipeline identifies, tracks, and quantifies fluorescence signals from LacI-Halo-SiR, TetR-tdTomato, and RPA-GFP foci in individual cells. At least 120 cells were analyzed and merged for each strain across 2\u0026ndash;5 independent experiments. Replication time data was statistically analyzed using Monte Carlo resampling with 1,000,000 iterations. Swarm plots were generated using the Seaborn package in Python to visualize replication timing distributions. Error bars in bulk viability analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB) were calculated after merging two independent experiments containing three technical repeats and represent standard deviation from the mean. DSB data statistics (\u003cb\u003eSupplementary Fig.\u0026nbsp;1D and 2C\u003c/b\u003e) was analyzed from three independent repeats using a t-test and the standard deviation from the mean is presented.\u003c/p\u003e \u003cp\u003eGFP-RPA analysis was performed using a custom computational pipeline designed to identify and quantify GFP-RPA foci that co-localize with the \u003cem\u003elacO\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e arrays, normalize their signals to the replication time of the arrays, and average the normalized RPA profiles of all cells. Thresholds for RPA foci intensity (65 AFU) and time duration (12 min) were set following visual inspection of the dynamics of colocalization and calculation of enrichment of RPA-positive cells between induced and uninduced strains. The outputs included replication-normalized signal averaging plots (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) and heatmap profiles (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Cells were then categorized into sub-populations based on predefined manually validated thresholds. RPA-positive cells were defined as having co-localized GFP foci with a total fluorescence intensity\u0026thinsp;\u0026gt;\u0026thinsp;65 arbitrary units for \u0026gt;\u0026thinsp;12 consecutive min. Within this population, early-RPA cells were defined by average normalized intensities of \u0026lt;\u0026thinsp;0.35, \u0026gt;\u0026thinsp;0.3, and \u0026lt;\u0026thinsp;0.4 during the replication-normalized time windows [-0.5, 0], [0.6, 1.6] and [2.2, 3], respectively. Late-RPA cells were defined by average normalized intensities\u0026thinsp;\u0026lt;\u0026thinsp;0.35, \u0026lt;\u0026thinsp;0.4, and \u0026gt;\u0026thinsp;0.3 during the same time windows. RAD51-positive cells were defined as having co-localized GFP foci with a total fluorescence intensity of \u0026gt;\u0026thinsp;105 arbitrary units for \u0026gt;\u0026thinsp;12 consecutive min. To ensure consistent sub-population definitions, all microscopy experiments in all strains were performed under identical illumination conditions, and all data analysis was performed using identical thresholds.\u003c/p\u003e \u003cp\u003eDSB analysis was performed by counting total live cells in the imaging field and identifying cells with DSBs following G1 synchronization, 2 h of Cas9 induction and release into the cell cycle. DSB-positive cells were defined as those exhibiting LacI-Halo-SiR and TetR-tdTomato foci separated by more than 1 \u0026micro;m \u003csup\u003e23\u003c/sup\u003e, identified using automated image analysis throughout a 3 h experiment. Statistical differences were validated using a Z-test. Viability analysis was performed by manually identifying anaphase timing in replicating cells. Cells were classified as viable if the anaphase event occurred within 80 mins of \u003cem\u003etetO\u003c/em\u003e array replication. Cells were excluded from anaphase analysis if \u003cem\u003etetO\u003c/em\u003e duplication took place less than 80 mins before the end of the experiment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eData and Code Availability\u003c/h2\u003e \u003cp\u003eThe sequence datasets generated and analyzed during this study are available in the Gene Expression Omnibus repository, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, under accession number GEO: GSE301837.\u003c/p\u003e \u003cp\u003eReviewer access: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE301837\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE301837\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eReviewer token: ojujwwuitzsbvmb\u003c/p\u003e \u003cp\u003eThe code used for image analysis of all microscopy experiments performed in this study is available in GitHub repository.\u003c/p\u003e \u003cp\u003eThe main repository for AutoCRAT: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/dovratd/AutoCRAT\u003c/span\u003e\u003cspan address=\"https://github.com/dovratd/AutoCRAT\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe repository for accessory scripts: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/dovratd/AutoCRAT-accessory-scripts\u003c/span\u003e\u003cspan address=\"https://github.com/dovratd/AutoCRAT-accessory-scripts\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Aharoni lab members for useful comments throughout the project, Giuseppe Petrosino and the Genomics and Bioinformatics Core Facilities at IMB for support with GLOE-Seq, and Marta Garbacz for helpful input at early stages. Work in the Aharoni laboratory is supported by the Israeli Science Foundation (ISF) grant number 707/21, the Binational Science Foundation (BSF-NSF) grant number 2021737, BSF grant number 2023164, and Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant numbers 552129721 and 548574498. In the Ulrich lab, the project was funded by DFG grant numbers 548574498 and 393547839 \u0026ndash; SFB 1361.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, A.A. and H.D.U.; Methodology, A.C., D.D., N.Z., E.R.C. and L.S.B.; Investigation \u0026amp; Data Analysis, A.C., D.D., W.K., N.Z., H.D.U. and A.A.; Writing, A.A. and H.D.U; Funding Acquisition, A.A. and H.D.U.; Resources, A.C. and D.D.; Supervision, A.A. and H.D.U.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJackson SP, Bartek J (2009) The DNA-damage response in human biology and disease. \u003cem\u003eNature\u003c/em\u003e vol. 461 1071\u0026ndash;1078 Preprint at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nature08467\u003c/span\u003e\u003cspan address=\"10.1038/nature08467\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCortez D, Replication-Coupled DNA, Repair (2019) Mol Cell 74:866\u0026ndash;876\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLisby M, Barlow JH, Burgess RC, Rothstein R (2004) Choreography of the DNA damage response: Spatiotemporal relationships among checkpoint and repair proteins. 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Nucleic Acids Res 42\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"DNA damage bypass, DNA replication, translesion synthesis, template switching, salvage recombination, daughter-strand gap, ubiquitin","lastPublishedDoi":"10.21203/rs.3.rs-8353672/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8353672/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReplication fork stalling or slowdown is a hallmark of replication stress and can lead to DNA damage-induced fork collapse and genetic instability. Stalled replication forks must be stabilized to enable damage processing, yet the connection between fork stalling and lesion bypass remains poorly understood. To explore this relationship, we developed a real-time system to monitor the replicative bypass of locus-specific abasic sites in individual live yeast cells. Using this approach, we find that delays in replisome progression through the DNA lesions arise from fork-associated activity of DNA damage bypass factors rather than from the lesions themselves. Specifically, replication delays are linked to competition between translesion synthesis and recombination-mediated bypass. Our work highlights the complex interplay between fork stalling and damage processing, demonstrating how pathway choice impacts cell survival.\u003c/p\u003e","manuscriptTitle":"Replication fork stalling at DNA lesions is driven by competition between damage bypass pathways","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-06 10:47:21","doi":"10.21203/rs.3.rs-8353672/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d50d7f0e-7fb9-4b11-b801-61e3e9d1355f","owner":[],"postedDate":"January 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":60624201,"name":"Biological sciences/Molecular biology/DNA replication/Translesion synthesis"},{"id":60624202,"name":"Biological sciences/Molecular biology/DNA damage and repair/DNA damage response"}],"tags":[],"updatedAt":"2026-01-20T22:45:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-06 10:47:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8353672","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8353672","identity":"rs-8353672","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}