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. 2018 Dec 17;7:e40802. doi: 10.7554/eLife.40802

Pervasive transcription fine-tunes replication origin activity

Tito Candelli 1,†,, Julien Gros 1,†,, Domenico Libri 1,
Editors: Bruce Stillman2, Kevin Struhl3
PMCID: PMC6314782  PMID: 30556807

Abstract

RNA polymerase (RNAPII) transcription occurs pervasively, raising the important question of its functional impact on other DNA-associated processes, including replication. In budding yeast, replication originates from Autonomously Replicating Sequences (ARSs), generally located in intergenic regions. The influence of transcription on ARSs function has been studied for decades, but these earlier studies have neglected the role of non-annotated transcription. We studied the relationships between pervasive transcription and replication origin activity using high-resolution transcription maps. We show that ARSs alter the pervasive transcription landscape by pausing and terminating neighboring RNAPII transcription, thus limiting the occurrence of pervasive transcription within origins. We propose that quasi-symmetrical binding of the ORC complex to ARS borders and/or pre-RC formation are responsible for pausing and termination. We show that low, physiological levels of pervasive transcription impact the function of replication origins. Overall, our results have important implications for understanding the impact of genomic location on origin function.

Research organism: S. cerevisiae

Introduction

The annotation of transcription units has traditionally heavily relied on the detection of RNA molecules. However, in the last decade, many genome-wide studies based on the direct detection of RNA polymerase II (RNAPII) have clearly established that transcription extends largely beyond the limits of regions annotated for coding functional RNA or protein products (Jacquier, 2009; Porrua and Libri, 2015). The generalized presence of transcribing RNA polymerases, not necessarily associated to the production of stable RNAs, defines pervasive or hidden transcription, which is a conserved feature of both eukaryotic and prokaryotic transcriptomes.

In S. cerevisiae, pervasive transcription accounts for the production of a multitude of transcripts generally non-coding, many of which undergo degradation in the nucleus or the cytoplasm (Jacquier, 2009; Porrua and Libri, 2015). Transcription termination limits the extension of many non-coding transcription events, compensating, to some extent, the promiscuity of initiation (for recent reviews see: Jensen et al., 2013; Porrua and Libri, 2015). In Saccharomyces cerevisiae cells, two main pathways are known for terminating normal and pervasive RNAPII transcription events (Porrua et al., 2016). The first is employed for termination of mRNA coding genes and depends on the CPF-CF (cleavage and polyadenylation factor-cleavage factor) complex. Besides participating in the production of mRNAs, this pathway is also important for transcription termination of several classes of non-coding RNAs, namely SUTs (stable unannotated transcripts) and XUTs (Xrn1-dependent unstable transcripts) (Marquardt et al., 2011). Transcription terminated by this pathway produces RNAs that are exported to the cytoplasm and enter translation. If they contain premature stop codons, they are subject to the nonsense mediated decay and might not be detected in wild-type cells (van Dijk et al., 2011; Malabat et al., 2015).

The second pathway depends on the NNS (Nrd1-Nab3-Sen1) complex and is responsible for terminating transcription of genes that do not code for proteins. Small nucleolar RNAs (snoRNAs) and cryptic unstable transcripts (CUTs), a prominent class of RNAPII pervasive transcripts, are typical targets of NNS-dependent termination. One important feature of this pathway is its association with proteins involved in nuclear RNA degradation such as the exosome and its cofactor, the Trf4-Mtr4-Air (TRAMP) complex. The released RNA is not exported to the cytoplasm but polyadenylated by TRAMP and nucleolytically attacked by the exosome that trims snoRNAs to their mature length and fully degrades CUTs.

Recent studies in yeast and other eukaryotes have shown that constitutive and regulated readthrough at terminators provides a very significant contribution to pervasive transcription (Vilborg et al., 2015; Grosso et al., 2015; Rutkowski et al., 2015; Candelli et al., 2018). Fail-safe mechanisms are in place to back up termination and restrict transcription leakage at terminators. One of these mechanisms terminates ‘stray’ transcription by harnessing the capability of DNA-bound proteins to roadblock RNAPII. Roadblocked polymerases are then released from the DNA via their ubiquitination and likely degradation (Colin et al., 2014).

The ubiquitous average coverage of the genome by transcription, coupled to the remarkable stability of the transcription elongation complex, raises the important question of the efficient coordination of machineries that must read, replicate, repair and maintain the same genomic sequences. The crosstalks between transcription and replication are paradigmatic in this respect.

Eukaryotic cells faithfully duplicate each of their chromosomes by initiating their replication from many origin sites (Bell and Labib, 2016). To ensure once-and-only-once DNA replication per cell cycle, coordination of initiation from these different sites is guaranteed by a two-step mechanism: replication origins have to be licensed before getting activated (Diffley, 2004). Licensing occurs from late mitosis to the end of G1 and consists in the deposition of pre-RCs (pre-replication complexes) around origin sites. To do so, ORC (origin recognition complex) recognizes and binds specifically origin DNA where it recruits Cdc6 and Cdt1 to coordinate the deposition of the replicative helicase engine, the hexameric Mcm2-7 complex. At each licensed origin is deposited a pair of Mcm2-7 hexamers assembled head-to-head as a still inactive double-hexamer (DH) encircling DNA. At the G1/S transition and throughout S-phase, the orderly recruitment of firing factors onto the Mcm2-7 DH activates it, ultimately triggering the building of two replisomes synthesizing DNA from the origin (Parker et al., 2017).

S. cerevisiae origins are specified in cis by the presence of Autonomously Replicating Sequences (ARSs). Within each ARS, ORC recognizes and binds specifically a bipartite DNA sequence composed of the ACS (ARS Consensus Sequence, 5’-WTTTATRTTTW-3’; Palzkill and Newlon, 1988; Diffley and Cocker, 1992; Bell and Stillman, 1992) and the B1 element (Rao and Stillman, 1995; Li et al., 2018). The ACS oriented by its T-rich strand is generally found at the 5’ ends of ARS sequences (Eaton et al., 2010). A-rich stretches are often present at the opposite end of ARSs and have been proposed to function as additional ACSs oriented opposite to the main ACS (Breier et al., 2004; Yardimci and Walter, 2014). Such secondary ACSs have been shown to strengthen pre-RC assembly at ARS in vitro and proposed to ensure ARS function in vivo by driving the cooperative recruitment of a second ORC (Coster and Diffley, 2017; see also Warner et al., 2017). This contrasts with earlier in vitro reconstitutions of pre-RC assembly on single DNA molecules, supporting the recruitment of only one ORC per DNA (Ticau et al., 2015; Duzdevich et al., 2015). Whether one or two ORC molecules are recruited at ARSs in vivo for efficient pre-RC assembly is still not fully understood.

ACS presence is necessary but not sufficient for ARS function in vivo, as only a small fraction of all ACSs found in the S. cerevisiae genome corresponds to active ARSs (Tuduri et al., 2010). Other DNA sequence elements and factors, including the structure of chromatin, participate to origin specification and usage. On the one hand, ORC binding at the ACS shapes NFR formation, nucleosome positioning and nucleosome occupancy, which all together maximize pre-RC formation (Lipford and Bell, 2001; Eaton et al., 2010; Belsky et al., 2015; Rodriguez et al., 2017). On the other hand, specific histone modifications mark replication initiation sites (Unnikrishnan et al., 2010) and chromatin-coupled activities ensure replication forks progression and origin efficiency (Kurat et al., 2017; Devbhandari et al., 2017; Azmi et al., 2017). The transcription machinery could participate to the establishment of a specific chromatin landscape and/or play a more direct role in the specification and function of origins. However, to what extent annotated and non-annotated transcription at and around origins can influence replication remains unclear.

The binding of general transcription factors such as Abf1 and Rap1, or even the tethering of transcription activation domains, TBP or Mediator components was shown to be required for efficient firing of a model ARS (Marahrens and Stillman, 1992; Stagljar et al., 1999; see also Knott et al., 2012). However, whether this implies the activation of transcription within origins has not been shown.

Strong transcription through ARSs has been demonstrated to be detrimental for their function (Snyder et al., 1988; Tanaka et al., 1994; Chen et al., 1996; Mori and Shirahige, 2007; Lõoke et al., 2010), and intragenic origins have been shown to be inactivated by meiotic-specific transcription (Mori and Shirahige, 2007; Blitzblau et al., 2012). Inactivation of origins by transcription has been correlated to the impairment of ORC binding and pre-RC assembly, possibly because of steric conflicts with transcribing RNAPII (Mori and Shirahige, 2007; Lõoke et al., 2010). Strong transcription through origins was found to terminate, at least to some extent, within ARS sequences at cryptic termination sites, generating stable and polyadenylated transcripts (Chen et al., 1996; Magrath et al., 1998). However, it was concluded that transcription termination within ARSs and origin function are not functionally linked, as mutationally impairing either one would not affect the other. In particular, it was found that transcription termination was not due to ORC roadblocking RNAPII and, conversely, that origin activity was not dependent on termination taking place within the ARS (Chen et al., 1996; Magrath et al., 1998).

Even if unrestricted transcription inactivates intragenic origins (Mori and Shirahige, 2007; Blitzblau et al., 2012), these cases hardly represent the chromosomal context of most mitotically active origins, which are intergenic (Donato et al., 2006; MacAlpine and Bell, 2005; Nieduszynski et al., 2005) and are generally not exposed to the levels of transcription found within genes. Most importantly, these earlier studies could not take into account the potential impact of annotated and non-annotated levels of pervasive transcription, which is not easily detected, due to the general instability of the RNA produced and to the poor resolution of many techniques for detecting RNAPII occupancy. Such generally low levels of transcription have been recently found to significantly impact the expression of canonical genes and to be limited by fail safe and redundant transcription termination pathways (Candelli et al., 2018; Roy et al., 2016).

We investigated here the impact of physiological levels of pervasive transcription on the function of replication origins in S. cerevisiae. Using nucleotide-resolution transcription maps, we studied the transcriptional landscape around and within origins, regardless of annotations. Origins generate a characteristic footprint in the ubiquitous transcriptional landscape due to the pausing of RNAPII at origin borders. On the one hand, transcription terminates at the border of the primary ACS, in an ORC and pre-RC-dependent manner, by a mechanism that has roadblock features. On the other hand, RNAPII pauses upstream of the secondary ACS but terminates within the ARS. The low levels of pervasive transcription that enter ARSs negatively affect the efficiency of licensing and firing, with pervasive transcription incoming from the secondary ACS affecting origin function to a higher extent.

These results have important implications for understanding the impact of genomic location on origin specification, efficiency and timing of activation. Because pervasive transcription is conserved and generally increases with increased genome complexity, they are also susceptible to be relevant for the mechanism of replication initiation in other eukaryotes, particularly in metazoans.

Results

RNAPII pausing and transcription termination occur at ARS borders

Although considerable efforts have been made to annotate transcription units independently from the production of stable RNAs, many transcribed regions still remain imprecisely or poorly annotated in the S. cerevisiae genome. Addressing the potential impact of transcription on the function of replication origins therefore requires taking into account the actual physiological levels of transcription, regardless of annotation. For these reasons, we relied on high-resolution transcription maps derived from the direct detection of RNAPII by the sequencing of the nascent transcript (RNAPII PAR-CLIP, photo-activable ribonucleoside-enhanced UV-crosslink and immunoprecipitation) (Schaughency et al., 2014). We also generated additional datasets using the analogous RNAPII CRAC, (crosslinking analysis of cDNAs, Granneman et al., 2009; Candelli et al., 2018). Both methods detect significant levels of transcription in many regions that lack annotations (data not shown; Candelli et al., 2018).

We retrieved a total of 228 origins that we oriented according to the direction of the T-rich strand of their proposed ACS (Nieduszynski et al., 2006). Origins were then anchored at the 5' ends of their ACS and the median distribution of RNAPII occupancy was plotted in a 1 kb window around the anchoring site (Figure 1A). Strikingly, RNAPII signal accumulates over the 200nt preceding the T-rich strand of the ACS and sharply decreases within the 25nt immediately preceding it (Figure 1A, blue trace; see also Figure 1—figure supplement 2A–B for the statistical significance of the signal loss over the primary ACSs). The RNAPII signal build-up suggests that pausing occurs before the ACS, while its abrupt reduction might indicate that transcription termination occurs immediately upstream of the site. This behavior is reminiscent of roadblock termination whereby transcription elongation is impeded by factors or complexes binding the DNA, and RNA polymerase is released following its ubiquitylation (Colin et al., 2014; Roy et al., 2016; Candelli et al., 2018). RNAPII signal also builds up from antisense transcription, although in a more articulated manner (Figure 1A, red trace) and starts declining on average 120nt upstream of the 5’ border of the ACS.

Figure 1. Metasite analysis of RNAPII occupancy and transcription termination at replication origins.

(A) RNAPII PAR-CLIP metaprofile at replication origins. 228 confirmed ARSs were oriented according to the direction of the T-rich strand of their proposed ACSs (blue arrow) (Nieduszynski et al., 2006) and aligned at the 5' ends of the oriented ACSs (red dashed line). The median number of RNAPII reads (Schaughency et al., 2014) calculated for each position is plotted. Transcription proceeding along the T-rich strand of the ACS is represented in blue and considered to be sense, while transcription on the opposite strand is plotted in red and considered to be antisense. (B). Distribution of poly(A)+RNA 3'-ends at genomic regions surrounding replication origins. Origins were oriented and anchored as in A). 3'-ends reads (Roy et al., 2016) of RNAs extracted from wild-type cells (WT, blue) or cells in which both Rrp6 and Dis3 were depleted from the nucleus (RRP6-DIS3-AA, transparent red) were plotted. At each position around the anchor, the presence or absence of an RNA 3'-end was scored independently of the read count. (C). Scheme of replication origins anchored at different ACS sequences. Left: sense polymerases transcribing upstream of primary ACSs (blue arrows) are colored in blue, while antisense polymerases transcribing upstream of secondary ACSs (orange arrows) are colored in red. Right: ARSs oriented according to antisense transcription were aligned at the 5' ends of the primary ACSs (top, corresponds to red trace in D) or at the 5' ends of the secondary ACSs (bottom, corresponds to black trace in D). (D). RNAPII PAR-CLIP metaprofile of antisense transcription aligned either to the 5’ ends of the primary (red) or the secondary (black) ACSs, as shown in (C). As in (A), the median number of RNAPII reads calculated for each position is plotted. (E). Distributions of RNA 3’-ends and RNAPII at genomic regions aligned at secondary ACSs. Origins were oriented and aligned as in (D). At each position around the anchor, presence or absence of an RNA 3'-end was scored independently of the read count (left y-axis). The distribution of RNAPII already shown in (C) is reported here for comparison (right y-axis).

Figure 1.

Figure 1—figure supplement 1. Measures on mapped secondary ACSs.

Figure 1—figure supplement 1.

(A) Average distribution of the distances between the main and the putative secondary ACS defined based on conformity to the consensus sequence defined in Coster and Diffley (2017) for every ARS. (B) Distribution of the average scores of main (blue) and putative secondary ACSs (red).
Figure 1—figure supplement 2. Statistical analysis of pausing and termination signals.

Figure 1—figure supplement 2.

(A) Regions around the ACS used for the Box Plots represented in (B) and (C). (B) Distributions of RNAPII occupancy signal before and after the primary ACSs, as indicated. The 100 origins that had the highest levels of surrounding transcription were used for this analysis. (C) Same as in (B), but regions were aligned at the predicted secondary ACSs. (D) Statistical significance of the transcription termination peak at aligned primary ACSs. p-Values associated to the detection of the observed number of termination events were calculated under the H0 hypothesis that the frequency of termination events is equal in the whole alignment region (‘background termination’). The expected frequency of termination was estimated based on the frequency observed in a window of 100nt located 500nt upstream of the ACS. The negative Log of the corrected p-value is plotted on the y-axis. The red line represents the significance level (p=0.05). (E) Same as in (D), but origins were aligned at the 5' ends of the predicted secondary ACSs. Note that in this case the significant termination peak is located downstream of the ACS and not immediately upstream, as in (D).

Although the sharp decrease of RNAPII signal immediately preceding the ACS is suggestive of transcription termination, it is possible that RNAPII occupancy downstream of the ACS decreases because of a shorter persistency of the elongation complex in these regions, for instance because of higher transcription speed. We thus sought independent evidence of transcription termination before the ACS. Transcription termination is accompanied by release of the transcript and generally by its polyadenylation. Therefore, we mapped the distribution of polyadenylated RNA 3’-ends around origins as a proxy for transcription termination (Figure 1B, blue). Because roadblock termination produces RNAs that are mainly degraded in the nucleus, we also profiled the distribution of RNA 3’-ends in cells depleted for the two catalytic subunits of the exosome, Rrp6 and Dis3 (Roy et al., 2016) (Figure 1B, transparent red). At each position around the ACS, we scored the number of genomic sites containing at least one RNA 3’-end without taking into consideration the read count at each site. This conservative strategy determines whether termination occurs at each position, and prevents high read count values from dominating the aggregate value. The distribution of RNA 3’-ends – and therefore of transcription termination events – closely mirrors the distribution of RNAPII on the T-rich strand of the ACS and peaks immediately upstream of the ACS. Note that because the whole read is taken into account to map RNAPII distribution, while only the terminal nucleotide is used to map the 3’-ends, the distribution of RNA 3’-ends is shifted downstream relative to the distribution of RNAPII. Importantly, and consistent with a roadblock mechanism, the 3’-end count upstream of the ACS is higher in the absence of the exosome (Figure 1B, transparent red), strongly suggesting that these termination events produce, at least to some extent, RNAs that are degraded in the nucleus. These peaks of RNA 3’-ends are significant, as demonstrated by the p-values associated to the frequencies of termination events observed around the ACS, which are significantly smaller than the ones detected in the flanking region (corrected p-value<10−20, Figure 1—figure supplement 2D and Material and methods).

These observations strongly suggest that the landscape of pervasive transcription is significantly altered by the presence of replication origins. Incoming RNAPIIs are paused with an asymmetric pattern around ARSs and termination occurs upstream of the primary ACS.

To assess the origin of the asymmetry in RNAPII distribution, we considered the possibility that RNAPIIs transcribing in the antisense direction relative to the ACS might be paused at the level of putative secondary ACSs located downstream within the ARS. Such secondary ACSs, proposed to be positioned 70-400nt downstream and in the opposite orientation of the main ACS, have been shown to be required in vitro for efficient pre-RC assembly and suggested to play an important role for origin function in vivo (Coster and Diffley, 2017). The variable position of these secondary ACS sequences could explain why the antisense RNAPII meta-signal spreads over a larger region when ARSs are aligned to the 5' ends of their primary ACSs (Figure 1C). We therefore mapped such putative secondary ACSs using a consensus matrix derived from the set of known primary ACSs (Coster and Diffley, 2017) (Table 2). As shown on Figure 1—figure supplement 1A, distances between the primary and the predicted secondary ACS distribute widely and preferentially cluster around ≈100nt (median 113.5), consistent with functional data obtained using artificial constructs (Coster and Diffley, 2017). As possibly expected, the calculated similarity scores for these predicted ACSs are generally lower than the ones calculated for the main ACSs (see the distribution in Figure 1—figure supplement 1B). When we aligned origins to the first position of their predicted secondary ACSs (Figure 1C and Figure 1D, black trace) we observed a significant sharpening of the RNAPII occupancy peak compared to the alignment on their primary ACSs (Figure 1D, compare red to black traces; Figure 1C; Figure 1—figure supplement 2c for the statistical significance of the signal loss over the secondary ACSs). This suggests that RNAPII is indeed pausing immediately upstream of the secondary ACS. Interestingly, when we aligned polyadenylated RNA 3'-ends using the first position of the predicted secondary ACSs, we observed that transcription termination distributed preferentially ≈50nt after the anchor (Figure 1E, blue trace, compare to RNAPII distribution, black trace; see also Figure 1—figure supplement 2E) indicating that in most instances antisense transcription terminates downstream of the site of RNAPII pausing.

To better highlight the presence and the role of a roadblock (RB) at these origins, we examined local transcription by RNAPII CRAC under conditions in which an essential component of either the CPF-CF or the NNS termination pathways is affected, that is in an rna15-2 mutant at the non-permissive temperature, or by depleting Nrd1 by the auxin-degron method (Candelli et al., 2018). We reasoned that defects in CPF-CF or the NNS pathways would affect the levels of neighboring readthrough transcription directed toward these origins and consequently increase the transcriptional loads challenging the roadblocks. Representative examples are shown in Figure 2.

Figure 2. RNAPII occupancy at individual ARS detected by CRAC analysis.

Figure 2.

RNAPII occupancy at sites of roadblock detected upstream ARS305 (A), ARS413 (B), ARS431 (C) and ARS432.5 (or ARS453, (D) by CRAC (Candelli et al., 2018). The pervasive transcriptional landscape at these ARSs is observed in wild-type cells (WT, blue) or cells bearing a mutant allele for an essential component of the CPF-CF transcription termination pathway (rna15-2, green) at permissive (25°C, dark colors) or non-permissive temperature (37°C, light colors). In the case of ARS305 (A), RNAPII occupancy is also shown in cells rapidly depleted for an essential component of the NNS transcription termination pathway through the use of an auxin-inducible degron tag (Nrd1-AID; (−) Auxin: no depletion, dark pink; (+) Auxin: depletion, light pink).

In the case of ARS305 (Figure 2A), low levels of readthrough transcription are found at the terminators of the adjacent transcription units (YCL049C or CUT040) and are subjected to roadblock termination at both the main (blue) or the putative secondary ACSs (red, overlaps with the previously mapped B4 element (Huang and Kowalski, 1996)), respectively. Increase in readthrough transcription at the YCL049C gene in rna15-2 cells (sense transcription, light green track) or at CUT040 upon Nrd1 depletion (antisense transcription, light pink track), leads to increased accumulation of RNAPII at both ACSs and to transcription invading the ARS.

Two ACSs were previously proposed for ARS413 (Figure 2B): sense ACS1 (Eaton et al., 2010) and antisense ACS2 (Nieduszynski et al., 2006). Transcription on the plus strand is strongly roadblocked at ACS1, while transcription on the minus strand is roadblocked at both ACS2 and ACS1. In both cases, transcription derives only from the upstream genes (YDL073W and YDL072C, respectively) because no additional initiation sites could be detected, even in cytoplasmic and nuclear RNA degradation mutants (data not shown). When the transcription load was increased by affecting the termination of YDL073W and YDL072C in rna15-2 cells at the non-permissive temperature (light green tracks), RNAPII occupancy at the RBs increases and some readthrough within the ARS occurs. This example suggests that both ACSs are occupied by the ORC complex, although it is not clear whether they function in conjunction or alternatively in different cells.

Two additional examples are shown in Figure 2. In the case or ARS431 (Figure 2C), the RB is more prominent on the site of the primary ACS and increases when the transcriptional load is higher due to readthrough from the upstream gene, YDR297W, in rna15-2 cells. On the contrary, a prominent site of RB at the secondary ACS is observed at ARS453 (or ARS432.5; Figure 2D), while the RB at primary ACS cannot be observed because transcription of CUT523 appears to terminate efficiently upstream.

Taken together, these results suggest that primary and secondary ACSs, both presumably bound by ORC, can induce RNAPII pausing at the borders of replication origins. However, while RNAPII generally pauses and terminates upstream of primary ACS sequences, RNAPII often pauses at secondary ACS but terminates downstream. Importantly, such ARS footprint in the pervasive transcription landscape (Figure 2) provides independent in vivo evidence of the role of secondary ACS sequences (Coster and Diffley, 2017), while our meta-analyses (Figure 1) strongly suggest a general functional difference between primary and secondary ACSs with regards to incoming transcription.

Termination of transcription at ARSs is mediated by ORC binding to the DNA

Transcription termination around origins might depend on many termination factors. The main transcription termination pathways in S. cerevisiae, NNS- and CPF-dependent, rely on the recognition of termination signals on the nascent RNA. Release of the polymerase occurs therefore after the termination signals that have been transcribed and recognized. Transcription termination by roadblock, on the other hand, ensues from a collision of the transcription elongation complex with a DNA bound protein, and therefore occurs upstream of the termination signal. Another characteristic feature of roadblock termination is that the released RNA is subject to exosome-dependent degradation. Both features, termination upstream of the termination signal and nuclear degradation of the released transcripts, are compatible with the notion that roadblock termination occurs at origins. Still, it remains possible that termination at the immediate borders of origins depends on conserved external signals allowing the recruitment of CPF- or NNS- components. According to the position of RNAPII pausing, the most likely roadblocking factor would be the ORC complex bound to the ACS.

We therefore first verified that termination depends on the ACS sequence and to this end we cloned a 500 bp DNA fragment containing ARS305 in a reporter system allowing the detection of transcription termination (Porrua et al., 2012) (Figure 3). This fragment conferred ACS-dependent mitotic maintenance to a centromeric version of the reporter construct, indicating that it is a functional ARS (Figure 3—figure supplement 1). In this system, a test terminator sequence is cloned between two promoters, the downstream of which allows the expression of a reporter gene, CUP1, which is required for yeast growth in the presence of copper ions (Figure 3A). Transcription from the upstream promoter interferes with and thus inactivates the promoter driving expression of CUP1 unless the test sequence contains a terminator. Copper resistant is therefore a reliable, positive read out of the presence of a transcription terminator in the cloned sequence. Consistent with the notion that termination occurs at replication origins, insertion of ARS305 in the orientation dictated by the T-rich strand of the ACS conferred robust copper-resistant growth to yeast cells (Figure 3B), Importantly, copper resistance was abolished when the ACS was mutated, strongly suggesting that termination is strictly dependent on the integrity of the ORC binding site.

Figure 3. Analysis of transcription termination at ARS305.

(A) Scheme of the reporter system (Porrua et al., 2012) used to assess termination at ARS305. PTETOFF: doxycycline-repressible promoter; PGAL: GAL1 promoter. Termination of transcription at a candidate sequence (blue) allows growth on copper containing plates while readthrough transcription inhibits the GAL1 promoter and leads to copper sensitivity, as indicated. (B) Growth assay of yeasts bearing reporters containing a Reb1-dependent terminator, (Colin et al., 2014, used as a positive control), or ARS305 (lanes 1 and 3, respectively). Variants containing mutations in the Reb1 binding site (Reb1 BS ‘−') or the ACS sequence are spotted for comparison (lanes 2 and 4, respectively). (C) Northern blot analysis of PTET transcripts produced in wild-type and rrp6∆ cells from reporters containing either a Reb1-binding site (Reb1 BS, lanes 1–2) or wild-type or mutant ARS305 sequences, as indicated (lanes 3–8). Transcripts terminated within ARS305 or at the CUP1 terminator are highlighted.

Figure 3.

Figure 3—figure supplement 1. ARS305 sequence confers mitotic maintenance to a centromeric plasmid when transcription is shut down.

Figure 3—figure supplement 1.

To assess the functionality of ARS305 in the reporter construct used for detecting transcription termination, we deleted the origin of the plasmid and transformed yeast in the presence or absence of doxycycline to control expression of the TET promoter. Transformants were only recovered in the absence of transcription, indicating that ARS305 is active but inactivated, as expected, when strong transcription runs through it. Candelli et al., Table 1.

This notion was further supported by Northern blot analysis of the transcripts produced when a shorter ARS305 fragment containing the ACS and the downstream 154nt were introduced in the same reporter construct (Figure 3C). A short transcript witnessing the occurrence of termination was readily detected in the presence of ARS305 (lane 3). Consistent with the notion that roadblock termination occurs at ARS305, the transcript released was subject to exosomal degradation and was stabilized by deletion of Rrp6 (lane 4). This short RNA disappeared when the ACS sequence was mutated, to the profit of a longer species resulting from termination downstream of ARS305, confirming the ACS-dependency of termination (lane 5). ARS305 contains, in addition to the ACS, two motifs, B1 and B4, required for full origin function (Huang and Kowalski, 1996). Interestingly, B4 is located roughly 100nt downstream of the ACS, and coincides with a predicted secondary ACS required for efficient symmetrical loading of the pre-RC (Figure 2 and Table 2) (Coster and Diffley, 2017). To assess whether the primary ACS is sufficient to induce transcription termination, we mutated both B1 and B4, alone or in combination, and assessed the level of termination by Northern blot. As shown in lanes 6 and 7, mutation of B4 had the strongest effect on termination, which was very similar to the effect observed when the main ACS was mutated. Mutation of B1 had a minor but significant effect. From these experiments, we conclude that the high-affinity ORC-binding site alone is necessary but not sufficient for inducing transcription termination at ARS305, and that the secondary ACS (B4) and the B1 motif are additionally required.

To provide independent evidence that ORC bound to the ARS triggers transcription termination by a roadblock mechanism, we took advantage of the finding that many sequences with a perfect match to the ACS consensus do not bind ORC. We used published coordinates of ACSs bound (ORC-ACSs) or not recognized (nr-ACSs) by the ORC complex in ORC-ChIP-seq experiments (Eaton et al., 2010), and mapped transcripts 3’-ends (Roy et al., 2016) as a proxy for the occurrence of transcription termination (Figure 4A and B). As previously, we oriented each ARS according to the direction of the T-rich ORC-ACS or nr-ACS. As expected, the distribution of transcription termination events around the set of ORC-bound ACSs is very similar to the one observed around replication origins mapped by Nieduszynski et al. (2006) (compare Figure 4A and Figure 1B). As in the previous analysis, many unstable transcripts are produced by termination around origins as witnessed by the overall higher level of 3'-ends mapped in an exosome-deficient strain (Figure 4A). The distribution of RNA 3’-ends around the set of nr-ACSs is however radically different, with transcription events presumably crossing the nr-ACS in both directions and terminating downstream (Figure 4B). Interestingly, at nr-ACSs, the amounts of 3’-ends detected are very similar in wild-type conditions or upon depletion of both Rrp6 and Dis3 subunits of the nuclear exosome, indicating that termination downstream of nr-ACSs does not produce unstable transcripts and is presumably dependent on the CPF pathway (Figure 4B).

Figure 4. Role of ORC in the roadblock of RNAPII at origins.

Figure 4.

(A) Distribution of RNA 3'-ends at genomic regions aligned at ACS sequences recognized by ORC (ORC-ACS) as defined by Eaton et al. (2010) (i.e. defined based on the best match to the consensus associated to each ORC-ChIP peak). Each origin was oriented according to the direction of the T-rich strand of its ORC-ACS and regions were aligned at the 5’ ends of the ORC-ACSs. As in 1B, RNA 3'-ends (Roy et al., 2016) were from transcripts expressed in wild-type cells (blue) or from cells depleted for exosome components (transparent red). At each position around the anchor, presence or absence of an RNA 3'-end was scored independently of the read count. Distributions of RNA 3’-ends both on the sense (top) and the antisense (bottom) strands relative to the ORC-ACSs are plotted. (B). Same as in (A) except that genomic regions were aligned at ACS sequences not recognized by ORC (nr-ACS) as defined by Eaton et al. (2010) (i.e. defined as ACS motifs for which no ORC ChIP signal could be detected). (C). Quantification of the roadblock at individual ARSs. For each ARS, the snapshot includes the upstream gene representing the incoming transcription. The distribution of RNA polymerase II (dark blue) detected by CRAC (Candelli et al., 2018) at ARS404 (left) and ARS1004 (right) oriented according to the direction of their T-rich ACS strands is shown. The positions of the qPCR amplicons used for the RT-qPCR analyses in (D) are indicated. (D). RT-qPCR analysis of transcriptional readthrough at ARS404 and ARS1004. Wild-type, orc2-1, orc5-1 and cdc6-1 cells were cultured at permissive temperature and maintained at permissive (23°C, blue) or non-permissive (37°C, red) temperature for 3 hr. The level of readthrough transcription at ARS404 (left) or ARS1004 ACS (right) was estimated by the ratio of RT-qPCR signals after and before the ACS, as indicated. Data were corrected by measuring the efficiency of qPCR for each couple of primers in each reaction. Values represent the average of at least three independent experiments. Error bars represent standard deviation.

Because the ACS sequence is nearly identical in the two datasets, it is unlikely that it alone could be responsible for the termination pattern observed at ORC-ACSs. These observations are consistent with the notion that the presence of ORC bound to the ACS is necessary to roadblock transcribing RNAPII, which releases a fraction of unstable RNAs. To substantiate these findings we set up to assess directly the impact of ORC depletion on transcribing RNAPII at two model origins, ARS404 and ARS1004, located downstream of the YDL227C and YJL217W genes, respectively. In both cases, RNAPII signals are present immediately upstream of the T-rich strand of the ACS, presumably because of transcription events reading through the upstream terminator that are roadblocked at the site of ORC binding (Figure 4C). To assess the efficiency of the roadblock we measured RNA levels immediately upstream and downstream of the T-rich strand of each ACS in a strand-specific manner by RT-quantitative PCR (Figure 4C and D). Because no transcription initiation can be detected at either one of the two ACSs (data not shown), RNA signals detected downstream of the ACS are most likely due to molecules that initiate upstream and cross the ACS. We therefore expressed the efficiency of the roadblock as the ratio between the signals downstream and upstream of the ACS. Release of the roadblock is expected to increase this ratio because more RNAPII molecule would traverse the ACS. To affect binding of ORC to the ACS, we used two thermosensitive mutants of two ORC subunits, Orc2-1 and Orc5-1, which affect the binding of ORC to the DNA (Santocanale and Diffley, 1996; Loo et al., 1995; Yuan et al., 2017; Shimada et al., 2002). As shown in Figure 4D, ORC roadblock at ARS404 and ARS1004 is efficient, allowing only between 1–10% of the incoming transcription to cross the ACS in wild-type cells or under permissive temperature for all mutants (Figure 4D, 23°C). When the binding of ORC to the ACS was affected in orc2-1 and orc5-1 cells at 37°C, a marked increase in the fraction of RNAPII going through the roadblock is observed, indicating that binding of the ORC complex to the ACS is necessary to terminate upstream incoming transcription.

Cdc6 binds DNA cooperatively with ORC and contributes to origin specification by participating to pre-RC assembly (Speck et al., 2005; Speck and Stillman, 2007; Yuan et al., 2017) and references therein). The thermosensitive mutant Cdc6-1 (Hartwell et al., 1973) which is affected in pre-RC assembly at the restrictive temperature (Cocker et al., 1996), still does not preclude ORC to footprint at candidate ARSs (Santocanale and Diffley, 1996). Remarkably, the transcriptional roadblock was markedly reduced in a cdc6-1 mutant at the non-permissive temperature, to a similar extent as for the orc2-1 and orc5-1 mutants. This indicates that the assembly of an ORC•Cdc6 complex, or the full complement of the pre-RC at the candidate ARS, is essential for efficiently roadblocking RNAPII.

From these results, we conclude that the stable binding of the ORC complex to the ACS is necessary but not sufficient to efficiently terminate incoming transcription at ARS by a roadblock mechanism.

Impact of local pervasive transcription on ARS function

In spite of the presence of bordering roadblocks, low levels of pervasive transcription, which presumably originates in neighboring regions and cross the sites of ORC occupancy, were detected within replication origins (Figures 13). To assess the impact of local physiological levels of transcription within ARS, we sought correlations between total RNAPII occupancy on both ARS strands in a window of 100nt starting at the first base of the primary ACS, and licensing efficiency or origin activation (Hawkins et al., 2013) We ordered the origins described by Nieduszynski et al. (2006) according to the levels of transcription at and immediately downstream of the T-rich ACS and compared the licensing efficiency of the 30 origins having the highest transcription levels to the rest of the population (160 origins) for which replication metrics were available (total of 190 origins) (Supplementary file 1 Table 1). We found that the efficiency of licensing was significantly lower for the origins having the highest levels of transcription (Figure 5A; p = 0.003). We also found that origins having the highest levels of transcription display a lower probability of firing compared to the rest of the population (Figure 5B; p = 0.012).

Figure 5. Local pervasive transcription impacts origin competence and efficiency.

Figure 5.

Transcription levels were assessed in the first 100 nt of each ARS, starting at the 5’ end of the ACS, by adding RNAPII read counts (Schaughency et al., 2014) on both strands of the region. Origins were ranked based on transcription levels and the origins having the highest transcription levels (30/192, grey boxplots) were compared to the rest of the population (162/192, white boxplots). Origin metrics (licensing, 5A, and firing efficiency, 5B) for the two classes of origins were retrieved from Hawkins et al. (2013). Boxplots were generated with BoxPlotR (http://shiny.chemgrid.org/boxplotr/); center lines show the medians; box limits indicate the 25th and 75th percentiles; whiskers extend 1.5 times the interquartile range (IQR) from the 25th and 75th percentiles. Notches are 1.58*IQR/n1/2.

The effect observed on origin firing might be a consequence of the impact of transcription on licensing. However, it is also possible that local levels of pervasive transcription impact origin activation after licensing. To address this possibility, we focused on the 30 origins that have the highest levels of incoming transcription as defined by the levels of RNAPII occupancy preceding (Figure 6A; ‘A’) and following (Figure 6A; ‘C’) a 200nt window aligned at the 5' end of the ACS (Figure 6A; ‘B’) (Supplementary file 1 Table 2, Supplementary file 1 Table 3). Consistent with the previous analyses performed on all origins, transcription over ‘B’ strongly anticorrelated with origin competence (p = 2*10−4; Figure 6B) and efficiency (p = 5*10−5; Figure 6C). When we plotted the probability of licensing (PL) against the probability of firing (PF), we identified two classes of origins: the first that aligns almost perfectly on the diagonal (R2 = 0.99; Figure 6D, red) contains origins that fire with high probability once licensed. The second contains on the contrary origins firing with a lower probability, even when efficiently licensed (Figure 6D, black). As the probability of firing (PF) is the product of the probability of licensing (PL) by the probability of firing once licensing has occurred (PF|L), the latter is defined by the ratio PF/PL. We then sought correlations between the total level of transcription over each ARS and the efficiency with which it is activated at the post-licensing step (PF|L). Strikingly, origins that have a high PF|L are generally insensitive to transcription (Figure 6E, red); on the contrary, origins that have a low PF|L are markedly sensitive to the levels of overlapping transcription (R2 = 0.55; p = 0.002; Figure 6E, black). This generally holds true when the median time of firing (Hawkins et al., 2013) is considered: origins with a high PF|L are generally firing earlier and in a manner that is independent from transcription levels over B (Figure 6F, red), while, conversely, origins that have a low PF|L tends to fire later when transcription over B increases (R2 = 0.44; p = 0.009; Figure 6F, black).

Figure 6. Correlations between transcription and origin function.

Figure 6.

(A) Origins were first selected based on the levels of pervasive transcription to which they are exposed, calculated by adding RNAPII reads (Schaughency et al., 2014) over the ‘A’ (sense direction) or the ‘C’ (antisense direction) regions. For the selected ARSs, levels of pervasive transcription were then calculated over the ‘B’ region by summing RNAPII reads over the ‘Ba’ (sense direction) and the ‘Bas’ (antisense direction) regions, as indicated in the scheme. (B) Correlation between transcription over the ARS and origin competence. (C) Correlation between transcription over the ARS and origin efficiency. (D) Identification of two classes of origins, one that fires with high probability when licensing has occurred (high PF|L, red dots) and the other that fires less efficiently once licensed (low PF|L, black dots). (E) Correlation between PF|L and transcription. The efficiency of firing at the post-licensing step correlates with the levels of pervasive transcription only for origins with low PF|L (black dots). Origins that fire very efficiently once licensing occurred (PF|L≈1) are generally not sensitive to pervasive transcription (red dots). (F) Origins with a low PF|L (black dots) have a firing time that correlates with pervasive transcription, while origins with high PF|L (red dots) fire early independently of pervasive transcription levels.

We conclude that the efficiency of origin licensing generally negatively correlates with the levels of pervasive transcription within the ARS. Interestingly, a class of origins exists for which the local levels of transcription also impact origin activation after licensing.

Asymmetry of origin sensitivity to transcription

It has been suggested that the ORC complex binds the secondary ACS with lower affinity relative to the primary ACS (Coster and Diffley, 2017). If the affinity of ORC binding to DNA reflected its efficiency at roadblocking RNA polymerases, the existence of both primary and secondary ACSs might imply that incoming transcription upstream of the primary ACS (defined as ‘sense’ transcription) might be roadblocked more efficiently than incoming transcription upstream of the secondary ACS (defined as ‘antisense’ transcription). As a consequence, antisense transcription would be more susceptible to affect origin function. To assess the functional impact of this asymmetry, we turned to a natural model case, ARS1206, which immediately follows HSP104, a gene activated during heat shock (Figure 7A).

Figure 7. Asymmetry of origin sensitivity to pervasive transcription.

Figure 7.

(A) Top: pervasive transcriptional landscape detected by RNAPII CRAC (Candelli et al., 2018) at YLL026W (HSP104) and ARS1206 in wild-type cells, both on Watson (blue) and Crick (red) strands, at 25°C (dark colors) and 37°C (light colors). The 5' ends and the sequences of the proposed primary ACS and the predicted secondary ACS for ARS1206 are shown. Bottom: schemes of the reporters containing the HSP104 gene and ARS1206 placed under the control of a doxycycline-repressible promoter (PTETOFF). The position of the amplicon used for the qPCR in (B) is shown. pS and pAS differ for the orientation of ARS1206, with the primary (pS) or the secondary ACS (pAS) exposed to constitutive readthrough transcription from HSP104. The sequence and the organization of the relevant region are indicated on the right for each plasmid. The positions of the oligonucleotides used for RNaseH cleavage (black arrows) and of the probe used in (C) are also indicated. The sequences of the oligonucleotides is reported in Table 1, with the following correspondence: cleaving oligo ‘a’=DL163; Northern probe = DL164; cleaving oligo ‘b’ = DL473; cleaving oligo ‘c’ = DL3991; cleaving oligo ‘d’ = DL3994. (B). Quantification by RT-qPCR of the HSP104 mRNA levels expressed from pS or pAS in the presence or absence of 5 µg/mL doxycycline. The position of the qPCR amplicon is reported in (A). (C). Northern blot analysis of HSP104 transcripts extracted from wild-type cells and subjected to RNAse H treatment before electrophoresis using oligonucleotides ‘a-d’ (positions shown in A). All RNAs were cleaved with oligonucleotide ‘a’ to decrease the size of the fragments analyzed and detect small differences in size. Cleavage with oligonucleotide ‘b’ (oligo-dT) (lanes 3, 4) allowed erasing length heterogeneity due to poly(A) tails. Oligonucleotides ‘c’ and ‘d’ were added in reactions run in lanes 1 and 6, respectively, to detect possible longer products that might originate from significant levels of transcription readthrough from HSP104, if the inversion of ARS1206 were to alter the transcription termination efficiency. Products of RNAse H degradation were run on a denaturing agarose gel and analyzed by Northern blot using a radiolabeled HSP104 probe (position shown in A). (D). Stability of plasmids depending on ARS1206 for replication as a function of ARS orientation. pS or pAS was transformed in wild-type cells and single transformants were grown and maintained in logarythmic phase in YPD for several generations. To assess the loss of the transformed plasmid, cells were retrieved at the indicated number of generations and serial dilutions spotted on YPD (left) or minimal media lacking uracile (right) for 2 or 3 days, respectively, at 30°C. (E). Mutation of ORC2 affects more severely the stability of pAS compared to pS. Transformation of pS and pAS in wild-type (ORC2, ‘−‘) or mutant (orc2-1, ‘+') cells. Pictures were taken after 5 days of incubation at permissive temperature (23°C).

We cloned the HSP104 coding sequence and the following ARS1206 under the control of a doxycyclin-repressible promoter (PTETOFF), similar in strength and characteristics to the HSP104 promoter (Mouaikel et al., 2013) (Figure 7A). We verified that the HSP104 gene is transcribed and produces a transcript similar in size to the endogenous HSP104 RNA (data not shown), implicating that transcription termination occurs efficiently in this construct. This is expected to allow origin function, even under conditions of the strong transcription levels induced by the TET promoter. Indeed, after deletion of the ARS present in the plasmid backbone (ARS1), the plasmid could still be maintained in yeast cells, showing that it can rely on ARS1206 for replication (data not shown; Figure 7D).

We recently showed that transcription readthrough at canonical terminators is widespread in yeast and is one important component of pervasive transcription (Candelli et al., 2018). Although ARS1206 is active, we predicted that the low levels of transcription reading through the HSP104 terminator might impact its efficiency in an orientation-dependent manner. To test this hypothesis, we inverted the orientation of ARS1206 on the plasmid, so that transcription from HSP104 would approach the origin from its secondary ACS side (Figure 7A). We observed equivalent levels of HSP104 expression from plasmids containing ARS1206 in the sense (pS) or the antisense (pAS) orientation (Figure 7B) and concluded that transcription termination, which would have created unstable RNAs when impaired (Libri et al., 2002), occured still efficiently upon ARS1206 inversion. Consistently, high resolution Northern blot analysis of the 3’-ends of the HSP104 RNA produced by pS and pAS confirmed that the site of polyadenylation was not altered by inversion of ARS1206 and no readthrough RNAs could be detected (Figure 7C). Strikingly, when pS or pAS were transformed into wild-type cells, and yeasts were grown in a medium non-selective for plasmid maintenance for the same number of generations, ARS1206 supported plasmid maintenance more efficiently when present on the sense (pS) relative to the antisense (pAS) orientation (Figure 7D).

This result is consistent with the notion that constitutive readthrough transcription from the HSP104 gene affects origin function more markedly when approaching ARS1206 from the side of the secondary ACS. This result is also consistent with the notion that incoming transcription is roadblocked more efficiently by ORC binding to the primary ACS as opposed to the secondary ACS, in line with the expected lower affinity of the latter interaction. To consolidate this result, we took advantage of previous work demonstrating that the orc2-1 mutation has a stronger impact on the binding of ORC to ACSs having a poor match to the consensus, even at permissive temperature (Hoggard et al., 2013). If binding of ORC to the ACS is the limiting factor for the functional asymmetry we observe, then affecting binding of ORC to the secondary, lower affinity site by the orc2-1 mutation should exacerbate the instability of the pAS plasmid. Indeed, while pS could be as efficiently maintained in wild-type and orc2-1 cells, pAS raised only sick uracil auxotroph transformants in the orc2-1 background, indicating that it could not be efficiently propagated (Figure 7E).

We conclude that, while presence of primary and secondary ACSs at origin borders participates to the shielding of origins from pervasive transcription, this protection occurs asymmetrically.

Discussion

Transcription by RNA polymerase II occurs largely beyond annotated regions and produces a wealth of non-coding RNAs. Such non-coding transcription events have the potential to alter the chromatin landscape and affect in many ways the dynamics of other chromatin-associated processes. They originate from non-canonical transcription start site usage or from transcription termination leakage, as recently shown in the yeast and mammalian systems (Vilborg et al., 2015; Grosso et al., 2015; Rutkowski et al., 2015; Candelli et al., 2018). Although the frequency of these events is generally low, the persistence of RNA polymerases is dependent on the speed of elongation and the occurrence of pausing and termination, potentially leading to significant occupancy at specific genomic locations where they could have a function. The crosstalks between transcription and replication have been traditionally analyzed in the context of strong levels of transcription, which, aside from a few specific cases, do not represent the natural exclusion of replication origins from regions of robust and generally constitutive transcription (MacAlpine and Bell, 2005; Nieduszynski et al., 2005; Donato et al., 2006). We studied here the impact of pervasive transcription on the specification and the function of replication origins. We demonstrate that origins have asymmetric properties in terms of the resistance to incoming transcription. The inherent protection of replication origins by transcription roadblocks limits the extent of transcription events within these regions. Nevertheless, polymerases that cross the roadblock borders impact both the efficiency of licensing and origin firing, demonstrating that physiological levels of pervasive transcription can shape the replication program of the cell. Importantly, since the global transcriptional landscape is sensitive to changes dictated by different physiological or stress conditions, pervasive transcription is susceptible to regulate the replication program according to cellular needs.

Replication initiates in regions of active transcription

Based on the presence and relative orientation of stable annotated transcripts, early studies have concluded that replication origins are excluded from regions of active transcription (Donato et al., 2006; Nieduszynski et al., 2005). To the light of our results it is clear that this notion needs to be revisited: if origins are generally excluded from regions of genic transcription, they dwell in a transcriptionally active environment populated by RNA polymerases that generate pervasive transcription events. These events have multiple origins and are generally of lower intensity relative to bona fide genic transcription. When ARSs are located in between divergent genes or more generally upstream of a gene, they might be exposed to natural levels of divergent transcription due to the intrinsic bidirectionality of promoters. When they are located downstream of a gene, they are potentially exposed to transcription naturally reading through termination signals (Candelli et al., 2018), which, depending on the level of expression of the gene and the robustness of termination signals, can be consequential.

Transcription termination occurs around and within origins

Nonetheless, origins are not porous to surrounding transcription and the presence of one ARS generates a characteristic footprint in the local RNAPII occupancy signal. When origins are oriented according to the main ORC binding site, the ACS, RNAPII signal is found to accumulate to some extent, depending on the levels of incoming transcription (Figures 1A and 2), and sharply decrease in correspondence of the ACS. We provide several lines of evidence supporting the notion that RNAPII is paused at the site of ORC binding and that transcription termination occurs by a roadblock mechanism. First, we observed a relative enrichment of RNA 3'-ends coinciding with the descending RNAPII signal, indicating that termination occurs at or before transcription has proceeded through the termination signal (the ACS). Second, a fraction of the RNAs produced are sensitive to exosomal degradation (Colin et al., 2014; Candelli et al., 2018). Third, mutation of the ORC-binding site prevents efficient termination in our reporter system. Finally, mutational inactivation of ORC and Cdc6 erases the roadblock and allows transcription to cross the ACS at two natural model origins.

These findings are seemingly in contrast with earlier reports showing that inserting model ARSs in a context of strong transcription leads to transcription termination within ARSs independently of the ORC-binding site or other sequence signals required for origin function in replication (Chen et al., 1996; Magrath et al., 1998). One possibility is that the cloned fragments in these early studies accidentally contain transcription termination signals, some of which were not annotated when these experiments were performed. This is likely the case for ARS305 and ARS209 that both contain a CUT directed antisense to the T-rich strand-oriented ACS. ARS416 (ARS1) and ARS209, also used in these studies, might also contain termination signals from the contiguous TRP1 and HHF1 genes, respectively. Another possibility is that transcription termination occurred both at the roadblock site (the ACS) and internally, but the former was missed because of the poor stability of the RNA produced. As discussed below, we also found evidence of internal termination, but preferentially when examining the fate of antisense transcription (i.e. entering the ARS from the opposite side of the main ACS oriented by its T-rich strand).

The transcriptional footprint observed for antisense transcription shows a large peak when origins are aligned on the main ACS but condenses into a well-defined peak when the alignment is done on the presumed secondary ORC-binding sites (Coster and Diffley, 2017) (Figure 1D), suggesting that RNAPII indeed pauses at these sites. However, transcription termination, inferred from the distribution of RNA 3'-ends, occurs downstream of the putative secondary ACS, within the ARS body (Figure 1E). Because these RNAs are stable, we suggest that they are generated by CPF-dependent termination, possibly because RNAPII encounters cryptic termination signals, or because the ARS chromatin environment prompts termination. Whether the occurrence of internal termination has functional implications for origin function is unclear; nevertheless, our analyses suggest that the presence of antisense RNAPIIs within the origin is important for modulating its function (see below).

Topological organization of replication origin factors detected by transcriptional footprinting

We propose that the asymmetrical distribution of RNAPII at ARS borders relates to the ‘quasi-symmetrical’ model for pre-RC assembly on chromatin, as proposed by Coster and Diffley (Coster and Diffley, 2017). Earlier data suggested that binding of a single ORC molecule at a primary ACS is necessary and sufficient to drive the deposition of one Mcm2-7 double-hexamer (DH) around one DNA molecule (Ticau et al., 2015). However, given the topology of ORC binding to DNA (Lee and Bell, 1997; Li et al., 2018) and the mode of Mcm2-7 deposition around DNA (Frigola et al., 2013), a drastic conformational change would be required to assemble one Mcm2-7 DH with only one ORC (Zhai et al., 2017; Bleichert et al., 2018). The quasi-symmetrical model, in contrast, postulates that two distinct ORC molecules bind cooperatively each ARS at two distinct ACS sequences. One ORC binds the ‘primary’ ACS to load one half of the pre-RC, while the second ORC binds a ‘secondary’, degenerate ACS, to load the other half of the pre-RC in opposite orientation (Yardimci and Walter, 2014; Coster and Diffley, 2017). Each Mcm2-7 hexamer translocating towards the other would then form the Mcm2-7 DH.

The transcriptional footprinting profile around origins shows an antisense RNAPII signal peaking at aligned potential secondary ACSs identified by their match to the consensus (Coster and Diffley, 2017), which testifies to the general functional significance of secondary ACSs prediction. The distribution of distances between the two 5' ends of the two ACSs has a mode of 110nt, which is consistent with the expected physical occupancy of at least one Mcm2-7 DH (Remus et al., 2009). This distance is also consistent with the optimal distance between the two ACSs for a functional cooperation in pre-RC complex formation in vitro (Coster and Diffley, 2017). We show that, presumably because of the average lower affinity of ORC binding to the secondary ACS, transcription termination does not occur upstream of the latter but within the ARS, where RNAPII could favor the translocation of one Mcm2-7 hexamer towards the other, or ‘push’ a pre-RC intermediate (Warner et al., 2017) or the DH away or against the high affinity ORC binding site. On a case-by-case basis, it can be envisioned that antisense transcription might participate to the specification of the position of licensing factors (Belsky et al., 2015).

Functional implications for pervasive transcription at ARS

As highlighted above, early studies examined the impact of transcription on origin function by driving strong transcription through candidate ARSs (Murray and Cesareni, 1986; Snyder et al., 1988; Chen et al., 1996; Kipling and Kearsey, 1989), or estimated the transcriptional output at ARSs based on the relative orientation of stable annotated transcripts (Nieduszynski et al., 2005; Donato et al., 2006). To the light of the recent, more extensive appreciation of the transcriptional landscape, these studies did not address the impact of local, physiological levels of transcription on origin function. Our results demonstrate that the predominant presence of replication origins at the 3'-ends of annotated genes or upstream of promoters in the S. cerevisiae genome (MacAlpine and Bell, 2005; Nieduszynski et al., 2005; Donato et al., 2006) does not preclude ARS from being challenged by transcription. Rather, pervasive transcription is likely to play an important role in fine-tuning origin function and influence their efficiency and the timing of activation. Similar conclusions have been recently reported in an independent study by Soudet et al. (2018).

The licensing of origin is predominantly sensitive to transcription within the ARS, which might have been expected. The presence of transcribing polymerases might prevent pre-RC assembly or ORC binding to the ACS (Mori and Shirahige, 2007; Lõoke et al., 2010). Transcription through promoters has been shown to inhibit de novo transcription initiation by increasing nucleosome occupancy in these regions and lead to the establishment of chromatin marks characteristic of elongating transcription. We propose that transcription though origins might induce similar changes that are susceptible to outcompete binding of ORC and/or pre-RC formation.

Once licensing has occurred, firing ensues a series of steps leading to Mcm2-7 DH activation. It was surprising to observe that firing once licensing has occurred is also sensitive to the levels of local pervasive transcription, possibly implying that post-licensing activation steps are also somehow sensitive to the presence of transcribing RNAPII. An alternative, interesting possibility is that transcription complexes might push the Mcm2-7 DH away from the main site of initiation (Gros et al., 2015). As a consequence, the actual position of replication initiation would be altered with a given frequency: replication might still initiate but in a more dispersed manner around the origin and would not be taken into consideration in the computation of initiation events. A final possibility is that pre-RC formation is to some extent reversible, and transcription might alter the equilibrium by occupying ARS sequences at a post-licensing but pre-activation step. The subset of origins that we found to be insensitive to transcription might be less prone to sliding or have a slower rate of pre-RC disassembly, which would make them less likely to be influenced by transcription.

The topological organization of replication origins and transcription units has been studied in many organisms, with the general consensus that the replication program is relatively flexible and adapts to the changing transcriptional environment during development or cellular differentiation in multicellular organisms (Powell et al., 2015; Petryk et al., 2016; Pourkarimi et al., 2016). The rapidly dividing S.cerevisiae has maintained some of this adaptation of replication to the needs of transcription, for example during meiotic differentiation (Blitzblau et al., 2012). Origin specification, nonetheless, relies on a relatively strict requirement for defined ARS sequences, which is possibly more efficient, but also less flexible for adapting to alterations in the transcription program and more sensitive to pervasive transcription. Transcription termination and RNAPII pausing at origin borders are some of the strategies that shape the local pervasive transcription landscape to the profit of origin function, and mute disruptive interferences into fine tuning of origin efficiency and activity.

Materials and methods

Yeast strains - oligonucleotides - plasmids

Yeast strains, oligonucleotides and plasmids used in this study are reported in Table 1.

Metagene analyses

RNAPII occupancy

For each feature included in the analysis, we extracted the polymerase occupancy values at every position around the feature and plotted the median over all the values for that position in the final aggregate plot.

Transcription termination around origins

To estimate the extent of transcription termination around replication origins, we considered the detection of 3'-ends of polyadenylated transcripts as a proxy for termination events. We counted, for each position, the number of origins for which at least one 3'-end could be mapped at that position. We then plotted the final score per-position in the aggregate plot. This allowed considering the occurrence of at least one termination event at a given position while minimizing the impact of the steady state level of the transcripts produced by termination. To assess the statistical significance of the peak observed upstream of the primary ACS, we adopted the H0 hypothesis that termination occurs with the same frequency in the whole region of alignment around the origin. We estimated the expected value based on the frequency of termination events (i.e. presence of at least one 3’-end) in a 100nt window located at position −500 from the primary ACS across all available sites. Using this estimate, we calculated the probability of detecting the number of termination events actually observed at every position using the binomial distribution and correcting for the multiple testing factor (Benjamini and Hochberg, 1995).

Analysis of termination at ORC-ACS and nr-ACS

ORC-ACSs are defined as the best match to the consensus under ORC ChIP peaks (Eaton et al., 2010). nr-ACSs are defined as sequences containing a nearly identical motif that are not occupied by ORC as defined by ChIP analysis (Eaton et al., 2010).

Correlation between transcription and replication metrics

For the boxplot analyses shown in Figure 5, we selected 190 origins out of the 228 described in Nieduszynski et al. (2006) for which replication metrics were available (Hawkins et al., 2013) and considered the RNAPII read counts in the 100nt following the 5’ end of the ACS, in the sense and antisense direction (Supplementary file 1 Table 1). Origins were ranked based on the transcription levels to establish two groups, one of high and one of low transcription, which were compared in terms of licensing and firing efficiencies. A Student t-test (two tailed, same variance, unpaired samples) was used to estimate the statistical significance of the differences between the two distributions of values.

For the correlation analyses shown in Figure 6, we selected origins with the highest levels of incoming transcription by considering a total coverage higher than 10 read counts in an area of 200 bp upstream of the area of origin activity, both on the T-rich and A-rich strand of the ACS consensus sequence (regions ‘A’ and ‘C’, Figure 5) (Supplementary file 1 Table 2). Then we summed the total read coverage over the area of origin activity (region ‘B’, Figure 5) on both sense and antisense strand (Supplementary file 1 Table 3). This value was then correlated with different measures of replication activity.

Secondary ACS mapping

The coordinates of the predicted secondary ACSs are reported in Table 2. To map putative secondary ACS sequences, we considered a nucleotide frequency matrix for the ACS consensus sequence (Coster and Diffley, 2017) and produced a PWM (Position Weight Matrix) using the function PWM from the R Bioconductor package ‘biostrings’ using default options. We used the ‘matchPWM’ function from ‘biostrings’ to look for the best match for putative secondary ACSs in the range between the position +10 to+400 relative to the main ACS. We then calculated the distribution of distances between the main and the putative secondary ACSs and the distribution of matching scores (Figure 1—figure supplement 1). For the meta-analyses shown in Figure 1D–E, we restricted this analysis to a shorter range, considering that secondary ACSs located less than 70nt or more than 200nt might not be biologically significant. The position and scores of all putative sense and antisense ACSs used for the metaanalyses are shown in Table 2.

Plasmid constructions

Oligonucleotides used for cloning and plasmids raised are reported in Table 1. PTETOFF-HSP104::ARS305::HSP104 PGAL1-CUP1 (, URA3) plasmids were constructed by inserting a 548 bp fragment containing the wild-type ARS305, as defined in OriDB v2.1.0 (http://cerevisiae.oridb.org; chrIII:39,158–39,706) in vector pDL454 (Porrua et al., 2012) by homologous recombination in yeast cells. ARS305 was PCR amplified from genomic DNA using primers DL3370 and DL3371 (Figure 3B) or DL3581 and DL3583 (Figure 3C). Mutations in ARS305 were obtained by inserting linkers by stitching PCR and homologous recombination in yeast in regions A, B1 and B4 corresponding to Lin4, Lin22 and Lin102, respectively (Huang and Kowalski, 1996).

PTETOFF-HSP104-ARS1206 (pDL214) plasmid was constructed by inserting the HSP104 gene and the downstream genomic region containing the HSP104 terminator and ARS1206 into pCM188 (ARS1, CEN4, URA3) by homologous recombination in yeast. ARS1 was removed from pDL214 by cleavage with NheI and repaired by homologous recombination using a fragment lacking ARS1 to obtain ‘pS’. PTETOFF-HSP104-6021sra (or ‘pAS’) was constructed by reversing ARS1206 orientation in ‘pS’ using homologous recombination in yeast.

RNA analyses

RNAs were prepared by the hot phenol method as previously described (Libri et al., 2002). Northern blot analyses were performed with current protocols and membranes were hybridized to the indicated radiolabeled probe (5'-end labelled oligonucleotide probes or PCR fragments labeled by random-priming in ULTRAhyb-Oligo or ULTRAhyb ultrasensitive hybridization buffers (Ambion)) at 42°C overnight. Oligonucleotides used for generating labeled probes are reported in Table 1. RNase H cleavage was performed by annealing 50pmoles of each oligonucleotide to 20 µg of total RNAs in 1X RNase H buffer (NEB) followed by addition of 2U of RNase H (NEB) and incubation at 30°C for 45 min. Reaction was stopped by addition of 200 mM sodium-acetate pH 5.5 and cleavage products were phenol extracted and ethanol precipitated. Pellets were resuspended in one volume of Northern sample loading buffer and the equivalent of 10 µg of total RNAs were analyzed by Northern blot on a 2% TBE1X agarose gel. Oligonucleotides used for RNase H cleavage assay are reported in Table 1.

For RT-qPCR analyses, RNAs were reverse transcribed with 200U of M-MLV reverse transcriptase (ThermoFisher) and strand specific primers for 45 min at 37°C. Reactions were diluted 10 times before qPCR analyses. Quantitative PCRs were performed on a LightCycler 480 (Roche) in 384-Multiwell plates (Roche) in 10 µL reactions that contained 1% of the reverse transcription mix and 0.25 pmoles of each priming oligonucleotides. Quantification was performed using the ∆∆Ct method. ‘No RT’ controls were systematically analyzed in parallel. Each transcription level reported represents the mean of three independent RNA extractions each assayed in duplicate qPCRs. Error bars represent standard deviations. Oligonucleotides used for RT-qPCR are reported in Table 1. Unless indicated otherwise, transcription levels were normalized to ACT1 mRNA levels.

Plasmid-loss assay

Cells were transformed with the indicated ARS1206-borne (CEN4, URA3) plasmid and plated on complete synthetic medium lacking uracile. Single transformants were used to inoculate liquid cultures of CSM −URA that were grown to saturation. Saturated cultures were back diluted into rich medium and maintained in logarythmic phase (i.e. below 0.8 OD600) for the indicated number of generations. Aliquots were pelleted, rinsed with water and seven-fold serial dilutions were spotted on YPD and CSM −URA, starting at 0.3 OD600. Growth on YPD plates was used to infer that the same numbers of cells were spotted, while reduced numbers of cells growing on CSM−URA reflected plasmid loss over the indicated number of generations.

Datasets

Datasets used in this study are available from GEO with accession numbers GSE56435 (Schaughency et al., 2014), GSE75586 (Roy et al., 2016) and GSE97913 (Candelli et al., 2018).

Tables

Table 1 and Table 2.

Table 1. Yeast strains, oligonucleotides and plasmids used in this work. .

Yeast strains Name Genotype Origin
 DLY671 W303-1a trp1∆ Libri laboratory (BMA64)
 DLY2923 W303-1a ORC2 ORC5 CDC6 Gift from the Pasero laboratory (PP2583)
 DLY2685 As W303-1a, ORC2 ORC5 cdc6-1 Gift from the Schwob laboratory (E589)
 DLY2687 As W303-1a, orc2-1 ORC5 CDC6 Gift from the Schwob laboratory (E1507)
 DLY2688 As W303-1a, ORC2 orc5-1 CDC6 Gift from the Schwob laboratory (E4649)
Oligonucleotides Name Sequence Purpose
 DL3370 CATCCACAATTACAACCTATACATATTCTAGCTGCCTTCATTGAAACGGCGACGCCCGACGCCGTAATAAC Amplification of ARS305 from genomic DNA. Fw primer bearing 48 bp of homology with DL1702.
 DL3371 gaatctttcttcgaaatcacctttgtatttagcacctgcggttaatgcggATATATCAGAAACATACATATG Amplification of ARS305 from genomic DNA. Rev primer bearing 50 bp of homology with DL1666.
 DL3446 CATCCACAATTACAACCTATACATATTCTAGCTGCCTTCATTGAAACGATATATCAGAAA
CATACATATG
Insertion of ARS305 in reverse orientation
(compare with primer pair DL3370/DL3371). Rev primer bearing homology with DL1702.
 DL3447 gaatctttcttcgaaatcacctttgtatttagcacctgcggttaatgcggGCG
ACGCCCGACGCCGTAATAAC
Insertion of ARS305 in reverse orientation (compare with primer pair DL3370/DL3371). Fwd primer bearing homology with DL1666.
 DL3581 gaatctttcttcgaaatcacctttgtatttagcacctgcggttaatgcggGTTTCATGTACTGTCCGGTGTGATT Insertion of shortened ARS305, fwd (cf. DL3447). Primes 32 bp downstream B4 element, removing 291 bp of ARS305 “full-length “3’ end.
 DL3583 CATCCACAATTACAACCTATACATATTCTAGCTGCCTTCATTGAAACGGAGTATTTGATCCTTTTTTTTATTGTG Insertion of shortened ARS305, rev (cf. DL3446). Primes 34 bp upstream ARS305 ACS, removing 83 bp of ARS305
“full-length “5’ end.
 DL3376 TTATTCCTCGAGGACTTTGTAGTTCTTAAAGC Insertion of linker substitution Lin102 (B4-) in ARS305 by two stages overlapping PCRs.
Fw primer,
pair with DL3371.
 DL3377 CTACAAAGTCCTCGAGGAATAATAAATCACACCGGAC Insertion of linker substitution Lin102 (B4-) in ARS305 by two stages overlapping PCRs. Rev primer, pair with DL3370.
 DL3378 GGGACCTCGAGGAATACATAACAAAACATATAAAAACC Insertion of linker substitution Lin22 (B1-) in ARS305 by two stages overlapping PCRs. Fw primer, pair with DL3371.
 DL3379 GTTATGTATTCCTCGAGGTCCCTTTAATTTTAGGATATG Insertion of linker substitution Lin22 (B1-) in ARS305 by two stages overlapping PCRs. Rev primer, pair with DL3370.
 DL3380 CATAACCCTCGAGGTAAAAACCAACACAATAAAAAAAAGG Insertion of linker substitution Lin4 (A-) in ARS305 by two stages overlapping PCRs. Fw primer, pair with DL3371.
 DL3381 GGTTTTTACCTCGAGGGTTATGTATTGTTTATTTTCC Insertion of linker substitution Lin4 (A-) in ARS305 by two stages overlapping PCRs. Rev primer, pair with DL3370.
 DL1359 CCTTATACATTAGGTCCTTT HSP104 Northern PCR probe, fwd. Primes about 100nt upstream HSP104 ATG in PTE
TOFF-HSP104 plasmid serie
 DL1360 ATCCCCCGAATTGATCCGG HSP104 Northern PCR probe, rev. Primes upstream BamHI site in PTETOFF-HSP104 plasmid serie
 DL377 ATGTTCCCAGGTATTGCCGA ACT1 Northern PCR probe/RT qPCR amplicon, fwd.
Oligonucleotides  DL378 acacttgtggtgaacgatag ACT1 Northern PCR probe/RT qPCR amplicon, rev.
 DL2627 ATTCAAAAGCGAACACCGAATTGACCATGAGGAGACGGTCTGGTTTAT snR14 Northern oligo probe
 DL3763 CTGGTTGAAACAAATCAGTGCCGGTAAC ARS404 qRT-PCR,
amplicon downstream ARS404 ACS. 5’ primes 202 bp
after SSB1 STOP, pair with DL3764.
 DL3764 GACTTTTTCTTAACTAGAATGCTGGAGTAGAAATACGC ARS404 qRT-PCR, amplicon downstream ARS404 ACS. 5’ primes 288 bp after SSB1 STOP, pair with DL3763.
 DL3767 CTTTTTAAACTAATATACACATTTTAGCAGATGCG ARS404 qRT-PCR,
amplicon upstream ARS404 ACS. 5’ primes 23 bp
after HO STOP, pair with DL3768.
 DL3768 GATGCTGTCCGCGGGCCTCATAAG ARS404 qRT-PCR, amplicon upstream ARS404 ACS. 5’ primes60 bp before HO STOP, pair with DL3767.
 DL3823 GGCACTATGCTTTTTAAAATTTTGTTTATACTCAATTTCG ARS1004 qRT-PCR, amplicon upstream
ARS1004 ACS. 5’ anneals80 bp after REE1 STOP
 DL3824 GCCCAGTATTTTGTTAACTGTATGGATTGTACTAG ARS1004 qRT-PCR, amplicon upstream ARS1004 ACS. 5’ anneals170 bp after REE1 STOP
 DL3827 GTGTTTTAAGATAAAGTGACGAAAGTTAGGGTG ARS1004 qRT-PCR, amplicon downstream ARS1004 ACS. 5’ anneals 228 bp after REE1 STOP
 DL3828 CATCATAAGTACTAATTACCACGAATTCAATAATTAGTAAATAC ARS1004 qRT-PCR, amplicon downstream ARS1004 ACS. 5’ anneals 318 bp after REE1 STOP
 DL187 ACACActaaattaccggatcaattcgggggatccATGAACGACCAAACGCAATT Cloning of HSP104 in pCM188, fwd.
 DL189 catgatgcggccctcctgcagggccctagcggccgcTTAATCTAGGTCATCATCAA Cloning of HSP104 in pCM188, rev.
 DL1124 taatgaggacagtatggaaattgatgatgacctagattaaTTTAATATAGTGTGATTTTT Cloning of HSP104 3' UTR in pCM188-HSP104, fwd.
 DL1125 ATTACATGATGCGGCCCTCCTGCAGGGCCCTAGCGGCCGCTTTAACATGATTTGGTAGTC Cloning of HSP104 3' UTR in pCM188-HSP104, fwd.
 DL4026 CGTTTATTCCCTTGTTTGATTCAGAAGCAG ARS1 KO in pDL214 by
overlapping PCRs, Fwd. Anneals 236 bp after pDL214’s
URA3 STOP. To be used for both 1 st and 2nd step of the reaction.
During 1 st step, use it in combination with DL4027. During 2nd step, use it in combination with DL4030.
Oligonucleotides  DL4027 GCTAGCAAGAATCGGCTCGGGGCTCTCTTGCCTTCCAAC ARS1 KO in pDL214 by overlapping PCRs, Rev. Anneals 334 bp after pDL214’s URA3 STOP.
To be used during 1 st step in combination with DL4026.
 DL4029 CAAGAGAGCCCCGAGCCGATTCTTGCTAGCCTTTTCTC ARS1 KO in pDL214 by overlapping PCRs, Fwd. Anneals 746 bp after pDL214’s URA3 STOP. To be used during 1 st step in combination with DL4030.
 DL4030 GATTACGAGGATACGGAGAGAGG ARS1 KO in pDL214 by overlapping PCRs, Rev. Anneals 843 bp after pDL214’s URA3 STOP. To be used for both 1 st and 2nd step of the reaction. During 1 st step, use it in combination with DL4029. During 2nd step, use it in combination with DL4026.
 DL4032 GTGAAGGAGCATGTTCGGCACAC ARS1 KO in pDL214 by overlapping PCRs, Rev sequencing primer. Anneals 1157 bp after pDL214’s URA3 STOP.
 DL4000 TTCAAATGTACAGTAACTATCAAAACCATT
ATTGTAGTACCCGTATTCTAATAATGAGCAAAAGAGCTCACATTTTAACG
Reverse ARS1206 orientation in pDL214, Fwd.
Bears 55 bp of homology with ARS1206 3’ end (+320 to+375 after HSP104 STOP) followed by 25 bp of homology
to 5’ of T-rich predicted ACS (+102 to+127 after HSP104 STOP). Pair with DL4001.
 DL4001 TATATATAATTAATAAAACTAATGGAATTTGTTTAATTGAACTTGACACCCGAGCGGACCAATCCGCGTGTGTTTTATAC Reverse ARS1206 orientation in pDL214, Rev. Bears 55 bp
of homology with ARS1206 5’ end (+51 to+106 after HSP104 STOP) followed by 25 bp of homology with 3’ end of ARS1206 (+295 to+320 after HSP104 STOP). Pair with DL4000.
 DL4061 ATTATTAGAATACGGGTACTAC Reverse ARS1206 orientation in pDL214, extension of homology region downstream ARS1206, Fwd. Primes 134 bp upstream CYC1 terminator. Pair with M13 reverse (DL2163).
 DL2163 caggaaacagctatgac Reverse ARS1206 orientation in pDL214, extension of homology region downstream ARS1206, Rev.
 DL4066 GCTCGGGTGTCAAGTTCAATTAAAC Reverse ARS1206 orientation in pDL214, extension of homology region
upstream ARS1206, Rev. Primes 106 bp downstream HSP104 STOP. Pair with DL530.
 DL530 GTTGAATTTAACTCAAGAGGC Reverse ARS1206 orientation in pDL214, extension of homology region upstream ARS1206, Fwd. Anneals 2409–2429 in
HSP104.
Oligonucleotides  DL3986 gctgaagaatgtctggaagttctacc Reverse ARS1206 orientation in pDL214, Fwd sequencing primer annealing 108 bp before HSP104 STOP.
 DL163 acattttcatcacgagatttaccc RNase H cleavage assay. HSP104, antisense, position 2606–2583
from HSP104 ATG.
 DL164 ttatcgtcatcacctaacgtgtcagcccctatagtagcttcgtgatttggtagaacttcc RNase H cleavage assay. HSP104 Northern oligonucleotide probe, antisense, position 2718–2631 from HSP104 ATG.
 DL473 TTTTTTTTTTT
TTTTTTTTT
RNase H cleavage assay. Poly(dT) oligonucleotide
 DL3991 GATTTGACGTCCAGTGGACTTTTTTGTCC RNase H cleavage assay, testHSP104 readthrough on pDL905, antisense, position 2923–2895 fromHSP104 ATG
 DL3994 GGAAGTAATAAGTGAAGGTTAAATCTGGACC RNase H cleavage assay, test HSP104 readthrough on pDL907, antisense, position 2909–2879 from HSP104 ATG
 Plasmids Name Features Reference
 pDL454 PTETOFF-HSP104::Reb1BS::HSP104, PGAL1-
CUP1, 2µ, URA3
Colin et al. Colin et al., 2014
 pDL551 PTETOFF-HSP104::
Reb1BS(−)::HSP104, PGAL1-
CUP1, 2µ, URA3
 pDL790 PTETOFF-HSP104::ARS305_548 bp::HSP104
, PGAL1-CUP1, 2µ, URA3
This study
 pDL793 PTETOFF-HSP104::ARS305(A−)_548 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL909 PTETOFF-HSP104::
ARS305_175 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL910 PTETOFF-HSP104::
ARS305(A−)_175 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL911 PTETOFF-HSP104::ARS305(B1−)_175 bp::HSP104, PGAL1-CUP1, 2µ, URA3
 pDL912 PTETOFF-HSP104
::ARS305(B4−)_175 bp::HSP104
, PGAL1-CUP1, 2µ, URA3
 pDL913 PTETOFF-HSP104
::ARS305(B1−B4−)_175 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL30 PTETOFF-HSP104,
ARS1, CEN4, URA3
Libri laboratory
 pDL214 PTETOFF-HSP104,
ARS1206, ARS1, CEN4, URA3
 pDL905 PTETOFF-HSP104, ARS1206, ∆ars1, CEN4, URA3 This study
 pDL907 PTETOFF-HSP104, 6021sra, ∆ars1, CEN4, URA3

Table 2. Coordinates of primary and secondary ACSs used in this study. .

Proposed primary ACS (Nieduszynski et al., 2006) Putative secondary ACS (this study)
ID Chromosome Strand Start End Match Score Chromosome Strand Start End Match Score Protected length (nt)
1 chrI + 31001 31018 TATTTTTAAGTTTTGTT 0.974909231 chrI - 31190 31173 GTATAATATTTTTAGTT 0.87301127 189
2 chrI - 70431 70414 ATTTTTTATGTTTAGAA 0.949548431 chrI + 70251 70268 ACTATCAATGTTTTATC 0.818662772 180
3 chrI - 124526 124509 ATTTTTTATATTTAAGT 0.939615332 chrI + 124412 124429 GTTTTCTCTATTTAAAT 0.76163459 114
4 chrI + 159951 159968 TTTATTTATATTTAGTG 0.951660057 chrI - 160108 160091 ATATAGCATAATTACTT 0.796339361 157
5 chrI + 176234 176251 TCTTTTTATGTTTTCTT 0.936946746 chrI - 176333 176316 TAAATATGTGTTTATTA 0.816621821 99
6 chrII + 28984 29001 TCACTCTATCTTTTTTA 0.78989004 chrII - 29092 29075 TATAACAAAAATTGGTC 0.767973746 108
7 chrII - 63376 63359 TTTTTTTAATTTTTGTC 0.934538928 chrII + 63256 63273 TAAAAATTTGTTTTCTT 0.843331211 120
8 chrII - 170228 170211 CCAGTGAACGCTTAAAA 0.646819795 chrII + 170126 170143 CTTTGCTACGATTTCTT 0.763191826 102
9 chrII - 198382 198365 AACTTCAAAGTACATTG 0.673812699 chrII + 198228 198245 ATTATAGACTTTCATTC 0.772245255 154
10 chrII - 237832 237815 AAGGTACATAGCGATTT 0.628400298 chrII + 237685 237702 TTATTAAAGGGTTTGGA 0.774836934 147
11 chrII - 255040 255023 AGGTAGAAGAGTTACGG 0.617416402 chrII + 254892 254909 TGATTTTTCATTTTACT 0.841326164 148
12 chrII + 326149 326166 CTATCGAAACTTTTGTT 0.748562634 chrII - 326273 326256 CTTTTAATAGTTTAGGT 0.860235002 124
13 chrII - 408006 407989 TAGGAAAATATATAGAG 0.708025047 chrII + 407871 407888 ATATTTAAAGAGTTGAA 0.77590664 135
14 chrII - 417974 417957 TGTAGAAATGTCTAGCG 0.67916971 chrII + 417844 417861 AAATTTAATATTTTTGA 0.912902242 130
15 chrII - 486855 486838 GAAGTCCTCTTCTTCGC 0.639951668 chrII + 486735 486752 ATTAATTATGTTTTTCC 0.89533109 120
16 chrII + 622713 622730 TATATAGAAAGTTGCTT 0.760778109 chrII - 622866 622849 TTTTTGTACGTTTTTTT 0.907808059 153
17 chrII + 704289 704306 CTACCAAAAGTGTACCG 0.581803503 chrII - 704455 704438 AATGTTTTTTTTTTTTT 0.897759223 166
18 chrII - 741746 741729 CGAAAAGATATGTGGGA 0.64946824 chrII + 741628 741645 TAAGATCAAGTTTGGTA 0.824844021 118
19 chrII + 757441 757458 TAAATCTAAGATAGCTG 0.682422088 chrII - 757613 757596 GTTATATAAGTATACGT 0.779064174 172
20 chrII + 792164 792181 TATTTCATGGTTTTTAG 0.736834685 chrII - 792287 792270 CTTTTTAAAATTCATTG 0.834945362 123
21 chrIII + 11254 11271 TTTTTTTATGTTTTTTT 0.985847127 chrIII - 11400 11383 GTTGAATTTGGTTAGAT 0.782826917 146
22 chrIII - 39591 39574 TTTTTATATGTTTTGTT 0.963617028 chrIII + 39476 39493 TTATTTTTTATTTACTT 0.914777509 115
23 chrIII + 74518 74535 TGTATTTATATTTATTT 0.944792175 chrIII - 74682 74665 GAGATCTTAATTTATCT 0.770457519 164
24 chrIII - 108972 108955 TTTATTTATGTTTTCTT 0.960865701 chrIII + 108832 108849 TAGAAATATGTTGAGTT 0.795588546 140
25 chrIII + 132036 132053 TTTGTACATTGTTTATA 0.792015393 chrIII - 132155 132138 CTTTTATATGTTTAAAT 0.885104513 119
26 chrIII + 166650 166667 GTTTTATTCCATTATTT 0.81768767 chrIII - 166768 166751 ATTATTTACATTTACGA 0.903103359 118
27 chrIII + 194302 194319 CTACTGCAATTTTTTAC 0.730959168 chrIII - 194402 194385 TGTAATTACATTTCTTA 0.79211775 100
28 chrIII - 197559 197542 AATATTCATGTTTAGTA 0.934784063 chrIII + 197415 197432 ATCTTAAACCTTTTTAG 0.797219912 144
29 chrIII + 224856 224873 TCAGTTTTTTTTATGTT 0.78153895 chrIII - 224956 224939 TTTATTTTTGTTTGTTT 0.899494022 100
30 chrIII - 273030 273013 TTTTTTCAAATTTAGTT 0.94325972 chrIII + 272904 272921 TTTATTCAAAATTTTTC 0.870692365 126
31 chrIII + 292584 292601 TATATATATATTTATTT 0.933162383 chrIII - 292695 292678 TATAATAACATTTTTTA 0.881496782 111
32 chrIII + 315872 315889 TGTATATAAATTAAGTG 0.777607317 chrIII - 315979 315962 CATTTTAATATCTATAT 0.829435873 107
33 chrIV - 15681 15664 ATTTTTTACGTTTTCTC 0.928797007 chrIV + 15525 15542 TAAATTCTAAGTTATTC 0.806599978 156
34 chrIV - 86123 86106 GATTTTTATGTTTGGGC 0.907628171 chrIV + 85996 86013 CTTTATAAAGATTTTAT 0.843543061 127
35 chrIV + 123677 123694 TGTTTTCACTTTGTGTT 0.820618605 chrIV - 123793 123776 TTAATATATATTTAGTT 0.9347773 116
36 chrIV - 212592 212575 TTTTTTTATATTTTGTT 0.991320747 chrIV + 212441 212458 TTTTTTTTTTTTTTTTT 0.926463613 151
37 chrIV + 253839 253856 ATTTTTTATAGTTTTGC 0.901024131 chrIV - 253948 253931 TAATTTTATCTTTAGAT 0.940018266 109
38 chrIV - 329742 329725 GATTTTTATTTTTTTGT 0.930581986 chrIV + 329601 329618 TATTATTATTATTATTC 0.884653435 141
39 chrIV + 408134 408151 TTATATTATATTTAGCG 0.896228674 chrIV - 408291 408274 TTATTACATATTTTTGT 0.898263462 157
40 chrIV - 484039 484022 TTTTTTTATATTTATGT 0.972409126 chrIV + 483896 483913 TTGTTTGTTCATTTCTT 0.792451309 143
41 chrIV - 505522 505505 TTTTTTTATATTTTTGC 0.95203234 chrIV + 505345 505362 CCTTTTCACGTTTTTGC 0.864843823 177
42 chrIV - 555401 555384 AAAGTTTATGTTTTTTC 0.925775335 chrIV + 555290 555307 ATAAATGTTGTTTTTTT 0.835510567 111
43 chrIV - 567681 567664 TTTTTTTATGTTTTGAG 0.946669447 chrIV + 567572 567589 ACTTTTAATTTTTTTTT 0.905571442 109
44 chrIV - 640068 640051 TTTTTTAAAGTTTTGGT 0.951500543 chrIV + 639918 639935 CTATAATATATTTATTC 0.86149187 150
45 chrIV + 702928 702945 AAAATAATTAATGTTTT 0.737939741 chrIV - 703030 703013 TGATTTAAAATTCTGTA 0.83908476 102
46 chrIV + 748452 748469 AAATTAATTGATTAATT 0.822458971 chrIV - 748585 748568 TTTTTTAATATTTAATA 0.915446997 133
47 chrIV - 753339 753322 TTTTTTTACATTTTGCT 0.953908195 chrIV + 753221 753238 AAACTTATTTTTTAAGC 0.78950557 118
48 chrIV + 806097 806114 CTCTTCCAAATTTTTAA 0.777746734 chrIV - 806256 806239 TCATATCCTGTTTTAAA 0.722790604 159
49 chrIV + 913859 913876 TTTTTTTATTTTTATAT 0.943491396 chrIV - 913957 913940 ACAATTTTTGTTTATTT 0.885371567 98
50 chrIV + 921736 921753 TCTTTAATCGATTTTAA 0.773941597 chrIV - 921840 921823 TTTGTTTATTTTTTTTT 0.943438157 104
51 chrIV - 1016854 1016837 TTTGTTTACGTTTTGGA 0.934312886 chrIV + 1016682 1016699 AGAATTCATTTTAATCT 0.772819262 172
52 chrIV + 1057886 1057903 TTCTTTTATTATTTTTT 0.899933367 chrIV - 1058017 1058000 AAAGTGAATTTTTTTGT 0.837029199 131
53 chrIV - 1110139 1110122 TTTTTTTATATTTTTAT 0.956467815 chrIV + 1109960 1109977 GAATTCTTCATTTAGAT 0.824896005 179
54 chrIV - 1159452 1159435 CTTTTCTAAGCTTTGAA 0.769370807 chrIV + 1159286 1159303 ATAATTAATTTTTTTGA 0.889208627 166
55 chrIV - 1166166 1166149 TCGGAATATTATTTCTT 0.763125812 chrIV + 1166064 1166081 CTTAATAAATTTTTGTA 0.854045557 102
56 chrIV + 1240920 1240937 CTTCTTGAAATTTGATT 0.771311686 chrIV - 1241096 1241079 TTTATAAAAATTTATAT 0.871453601 176
57 chrIV + 1276271 1276288 TTCGTTTTCTTTTTCTC 0.82062871 chrIV - 1276405 1276388 CAAATATATATTGATCA 0.767679431 134
58 chrIV - 1302763 1302746 TATATATTTAGTTAATG 0.795859241 chrIV + 1302616 1302633 GAGTTTTACGTATTCTT 0.80224896 147
59 chrIV + 1404323 1404340 TAAAATCATTTTCTTTT 0.829710275 chrIV - 1404511 1404494 AGGATTCTTTATTACGT 0.774058834 188
60 chrIV + 1461890 1461907 GAGTAACTTCTTGTCGG 0.624436491 chrIV - 1462038 1462021 AACATTAATTGTTGTTA 0.790149896 148
61 chrIV - 1487098 1487081 TTAAATTTAGTTTTTTT 0.870549799 chrIV + 1486965 1486982 CCAATACATGATTGGAT 0.773138313 133
62 chrV - 59469 59452 AATATTTACATTTTGAT 0.935717414 chrV + 59363 59380 TTTTTTTTTCTTTTTTT 0.922560213 106
63 chrV + 94055 94072 CAAGTTTATATTTTGTT 0.938620288 chrV - 94173 94156 TATGTTTAATTATATTG 0.79888376 118
64 chrV - 145714 145697 CAGTTTTTTGTTTAGTT 0.906995194 chrV + 145608 145625 TTATATAATATTTTAGG 0.854409653 106
65 chrV - 173808 173791 TAATTTTATATTTTGCC 0.93759113 chrV + 173704 173721 TATTTATACTTTTACGG 0.861582181 104
66 chrV + 212455 212472 TAAAATTATGTTTAGGT 0.938368393 chrV - 212555 212538 CGTATACTTTTTTTGTG 0.794230687 100
67 chrV + 287567 287584 TTTATTTATGTTTTGTT 0.988690479 chrV - 287761 287744 CTTTGTTATCTTGTGAA 0.729422588 194
68 chrV + 353586 353603 AATATTTACTTTTTGGT 0.936542643 chrV - 353774 353757 TTGAATTATGCTTATGT 0.812386986 188
69 chrV - 406906 406889 TTTTTTTATATATAGTC 0.881971164 chrV + 406734 406751 GTAATTTATGATTAATC 0.864888268 172
70 chrV - 439105 439088 ATTTTTTAAGTTTTGCG 0.915882066 chrV + 438997 439014 GGTATTCTTCTTTTTCT 0.814453982 108
71 chrV + 549589 549606 TATTATTAATATCTTGT 0.818517794 chrV - 549686 549669 TAATTTAATATTTTTTT 0.948482332 97
72 chrVI - 167738 167721 TATATTTATATTTTCGT 0.945765544 chrVI + 167551 167568 AATATTTAAATATAAGT 0.814242246 187
73 chrVI + 199397 199414 TTATTTCGAGCTTTGTC 0.737504399 chrVI - 199507 199490 ATCCATAATATTTACCT 0.801830214 110
74 chrVI + 216470 216487 CATTTCTATTTTTTTTT 0.890722071 chrVI - 216600 216583 TAATGTGATGGTTAGTT 0.802062704 130
75 chrVI - 256383 256366 TTTATGTTTTTTCCGGA 0.701845209 chrVI + 256263 256280 AAAAATTCCGATCTTGT 0.72753389 120
76 chrVII - 64458 64441 ATTTTTAATATTTTGTT 0.966859378 chrVII + 64357 64374 TATTGTTATATTTAGTT 0.901272249 101
77 chrVII + 112124 112141 ATTTTATACGTTTATGT 0.921703978 chrVII - 112271 112254 ATAGTTTTTTTTTATGC 0.861155565 147
78 chrVII + 163235 163252 TCATTTTATAATTTGTT 0.916233817 chrVII - 163378 163361 GTAATATATGATTAGAA 0.844307348 143
79 chrVII + 203971 203988 ATTTTTTATATTTATTA 0.950625858 chrVII - 204165 204148 CATTTTAAACTCTATAT 0.78805761 194
80 chrVII + 286003 286020 TTTATTTACTTTTAGTC 0.933155022 chrVII - 286153 286136 CTAGTAATCTTTCAGTC 0.747097252 150
81 chrVII - 352863 352846 TTTAATTACGTTTAGTT 0.942276914 chrVII + 352758 352775 TACTTTTATGATTCATT 0.812763403 105
82 chrVII - 388846 388829 TTTATTTAACTTTTGTT 0.939702794 chrVII + 388738 388755 TTAGTTCTCATTTATAA 0.82432824 108
83 chrVII - 421280 421263 ATAAATTATTGTTTAGT 0.826708937 chrVII + 421176 421193 CTATTTCAAATTTGTTT 0.859366438 104
84 chrVII - 485110 485093 TTTATTTATGTTTTGCC 0.947613634 chrVII + 484978 484995 AATTATCAAGTTTTTCT 0.875154553 132
85 chrVII - 508907 508890 CATTTTAATGTTTGGTT 0.923555282 chrVII + 508801 508818 ATCTTTTATCTTTTATC 0.872797056 106
86 chrVII - 568660 568643 AGTATTTATATTTAGCC 0.909439604 chrVII + 568509 568526 GTCATTCATGATTTATT 0.834093344 151
87 chrVII + 574700 574717 AGTATTTATGTTTTGTC 0.937749085 chrVII - 574854 574837 TATACTCATATTTTGGC 0.838055118 154
88 chrVII - 660000 659983 ATATTTTATGTTTACTT 0.952756007 chrVII + 659904 659921 TTGTTTTTTTATTGTTT 0.823819951 96
89 chrVII + 715314 715331 TTTGTTTATATTTTGTT 0.970567449 chrVII - 715431 715414 AATCTTTAACTTGTGAT 0.779912848 117
90 chrVII + 778013 778030 CTTTTTTACCTTTTGTT 0.938434047 chrVII - 778193 778176 AGTGTTTATATTTATTT 0.926919799 180
91 chrVII - 834664 834647 TTGTATATAGTTTAGTT 0.854509956 chrVII + 834549 834566 GGTTTTTAACTTTTCCC 0.830646453 115
92 chrVII + 888412 888429 TATTTTAATATTTTGTT 0.973625821 chrVII - 888567 888550 TTTATATATATATATTC 0.823335292 155
93 chrVII - 977904 977887 TTTTTTAATTTTTTTAT 0.925318963 chrVII + 977810 977827 TTTTTTTAATGATTTTT 0.806000942 94
94 chrVII + 999468 999485 CTTTTTTACTTTTTGGG 0.904948204 chrVII - 999575 999558 TATTTTTTTTTTTTTTT 0.925871289 107
95 chrVIII - 7755 7738 TATTTTTATATTTAGGT 0.984899843 chrVIII + 7618 7635 CTTGTTTATTATTATTA 0.875022851 137
96 chrVIII + 64302 64319 TAATTTTAATTTTAGTT 0.942262943 chrVIII - 64434 64417 ATTCTTTATATTTATTT 0.922675429 132
97 chrVIII - 133538 133521 TATTTTAACATTTAGTT 0.959052991 chrVIII + 133406 133423 TTCTTTTATGTGTATGC 0.834208883 132
98 chrVIII + 168597 168614 TTGTGTCATATTTAGAC 0.799695233 chrVIII - 168793 168776 TATATATATATATACGT 0.820409776 196
99 chrVIII + 245788 245805 CTATTTTATGATTAGTT 0.939777326 chrVIII - 245940 245923 CAATTCCAAATTTAGGC 0.831524522 152
100 chrVIII - 392260 392243 TTTTTTCTTGAGTACTT 0.788764838 chrVIII + 392088 392105 ATAATTTACATTAATAT 0.821200767 172
101 chrVIII - 447794 447777 TATGTTTATGTTTTGTG 0.947093715 chrVIII + 447598 447615 TTGCTTAATATTTTGCA 0.846461752 196
102 chrVIII - 501949 501932 CGTTTATACATTTTGTT 0.896794884 chrVIII + 501752 501769 ATATTTTACGGTTCTTT 0.824337524 197
103 chrVIII + 556140 556157 AATTTTTACGTTTAGGT 0.969507836 chrVIII - 556301 556284 CATTTTAATATCTATAT 0.829435873 161
104 chrIX - 105966 105949 ATTATTCATGTTTTCTT 0.92780469 chrIX + 105812 105829 AATAATAATAATAATGG 0.754881026 154
105 chrIX - 136290 136273 GCAGTTTATGTTTTGTT 0.905839044 chrIX + 136160 136177 GATATCTATATTTTATA 0.840946348 130
106 chrIX + 175173 175190 ATGTTTTATGTTTTGTC 0.936874196 chrIX - 175339 175322 CAATTTCAAATTTAAAA 0.82970169 166
107 chrIX + 214735 214752 TTAATTTATGTTTTGTA 0.95530712 chrIX - 214909 214892 TGTTTTTATATATTCGT 0.841209426 174
108 chrIX - 245882 245865 TTTTTTAATGTTTTGTC 0.962520612 chrIX + 245773 245790 CCTTAAAAAGGTCTCAC 0.67119524 109
109 chrIX - 247754 247737 TTTTTTAATGTTTTGTC 0.962520612 chrIX + 247631 247648 TACATTTCTCTTTTTTT 0.823299168 123
110 chrIX - 342031 342014 TTTTTTAATGTTTAGCT 0.961127508 chrIX + 341853 341870 TAAGGTCTTGTTTGTTT 0.760099392 178
111 chrIX + 357225 357242 AATTTTTATATTTTGTT 0.983369656 chrIX - 357356 357339 TATTTATAGATTTTTCT 0.83281607 131
112 chrIX - 412003 411986 AATTTTAATGTTTTGTC 0.954569521 chrIX + 411895 411912 AAGGTATAAATGTAGTT 0.778441725 108
113 chrX - 7731 7714 TATTTTTATGTTTAGGT 0.992509265 chrX + 7570 7587 CATTTTAATATCTATAT 0.829435873 161
114 chrX - 67714 67697 CTTTTTTATTTTTTTTT 0.944897067 chrX + 67593 67610 AAAATTAATAAATTTCC 0.769826733 121
115 chrX + 99498 99515 TTTTTTAATTTTTTTTT 0.947088854 chrX - 99625 99608 TTTATTTATGTTTTGTT 0.988690479 127
116 chrX + 298616 298633 TGACTCTAACTCCAGTT 0.666661983 chrX - 298725 298708 CTAATAAAACTTTTTCC 0.801772328 109
117 chrX + 337049 337066 CTTAAATAAGGTGAAGA 0.678459288 chrX - 337193 337176 CTCTTGCTTGTTTAGTT 0.819488866 144
118 chrX + 374633 374650 AATTACTACAATTTTCG 0.788091986 chrX - 374774 374757 GAAATTTACATTTATTT 0.914653679 141
119 chrX - 375586 375569 TTAGTGCAAAATATGAG 0.674815863 chrX + 375403 375420 TTCTTTAAACTTTTTGA 0.856145267 183
120 chrX - 417088 417071 TTGATGCACTATCATGA 0.704755133 chrX + 416918 416935 GATTTCTATGTTCTCGA 0.808544598 170
121 chrX + 540294 540311 GGGTAAAATGCGCTGTA 0.572247037 chrX - 540461 540444 AAAAATTACTTCCAGTT 0.755451504 167
122 chrX - 612772 612755 CACCAACAAATTGACAG 0.600434727 chrX + 612662 612679 GGATTTCATAATTGTGG 0.785437954 110
123 chrX - 654253 654236 TAAAGTTAACGTAACCA 0.631991513 chrX + 654127 654144 TCAAAACTTGATTTGTT 0.783019587 126
124 chrX + 683708 683725 CAGATAAAACAGCATAT 0.624200951 chrX - 683904 683887 GTATTGTACATTTACCT 0.826577659 196
125 chrX + 711652 711669 ATTTCTAATGCCTTGTG 0.672178619 chrX - 711852 711835 TTTGTTCACTGTTAGTT 0.872596683 200
126 chrX + 729810 729827 TAGTTGAATAATTCGTA 0.742850129 chrX - 729989 729972 CGATTAAGCGTTTTGCC 0.743397787 179
127 chrX - 736901 736884 CAATTGGAAAATTAGTG 0.76415065 chrX + 736789 736806 TGTTTGAGTGTTCAGGT 0.744514544 112
128 chrX + 744625 744642 TAATTAGCACTTCTCCC 0.637153506 chrX - 744819 744802 GTAATATAACTGTACTC 0.72903611 194
129 chrXI - 55866 55849 TTCATTAATGTTTAGTT 0.937267458 chrXI + 55685 55702 ATTTTTCATCTTTATTA 0.906973964 181
130 chrXI + 98384 98401 TTTTTTTATGTTTAGTG 0.969509169 chrXI - 98530 98513 GTACTTTATTTTTGGTT 0.851436401 146
131 chrXI - 153120 153103 AATTTTTACAATTTGTC 0.919552201 chrXI + 152995 153012 TAGTTATAAGATTATCT 0.841554901 125
132 chrXI - 196216 196199 TTTTTTCATTTTTTGTT 0.951572253 chrXI + 196020 196037 TTTGCTCATTTTTAAGT 0.795946302 196
133 chrXI - 213317 213300 AGAGTTTGTCATTACCA 0.719440701 chrXI + 213207 213224 ATTAATAATCTGTATTT 0.803703635 110
134 chrXI - 329497 329480 GGTACTGAAATTTCGGT 0.675926258 chrXI + 329388 329405 AAAATTCTTGATGTGTT 0.785345702 109
135 chrXI + 388665 388682 GGTGTTTAAGGGTAAAT 0.710373823 chrXI - 388778 388761 TTCGTTTTTAGTTAGTA 0.833546833 113
136 chrXI + 416880 416897 CGCGAGATCCATAGGCT 0.528888624 chrXI - 416990 416973 TATATTCTTGATTGGAT 0.835644767 110
137 chrXI - 447845 447828 CACATACATATTTTAAC 0.785193796 chrXI + 447678 447695 GTAATAAATATTCTCAT 0.786845724 167
138 chrXI + 516676 516693 ACTTGTTATGGTTATGT 0.80432569 chrXI - 516825 516808 CATAATTGCCTTTTCTT 0.777169896 149
139 chrXI + 581535 581552 ACTATGTATCTTGCAGT 0.639967512 chrXI - 581699 581682 TATTTTTTTAATTATGC 0.885914166 164
140 chrXI - 612054 612037 TTTGGATTCATCTAACG 0.610536381 chrXI + 611861 611878 GAGAATGACGATTCCGT 0.681607383 193
141 chrXI + 642416 642433 GGATGCGACATTTAACT 0.658787349 chrXI - 642546 642529 CGCTTATATGTTGGTAT 0.720382898 130
142 chrXII + 91467 91484 CATTTTAACGTTTAGTT 0.947368024 chrXII - 91595 91578 TCCTTTAAACTTTAGTT 0.864360818 128
143 chrXII + 156701 156718 TGATTTTACTTTTTGGA 0.897074392 chrXII - 156822 156805 TAAGATTACGTTTTTAA 0.861864859 121
144 chrXII + 231249 231266 TTTGTTTATATTTTTGT 0.950585996 chrXII - 231358 231341 GTTGTTTAGTTTTATTT 0.830642974 109
145 chrXII - 289420 289403 AAAATTAATGTTTTGCT 0.929806448 chrXII + 289325 289342 TATATCCTTCTTTATAT 0.811743224 95
146 chrXII - 373327 373310 TTTTTTTATATTTTCTC 0.944189014 chrXII + 373227 373244 TTCGATAAAGGTTTGTC 0.807458273 100
147 chrXII - 412852 412835 ATGTTTTTTGTTTTGTT 0.918453308 chrXII + 412678 412695 GTTTTGTACCTTTAGCT 0.848513235 174
148 chrXII - 450659 450642 TTTTTTTATATCTTGCT 0.878438397 chrXII + 450505 450522 CGTTTTTATGTTTATTC 0.924039943 154
149 chrXII - 459090 459073 ATTGTTTATGTTTTGTG 0.940327272 chrXII + 458995 459012 CTATTCTATGTTTTCTT 0.886167882 95
150 chrXII - 513083 513066 TTTATTTATGTTTTTGT 0.968709027 chrXII + 512958 512975 ATTATAAACATTTTATA 0.845822907 125
151 chrXII - 603109 603092 TTTTTTAATGTTTATGT 0.962915946 chrXII + 602997 603014 GTTTTTATCAGTTTCAT 0.801484796 112
152 chrXII + 659892 659909 GCTTTTTATGTTTATTT 0.92663958 chrXII - 660003 659986 AGTATTCATGTTTTACT 0.871065837 111
153 chrXII - 745115 745098 TATCTTTATGTTTTGTT 0.949064504 chrXII + 745006 745023 TCGTTCAAACTTTTGTC 0.79040136 109
154 chrXII - 794207 794190 AAAGTTTAAGTTTAGTT 0.935806549 chrXII + 794096 794113 TTTGATCATAATTATTT 0.872143422 111
155 chrXII - 888740 888723 GTTTTTTATGTTTAGAT 0.952111375 chrXII + 888618 888635 AATTTTTATAATTAATG 0.88656275 122
156 chrXII + 1007232 1007249 ATGTTTCATATTTTTAT 0.888016553 chrXII - 1007338 1007321 AAAATTTATAATTTAGT 0.886785202 106
157 chrXII + 1013789 1013806 TTTTTTTATGTTTTCTC 0.951798435 chrXII - 1013882 1013865 AAACAGTACGTATTTTT 0.715569985 93
158 chrXII - 1024156 1024139 CTTAATGATGTTTAGTT 0.887516109 chrXII + 1024017 1024034 CTAGTTTTTAATTATAT 0.838833831 139
159 chrXIII + 31766 31783 GTAGTTTATTATTAGTT 0.89054401 chrXIII - 31876 31859 CATTAAAATAATTATAT 0.824526619 110
160 chrXIII - 94390 94373 ATTAATTATATTTAGAT 0.921181496 chrXIII + 94266 94283 ATGTTAAATATTTTATT 0.857637919 124
161 chrXIII + 137321 137338 AATATTTATGTTTTGTT 0.980739388 chrXIII - 137437 137420 TTGTTATTTATTTTTGA 0.841585149 116
162 chrXIII - 184017 184000 GTTATATATGGTTAGTT 0.884678994 chrXIII + 183864 183881 ACATTAAATATTTTTGG 0.834854862 153
163 chrXIII + 263126 263143 ATTTTTTATATTTTGTG 0.953471148 chrXIII - 263313 263296 TATGTATATATTTATCT 0.900878883 187
164 chrXIII + 286846 286863 ATTTTTCTTATTTAGTT 0.921601724 chrXIII - 286946 286929 AGGATTTATGTTTTTTT 0.908582747 100
165 chrXIII + 371020 371037 AATTTTATTGTTTAGTT 0.937218464 chrXIII - 371128 371111 CACTTATATTTTTTTAT 0.851831461 108
166 chrXIII + 468237 468254 TTTTTTTATTTTTTGTT 0.977274497 chrXIII - 468357 468340 ATCATTTTTAATTAGTA 0.851483278 120
167 chrXIII - 535770 535753 TTAATTTATATTTAGTT 0.970090441 chrXIII + 535662 535679 AGTTGTTTTGTTTTTTT 0.82595884 108
168 chrXIII + 611318 611335 ATTGTTTATGTTTATGT 0.951906482 chrXIII - 611459 611442 ATTTGGCATCATTGTAT 0.685281331 141
169 chrXIII + 634521 634538 TATTTTTACTATTTGTA 0.910848762 chrXIII - 634639 634622 CAATTTTATGGTCATTT 0.857274617 118
170 chrXIII + 649362 649379 TTATTTCATATTTTGTT 0.953558055 chrXIII - 649549 649532 CTTACTAACAATTTCTC 0.76251583 187
171 chrXIII - 758417 758400 AAATTTTATGTTTTTTT 0.965835588 chrXIII + 758312 758329 ACTTAGCGCGGTTTTTT 0.674331603 105
172 chrXIII + 772677 772694 TTTTTTTACTATTACTT 0.90600905 chrXIII - 772820 772803 AATTTATACAACTATAT 0.778650456 143
173 chrXIII + 805162 805179 TATTTTTGTATTTAGTC 0.881724676 chrXIII - 805312 805295 TTTTTTTACCTTTTTCC 0.903568549 150
174 chrXIII + 815391 815408 AAATTCTATGTTTTGTT 0.925335958 chrXIII - 815493 815476 ATTTTTTTTTTTTTGGA 0.903966564 102
175 chrXIII - 897976 897959 TTTTTTTATGTTTGGTT 0.960544596 chrXIII + 897881 897898 TTATTTTATCATTTTCT 0.89758988 95
176 chrXIV - 28654 28637 TTTTTTTATTTTTAGGT 0.971445917 chrXIV + 28486 28503 AAGTTAGATAATTAGCG 0.781498458 168
177 chrXIV + 61695 61712 GTTTTTAATGTTTTGTA 0.934385921 chrXIV - 61857 61840 TTTATTTAAATTTTGCC 0.916575598 162
178 chrXIV - 89756 89739 TATTTTTAAGTTTTGTT 0.974909231 chrXIV + 89644 89661 CTACTTATAGTTTTTCT 0.805190002 112
179 chrXIV - 169748 169731 TAATTTAACGTTTTGTT 0.953532134 chrXIV + 169589 169606 TTTATATATATGTATGT 0.835743836 159
180 chrXIV - 196225 196208 TTTTTTAACTTTTAGCC 0.904522219 chrXIV + 196096 196113 TTCGTAAAAATTTTTGC 0.820044435 129
181 chrXIV - 250464 250447 AATTTTTACGGTTTTTT 0.918603933 chrXIV + 250330 250347 GATAAACATATTCTTGT 0.787486687 134
182 chrXIV - 280066 280049 ATTATTTATGTTTTTCT 0.94647878 chrXIV + 279948 279965 ATAATAATTAATTAGTT 0.843720251 118
183 chrXIV + 322003 322020 TTTGTTTACGTTTAGGC 0.937398674 chrXIV - 322198 322181 GTTATAAATATTTATAA 0.847440569 195
184 chrXIV - 412441 412424 TTTTTTTATATTTCTGC 0.869234054 chrXIV + 412299 412316 CAACTTCTACATTACAT 0.72789922 142
185 chrXIV - 449536 449519 CATATTTACATTTAGCC 0.905544669 chrXIV + 449372 449389 TAAATACACTGTTATTT 0.822061337 164
186 chrXIV + 499040 499057 TTTCTTTATGTTTAGCT 0.928956769 chrXIV - 499150 499133 TATCTCTTCTTTTTGTT 0.820455656 110
187 chrXIV - 546149 546132 TATTTTTACGTTTTGGC 0.956489817 chrXIV + 545981 545998 AACATTAGTATTTAATT 0.792422254 168
188 chrXIV - 561330 561313 TTTGTTCACATTTAGTT 0.930292374 chrXIV + 561216 561233 TTGATTTACATTCAAAC 0.797477323 114
189 chrXIV + 609536 609553 TTTTTTTATGTTTATTT 0.986916959 chrXIV - 609674 609657 TATTTATGTCTTTACTT 0.819944062 138
190 chrXIV - 635833 635816 TTTTTTTAATTTTAGTT 0.954915715 chrXIV + 635716 635733 TGTTTTTTTTTTTTGCA 0.87217818 117
191 chrXIV - 691680 691663 GTAATTAACATTTTGTT 0.910156612 chrXIV + 691559 691576 GATATTTCCCTTTTGGA 0.801789741 121
192 chrXV + 35714 35731 TATATTTATATTTAGAG 0.929297843 chrXV - 35855 35838 CATATTTATGTTTCATT 0.847487414 141
193 chrXV + 72688 72705 TTTTTTTACTTTTAGTT 0.962701666 chrXV - 72794 72777 TTTTATCACGTTTAGCA 0.883721557 106
194 chrXV - 85366 85349 TATACCTATATTTATGT 0.817468435 chrXV + 85268 85285 GCTTTTAATTTTTATTT 0.887881307 98
195 chrXV + 113895 113912 ATTGTTTATATTTTTGT 0.943227229 chrXV - 114058 114041 TAATATCATGTTTTATA 0.868893438 163
196 chrXV + 167003 167020 TTTATTTATGTTTTCGT 0.95396729 chrXV - 167143 167126 TTTAAAACTGTTTACGT 0.78001402 140
197 chrXV - 277732 277715 GTTGTTTATCTTTTGTT 0.926499065 chrXV + 277562 277579 TTATAAAAAATTTATTT 0.859561998 170
198 chrXV - 337483 337466 TCTTTTTACCTTTTGTC 0.904262836 chrXV + 337385 337402 TATTTTAGTATTTATTT 0.870845988 98
199 chrXV + 436790 436807 TATATTTATTTTTATTC 0.935122318 chrXV - 436888 436871 TTCTTTTTTCATTTATT 0.832867098 98
200 chrXV - 490060 490043 GTTGTTTTTCTTTTCTT 0.860946443 chrXV + 489890 489907 TAAGTTTATATTTTGGT 0.951016266 170
201 chrXV - 566597 566580 AAATTTTACCTTTTGAT 0.915947006 chrXV + 566499 566516 AATATTTAATATCTCTT 0.824916747 98
202 chrXV + 656701 656718 CTATTTAATGATTAGTA 0.901351813 chrXV - 656901 656884 GTTGATTTCTTTTTCTT 0.817366446 200
203 chrXV + 729795 729812 TATTTTTATATTTTGGC 0.964523057 chrXV - 729894 729877 TTCTTTCATTTTTGTAC 0.823636542 99
204 chrXV + 766689 766706 GTATTTTACGTTTTTTC 0.912718329 chrXV - 766791 766774 TATTTTAAATTTCTGTA 0.860782306 102
205 chrXV + 783386 783403 TATTTTTAACTTTTGGT 0.942451749 chrXV - 783582 783565 TCTTTTTATCTCTTCAA 0.777182413 196
206 chrXV - 874370 874353 CATTTTAATATTTGTTA 0.881539907 chrXV + 874192 874209 AAGTTTTCCGTTTAGCA 0.807156571 178
207 chrXV + 908307 908324 CTAAACTTTGTTTATGT 0.815272772 chrXV - 908439 908422 GGTTTTTTTTTTTAAGT 0.8448056 132
208 chrXV + 981507 981524 TTTTTTTATTTATATTT 0.874148828 chrXV - 981603 981586 TTTTTTCATGATTTTGT 0.924378634 96
209 chrXV + 1053687 1053704 TAATTAATTGTTTTGTT 0.896133812 chrXV - 1053797 1053780 CGATTAAATGTTTTTAT 0.856030986 110
210 chrXVI - 43150 43133 TTTGTTTATATTTTTGA 0.929263085 chrXVI + 42958 42975 TTCTTTTACCTTTAATA 0.863567037 192
211 chrXVI + 73104 73121 GTTTTTTTTGTTTTTTC 0.902693595 chrXVI - 73301 73284 TATATTTATAATTATAA 0.896514883 197
212 chrXVI + 116593 116610 TATTTTTATGTTTTGTT 0.998337845 chrXVI - 116770 116753 TAAAATTAAGTTTTGCG 0.868507637 177
213 chrXVI + 289531 289548 ATAATTAATGTTTACTT 0.925413716 chrXVI - 289675 289658 AAAGTTAATTTTTATAT 0.885623957 144
214 chrXVI + 384591 384608 TATTCTAAAATTTATGT 0.840759582 chrXVI - 384718 384701 TTTAAATATATTTAAGT 0.869580534 127
215 chrXVI + 418177 418194 TTCTTTCTTATTTACAA 0.82265266 chrXVI - 418289 418272 TATTATTTTGTTTTCTT 0.900944489 112
216 chrXVI - 456763 456746 TTTTATTATTTTTTGTT 0.945433762 chrXVI + 456626 456643 CTTATTCACAATTTCAA 0.820656345 137
217 chrXVI + 511708 511725 TATTTTTATGTTTTTTG 0.954763972 chrXVI - 511820 511803 GTGGTTATCATTTATTT 0.826572147 112
218 chrXVI + 563881 563898 AGTCTTTTATATTTAGT 0.760925944 chrXVI - 563991 563974 TCTAAATATATTCATCT 0.791939697 110
219 chrXVI + 565119 565136 TGTTTTTAATTTTTAGT 0.884153732 chrXVI - 565272 565255 TTTTTGGTTCTTTTGTT 0.822137769 153
220 chrXVI + 633925 633942 CGTTTTTATAGTTTAGT 0.858684766 chrXVI - 634064 634047 TTGTTTTATATTTAACA 0.875389458 139
221 chrXVI + 684409 684426 TTTTTTTTACTTTTTGT 0.892233188 chrXVI - 684534 684517 CATATGTTTGTTTAGCT 0.847979457 125
222 chrXVI - 695624 695607 TTTTTTTTTAATTTTCT 0.889872135 chrXVI + 695470 695487 AATTTTTATATTTGGTT 0.944984083 154
223 chrXVI + 749121 749138 AATTTTTAAGTTTAGTA 0.947297384 chrXVI - 749222 749205 ATAATTTACATTTTATT 0.907501113 101
224 chrXVI - 777098 777081 TTTATTTATATTTTGGC 0.954875691 chrXVI + 776923 776940 AATGTGTTAGTTTTTCT 0.811819984 175
225 chrXVI - 819345 819328 AATTTTTATATTTATTC 0.952049491 chrXVI + 819204 819221 TATATTATCATATAGTT 0.819972999 141
226 chrXVI - 842856 842839 TTTATTTAGATTTAGTT 0.894404608 chrXVI + 842714 842731 AATTTTAATCTTTAGTA 0.928064324 142
227 chrXVI + 880904 880921 CTCATATATATTTTATG 0.822074378 chrXVI - 881035 881018 TAACTCTAACTTTTTTA 0.800027746 131
228 chrXVI - 933170 933153 CTTATTTACGTTTAGCT 0.93305337 chrXVI + 933047 933064 ATTCAAAATATTTTGGA 0.822210839 123

Acknowledgements

We thank Etienne Schwob (IGMM, Montpellier) for providing us the orc2-1, orc5-1 and cdc6-1 strains. Dirk Remus (MSKCC, New-York), Philippe Pasero (IGH, Montpellier), Armelle Lengronne and members of both Pasero and Libri laboratories for critical reading of the manuscript and fruitful discussions. Julien Soudet and Françoise Stutz (University of Geneva, Geneva) for sharing results before publication. This work was supported by the Centre National de la Recherche Scientifique (CNRS), the Fondation pour la Recherche Medicale (FRM, programme équipes 2013), l’Agence National pour la Recherche (ANR, grant ANR-16-CE12-0022-01), the Labex Who Am I? (ANR-11-LABX-0071 and Idex ANR-11-IDEX-0005–02). TC and JG were supported by fellowships from the French Ministry of Research and the Ligue Nationale contre le Cancer (allocation GB/MA/CD/IQ – 12031), respectively.

Funding Statement

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

Contributor Information

Julien Gros, Email: julien.gros@ijm.fr.

Domenico Libri, Email: domenico.libri@ijm.fr.

Bruce Stillman, Cold Spring Harbor Laboratory, United States.

Kevin Struhl, Harvard Medical School, United States.

Funding Information

This paper was supported by the following grants:

  • Centre National de la Recherche Scientifique to Domenico Libri.

  • Fondation pour la Recherche Médicale F.R.M. programme équipes 2013 to Domenico Libri.

  • Agence Nationale de la Recherche Grant ANR-16-CE12-0022-01 to Domenico Libri.

  • Labex WhoamI? ANR-11-LABX-0071 to Domenico Libri.

  • French Ministry of Research Fellowship to Tito Candelli.

  • Ligue Contre le Cancer GB/MA/CD/IQ - 12031 to Julien Gros.

  • Labex WhoamI? ANR-11-IDEX-0005-02 to Domenico Libri.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Methodology, Writing—review and editing.

Conceptualization, Data curation, Supervision, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing.

Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing.

Additional files

Supplementary file 1. Supplementary tables 1, 2, 3.
elife-40802-supp1.xlsx (26.8KB, xlsx)
DOI: 10.7554/eLife.40802.014
Transparent reporting form
DOI: 10.7554/eLife.40802.015

Data availability

All data analyzed in this manuscript have been previously published and appropriate GEO accession codes and references have been provided.

The following previously published datasets were used:

Schaughency P, Merran J, Corden JL. 2014. Genome-wide mapping of yeast RNA polymerase II termination. NCBI Gene Expression Omnibus. GSE56435

Candelli T, Challal D, Briand J, Boulay J, Porrua O, Colin J, Libri D. 2018. CRAC of yeast RNA polymerase II in various thermosensitive strains at permissive and non-permissive temperature and anchor-away strains with the addition of rapamycin. NCBI Gene Expression Omnibus. GSE97913

Roy K, Gabunilas J, Gillespie A, Ngo D, Chanfreau GF. 2016. 3´-end sequencing of poly(A)+ RNA in wild-type Saccharomyces cerevisiae and nuclear exosome mutant strains. NCBI Gene Expression Omnibus. GSE75586

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Decision letter

Editor: Bruce Stillman1

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

Thank you for submitting your article "Pervasive transcription fine-tunes replication origin activity" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Bruce Stillman as Reviewing Editor and Kevin Struhl as the Senior Editor. The reviewers have opted to remain anonymous.

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

Summary:

This paper aims to define how transcription influences replication origin function in budding yeast. It is known that transcription through origin sequences can influence DNA replication, but it is unclear how many origins are affected. mRNA abundance, measured at steady state, is a poor indication of ongoing transcription so Candelli et al. use a newer method to map nascent RNA and RNA polymerase occupancy across the genome. Their most prominent conclusions are: (1) that replication origins function as strong transcription terminators; (2) termination sites are correlated with ACS locations; (3) most origins utilize two ACS sequences – by implication two sites for ORC loading; (4) ORC, Cdc6 or the entire pre-RC mediates transcription termination; (5) transcription through some replication origins influences origin activity.

Taken together this report provides a solid advance for our understanding of how transcription may influence origin activity, or how assembly of proteins at origins of DNA replication affect transcription. The major finding, which is convincingly supported by the data, is the demonstration that proteins assembled in an ORC- and Cdc6-dependent manner can inhibit transcriptional elongation. This result is likely to be of broad interest. The second important finding is that the level of transcription across origins may influence origin activity. Beyond these findings the paper does not elaborate a more comprehensive understanding of how transcription may influence origin function. The role of the second ACS/ORC binding site is not particularly well supported; how and why some origins are more sensitive to transcription is also not defined.

The paper is of sufficient interest and the authors are requested to respond to specific issues, some relating to individual conclusions. The following are specific issues that the reviewers have raised about the manuscript that need to be addressed before publication.

Essential revisions:

1) It is clear that transcription can terminate in the vicinity of the primary ACS, however the data showing termination near the secondary ACS is unconvincing. The data in Figure 1D, E are noisy (see point 2 below) and the small peak near the secondary ACS could be an artifact from a single over-represented site.Further investigation of the second ACS site in the paper is also not particularly convincing. Thus, the conclusions about these data supporting the model that multiple ORC proteins assemble the pre-RC are not warranted.

2) Related to point 1, the authors use the technique of Schaughency et al., 2014 for measuring RNA reads at genomic loci. The data in Schaughency et al., 2014 show mean reads of 30-60 (e.g., near Poly A sites), but the data in Figure 1 A show mean number of RNAPII reads of 2-7 near origin sequences. How significant are these reads? Is there anywhere in the genome that does not have reads of at least 2-7 (i.e., lacks RNAPII)? The low reads could be experimental background and the dip could be because a protein (ORC-Cdc6) is bound at the origin. Again, what are the mean reads near poly(A)+ sites analyzed in Figure 1B. Only a summary of the location of these reads is shown. Showing the mean Poly(A)+ reads over the origin in addition to the summary analysis would be more convincing. Figure 1D: Again, the number of reads is very low and this could be due to random noise. What is convincing about the peaks, particularly at secondary ACS sites?

3) The data in Figure 2 is interpreted to show significant roadblock of RNA polymerase II at ACS sites. However, given that the mapped signal fluctuates significantly across the regions shown, it is unclear how the authors can conclude that one specific site is a "roadblock" whereas another nearby site isn't? Specifically, Figure 2A and subsection “RNAPII pausing and transcription termination occur at ARS borders”. The light green track in Figure 2A show that in the mutant, many peaks of RNAPII pausing are observed, but the authors only point to the ACS. Why? What about all the other peaks in the track? Same for Figure 2B, Figure 2C and Figure 2D and yet the authors point out that ACSs are occupied by ORC. But ORC or the pre-RC is most likely not at the other pauses.

4) The Abstract states, " We provide evidence that quasi-symmetrical binding of the ORC complex to ARS borders is responsible for pausing/termination." This is too strong a statement since they have not shown that ORC does this. Indeed, it is shown that Cdc6 mutants also compromise termination. It could be that loaded pre-RC or the Mcm2-7 double hexamers are the terminator, not ORC. Please clarify the abstract, otherwise it will become accepted that ORC causes termination

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Pervasive Transcription Fine-tunes Replication Origin Activity" for further consideration at eLife. Your revised article has been favorably evaluated by Kevin Struhl (Senior Editor) and a Reviewing Editor.

The revised paper has been improved and the authors have addressed the questions raised by the reviewers. As such it is now appropriate for publication in eLife, with some modifications or a brief response to issues raised below. The paper does show that proteins assembled at ARS origins can contribute to termination of transcription through the origin. The problem remains in the interpretation of the results and here the authors even propose contradictory ideas. In re-reading the paper, there are some miss-statements or contradictions that could be corrected.

These are:

Introduction, the authors should reference that Steve Bell's laboratory, who performed the cited single molecule experiments, but has published subsequent research consistent with the two ORC-Cdc6 model. Thus, the paragraph about a controversy should be toned down and their reference cited in the Introduction [Warner et al. (2017)].

Introduction. The paragraph starts of by stating that "Studies have proposed that transcription might activate replication origins" and then in the second sentence Marahrens and Stillman, 1992 is cited as evidence. Marahrens and Stillman, 1992 did not propose that transcriptional activators activate replication by via transcription, but by activators likely modulating chromatin structure. Thus, this paper does not support the hypothesis by the authors. Even Stagljar et al., 1999 did not show that transcription activates an origin. These papers are not "in apparent contrast with the demonstration that strong transcription through ARSs is detrimental for their function" (Introduction). While it is true that transcription is detrimental for replication initiation, accurate citing of references is needed.

Subsection “Topological organization of replication origin factors detected by transcriptional footprinting” and later in subsection “Functional implications for pervasive transcription at ARS”. The authors argue that transcription may "play an important role" in the initiation of DNA replication by pushing the first loaded Mcm2-7 hexamer away from the ORC binding site. This is clearly not the case since initiation of DNA replication in vitro is very efficient and does not require transcription, even on chromatin templates (Kurat et al., 2017). It seems the authors are stating on one case that ARSs and their binding proteins terminate transcription and yet then state that transcription may play an important role in replication initiation. This, based on the data presented, does not seem likely (at least it has not been demonstrated). Indeed, subsection “Functional implications for pervasive transcription at ARS”, the authors state " We propose that transcription though origins might induce similar changes that are susceptible to outcompete binding of ORC and/or pre-RC formation." They cannot have it both ways.

eLife. 2018 Dec 17;7:e40802. doi: 10.7554/eLife.40802.025

Author response


Essential revisions:

1) It is clear that transcription can terminate in the vicinity of the primary ACS, however the data showing termination near the secondary ACS is unconvincing. The data in Figure 1D, E are noisy (see point 2 below) and the small peak near the secondary ACS could be an artifact from a single over-represented site. Further investigation of the second ACS site in the paper is also not particularly convincing. Thus, the conclusions about these data supporting the model that multiple ORC proteins assemble the pre-RC are not warranted.

2) Related to point 1, the authors use the technique of Schaughency et al., 2014 for measuring RNA reads at genomic loci. The data in Schaughency et al., 2014 show mean reads of 30-60 (e.g., near Poly A sites), but the data in Figure 1 A show mean number of RNAPII reads of 2-7 near origin sequences. How significant are these reads? Is there anywhere in the genome that does not have reads of at least 2-7 (i.e., lacks RNAPII)? The low reads could be experimental background and the dip could be because a protein (ORC-Cdc6) is bound at the origin. Again, what are the mean reads near poly(A)+ sites analyzed in Figure 1B. Only a summary of the location of these reads is shown. Showing the mean Poly(A)+ reads over the origin in addition to the summary analysis would be more convincing. Figure 1D: Again, the number of reads is very low and this could be due to random noise. What is convincing about the peaks, particularly at secondary ACS sites?

Essential revisions #1 and #2 are very much related and will be answered together below. For matching questions and answers we added to each question or group of related questions a letter (A, B and C) that refers to the answer.

A) On the significance of RNAPII pausing at the primary ACSs

The first concern we will discuss is the significance of the distribution of RNAPII around origins at the primary sites. As stated in the manuscript, the main aim of these analyses was to assess the impact of the low levels of pervasive transcription around origins, transcription that is generally non-annotated and often due to readthrough at canonical terminators. It is therefore expected that the average level of reads around origins be lower than the genome average of 30-60 reads, since we are sampling the lowest percentile of the distribution. Importantly, however, we did not profile the mean levels of reads but the median, which was done precisely in order to undermine the contribution of highly represented sites. With a less stringent analysis, i.e. when plotting the mean values (Author response image 1), the levels of the RNAPII reads in the region of the roadblock (around 15) are very comparable with the genome average as cited by the referee (30-60) and the drop in the signal clearly visible.

Author response image 1. RNAPII ParCLIP reads (mean values) are profiled around origins aligned on the first nucleotide of the primary ACS.

Author response image 1.

However, we believe that presenting these data could be misleading, as at least a fraction of the signal at the roadblock could be due to a very limited number of sites with high values. Indeed, some peaks are only visible using the mean (see for instance the peak at +200) and clearly due to outliers that do not represent the overall population (in this case probably a site of initiation after the origin).

Use of the median is more stringent and generally more appropriate for representing distribution that deviate from normality.

We considered that good evidence for the existence of a significant signal at the roadblock would be loss of that signal immediately after the ACS. Therefore, we compared the reads levels in the 100nt before and after the ACS for every region (Figure 1—figure supplement 2A). The distributions of these values for the 100 origins with the highest levels of surrounding transcription are now shown in Figure 1—figure supplement 2B under the form of Box Plots. It appears clearly that the median signal is higher before the ACS and drops immediately after, and that the loss of signal is highly significant according to both parametric and non-parametric tests. A strong statistical significance is observed even when all the origins are considered (data not shown).

This signal derives from the crosslinking of the nascent RNA to the polymerase, and the absence of signal (and nascent RNA) can only derive from the failure of RNAPII from actively transcribing that particular region. The drop in the RNAPII signal occurs thereforebecause of the presence of a protein complex bound at the ACS. This is not a technical artefact as the one that could be expected from ChIP datasets, in which the absence of crosslinking could be due to the steric hindrance due to another complex bound at the same location. Lastly, we would also like to stress that the poor signal around ACSs cannot be ascribed to the poor "mappability" of reads derived from such AT rich regions, because: i) similar AT-rich regions elsewhere in the genome have signals and ii) a signal at origins can be detected when incoming transcription is "forced" in transcription termination mutants (e.g. rna15-2 or NRD1::AID).

B) On the significance of RNAPII pausing at the secondary ACSs

We agree with the referees that we did not provide a strong experimental support for the existence of a second ORC complex bound to the secondary ACS. We did our best to tone down these claims and we only claim consistency with this hypothesis in the revised manuscript.

Concerning the analyses of transcription around the putative secondary ACSs, we did not intend to claim that secondary ACSs induce transcription termination and apologize if this was not sufficiently clear in the manuscript. In Results section and subsection “Topological organization of replication origin factors detected by transcriptional footprinting”of the original manuscript we had proposed that the best interpretation of the data shown in Figure 1D-E is that RNAPII pauses at the secondary ACS but that termination occurs later on, which is actually the basis of the asymmetry that we observed. We have added a few sentences to strengthen this notion in the revised version of the manuscript. We also added a probability profile of termination around secondary ACS (see below, Figure 1—figure supplement 2E) from which it is clear that statistically significant termination only occurs after the ACS.

Concerning the significance of the RNAPII occupancy peak upstream of the putative secondary ACSs, we plotted in Figure 1D the median number of reads and not the average. By definition, the peak in the median profile upstream of the secondary ACSs cannot be due to the contribution of only a single (or a few) overrepresented values as it depends on half of the values of the distribution. To further support the significance of RNAPII pausing upstream of the secondary ACSs, we compared the distributions of RNAPII levels before and after the aligned, putative secondary ACSs. Here again we found a very significant decrease in the signal (Figure 1—figure supplement 2C).

C) On the significance of termination at primary ACSs

Finally, the referees request the metaprofile of the mean level of RNA 3’-ends around ACSs. We would like to stress that the question addressed in Figures 1B,1E, Figure 4A and 4B was whether termination occurred upstream of origins, using as a proxy the presence/absence of RNA 3’ ends in the regions analyzed. Because the RNAs produced can have different stabilities, the average 3’-ends signal (as opposed by the 3’-ends count) is strongly influenced by the steady state level of the RNAs. Using this indicator for termination might introduce a major bias, as one or a few RNAs with high steady state levels would dominate the signal, which would be artefactual. This was particularly relevant at origins because many of the RNAs produced in these regions are poorly abundant, and because roadblocked transcription events tend to produce mainly non-coding and unstable RNAs (Colin et al., 2014).

Since it is the occurrence of termination events that we profile independently of the RNA steady state levels, profiling the average 3’-ends signal would therefore not be appropriate.

Nevertheless, to convince the referees that there is increased occurrence of termination events immediately preceding the average ACS, we calculated the statistical significance of the observed number of termination events at the ACS peak. To do so, we adopted the H0 hypothesis that termination occurs with equal frequency in the whole region of alignment (-500 to +500 from the ACS), and calculated a p-value for each position based on the frequency observed in the first 100nt window (position -500) and on the actual values observed at every position.

As shown in Figure 1—figure supplement 2D, the frequency of termination events is not significantly different in most of the region. However, a prominent peak of very low p-value is seen immediately upstream of the ACS, demonstrating that termination occurs with higher frequency in this region (p<10-20). We also performed the same analysis around secondary ACSs (Figure 1—figure supplement 2E), from which it is clear that termination occurs with high significance only after the ACS.

We conclude from these analyses, which have been included in the revised version of the manuscript, that transcription termination occurs immediately upstream of the primary ACSs with high statistical significance.

3) The data in Figure 2 is interpreted to show significant roadblock of RNA polymerase II at ACS sites. However, given that the mapped signal fluctuates significantly across the regions shown, it is unclear how the authors can conclude that one specific site is a "roadblock" whereas another nearby site isn't? Specifically, Figure 2A and subsection “RNAPII pausing and transcription termination occur at ARS borders”. The light green track in Figure 2A show that in the mutant, many peaks of RNAPII pausing are observed, but the authors only point to the ACS. Why? What about all the other peaks in the track? Same for Figure 2B, Figure 2C and Figure 2D and yet the authors point out that ACSs are occupied by ORC. But ORC or the pre-RC is most likely not at the other pauses.

We thank the referees for giving us the opportunity to clarify this point. The snapshots in Figure 2 are only shown with the purpose of illustrating the behavior of RNAPII around specific origins. These snapshots alone do not demonstrate that the pausing that is observed is specifically due to the presence of an origin. Indeed, many additional sites of pausing are observed within genes and sometimes in the downstream region, at a distance from origins. What is telling us that ACS sequences induce pausing is the aggregate signal (Figure 1), in which other sites of pausing are averaged out while pausing immediately preceding the ACSs remains visible. This implies that pausing occurs at the majority of origins; otherwise it would not be detected by the median. Also, note that RNAPII pausing peaks at ACSs often appear after a region of low signal, which is consistent with an accumulation of polymerases fed by low levels of upstream readthrough transcription. To better highlight this point we have modified Figure 2 by adding an inset at panel 2A.

4) The Abstract states " We provide evidence that quasi-symmetrical binding of the ORC complex to ARS borders is responsible for pausing/termination." This is too strong a statement since they have not shown that ORC does this. Indeed, it is shown that Cdc6 mutants also compromise termination. It could be that loaded pre-RC or the Mcm2-7 double hexamers are the terminator, not ORC. Please clarify the abstract, otherwise it will become accepted that ORC causes termination.

We agree, we did not show that ORC alone is sufficient for termination, only that is necessary. We modified the abstract as requested.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

The revised paper has been improved and the authors have addressed the questions raised by the reviewers. As such it is now appropriate for publication in eLife, with some modifications or a brief response to issues raised below. The paper does show that proteins assembled at ARS origins can contribute to termination of transcription through the origin. The problem remains in the interpretation of the results and here the authors even propose contradictory ideas. In re-reading the paper, there are some miss-statements or contradictions that could be corrected.

We thank the editors for re-evaluating favorably our revised manuscript. We briefly answer below to the last concerns.

These are:

Introduction, the authors should reference that Steve Bell's laboratory, who performed the cited single molecule experiments, but has published subsequent research consistent with the two ORC-Cdc6 model. Thus, the paragraph about a controversy should be toned down and their reference cited in the Introduction [Warner et al. (2017)].

This reference had been included in the original manuscript subsection “Topological organization of replication origin factors detected by transcriptional footprinting”) to discuss the possible sliding of an intermediate during helicase loading. Results presented in Warner et al. are consistent with the quasi-symmetrical model, as the authors suggest, but do not prove that ORC binds to the B2 element when sliding is prevented. We therefore cited the work as "see also", together with the Coster et al. article. We also eliminated the notion of controversy, but we believe that the single molecule studies of the Bell and Greene laboratories should still be referenced.

Introduction. The paragraph starts of by stating that "Studies have proposed that transcription might activate replication origins" and then in the second sentence Marahrens and Stillman, 1992 is cited as evidence. Marahrens and Stillman, 1992 did not propose that transcriptional activators activate replication by via transcription, but by activators likely modulating chromatin structure. Thus, this paper does not support the hypothesis by the authors. Even Stagljar et al., 1999 did not show that transcription activates an origin. These papers are not "in apparent contrast with the demonstration that strong transcription through ARSs is detrimental for their function" (Introduction). While it is true that transcription is detrimental for replication initiation, accurate citing of references is needed.

We had cited these papers for reporting that transcription activators binding is required for efficient origin firing (Introduction: "The binding of general transcription factors such as Abf1 and Rap1, or even the tethering of transcription activation domains, TBP or Mediator components was shown to be required for efficient firing of a model ARS"). Indeed, these studies do not show that transcription is induced at the studied origins, but they do not prove either that it is not. In the Stagljar et al. paper, this is actually suggested. This is why we considered this in apparent contradiction with the notion that strong transcription inactivates origins. We clarified this point and also deleted the first sentence that was associated to incorrect references. The reference to the Knott et al. study was associated to the references describing the importance of transcription factors at origins.

Subsection “Topological organization of replication origin factors detected by transcriptional footprinting” and later in subsection “Functional implications for pervasive transcription at ARS”. The authors argue that transcription may "play an important role" in the initiation of DNA replication by pushing the first loaded Mcm2-7 hexamer away from the ORC binding site. This is clearly not the case since initiation of DNA replication in vitro is very efficient and does not require transcription, even on chromatin templates (Kurat et al., 2017). It seems the authors are stating on one case that ARSs and their binding proteins terminate transcription and yet then state that transcription may play an important role in replication initiation. This, based on the data presented, does not seem likely (at least it has not been demonstrated). Indeed, subsection “Functional implications for pervasive transcription at ARS”, the authors state " We propose that transcription though origins might induce similar changes that are susceptible to outcompete binding of ORC and/or pre-RC formation." They cannot have it both ways.

Our analyses are based on the average, negative effect of pervasive transcription on replication initiation. They do not exclude that in individual cases, pushing of the DH by transcription might also favor initiation of replication (even though this is not required in vitro). This is the reason of the apparent contradiction. Nevertheless, we agree that this is only a point of discussion and that we did not address here this possibility. Therefore, we eliminated the claim that transcription might favor firing by deleting this sentence.

Lastly, we also added a missing reference to the recent Soudet et al. paper.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Schaughency P, Merran J, Corden JL. 2014. Genome-wide mapping of yeast RNA polymerase II termination. NCBI Gene Expression Omnibus. GSE56435 [DOI] [PMC free article] [PubMed]
    2. Candelli T, Challal D, Briand J, Boulay J, Porrua O, Colin J, Libri D. 2018. CRAC of yeast RNA polymerase II in various thermosensitive strains at permissive and non-permissive temperature and anchor-away strains with the addition of rapamycin. NCBI Gene Expression Omnibus. GSE97913
    3. Roy K, Gabunilas J, Gillespie A, Ngo D, Chanfreau GF. 2016. 3´-end sequencing of poly(A)+ RNA in wild-type Saccharomyces cerevisiae and nuclear exosome mutant strains. NCBI Gene Expression Omnibus. GSE75586

    Supplementary Materials

    Supplementary file 1. Supplementary tables 1, 2, 3.
    elife-40802-supp1.xlsx (26.8KB, xlsx)
    DOI: 10.7554/eLife.40802.014
    Transparent reporting form
    DOI: 10.7554/eLife.40802.015

    Data Availability Statement

    All data analyzed in this manuscript have been previously published and appropriate GEO accession codes and references have been provided.

    The following previously published datasets were used:

    Schaughency P, Merran J, Corden JL. 2014. Genome-wide mapping of yeast RNA polymerase II termination. NCBI Gene Expression Omnibus. GSE56435

    Candelli T, Challal D, Briand J, Boulay J, Porrua O, Colin J, Libri D. 2018. CRAC of yeast RNA polymerase II in various thermosensitive strains at permissive and non-permissive temperature and anchor-away strains with the addition of rapamycin. NCBI Gene Expression Omnibus. GSE97913

    Roy K, Gabunilas J, Gillespie A, Ngo D, Chanfreau GF. 2016. 3´-end sequencing of poly(A)+ RNA in wild-type Saccharomyces cerevisiae and nuclear exosome mutant strains. NCBI Gene Expression Omnibus. GSE75586


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