1. Chromosomes and Gene Expression
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Pervasive transcription fine-tunes replication origin activity

  1. Tito Candelli
  2. Julien Gros  Is a corresponding author
  3. Domenico Libri  Is a corresponding author
  1. Institut Jacques Monod, CNRS UMR 7592, Université Paris Diderot, Sorbonne Paris Cité, France
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Cite this article as: eLife 2018;7:e40802 doi: 10.7554/eLife.40802

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.

https://doi.org/10.7554/eLife.40802.001

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 with 2 supplements see all
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).

https://doi.org/10.7554/eLife.40802.002

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.

RNAPII occupancy at individual ARS detected by CRAC analysis.

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).

https://doi.org/10.7554/eLife.40802.005

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 with 1 supplement see all
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.

https://doi.org/10.7554/eLife.40802.006

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).

Role of ORC in the roadblock of RNAPII at origins.

(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.

https://doi.org/10.7554/eLife.40802.010

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).

Local pervasive transcription impacts origin competence and efficiency.

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.

https://doi.org/10.7554/eLife.40802.011

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).

Correlations between transcription and origin function.

(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.

https://doi.org/10.7554/eLife.40802.012

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).

Asymmetry of origin sensitivity to pervasive transcription.

(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).

https://doi.org/10.7554/eLife.40802.013

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. 
https://doi.org/10.7554/eLife.40802.008
Yeast strainsNameGenotypeOrigin
 DLY671W303-1a trp1∆Libri laboratory (BMA64)
 DLY2923W303-1a ORC2 ORC5 CDC6Gift from the Pasero laboratory (PP2583)
 DLY2685As W303-1a, ORC2 ORC5 cdc6-1Gift from the Schwob laboratory (E589)
 DLY2687As W303-1a, orc2-1 ORC5 CDC6Gift from the Schwob laboratory (E1507)
 DLY2688As W303-1a, ORC2 orc5-1 CDC6Gift from the Schwob laboratory (E4649)
OligonucleotidesNameSequencePurpose
 DL3370CATCCACAATTACAACCTATACATATTCTAGCTGCCTTCATTGAAACGGCGACGCCCGACGCCGTAATAACAmplification of ARS305 from genomic DNA. Fw primer bearing 48 bp of homology with DL1702.
 DL3371gaatctttcttcgaaatcacctttgtatttagcacctgcggttaatgcggATATATCAGAAACATACATATGAmplification of ARS305 from genomic DNA. Rev primer bearing 50 bp of homology with DL1666.
 DL3446CATCCACAATTACAACCTATACATATTCTAGCTGCCTTCATTGAAACGATATATCAGAAA
CATACATATG
Insertion of ARS305 in reverse orientation
(compare with primer pair DL3370/DL3371). Rev primer bearing homology with DL1702.
 DL3447gaatctttcttcgaaatcacctttgtatttagcacctgcggttaatgcggGCG
ACGCCCGACGCCGTAATAAC
Insertion of ARS305 in reverse orientation (compare with primer pair DL3370/DL3371). Fwd primer bearing homology with DL1666.
 DL3581gaatctttcttcgaaatcacctttgtatttagcacctgcggttaatgcggGTTTCATGTACTGTCCGGTGTGATTInsertion of shortened ARS305, fwd (cf. DL3447). Primes 32 bp downstream B4 element, removing 291 bp of ARS305 “full-length “3’ end.
 DL3583CATCCACAATTACAACCTATACATATTCTAGCTGCCTTCATTGAAACGGAGTATTTGATCCTTTTTTTTATTGTGInsertion of shortened ARS305, rev (cf. DL3446). Primes 34 bp upstream ARS305 ACS, removing 83 bp of ARS305
“full-length “5’ end.
 DL3376TTATTCCTCGAGGACTTTGTAGTTCTTAAAGCInsertion of linker substitution Lin102 (B4-) in ARS305 by two stages overlapping PCRs.
Fw primer,
pair with DL3371.
 DL3377CTACAAAGTCCTCGAGGAATAATAAATCACACCGGACInsertion of linker substitution Lin102 (B4-) in ARS305 by two stages overlapping PCRs. Rev primer, pair with DL3370.
 DL3378GGGACCTCGAGGAATACATAACAAAACATATAAAAACCInsertion of linker substitution Lin22 (B1-) in ARS305 by two stages overlapping PCRs. Fw primer, pair with DL3371.
 DL3379GTTATGTATTCCTCGAGGTCCCTTTAATTTTAGGATATGInsertion of linker substitution Lin22 (B1-) in ARS305 by two stages overlapping PCRs. Rev primer, pair with DL3370.
 DL3380CATAACCCTCGAGGTAAAAACCAACACAATAAAAAAAAGGInsertion of linker substitution Lin4 (A-) in ARS305 by two stages overlapping PCRs. Fw primer, pair with DL3371.
 DL3381GGTTTTTACCTCGAGGGTTATGTATTGTTTATTTTCCInsertion of linker substitution Lin4 (A-) in ARS305 by two stages overlapping PCRs. Rev primer, pair with DL3370.
 DL1359CCTTATACATTAGGTCCTTTHSP104 Northern PCR probe, fwd. Primes about 100nt upstream HSP104 ATG in PTE
TOFF-HSP104 plasmid serie
 DL1360ATCCCCCGAATTGATCCGGHSP104 Northern PCR probe, rev. Primes upstream BamHI site in PTETOFF-HSP104 plasmid serie
 DL377ATGTTCCCAGGTATTGCCGAACT1 Northern PCR probe/RT qPCR amplicon, fwd.
Oligonucleotides DL378acacttgtggtgaacgatagACT1 Northern PCR probe/RT qPCR amplicon, rev.
 DL2627ATTCAAAAGCGAACACCGAATTGACCATGAGGAGACGGTCTGGTTTATsnR14 Northern oligo probe
 DL3763CTGGTTGAAACAAATCAGTGCCGGTAACARS404 qRT-PCR,
amplicon downstream ARS404 ACS. 5’ primes 202 bp
after SSB1 STOP, pair with DL3764.
 DL3764GACTTTTTCTTAACTAGAATGCTGGAGTAGAAATACGCARS404 qRT-PCR, amplicon downstream ARS404 ACS. 5’ primes 288 bp after SSB1 STOP, pair with DL3763.
 DL3767CTTTTTAAACTAATATACACATTTTAGCAGATGCGARS404 qRT-PCR,
amplicon upstream ARS404 ACS. 5’ primes 23 bp
after HO STOP, pair with DL3768.
 DL3768GATGCTGTCCGCGGGCCTCATAAGARS404 qRT-PCR, amplicon upstream ARS404 ACS. 5’ primes60 bp before HO STOP, pair with DL3767.
 DL3823GGCACTATGCTTTTTAAAATTTTGTTTATACTCAATTTCGARS1004 qRT-PCR, amplicon upstream
ARS1004 ACS. 5’ anneals80 bp after REE1 STOP
 DL3824GCCCAGTATTTTGTTAACTGTATGGATTGTACTAGARS1004 qRT-PCR, amplicon upstream ARS1004 ACS. 5’ anneals170 bp after REE1 STOP
 DL3827GTGTTTTAAGATAAAGTGACGAAAGTTAGGGTGARS1004 qRT-PCR, amplicon downstream ARS1004 ACS. 5’ anneals 228 bp after REE1 STOP
 DL3828CATCATAAGTACTAATTACCACGAATTCAATAATTAGTAAATACARS1004 qRT-PCR, amplicon downstream ARS1004 ACS. 5’ anneals 318 bp after REE1 STOP
 DL187ACACActaaattaccggatcaattcgggggatccATGAACGACCAAACGCAATTCloning of HSP104 in pCM188, fwd.
 DL189catgatgcggccctcctgcagggccctagcggccgcTTAATCTAGGTCATCATCAACloning of HSP104 in pCM188, rev.
 DL1124taatgaggacagtatggaaattgatgatgacctagattaaTTTAATATAGTGTGATTTTTCloning of HSP104 3' UTR in pCM188-HSP104, fwd.
 DL1125ATTACATGATGCGGCCCTCCTGCAGGGCCCTAGCGGCCGCTTTAACATGATTTGGTAGTCCloning of HSP104 3' UTR in pCM188-HSP104, fwd.
 DL4026CGTTTATTCCCTTGTTTGATTCAGAAGCAGARS1 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 DL4027GCTAGCAAGAATCGGCTCGGGGCTCTCTTGCCTTCCAACARS1 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.
 DL4029CAAGAGAGCCCCGAGCCGATTCTTGCTAGCCTTTTCTCARS1 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.
 DL4030GATTACGAGGATACGGAGAGAGGARS1 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.
 DL4032GTGAAGGAGCATGTTCGGCACACARS1 KO in pDL214 by overlapping PCRs, Rev sequencing primer. Anneals 1157 bp after pDL214’s URA3 STOP.
 DL4000TTCAAATGTACAGTAACTATCAAAACCATT
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.
 DL4001TATATATAATTAATAAAACTAATGGAATTTGTTTAATTGAACTTGACACCCGAGCGGACCAATCCGCGTGTGTTTTATACReverse 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.
 DL4061ATTATTAGAATACGGGTACTACReverse ARS1206 orientation in pDL214, extension of homology region downstream ARS1206, Fwd. Primes 134 bp upstream CYC1 terminator. Pair with M13 reverse (DL2163).
 DL2163caggaaacagctatgacReverse ARS1206 orientation in pDL214, extension of homology region downstream ARS1206, Rev.
 DL4066GCTCGGGTGTCAAGTTCAATTAAACReverse ARS1206 orientation in pDL214, extension of homology region
upstream ARS1206, Rev. Primes 106 bp downstream HSP104 STOP. Pair with DL530.
 DL530GTTGAATTTAACTCAAGAGGCReverse ARS1206 orientation in pDL214, extension of homology region upstream ARS1206, Fwd. Anneals 2409–2429 in
HSP104.
Oligonucleotides DL3986gctgaagaatgtctggaagttctaccReverse ARS1206 orientation in pDL214, Fwd sequencing primer annealing 108 bp before HSP104 STOP.
 DL163acattttcatcacgagatttacccRNase H cleavage assay. HSP104, antisense, position 2606–2583
from HSP104 ATG.
 DL164ttatcgtcatcacctaacgtgtcagcccctatagtagcttcgtgatttggtagaacttccRNase H cleavage assay. HSP104 Northern oligonucleotide probe, antisense, position 2718–2631 from HSP104 ATG.
 DL473TTTTTTTTTTT
TTTTTTTTT
RNase H cleavage assay. Poly(dT) oligonucleotide
 DL3991GATTTGACGTCCAGTGGACTTTTTTGTCCRNase H cleavage assay, testHSP104 readthrough on pDL905, antisense, position 2923–2895 fromHSP104 ATG
 DL3994GGAAGTAATAAGTGAAGGTTAAATCTGGACCRNase H cleavage assay, test HSP104 readthrough on pDL907, antisense, position 2909–2879 from HSP104 ATG
 PlasmidsNameFeaturesReference
 pDL454PTETOFF-HSP104::Reb1BS::HSP104, PGAL1-
CUP1, 2µ, URA3
Colin et al. Colin et al., 2014
 pDL551PTETOFF-HSP104::
Reb1BS(−)::HSP104, PGAL1-
CUP1, 2µ, URA3
 pDL790PTETOFF-HSP104::ARS305_548 bp::HSP104
, PGAL1-CUP1, 2µ, URA3
This study
 pDL793PTETOFF-HSP104::ARS305(A−)_548 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL909PTETOFF-HSP104::
ARS305_175 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL910PTETOFF-HSP104::
ARS305(A−)_175 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL911PTETOFF-HSP104::ARS305(B1−)_175 bp::HSP104, PGAL1-CUP1, 2µ, URA3
 pDL912PTETOFF-HSP104
::ARS305(B4−)_175 bp::HSP104
, PGAL1-CUP1, 2µ, URA3
 pDL913PTETOFF-HSP104
::ARS305(B1−B4−)_175 bp::HSP104,
PGAL1-CUP1, 2µ, URA3
 pDL30PTETOFF-HSP104,
ARS1, CEN4, URA3
Libri laboratory
 pDL214PTETOFF-HSP104,
ARS1206, ARS1, CEN4, URA3
 pDL905PTETOFF-HSP104, ARS1206, ∆ars1, CEN4, URA3This study
 pDL907PTETOFF-HSP104, 6021sra, ∆ars1, CEN4, URA3
Table 2
Coordinates of primary and secondary ACSs used in this study. 
https://doi.org/10.7554/eLife.40802.009
Proposed primary ACS (Nieduszynski et al., 2006)Putative secondary ACS (this study)
IDChromosomeStrandStartEndMatchScoreChromosomeStrandStartEndMatchScoreProtected length (nt)
1chrI+3100131018TATTTTTAAGTTTTGTT0.974909231chrI-3119031173GTATAATATTTTTAGTT0.87301127189
2chrI-7043170414ATTTTTTATGTTTAGAA0.949548431chrI+7025170268ACTATCAATGTTTTATC0.818662772180
3chrI-124526124509ATTTTTTATATTTAAGT0.939615332chrI+124412124429GTTTTCTCTATTTAAAT0.76163459114
4chrI+159951159968TTTATTTATATTTAGTG0.951660057chrI-160108160091ATATAGCATAATTACTT0.796339361157
5chrI+176234176251TCTTTTTATGTTTTCTT0.936946746chrI-176333176316TAAATATGTGTTTATTA0.81662182199
6chrII+2898429001TCACTCTATCTTTTTTA0.78989004chrII-2909229075TATAACAAAAATTGGTC0.767973746108
7chrII-6337663359TTTTTTTAATTTTTGTC0.934538928chrII+6325663273TAAAAATTTGTTTTCTT0.843331211120
8chrII-170228170211CCAGTGAACGCTTAAAA0.646819795chrII+170126170143CTTTGCTACGATTTCTT0.763191826102
9chrII-198382198365AACTTCAAAGTACATTG0.673812699chrII+198228198245ATTATAGACTTTCATTC0.772245255154
10chrII-237832237815AAGGTACATAGCGATTT0.628400298chrII+237685237702TTATTAAAGGGTTTGGA0.774836934147
11chrII-255040255023AGGTAGAAGAGTTACGG0.617416402chrII+254892254909TGATTTTTCATTTTACT0.841326164148
12chrII+326149326166CTATCGAAACTTTTGTT0.748562634chrII-326273326256CTTTTAATAGTTTAGGT0.860235002124
13chrII-408006407989TAGGAAAATATATAGAG0.708025047chrII+407871407888ATATTTAAAGAGTTGAA0.77590664135
14chrII-417974417957TGTAGAAATGTCTAGCG0.67916971chrII+417844417861AAATTTAATATTTTTGA0.912902242130
15chrII-486855486838GAAGTCCTCTTCTTCGC0.639951668chrII+486735486752ATTAATTATGTTTTTCC0.89533109120
16chrII+622713622730TATATAGAAAGTTGCTT0.760778109chrII-622866622849TTTTTGTACGTTTTTTT0.907808059153
17chrII+704289704306CTACCAAAAGTGTACCG0.581803503chrII-704455704438AATGTTTTTTTTTTTTT0.897759223166
18chrII-741746741729CGAAAAGATATGTGGGA0.64946824chrII+741628741645TAAGATCAAGTTTGGTA0.824844021118
19chrII+757441757458TAAATCTAAGATAGCTG0.682422088chrII-757613757596GTTATATAAGTATACGT0.779064174172
20chrII+792164792181TATTTCATGGTTTTTAG0.736834685chrII-792287792270CTTTTTAAAATTCATTG0.834945362123
21chrIII+1125411271TTTTTTTATGTTTTTTT0.985847127chrIII-1140011383GTTGAATTTGGTTAGAT0.782826917146
22chrIII-3959139574TTTTTATATGTTTTGTT0.963617028chrIII+3947639493TTATTTTTTATTTACTT0.914777509115
23chrIII+7451874535TGTATTTATATTTATTT0.944792175chrIII-7468274665GAGATCTTAATTTATCT0.770457519164
24chrIII-108972108955TTTATTTATGTTTTCTT0.960865701chrIII+108832108849TAGAAATATGTTGAGTT0.795588546140
25chrIII+132036132053TTTGTACATTGTTTATA0.792015393chrIII-132155132138CTTTTATATGTTTAAAT0.885104513119
26chrIII+166650166667GTTTTATTCCATTATTT0.81768767chrIII-166768166751ATTATTTACATTTACGA0.903103359118
27chrIII+194302194319CTACTGCAATTTTTTAC0.730959168chrIII-194402194385TGTAATTACATTTCTTA0.79211775100
28chrIII-197559197542AATATTCATGTTTAGTA0.934784063chrIII+197415197432ATCTTAAACCTTTTTAG0.797219912144
29chrIII+224856224873TCAGTTTTTTTTATGTT0.78153895chrIII-224956224939TTTATTTTTGTTTGTTT0.899494022100
30chrIII-273030273013TTTTTTCAAATTTAGTT0.94325972chrIII+272904272921TTTATTCAAAATTTTTC0.870692365126
31chrIII+292584292601TATATATATATTTATTT0.933162383chrIII-292695292678TATAATAACATTTTTTA0.881496782111
32chrIII+315872315889TGTATATAAATTAAGTG0.777607317chrIII-315979315962CATTTTAATATCTATAT0.829435873107
33chrIV-1568115664ATTTTTTACGTTTTCTC0.928797007chrIV+1552515542TAAATTCTAAGTTATTC0.806599978156
34chrIV-8612386106GATTTTTATGTTTGGGC0.907628171chrIV+8599686013CTTTATAAAGATTTTAT0.843543061127
35chrIV+123677123694TGTTTTCACTTTGTGTT0.820618605chrIV-123793123776TTAATATATATTTAGTT0.9347773116
36chrIV-212592212575TTTTTTTATATTTTGTT0.991320747chrIV+212441212458TTTTTTTTTTTTTTTTT0.926463613151
37chrIV+253839253856ATTTTTTATAGTTTTGC0.901024131chrIV-253948253931TAATTTTATCTTTAGAT0.940018266109
38chrIV-329742329725GATTTTTATTTTTTTGT0.930581986chrIV+329601329618TATTATTATTATTATTC0.884653435141
39chrIV+408134408151TTATATTATATTTAGCG0.896228674chrIV-408291408274TTATTACATATTTTTGT0.898263462157
40chrIV-484039484022TTTTTTTATATTTATGT0.972409126chrIV+483896483913TTGTTTGTTCATTTCTT0.792451309143
41chrIV-505522505505TTTTTTTATATTTTTGC0.95203234chrIV+505345505362CCTTTTCACGTTTTTGC0.864843823177
42chrIV-555401555384AAAGTTTATGTTTTTTC0.925775335chrIV+555290555307ATAAATGTTGTTTTTTT0.835510567111
43chrIV-567681567664TTTTTTTATGTTTTGAG0.946669447chrIV+567572567589ACTTTTAATTTTTTTTT0.905571442109
44chrIV-640068640051TTTTTTAAAGTTTTGGT0.951500543chrIV+639918639935CTATAATATATTTATTC0.86149187150
45chrIV+702928702945AAAATAATTAATGTTTT0.737939741chrIV-703030703013TGATTTAAAATTCTGTA0.83908476102
46chrIV+748452748469AAATTAATTGATTAATT0.822458971chrIV-748585748568TTTTTTAATATTTAATA0.915446997133
47chrIV-753339753322TTTTTTTACATTTTGCT0.953908195chrIV+753221753238AAACTTATTTTTTAAGC0.78950557118
48chrIV+806097806114CTCTTCCAAATTTTTAA0.777746734chrIV-806256806239TCATATCCTGTTTTAAA0.722790604159
49chrIV+913859913876TTTTTTTATTTTTATAT0.943491396chrIV-913957913940ACAATTTTTGTTTATTT0.88537156798
50chrIV+921736921753TCTTTAATCGATTTTAA0.773941597chrIV-921840921823TTTGTTTATTTTTTTTT0.943438157104
51chrIV-10168541016837TTTGTTTACGTTTTGGA0.934312886chrIV+10166821016699AGAATTCATTTTAATCT0.772819262172
52chrIV+10578861057903TTCTTTTATTATTTTTT0.899933367chrIV-10580171058000AAAGTGAATTTTTTTGT0.837029199131
53chrIV-11101391110122TTTTTTTATATTTTTAT0.956467815chrIV+11099601109977GAATTCTTCATTTAGAT0.824896005179
54chrIV-11594521159435CTTTTCTAAGCTTTGAA0.769370807chrIV+11592861159303ATAATTAATTTTTTTGA0.889208627166
55chrIV-11661661166149TCGGAATATTATTTCTT0.763125812chrIV+11660641166081CTTAATAAATTTTTGTA0.854045557102
56chrIV+12409201240937CTTCTTGAAATTTGATT0.771311686chrIV-12410961241079TTTATAAAAATTTATAT0.871453601176
57chrIV+12762711276288TTCGTTTTCTTTTTCTC0.82062871chrIV-12764051276388CAAATATATATTGATCA0.767679431134
58chrIV-13027631302746TATATATTTAGTTAATG0.795859241chrIV+13026161302633GAGTTTTACGTATTCTT0.80224896147
59chrIV+14043231404340TAAAATCATTTTCTTTT0.829710275chrIV-14045111404494AGGATTCTTTATTACGT0.774058834188
60chrIV+14618901461907GAGTAACTTCTTGTCGG0.624436491chrIV-14620381462021AACATTAATTGTTGTTA0.790149896148
61chrIV-14870981487081TTAAATTTAGTTTTTTT0.870549799chrIV+14869651486982CCAATACATGATTGGAT0.773138313133
62chrV-5946959452AATATTTACATTTTGAT0.935717414chrV+5936359380TTTTTTTTTCTTTTTTT0.922560213106
63chrV+9405594072CAAGTTTATATTTTGTT0.938620288chrV-9417394156TATGTTTAATTATATTG0.79888376118
64chrV-145714145697CAGTTTTTTGTTTAGTT0.906995194chrV+145608145625TTATATAATATTTTAGG0.854409653106
65chrV-173808173791TAATTTTATATTTTGCC0.93759113chrV+173704173721TATTTATACTTTTACGG0.861582181104
66chrV+212455212472TAAAATTATGTTTAGGT0.938368393chrV-212555212538CGTATACTTTTTTTGTG0.794230687100
67chrV+287567287584TTTATTTATGTTTTGTT0.988690479chrV-287761287744CTTTGTTATCTTGTGAA0.729422588194
68chrV+353586353603AATATTTACTTTTTGGT0.936542643chrV-353774353757TTGAATTATGCTTATGT0.812386986188
69chrV-406906406889TTTTTTTATATATAGTC0.881971164chrV+406734406751GTAATTTATGATTAATC0.864888268172
70chrV-439105439088ATTTTTTAAGTTTTGCG0.915882066chrV+438997439014GGTATTCTTCTTTTTCT0.814453982108
71chrV+549589549606TATTATTAATATCTTGT0.818517794chrV-549686549669TAATTTAATATTTTTTT0.94848233297
72chrVI-167738167721TATATTTATATTTTCGT0.945765544chrVI+167551167568AATATTTAAATATAAGT0.814242246187
73chrVI+199397199414TTATTTCGAGCTTTGTC0.737504399chrVI-199507199490ATCCATAATATTTACCT0.801830214110
74chrVI+216470216487CATTTCTATTTTTTTTT0.890722071chrVI-216600216583TAATGTGATGGTTAGTT0.802062704130
75chrVI-256383256366TTTATGTTTTTTCCGGA0.701845209chrVI+256263256280AAAAATTCCGATCTTGT0.72753389120
76chrVII-6445864441ATTTTTAATATTTTGTT0.966859378chrVII+6435764374TATTGTTATATTTAGTT0.901272249101
77chrVII+112124112141ATTTTATACGTTTATGT0.921703978chrVII-112271112254ATAGTTTTTTTTTATGC0.861155565147
78chrVII+163235163252TCATTTTATAATTTGTT0.916233817chrVII-163378163361GTAATATATGATTAGAA0.844307348143
79chrVII+203971203988ATTTTTTATATTTATTA0.950625858chrVII-204165204148CATTTTAAACTCTATAT0.78805761194
80chrVII+286003286020TTTATTTACTTTTAGTC0.933155022chrVII-286153286136CTAGTAATCTTTCAGTC0.747097252150
81chrVII-352863352846TTTAATTACGTTTAGTT0.942276914chrVII+352758352775TACTTTTATGATTCATT0.812763403105
82chrVII-388846388829TTTATTTAACTTTTGTT0.939702794chrVII+388738388755TTAGTTCTCATTTATAA0.82432824108
83chrVII-421280421263ATAAATTATTGTTTAGT0.826708937chrVII+421176421193CTATTTCAAATTTGTTT0.859366438104
84chrVII-485110485093TTTATTTATGTTTTGCC0.947613634chrVII+484978484995AATTATCAAGTTTTTCT0.875154553132
85chrVII-508907508890CATTTTAATGTTTGGTT0.923555282chrVII+508801508818ATCTTTTATCTTTTATC0.872797056106
86chrVII-568660568643AGTATTTATATTTAGCC0.909439604chrVII+568509568526GTCATTCATGATTTATT0.834093344151
87chrVII+574700574717AGTATTTATGTTTTGTC0.937749085chrVII-574854574837TATACTCATATTTTGGC0.838055118154
88chrVII-660000659983ATATTTTATGTTTACTT0.952756007chrVII+659904659921TTGTTTTTTTATTGTTT0.82381995196
89chrVII+715314715331TTTGTTTATATTTTGTT0.970567449chrVII-715431715414AATCTTTAACTTGTGAT0.779912848117
90chrVII+778013778030CTTTTTTACCTTTTGTT0.938434047chrVII-778193778176AGTGTTTATATTTATTT0.926919799180
91chrVII-834664834647TTGTATATAGTTTAGTT0.854509956chrVII+834549834566GGTTTTTAACTTTTCCC0.830646453115
92chrVII+888412888429TATTTTAATATTTTGTT0.973625821chrVII-888567888550TTTATATATATATATTC0.823335292155
93chrVII-977904977887TTTTTTAATTTTTTTAT0.925318963chrVII+977810977827TTTTTTTAATGATTTTT0.80600094294
94chrVII+999468999485CTTTTTTACTTTTTGGG0.904948204chrVII-999575999558TATTTTTTTTTTTTTTT0.925871289107
95chrVIII-77557738TATTTTTATATTTAGGT0.984899843chrVIII+76187635CTTGTTTATTATTATTA0.875022851137
96chrVIII+6430264319TAATTTTAATTTTAGTT0.942262943chrVIII-6443464417ATTCTTTATATTTATTT0.922675429132
97chrVIII-133538133521TATTTTAACATTTAGTT0.959052991chrVIII+133406133423TTCTTTTATGTGTATGC0.834208883132
98chrVIII+168597168614TTGTGTCATATTTAGAC0.799695233chrVIII-168793168776TATATATATATATACGT0.820409776196
99chrVIII+245788245805CTATTTTATGATTAGTT0.939777326chrVIII-245940245923CAATTCCAAATTTAGGC0.831524522152
100chrVIII-392260392243TTTTTTCTTGAGTACTT0.788764838chrVIII+392088392105ATAATTTACATTAATAT0.821200767172
101chrVIII-447794447777TATGTTTATGTTTTGTG0.947093715chrVIII+447598447615TTGCTTAATATTTTGCA0.846461752196
102chrVIII-501949501932CGTTTATACATTTTGTT0.896794884chrVIII+501752501769ATATTTTACGGTTCTTT0.824337524197
103chrVIII+556140556157AATTTTTACGTTTAGGT0.969507836chrVIII-556301556284CATTTTAATATCTATAT0.829435873161
104chrIX-105966105949ATTATTCATGTTTTCTT0.92780469chrIX+105812105829AATAATAATAATAATGG0.754881026154
105chrIX-136290136273GCAGTTTATGTTTTGTT0.905839044chrIX+136160136177GATATCTATATTTTATA0.840946348130
106chrIX+175173175190ATGTTTTATGTTTTGTC0.936874196chrIX-175339175322CAATTTCAAATTTAAAA0.82970169166
107chrIX+214735214752TTAATTTATGTTTTGTA0.95530712chrIX-214909214892TGTTTTTATATATTCGT0.841209426174
108chrIX-245882245865TTTTTTAATGTTTTGTC0.962520612chrIX+245773245790CCTTAAAAAGGTCTCAC0.67119524109
109chrIX-247754247737TTTTTTAATGTTTTGTC0.962520612chrIX+247631247648TACATTTCTCTTTTTTT0.823299168123
110chrIX-342031342014TTTTTTAATGTTTAGCT0.961127508chrIX+341853341870TAAGGTCTTGTTTGTTT0.760099392178
111chrIX+357225357242AATTTTTATATTTTGTT0.983369656chrIX-357356357339TATTTATAGATTTTTCT0.83281607131
112chrIX-412003411986AATTTTAATGTTTTGTC0.954569521chrIX+411895411912AAGGTATAAATGTAGTT0.778441725108
113chrX-77317714TATTTTTATGTTTAGGT0.992509265chrX+75707587CATTTTAATATCTATAT0.829435873161
114chrX-6771467697CTTTTTTATTTTTTTTT0.944897067chrX+6759367610AAAATTAATAAATTTCC0.769826733121
115chrX+9949899515TTTTTTAATTTTTTTTT0.947088854chrX-9962599608TTTATTTATGTTTTGTT0.988690479127
116chrX+298616298633TGACTCTAACTCCAGTT0.666661983chrX-298725298708CTAATAAAACTTTTTCC0.801772328109
117chrX+337049337066CTTAAATAAGGTGAAGA0.678459288chrX-337193337176CTCTTGCTTGTTTAGTT0.819488866144
118chrX+374633374650AATTACTACAATTTTCG0.788091986chrX-374774374757GAAATTTACATTTATTT0.914653679141
119chrX-375586375569TTAGTGCAAAATATGAG0.674815863chrX+375403375420TTCTTTAAACTTTTTGA0.856145267183
120chrX-417088417071TTGATGCACTATCATGA0.704755133chrX+416918416935GATTTCTATGTTCTCGA0.808544598170
121chrX+540294540311GGGTAAAATGCGCTGTA0.572247037chrX-540461540444AAAAATTACTTCCAGTT0.755451504167
122chrX-612772612755CACCAACAAATTGACAG0.600434727chrX+612662612679GGATTTCATAATTGTGG0.785437954110
123chrX-654253654236TAAAGTTAACGTAACCA0.631991513chrX+654127654144TCAAAACTTGATTTGTT0.783019587126
124chrX+683708683725CAGATAAAACAGCATAT0.624200951chrX-683904683887GTATTGTACATTTACCT0.826577659196
125chrX+711652711669ATTTCTAATGCCTTGTG0.672178619chrX-711852711835TTTGTTCACTGTTAGTT0.872596683200
126chrX+729810729827TAGTTGAATAATTCGTA0.742850129chrX-729989729972CGATTAAGCGTTTTGCC0.743397787179
127chrX-736901736884CAATTGGAAAATTAGTG0.76415065chrX+736789736806TGTTTGAGTGTTCAGGT0.744514544112
128chrX+744625744642TAATTAGCACTTCTCCC0.637153506chrX-744819744802GTAATATAACTGTACTC0.72903611194
129chrXI-5586655849TTCATTAATGTTTAGTT0.937267458chrXI+5568555702ATTTTTCATCTTTATTA0.906973964181
130chrXI+9838498401TTTTTTTATGTTTAGTG0.969509169chrXI-9853098513GTACTTTATTTTTGGTT0.851436401146
131chrXI-153120153103AATTTTTACAATTTGTC0.919552201chrXI+152995153012TAGTTATAAGATTATCT0.841554901125
132chrXI-196216196199TTTTTTCATTTTTTGTT0.951572253chrXI+196020196037TTTGCTCATTTTTAAGT0.795946302196
133chrXI-213317213300AGAGTTTGTCATTACCA0.719440701chrXI+213207213224ATTAATAATCTGTATTT0.803703635110
134chrXI-329497329480GGTACTGAAATTTCGGT0.675926258chrXI+329388329405AAAATTCTTGATGTGTT0.785345702109
135chrXI+388665388682GGTGTTTAAGGGTAAAT0.710373823chrXI-388778388761TTCGTTTTTAGTTAGTA0.833546833113
136chrXI+416880416897CGCGAGATCCATAGGCT0.528888624chrXI-416990416973TATATTCTTGATTGGAT0.835644767110
137chrXI-447845447828CACATACATATTTTAAC0.785193796chrXI+447678447695GTAATAAATATTCTCAT0.786845724167
138chrXI+516676516693ACTTGTTATGGTTATGT0.80432569chrXI-516825516808CATAATTGCCTTTTCTT0.777169896149
139chrXI+581535581552ACTATGTATCTTGCAGT0.639967512chrXI-581699581682TATTTTTTTAATTATGC0.885914166164
140chrXI-612054612037TTTGGATTCATCTAACG0.610536381chrXI+611861611878GAGAATGACGATTCCGT0.681607383193
141chrXI+642416642433GGATGCGACATTTAACT0.658787349chrXI-642546642529CGCTTATATGTTGGTAT0.720382898130
142chrXII+9146791484CATTTTAACGTTTAGTT0.947368024chrXII-9159591578TCCTTTAAACTTTAGTT0.864360818128
143chrXII+156701156718TGATTTTACTTTTTGGA0.897074392chrXII-156822156805TAAGATTACGTTTTTAA0.861864859121
144chrXII+231249231266TTTGTTTATATTTTTGT0.950585996chrXII-231358231341GTTGTTTAGTTTTATTT0.830642974109
145chrXII-289420289403AAAATTAATGTTTTGCT0.929806448chrXII+289325289342TATATCCTTCTTTATAT0.81174322495
146chrXII-373327373310TTTTTTTATATTTTCTC0.944189014chrXII+373227373244TTCGATAAAGGTTTGTC0.807458273100
147chrXII-412852412835ATGTTTTTTGTTTTGTT0.918453308chrXII+412678412695GTTTTGTACCTTTAGCT0.848513235174
148chrXII-450659450642TTTTTTTATATCTTGCT0.878438397chrXII+450505450522CGTTTTTATGTTTATTC0.924039943154
149chrXII-459090459073ATTGTTTATGTTTTGTG0.940327272chrXII+458995459012CTATTCTATGTTTTCTT0.88616788295
150chrXII-513083513066TTTATTTATGTTTTTGT0.968709027chrXII+512958512975ATTATAAACATTTTATA0.845822907125
151chrXII-603109603092TTTTTTAATGTTTATGT0.962915946chrXII+602997603014GTTTTTATCAGTTTCAT0.801484796112
152chrXII+659892659909GCTTTTTATGTTTATTT0.92663958chrXII-660003659986AGTATTCATGTTTTACT0.871065837111
153chrXII-745115745098TATCTTTATGTTTTGTT0.949064504chrXII+745006745023TCGTTCAAACTTTTGTC0.79040136109
154chrXII-794207794190AAAGTTTAAGTTTAGTT0.935806549chrXII+794096794113TTTGATCATAATTATTT0.872143422111
155chrXII-888740888723GTTTTTTATGTTTAGAT0.952111375chrXII+888618888635AATTTTTATAATTAATG0.88656275122
156chrXII+10072321007249ATGTTTCATATTTTTAT0.888016553chrXII-10073381007321AAAATTTATAATTTAGT0.886785202106
157chrXII+10137891013806TTTTTTTATGTTTTCTC0.951798435chrXII-10138821013865AAACAGTACGTATTTTT0.71556998593
158chrXII-10241561024139CTTAATGATGTTTAGTT0.887516109chrXII+10240171024034CTAGTTTTTAATTATAT0.838833831139
159chrXIII+3176631783GTAGTTTATTATTAGTT0.89054401chrXIII-3187631859CATTAAAATAATTATAT0.824526619110
160chrXIII-9439094373ATTAATTATATTTAGAT0.921181496chrXIII+9426694283ATGTTAAATATTTTATT0.857637919124
161chrXIII+137321137338AATATTTATGTTTTGTT0.980739388chrXIII-137437137420TTGTTATTTATTTTTGA0.841585149116
162chrXIII-184017184000GTTATATATGGTTAGTT0.884678994chrXIII+183864183881ACATTAAATATTTTTGG0.834854862153
163chrXIII+263126263143ATTTTTTATATTTTGTG0.953471148chrXIII-263313263296TATGTATATATTTATCT0.900878883187
164chrXIII+286846286863ATTTTTCTTATTTAGTT0.921601724chrXIII-286946286929AGGATTTATGTTTTTTT0.908582747100
165chrXIII+371020371037AATTTTATTGTTTAGTT0.937218464chrXIII-371128371111CACTTATATTTTTTTAT0.851831461108
166chrXIII+468237468254TTTTTTTATTTTTTGTT0.977274497chrXIII-468357468340ATCATTTTTAATTAGTA0.851483278120
167chrXIII-535770535753TTAATTTATATTTAGTT0.970090441chrXIII+535662535679AGTTGTTTTGTTTTTTT0.82595884108
168chrXIII+611318611335ATTGTTTATGTTTATGT0.951906482chrXIII-611459611442ATTTGGCATCATTGTAT0.685281331141
169chrXIII+634521634538TATTTTTACTATTTGTA0.910848762chrXIII-634639634622CAATTTTATGGTCATTT0.857274617118
170chrXIII+649362649379TTATTTCATATTTTGTT0.953558055chrXIII-649549649532CTTACTAACAATTTCTC0.76251583187
171chrXIII-758417758400AAATTTTATGTTTTTTT0.965835588chrXIII+758312758329ACTTAGCGCGGTTTTTT0.674331603105
172chrXIII+772677772694TTTTTTTACTATTACTT0.90600905chrXIII-772820772803AATTTATACAACTATAT0.778650456143
173chrXIII+805162805179TATTTTTGTATTTAGTC0.881724676chrXIII-805312805295TTTTTTTACCTTTTTCC0.903568549150
174chrXIII+815391815408AAATTCTATGTTTTGTT0.925335958chrXIII-815493815476ATTTTTTTTTTTTTGGA0.903966564102
175chrXIII-897976897959TTTTTTTATGTTTGGTT0.960544596chrXIII+897881897898TTATTTTATCATTTTCT0.8975898895
176chrXIV-2865428637TTTTTTTATTTTTAGGT0.971445917chrXIV+2848628503AAGTTAGATAATTAGCG0.781498458168
177chrXIV+6169561712GTTTTTAATGTTTTGTA0.934385921chrXIV-6185761840TTTATTTAAATTTTGCC0.916575598162
178chrXIV-8975689739TATTTTTAAGTTTTGTT0.974909231chrXIV+8964489661CTACTTATAGTTTTTCT0.805190002112
179chrXIV-169748169731TAATTTAACGTTTTGTT0.953532134chrXIV+169589169606TTTATATATATGTATGT0.835743836159
180chrXIV-196225196208TTTTTTAACTTTTAGCC0.904522219chrXIV+196096196113TTCGTAAAAATTTTTGC0.820044435129
181chrXIV-250464250447AATTTTTACGGTTTTTT0.918603933chrXIV+250330250347GATAAACATATTCTTGT0.787486687134
182chrXIV-280066280049ATTATTTATGTTTTTCT0.94647878chrXIV+279948279965ATAATAATTAATTAGTT0.843720251118
183chrXIV+322003322020TTTGTTTACGTTTAGGC0.937398674chrXIV-322198322181GTTATAAATATTTATAA0.847440569195
184chrXIV-412441412424TTTTTTTATATTTCTGC0.869234054chrXIV+412299412316CAACTTCTACATTACAT0.72789922142
185chrXIV-449536449519CATATTTACATTTAGCC0.905544669chrXIV+449372449389TAAATACACTGTTATTT0.822061337164
186chrXIV+499040499057TTTCTTTATGTTTAGCT0.928956769chrXIV-499150499133TATCTCTTCTTTTTGTT0.820455656110
187chrXIV-546149546132TATTTTTACGTTTTGGC0.956489817chrXIV+545981545998AACATTAGTATTTAATT0.792422254168
188chrXIV-561330561313TTTGTTCACATTTAGTT0.930292374chrXIV+561216561233TTGATTTACATTCAAAC0.797477323114
189chrXIV+609536609553TTTTTTTATGTTTATTT0.986916959chrXIV-609674609657TATTTATGTCTTTACTT0.819944062138
190chrXIV-635833635816TTTTTTTAATTTTAGTT0.954915715chrXIV+635716635733TGTTTTTTTTTTTTGCA0.87217818117
191chrXIV-691680691663GTAATTAACATTTTGTT0.910156612chrXIV+691559691576GATATTTCCCTTTTGGA0.801789741121
192chrXV+3571435731TATATTTATATTTAGAG0.929297843chrXV-3585535838CATATTTATGTTTCATT0.847487414141
193chrXV+7268872705TTTTTTTACTTTTAGTT0.962701666chrXV-7279472777TTTTATCACGTTTAGCA0.883721557106
194chrXV-8536685349TATACCTATATTTATGT0.817468435chrXV+8526885285GCTTTTAATTTTTATTT0.88788130798
195chrXV+113895113912ATTGTTTATATTTTTGT0.943227229chrXV-114058114041TAATATCATGTTTTATA0.868893438163
196chrXV+167003167020TTTATTTATGTTTTCGT0.95396729chrXV-167143167126TTTAAAACTGTTTACGT0.78001402140
197chrXV-277732277715GTTGTTTATCTTTTGTT0.926499065chrXV+277562277579TTATAAAAAATTTATTT0.859561998170
198chrXV-337483337466TCTTTTTACCTTTTGTC0.904262836chrXV+337385337402TATTTTAGTATTTATTT0.87084598898
199chrXV+436790436807TATATTTATTTTTATTC0.935122318chrXV-436888436871TTCTTTTTTCATTTATT0.83286709898
200chrXV-490060490043GTTGTTTTTCTTTTCTT0.860946443chrXV+489890489907TAAGTTTATATTTTGGT0.951016266170
201chrXV-566597566580AAATTTTACCTTTTGAT0.915947006chrXV+566499566516AATATTTAATATCTCTT0.82491674798
202chrXV+656701656718CTATTTAATGATTAGTA0.901351813chrXV-656901656884GTTGATTTCTTTTTCTT0.817366446200
203chrXV+729795729812TATTTTTATATTTTGGC0.964523057chrXV-729894729877TTCTTTCATTTTTGTAC0.82363654299
204chrXV+766689766706GTATTTTACGTTTTTTC0.912718329chrXV-766791766774TATTTTAAATTTCTGTA0.860782306102
205chrXV+783386783403TATTTTTAACTTTTGGT0.942451749chrXV-783582783565TCTTTTTATCTCTTCAA0.777182413196
206chrXV-874370874353CATTTTAATATTTGTTA0.881539907chrXV+874192874209AAGTTTTCCGTTTAGCA0.807156571178
207chrXV+908307908324CTAAACTTTGTTTATGT0.815272772chrXV-908439908422GGTTTTTTTTTTTAAGT0.8448056132
208chrXV+981507981524TTTTTTTATTTATATTT0.874148828chrXV-981603981586TTTTTTCATGATTTTGT0.92437863496
209chrXV+10536871053704TAATTAATTGTTTTGTT0.896133812chrXV-10537971053780CGATTAAATGTTTTTAT0.856030986110
210chrXVI-4315043133TTTGTTTATATTTTTGA0.929263085chrXVI+4295842975TTCTTTTACCTTTAATA0.863567037192
211chrXVI+7310473121GTTTTTTTTGTTTTTTC0.902693595chrXVI-7330173284TATATTTATAATTATAA0.896514883197
212chrXVI+116593116610TATTTTTATGTTTTGTT0.998337845chrXVI-116770116753TAAAATTAAGTTTTGCG0.868507637177
213chrXVI+289531289548ATAATTAATGTTTACTT0.925413716chrXVI-289675289658AAAGTTAATTTTTATAT0.885623957144
214chrXVI+384591384608TATTCTAAAATTTATGT0.840759582chrXVI-384718384701TTTAAATATATTTAAGT0.869580534127
215chrXVI+418177418194TTCTTTCTTATTTACAA0.82265266chrXVI-418289418272TATTATTTTGTTTTCTT0.900944489112
216chrXVI-456763456746TTTTATTATTTTTTGTT0.945433762chrXVI+456626456643CTTATTCACAATTTCAA0.820656345137
217chrXVI+511708511725TATTTTTATGTTTTTTG0.954763972chrXVI-511820511803GTGGTTATCATTTATTT0.826572147112
218chrXVI+563881563898AGTCTTTTATATTTAGT0.760925944chrXVI-563991563974TCTAAATATATTCATCT0.791939697110
219chrXVI+565119565136TGTTTTTAATTTTTAGT0.884153732chrXVI-565272565255TTTTTGGTTCTTTTGTT0.822137769153
220chrXVI+633925633942CGTTTTTATAGTTTAGT0.858684766chrXVI-634064634047TTGTTTTATATTTAACA0.875389458139
221chrXVI+684409684426TTTTTTTTACTTTTTGT0.892233188chrXVI-684534684517CATATGTTTGTTTAGCT0.847979457125
222chrXVI-695624695607TTTTTTTTTAATTTTCT0.889872135chrXVI+695470695487AATTTTTATATTTGGTT0.944984083154
223chrXVI+749121749138AATTTTTAAGTTTAGTA0.947297384chrXVI-749222749205ATAATTTACATTTTATT0.907501113101
224chrXVI-777098777081TTTATTTATATTTTGGC0.954875691chrXVI+776923776940AATGTGTTAGTTTTTCT0.811819984175
225chrXVI-819345819328AATTTTTATATTTATTC0.952049491chrXVI+819204819221TATATTATCATATAGTT0.819972999141
226chrXVI-842856842839TTTATTTAGATTTAGTT0.894404608chrXVI+842714842731AATTTTAATCTTTAGTA0.928064324142
227chrXVI+880904880921CTCATATATATTTTATG0.822074378chrXVI-881035881018TAACTCTAACTTTTTTA0.800027746131
228chrXVI-933170933153CTTATTTACGTTTAGCT0.93305337chrXVI+933047933064ATTCAAAATATTTTGGA0.822210839123

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    Genetic control of the cell division cycle in yeast: v. genetic analysis of cdc mutants
    1. LH Hartwell
    2. RK Mortimer
    3. J Culotti
    4. M Culotti
    (1973)
    Genetics 74:267–286.
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Decision letter

  1. Bruce Stillman
    Reviewing Editor; Cold Spring Harbor Laboratory, United States
  2. Kevin Struhl
    Senior Editor; Harvard Medical School, United States

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

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.

https://doi.org/10.7554/eLife.40802.024

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.
https://doi.org/10.7554/eLife.40802.017

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.

https://doi.org/10.7554/eLife.40802.025

Article and author information

Author details

  1. Tito Candelli

    Institut Jacques Monod, CNRS UMR 7592, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
    Present address
    Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
    Contribution
    Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Methodology, Writing—review and editing
    Contributed equally with
    Julien Gros
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2440-6032
  2. Julien Gros

    Institut Jacques Monod, CNRS UMR 7592, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
    Contribution
    Conceptualization, Data curation, Supervision, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing
    Contributed equally with
    Tito Candelli
    For correspondence
    julien.gros@ijm.fr
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8316-0207
  3. Domenico Libri

    Institut Jacques Monod, CNRS UMR 7592, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing
    For correspondence
    domenico.libri@ijm.fr
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6728-0594

Funding

Centre National de la Recherche Scientifique

  • Domenico Libri

Fondation pour la Recherche Médicale (F.R.M. programme équipes 2013)

  • Domenico Libri

Agence Nationale de la Recherche (Grant ANR-16-CE12-0022-01)

  • Domenico Libri

Labex (WhoamI? ANR-11-LABX-0071)

  • Domenico Libri

French Ministry of Research (Fellowship)

  • Tito Candelli

Ligue Contre le Cancer (GB/MA/CD/IQ - 12031)

  • Julien Gros

Labex (WhoamI? ANR-11-IDEX-0005-02)

  • Domenico Libri

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

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.

Senior Editor

  1. Kevin Struhl, Harvard Medical School, United States

Reviewing Editor

  1. Bruce Stillman, Cold Spring Harbor Laboratory, United States

Publication history

  1. Received: August 6, 2018
  2. Accepted: December 17, 2018
  3. Accepted Manuscript published: December 17, 2018 (version 1)
  4. Version of Record published: January 2, 2019 (version 2)

Copyright

© 2018, Candelli et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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