Mathematical modelling of whole chromosome replication

Rif1 restrains the rate of replication origin firing in Xenopus laevis

Metazoan genomes are duplicated by the coordinated activation of clusters of replication origins at different times during S phase, but the underlying mechanisms of this temporal program remain unclear during early development. Rif1, a key replication timing factor, inhibits origin firing by recruiting protein phosphatase 1 (PP1) to chromatin counteracting S phase kinases. We have previously described that Rif1 depletion accelerates early Xenopus laevis embryonic cell cycles. Here, we find that in the absence of Rif1, patterns of replication foci change along with the acceleration of replication cluster activation. However, initiations increase only moderately inside active clusters. Our numerical simulations suggest that the absence of Rif1 compresses the temporal program towards more homogeneity and increases the availability of limiting initiation factors. We experimentally demonstrate that Rif1 depletion increases the chromatin-binding of the S phase kinase Cdc7/Drf1, the firing factors Treslin, MTBP, Cdc45, RecQL4, and the phosphorylation of both Treslin and MTBP. We show that Rif1 globally, but not locally, restrains the replication program in early embryos, possibly by inhibiting or excluding replication factors from chromatin.

DNA replication timing: Biochemical mechanisms and biological significance

The regulation of DNA replication is a fascinating biological problem both from a mechanistic angle-How is replication timing regulated?-and from an evolutionary one-Why is replication timing regulated? Recent work has provided significant insight into the first question. Detailed biochemical understanding of the mechanism and regulation of replication initiation has made possible robust hypotheses for how replication timing is regulated. Moreover, technical progress, including high-throughput, single-molecule mapping of replication initiation and single-cell assays of replication timing, has allowed for direct testing of these hypotheses in mammalian cells. This work has consolidated the conclusion that differential replication timing is a consequence of the varying probability of replication origin initiation. The second question is more difficult to directly address experimentally. Nonetheless, plausible hypotheses can be made and one-that replication timing contributes to the regulation of chromatin structure-has received new experimental support.

Genome-wide mapping of individual replication fork velocities using nanopore sequencing

Little is known about replication fork velocity variations along eukaryotic genomes, since reference techniques to determine fork speed either provide no sequence information or suffer from low throughput. Here we present NanoForkSpeed, a nanopore sequencing-based method to map and extract the velocity of individual forks detected as tracks of the thymidine analogue bromodeoxyuridine incorporated during a brief pulse-labelling of asynchronously growing cells. NanoForkSpeed retrieves previous Saccharomyces cerevisiae mean fork speed estimates (≈2 kb/min) in the BT1 strain exhibiting highly efficient bromodeoxyuridine incorporation and wild-type growth, and precisely quantifies speed changes in cells with altered replisome progression or exposed to hydroxyurea. The positioning of >125,000 fork velocities provides a genome-wide map of fork progression based on individual fork rates, showing a uniform fork speed across yeast chromosomes except for a marked slowdown at known pausing sites.

Theulot et al. introduce NanoForkSpeed, a nanopore sequencing-based method to map individual replication fork velocities on entire genomes. NFS shows that fork speed is uniform across yeast chromosomes except for a marked slowdown at pausing sites.

f = m*a: A Framework for Investigating the Regulation of Replication Timing

Stochastic models of replication timing posit that origin firing timing is regulated by origin firing probability, with early-firing origins having a high probability of firing and late-firing origins having a lower probability. However, they offer no insight into why one origin should have a higher firing probability than another. Here, a simple framework is suggested for how to approach the question by noting that the firing probability (f) must be the product of the stoichiometry of the MCM replicative helicase loaded at the origin (m) and the probability with which that MCM is activated (a). This framework emphasizes that mechanistic understanding of replication timing must focus on MCM loading and activation and can be simplified to the equation f = m*a.

Chromosomal Mcm2-7 distribution and the genome replication program in species from yeast to humans

The spatio-temporal program of genome replication across eukaryotes is thought to be driven both by the uneven loading of pre-replication complexes (pre-RCs) across the genome at the onset of S-phase, and by differences in the timing of activation of these complexes during S phase. To determine the degree to which distribution of pre-RC loading alone could account for chromosomal replication patterns, we mapped the binding sites of the Mcm2-7 helicase complex (MCM) in budding yeast, fission yeast, mouse and humans. We observed similar individual MCM double-hexamer (DH) footprints across the species, but notable differences in their distribution: Footprints in budding yeast were more sharply focused compared to the other three organisms, consistent with the relative sequence specificity of replication origins in S. cerevisiae. Nonetheless, with some clear exceptions, most notably the inactive X-chromosome, much of the fluctuation in replication timing along the chromosomes in all four organisms reflected uneven chromosomal distribution of pre-replication complexes.

Gene-rich regions of the genome tend to replicate earlier in S phase than do repetitive and other non-genic regions. This may be an evolutionary consequence of the fact that replication later in S phase is associated with higher frequencies of mutation and genome rearrangement. Replication timing along the chromosome is determined by 1) events prior to S-phase that specify the locations where DNA replication can be initiated, referred to as origin licensing; and 2) the timing of activation of these licensed origins during S-phase, referred to as origin firing. To determine the relative importance of these two mechanisms, here we identify both the binding sites and the abundance of a key component of the origin licensing machinery in budding yeast, fission yeast, mice, and humans, namely the replicative helicase complex. We discovered that, with a few notable exceptions, which include the inactive X chromosome in mammals, the program of replication timing can be largely explained simply on the basis of origin licensing. Our results support a model for replication timing that emphasizes stochastic firing of origins that have been licensed before S phase begins.

Genome-wide mapping of human DNA replication by optical replication mapping supports a stochastic model of eukaryotic replication

The heterogeneous nature of eukaryotic replication kinetics and the low efficiency of individual initiation sites make mapping the location and timing of replication initiation in human cells difficult. To address this challenge, we have developed optical replication mapping (ORM), a high-throughput single-molecule approach, and used it to map early-initiation events in human cells. The single-molecule nature of our data and a total of >2,500-fold coverage of the human genome on 27 million fibers averaging ∼300 kb in length allow us to identify initiation sites and their firing probability with high confidence. We find that the distribution of human replication initiation is consistent with inefficient, stochastic activation of heterogeneously distributed potential initiation complexes enriched in accessible chromatin. These observations are consistent with stochastic models of initiation-timing regulation and suggest that stochastic regulation of replication kinetics is a fundamental feature of eukaryotic replication, conserved from yeast to humans.

An evolutionary model identifies the main evolutionary biases for the evolution of genome-replication profiles

Recent results comparing the temporal program of genome replication of yeast species belonging to the Lachancea clade support the scenario that the evolution of the replication timing program could be mainly driven by correlated acquisition and loss events of active replication origins. Using these results as a benchmark, we develop an evolutionary model defined as birth-death process for replication origins and use it to identify the evolutionary biases that shape the replication timing profiles. Comparing different evolutionary models with data, we find that replication origin birth and death events are mainly driven by two evolutionary pressures, the first imposes that events leading to higher double-stall probability of replication forks are penalized, while the second makes less efficient origins more prone to evolutionary loss. This analysis provides an empirically grounded predictive framework for quantitative evolutionary studies of the replication timing program.

The capacity of origins to load MCM establishes replication timing patterns

Loading of the MCM replicative helicase at origins of replication is a highly regulated process that precedes DNA replication in all eukaryotes. The stoichiometry of MCM loaded at origins has been proposed to be a key determinant of when those origins initiate replication during S phase. Nevertheless, the genome-wide regulation of MCM loading stoichiometry and its direct effect on replication timing remain unclear. In order to investigate why some origins load more MCM than others, we perturbed MCM levels in budding yeast cells and, for the first time, directly measured MCM levels and replication timing in the same experiment. Reduction of MCM levels through degradation of Mcm4, one of the six obligate components of the MCM complex, slowed progression through S phase and increased sensitivity to replication stress. Reduction of MCM levels also led to differential loading at origins during G1, revealing origins that are sensitive to reductions in MCM and others that are not. Sensitive origins loaded less MCM under normal conditions and correlated with a weak ability to recruit the origin recognition complex (ORC). Moreover, reduction of MCM loading at specific origins of replication led to a delay in their replication during S phase. In contrast, overexpression of MCM had no effects on cell cycle progression, relative MCM levels at origins, or replication timing, suggesting that, under optimal growth conditions, cellular MCM levels are not limiting for MCM loading. Our results support a model in which the loading capacity of origins is the primary determinant of MCM stoichiometry in wild-type cells, but that stoichiometry is controlled by origins' ability to recruit ORC and compete for MCM when MCM becomes limiting.

In silico analysis of DNA re-replication across a complete genome reveals cell-to-cell heterogeneity and genome plasticity

DNA replication is a complex and remarkably robust process: despite its inherent uncertainty, manifested through stochastic replication timing at a single-cell level, multiple control mechanisms ensure its accurate and timely completion across a population. Disruptions in these mechanisms lead to DNA re-replication, closely connected to genomic instability and oncogenesis. Here, we present a stochastic hybrid model of DNA re-replication that accurately portrays the interplay between discrete dynamics, continuous dynamics and uncertainty. Using experimental data on the fission yeast genome, model simulations show how different regions respond to re-replication and permit insight into the key mechanisms affecting re-replication dynamics. Simulated and experimental population-level profiles exhibit a good correlation along the genome, robust to model parameters, validating our approach. At a single-cell level, copy numbers of individual loci are affected by intrinsic properties of each locus, in cis effects from adjoining loci and in trans effects from distant loci. In silico analysis and single-cell imaging reveal that cell-to-cell heterogeneity is inherent in re-replication and can lead to genome plasticity and a plethora of genotypic variations.

FORK-seq: replication landscape of the Saccharomyces cerevisiae genome by nanopore sequencing

Genome replication mapping methods profile cell populations, masking cell-to-cell heterogeneity. Here, we describe FORK-seq, a nanopore sequencing method to map replication of single DNA molecules at 200-nucleotide resolution. By quantifying BrdU incorporation along pulse-chased replication intermediates from Saccharomyces cerevisiae, we orient 58,651 replication tracks reproducing population-based replication directionality profiles and map 4964 and 4485 individual initiation and termination events, respectively. Although most events cluster at known origins and fork merging zones, 9% and 18% of initiation and termination events, respectively, occur at many locations previously missed. Thus, FORK-seq reveals the full extent of cell-to-cell heterogeneity in DNA replication.

The Beacon Calculus: A formal method for the flexible and concise modelling of biological systems

Biological systems are made up of components that change their actions (and interactions) over time and coordinate with other components nearby. Together with a large state space, the complexity of this behaviour can make it difficult to create concise mathematical models that can be easily extended or modified. This paper introduces the Beacon Calculus, a process algebra designed to simplify the task of modelling interacting biological components. Its breadth is demonstrated by creating models of DNA replication dynamics, the gene expression dynamics in response to DNA methylation damage, and a multisite phosphorylation switch. The flexibility of these models is shown by adapting the DNA replication model to further include two topics of interest from the literature: cooperative origin firing and replication fork barriers. The Beacon Calculus is supported with the open-source simulator bcs (https://github.com/MBoemo/bcs.git) to allow users to develop and simulate their own models.

Simulating a model of a biological system can suggest ideas for future experiments and help ensure that conclusions about a mechanism are consistent with data. The Beacon Calculus is a new language that makes modelling simple by allowing users to simulate a biological system in only a few lines of code. This simplicity is critical as it allows users the freedom to come up with new ideas and rapidly test them. Models written in the Beacon Calculus are also easy to modify and extend, allowing users to add new features to the model or incorporate it into a larger biological system. We demonstrate the breadth of applications in this paper by applying the Beacon Calculus to DNA replication and DNA damage repair, both of which have implications for genome stability and cancer. We also apply it to multisite phosphorylation, which is important for cellular signalling. To enable users to create their own models, we created the open-source Beacon Calculus simulator bcs (https://github.com/MBoemo/bcs.git) which is easy to install and is well-supported by documentation and examples.

Genomic methods for measuring DNA replication dynamics

Genomic DNA replicates according to a defined temporal program in which early-replicating loci are associated with open chromatin, higher gene density, and increased gene expression levels, while late-replicating loci tend to be heterochromatic and show higher rates of genomic instability. The ability to measure DNA replication dynamics at genome scale has proven crucial for understanding the mechanisms and cellular consequences of DNA replication timing. Several methods, such as quantification of nucleotide analog incorporation and DNA copy number analyses, can accurately reconstruct the genomic replication timing profiles of various species and cell types. More recent developments have expanded the DNA replication genomic toolkit to assays that directly measure the activity of replication origins, while single-cell replication timing assays are beginning to reveal a new level of replication timing regulation. The combination of these methods, applied on a genomic scale and in multiple biological systems, promises to resolve many open questions and lead to a holistic understanding of how eukaryotic cells replicate their genomes accurately and efficiently.

DNA copy-number measurement of genome replication dynamics by high-throughput sequencing: the sort-seq, sync-seq and MFA-seq family

Genome replication follows a defined temporal programme that can change during cellular differentiation and disease onset. DNA replication results in an increase in DNA copy number that can be measured by high-throughput sequencing. Here we present a protocol to determine genome replication dynamics using DNA copy-number measurements. Cell populations can be obtained in three variants of the method. First, sort-seq reveals the average replication dynamics across S phase in an unperturbed cell population; FACS is used to isolate replicating and non-replicating subpopulations from asynchronous cells. Second, sync-seq measures absolute replication time at specific points during S phase using a synchronized cell population. Third, marker frequency analysis can be used to reveal the average replication dynamics using copy-number analysis in any proliferating asynchronous cell culture. These approaches have been used to reveal genome replication dynamics in prokaryotes, archaea and a wide range of eukaryotes, including yeasts and mammalian cells. We have found this approach straightforward to apply to other organisms and highlight example studies from across the three domains of life. Here we present a Saccharomyces cerevisiae version of the protocol that can be performed in 7-10 d. It requires basic molecular and cellular biology skills, as well as a basic understanding of Unix and R.

Stochasticity of replication forks' speeds plays a key role in the dynamics of DNA replication

Eukaryotic DNA replication is elaborately orchestrated to duplicate the genome timely and faithfully. Replication initiates at multiple origins from which replication forks emanate and travel bi-directionally. The complex spatio-temporal regulation of DNA replication remains incompletely understood. To study it, computational models of DNA replication have been developed in S. cerevisiae. However, in spite of the experimental evidence of forks’ speed stochasticity, all models assumed that forks’ speeds are the same. Here, we present the first model of DNA replication assuming that speeds vary stochastically between forks. Utilizing data from both wild-type and hydroxyurea-treated yeast cells, we show that our model is more accurate than models assuming constant forks’ speed and reconstructs dynamics of DNA replication faithfully starting both from population-wide data and data reflecting fork movement in individual cells. Completion of replication in a timely manner is a challenge due to its stochasticity; we propose an empirically derived modification to replication speed based on the distance to the approaching fork, which promotes timely completion of replication. In summary, our work discovers a key role that stochasticity of the forks’ speed plays in the dynamics of DNA replication. We show that without including stochasticity of forks’ speed it is not possible to accurately reconstruct movement of individual replication forks, measured by DNA combing.

DNA replication in eukaryotes starts from multiple sites termed replication origins. Replication timing at individual sites is stochastic, but reproducible population-wide. Complex and not yet completely understood mechanisms ensure that genome is replicated exactly once and that replication is finished in time. This complex spatio-temporal organization of DNA replication makes computational modeling a useful tool to study replication mechanisms. For simplicity, all previous models assumed constant replication forks’ speed. Here, we show that such models are incapable of accurately reconstructing distances travelled by individual replication forks. Therefore, we propose a model assuming that replication speed varies stochastically between forks. We show that such model reproduces faithfully distances travelled by individual replication forks. Moreover, our model is simpler than previous model and thus avoids over-learning (fitting noise). We also discover how replication speed may be attuned to timely complete replication. We propose that forks’ speed increases with diminishing distance to the approaching fork, which we show promotes timely completion of replication. Such speed up can be e.g. explained by a synergy effect of chromatin unwinding by both forks. Our model can be used to simulate phenomena beyond replication, e.g. DNA double-strand breaks resulting from broken replication forks.

Replication dynamics of individual loci in single living cells reveal changes in the degree of replication stochasticity through S phase

Eukaryotic genomes are replicated under the control of a highly sophisticated program during the restricted time period corresponding to S phase. The most widely used replication timing assays, which are performed on populations of millions of cells, suggest that most of the genome is synchronously replicated on homologous chromosomes. We investigated the stochastic nature of this temporal program, by comparing the precise replication times of allelic loci within single vertebrate cells progressing through S phase at six loci replicated from very early to very late. We show that replication timing is strictly controlled for the three loci replicated in the first half of S phase. Out of the three loci replicated in the second part of S phase, two present a significantly more stochastic pattern. Surprisingly, we find that the locus replicated at the very end of S phase, presents stochasticity similar to those replicated in early S phase. We suggest that the richness of loci in efficient origins of replication, which decreases from early- to late-replicating regions, and the strength of interaction with the nuclear lamina may underlie the variation of timing control during S phase.

Molecular Mechanisms of DNA Replication and Repair Machinery: Insights from Microscopic Simulations

Reproduction, the hallmark of biological activity, requires making an accurate copy of the genetic material to allow the progeny to inherit parental traits. In all living cells, the process of DNA replication is carried out by a concerted action of multiple protein species forming a loose protein-nucleic acid complex, the replisome. Proofreading and error correction generally accompany replication but also occur independently, safeguarding genetic information through all phases of the cell cycle. Advances in biochemical characterization of intracellular processes, proteomics and the advent of single-molecule biophysics have brought about a treasure trove of information awaiting to be assembled into an accurate mechanistic model of the DNA replication process. In this review, we describe recent efforts to model elements of DNA replication and repair processes using computer simulations, an approach that has gained immense popularity in many areas of molecular biophysics but has yet to become mainstream in the DNA metabolism community. We highlight the use of diverse computational methods to address specific problems of the fields and discuss unexplored possibilities that lie ahead for the computational approaches in these areas.

DNA Replication Timing Enters the Single-Cell Era

In mammalian cells, DNA replication timing is controlled at the level of megabase (Mb)-sized chromosomal domains and correlates well with transcription, chromatin structure, and three-dimensional (3D) genome organization. Because of these properties, DNA replication timing is an excellent entry point to explore genome regulation at various levels and a variety of studies have been carried out over the years. However, DNA replication timing studies traditionally required at least tens of thousands of cells, and it was unclear whether the replication domains detected by cell population analyses were preserved at the single-cell level. Recently, single-cell DNA replication profiling methods became available, which revealed that the Mb-sized replication domains detected by cell population analyses were actually well preserved in individual cells. In this article, we provide a brief overview of our current knowledge on DNA replication timing regulation in mammals based on cell population studies, outline the findings from single-cell DNA replication profiling, and discuss future directions and challenges.

On the Interplay of the DNA Replication Program and the Intra-S Phase Checkpoint Pathway

DNA replication in eukaryotes is achieved by the activation of multiple replication origins which needs to be precisely coordinated in space and time. This spatio-temporal replication program is regulated by many factors to maintain genome stability, which is frequently threatened through stresses of exogenous or endogenous origin. Intra-S phase checkpoints monitor the integrity of DNA synthesis and are activated when replication forks are stalled. Their activation leads to the stabilization of forks, to the delay of the replication program by the inhibition of late firing origins, and the delay of G2/M phase entry. In some cell cycles during early development these mechanisms are less efficient in order to allow rapid cell divisions. In this article, we will review our current knowledge of how the intra-S phase checkpoint regulates the replication program in budding yeast and metazoan models, including early embryos with rapid S phases. We sum up current models on how the checkpoint can inhibit origin firing in some genomic regions, but allow dormant origin activation in other regions. Finally, we discuss how numerical and theoretical models can be used to connect the multiple different actors into a global process and to extract general rules.

The evolution of the temporal program of genome replication

Genome replication is highly regulated in time and space, but the rules governing the remodeling of these programs during evolution remain largely unknown. We generated genome-wide replication timing profiles for ten Lachancea yeasts, covering a continuous evolutionary range from closely related to more divergent species. We show that replication programs primarily evolve through a highly dynamic evolutionary renewal of the cohort of active replication origins. We found that gained origins appear with low activity yet become more efficient and fire earlier as they evolutionarily age. By contrast, origins that are lost comprise the complete range of firing strength. Additionally, they preferentially occur in close vicinity to strong origins. Interestingly, despite high evolutionary turnover, active replication origins remain regularly spaced along chromosomes in all species, suggesting that origin distribution is optimized to limit large inter-origin intervals. We propose a model on the evolutionary birth, death, and conservation of active replication origins.

Temporal programs of genome replication show different levels of conservation between closely or distantly related species. Here, the authors generate genome-wide replication timing profiles for ten yeast species, and analyze their evolutionary dynamics.

The eukaryotic bell-shaped temporal rate of DNA replication origin firing emanates from a balance between origin activation and passivation

The time-dependent rate I(t) of origin firing per length of unreplicated DNA presents a universal bell shape in eukaryotes that has been interpreted as the result of a complex time-evolving interaction between origins and limiting firing factors. Here, we show that a normal diffusion of replication fork components towards localized potential replication origins (p-oris) can more simply account for the I(t) universal bell shape, as a consequence of a competition between the origin firing time and the time needed to replicate DNA separating two neighboring p-oris. We predict the I(t) maximal value to be the product of the replication fork speed with the squared p-ori density. We show that this relation is robustly observed in simulations and in experimental data for several eukaryotes. Our work underlines that fork-component recycling and potential origins localization are sufficient spatial ingredients to explain the universality of DNA replication kinetics.

Before a cell can divide, it must duplicate its DNA. In eukaryotes – organisms such as animals and fungi, which store their DNA in the cell’s nucleus – DNA replication starts at specific sites in the genome called replication origins. At each origin sits a protein complex that will activate when it randomly captures an activating protein that diffuses within the nucleus. Once a replication origin activates or “fires”, the complex then splits into two new complexes that move away from each other as they duplicate the DNA. If an active complex collides with an inactive one at another origin, the latter is inactivated – a phenomenon known as origin passivation. When two active complexes meet, they release the activating proteins, which diffuse away and eventually activate other origins in unreplicated DNA.

The number of origins that activate each minute divided by the length of unreplicated DNA is referred to as the “rate of origin firing”. In all eukaryotes, this rate – also known as I(t) – follows the same pattern. First, it increases until more than half of the DNA is duplicated. Then it decreases until everything is duplicated. This means that, if plotted out, the graph of origin firing rate would always be a bell-shaped curve, even for organisms with genomes of different sizes that have different numbers of origins. The reason for this universal shape remained unclear.

Scientists had tried to create numerical simulations that model the rate of origin firing. However, for these simulations to reproduce the bell-shape curve, a number of untested assumptions had to be made about how DNA replication takes place. In addition, these models ignored the fact that it takes time to replicate the DNA between origins.

To take this time into account, Arbona et al. instead decided to model the replication origins as discrete and distinct entities. This way of building the mathematical model succeeded in reproducing the universal bell curve shape without additional assumptions. With this simulation, the balance between origin activation and passivation is enough to achieve the observed pattern.

The new model also predicts that the maximum rate of origin firing is determined by the speed of DNA replication and the density of origins in the genome. Arbona et al. verified this prediction in yeast, fly, frog and human cells – organisms with different sized genomes that take between 20 minutes and 8 hours to replicate their DNA. Lastly, the prediction also held true in yeast treated with hydroxyurea, an anticancer drug that slows DNA replication.

A better understanding of DNA replication can help scientists to understand how this process is perturbed in cancers and how drugs that target DNA replication can treat these diseases. Future work will explore how the 3D organization of the genome affects the diffusion of activating proteins within the cell nucleus.

Cell-to-cell variability and robustness in S-phase duration from genome replication kinetics

Genome replication, a key process for a cell, relies on stochastic initiation by replication origins, causing a variability of replication timing from cell to cell. While stochastic models of eukaryotic replication are widely available, the link between the key parameters and overall replication timing has not been addressed systematically. We use a combined analytical and computational approach to calculate how positions and strength of many origins lead to a given cell-to-cell variability of total duration of the replication of a large region, a chromosome or the entire genome. Specifically, the total replication timing can be framed as an extreme-value problem, since it is due to the last region that replicates in each cell. Our calculations identify two regimes based on the spread between characteristic completion times of all inter-origin regions of a genome. For widely different completion times, timing is set by the single specific region that is typically the last to replicate in all cells. Conversely, when the completion time of all regions are comparable, an extreme-value estimate shows that the cell-to-cell variability of genome replication timing has universal properties. Comparison with available data shows that the replication program of three yeast species falls in this extreme-value regime.

Model-based analysis of DNA replication profiles: predicting replication fork velocity and initiation rate by profiling free-cycling cells

Eukaryotic cells initiate DNA synthesis by sequential firing of hundreds of origins. This ordered replication is described by replication profiles, which measure the DNA content within a cell population. Here, we show that replication dynamics can be deduced from replication profiles of free-cycling cells. While such profiles lack explicit temporal information, they are sensitive to fork velocity and initiation capacity through the passive replication pattern, namely the replication of origins by forks emanating elsewhere. We apply our model-based approach to a compendium of profiles that include most viable budding yeast mutants implicated in replication. Predicted changes in fork velocity or initiation capacity are verified by profiling synchronously replicating cells. Notably, most mutants implicated in late (or early) origin effects are explained by global modulation of fork velocity or initiation capacity. Our approach provides a rigorous framework for analyzing DNA replication profiles of free-cycling cells.

Establishment of a promoter-based chromatin architecture on recently replicated DNA can accommodate variable inter-nucleosome spacing

Nucleosomes, the fundamental subunits of eukaryotic chromatin, are organized with respect to transcriptional start sites. A major challenge to the persistence of this organization is the disassembly of nucleosomes during DNA replication. Here, we use complimentary approaches to map the locations of nucleosomes on recently replicated DNA. We find that nucleosomes are substantially realigned with promoters during the minutes following DNA replication. As a result, the nucleosomal landscape is largely re-established before newly replicated chromosomes are partitioned into daughter cells and can serve as a platform for the re-establishment of gene expression programmes. When the supply of histones is disrupted through mutation of the chaperone Caf1, a promoter-based architecture is generated, but with increased inter-nucleosomal spacing. This indicates that the chromatin remodelling enzymes responsible for spacing nucleosomes are capable of organizing nucleosomes with a range of different linker DNA lengths.

Deciphering DNA replication dynamics in eukaryotic cell populations in relation with their averaged chromatin conformations

We propose a non-local model of DNA replication that takes into account the observed uncertainty on the position and time of replication initiation in eukaryote cell populations. By picturing replication initiation as a two-state system and considering all possible transition configurations, and by taking into account the chromatin’s fractal dimension, we derive an analytical expression for the rate of replication initiation. This model predicts with no free parameter the temporal profiles of initiation rate, replication fork density and fraction of replicated DNA, in quantitative agreement with corresponding experimental data from both S. cerevisiae and human cells and provides a quantitative estimate of initiation site redundancy. This study shows that, to a large extent, the program that regulates the dynamics of eukaryotic DNA replication is a collective phenomenon that emerges from the stochastic nature of replication origins initiation.

Replication timing is regulated by the number of MCMs loaded at origins

Replication timing is a crucial aspect of genome regulation that is strongly correlated with chromatin structure, gene expression, DNA repair, and genome evolution. Replication timing is determined by the timing of replication origin firing, which involves activation of MCM helicase complexes loaded at replication origins. Nonetheless, how the timing of such origin firing is regulated remains mysterious. Here, we show that the number of MCMs loaded at origins regulates replication timing. We show for the first time in vivo that multiple MCMs are loaded at origins. Because early origins have more MCMs loaded, they are, on average, more likely to fire early in S phase. Our results provide a mechanistic explanation for the observed heterogeneity in origin firing and help to explain how defined replication timing profiles emerge from stochastic origin firing. These results establish a framework in which further mechanistic studies on replication timing, such as the strong effect of heterochromatin, can be pursued.

Embryonic stem cell specific "master" replication origins at the heart of the loss of pluripotency

Epigenetic regulation of the replication program during mammalian cell differentiation remains poorly understood. We performed an integrative analysis of eleven genome-wide epigenetic profiles at 100 kb resolution of Mean Replication Timing (MRT) data in six human cell lines. Compared to the organization in four chromatin states shared by the five somatic cell lines, embryonic stem cell (ESC) line H1 displays (i) a gene-poor but highly dynamic chromatin state (EC4) associated to histone variant H2AZ rather than a HP1-associated heterochromatin state (C4) and (ii) a mid-S accessible chromatin state with bivalent gene marks instead of a polycomb-repressed heterochromatin state. Plastic MRT regions (≲ 20% of the genome) are predominantly localized at the borders of U-shaped timing domains. Whereas somatic-specific U-domain borders are gene-dense GC-rich regions, 31.6% of H1-specific U-domain borders are early EC4 regions enriched in pluripotency transcription factors NANOG and OCT4 despite being GC poor and gene deserts. Silencing of these ESC-specific “master” replication initiation zones during differentiation corresponds to a loss of H2AZ and an enrichment in H3K9me3 mark characteristic of late replicating C4 heterochromatin. These results shed a new light on the epigenetically regulated global chromatin reorganization that underlies the loss of pluripotency and lineage commitment.

During development, embryonic stem cell (ESC) enter a program of cell differentiation eventually leading to all the necessary differentiated cell types. Understanding the mechanisms responsible for the underlying modifications of the gene expression program is of fundamental importance, as it will likely have strong impact on the development of regenerative medicine. We show that besides some epigenetic regulation, ubiquitous master replication origins at replication timing U-domain borders shared by 6 human cell types are transcriptionally active open chromatin regions specified by a local enrichment in nucleosome free regions encoded in the DNA sequence suggesting that they have been selected during evolution. In contrast, ESC specific master replication origins bear a unique epigenetic signature (enrichment in CTCF, H2AZ, NANOG, OCT4, …) likely contributing to maintain ESC chromatin in a highly dynamic and accessible state that is refractory to polycomb and HP1 heterochromatin spreading. These ESC specific master origins thus appear as key genomic regions where epigenetic control of chromatin organization is at play to maintain pluripotency of stem cell lineages and to guide lineage commitment to somatic cell types.

Mechanism of Gene Amplification via Yeast Autonomously Replicating Sequences

The present investigation was aimed at understanding the molecular mechanism of gene amplification. Interplay of fragile sites in promoting gene amplification was also elucidated. The amplification promoting sequences were chosen from theSaccharomyces cerevisiaeARS, 5S rRNA regions ofPlantago ovataandP. lagopus, proposed sites of replication pausing atSte20gene locus ofS. cerevisiae,and the bend DNA sequences within fragile site FRA11A in humans. The gene amplification assays showed that plasmid bearing APS from yeast and human beings led to enhanced protein concentration as compared to the wild type. Both thein silicoandin vitroanalyses were pointed out at the strong bending potential of these APS. In addition, high mitotic stability and presence of TTTT repeats and SAR amongst these sequences encourage gene amplification. Phylogenetic analysis ofS. cerevisiaeARS was also conducted. The combinatorial power of different aspects of APS analyzed in the present investigation was harnessed to reach a consensus about the factors which stimulate gene expression, in presence of these sequences. It was concluded that the mechanism of gene amplification was that AT rich tracts present in fragile sites of yeast serve as binding sites for MAR/SAR and DNA unwinding elements. The DNA protein interactions necessary for ORC activation are facilitated by DNA bending. These specific bindings at ORC promote repeated rounds of DNA replication leading to gene amplification.

Different rates of DNA replication at early versus late S-phase sections: multiscale modeling of stochastic events related to DNA content/EdU (5-ethynyl-2'deoxyuridine) incorporation distributions

Mathematical modeling allows relating molecular events to single-cell characteristics assessed by multiparameter cytometry. In the present study we labeled newly synthesized DNA in A549 human lung carcinoma cells with 15-120 min pulses of EdU. All DNA was stained with DAPI and cellular fluorescence was measured by laser scanning cytometry. The frequency of cells in the ascending (left) side of the "horseshoe"-shaped EdU/DAPI bivariate distributions reports the rate of DNA replication at the time of entrance to S phase while their frequency in the descending (right) side is a marker of DNA replication rate at the time of transition from S to G2 phase. To understand the connection between molecular-scale events and scatterplot asymmetry, we developed a multiscale stochastic model, which simulates DNA replication and cell cycle progression of individual cells and produces in silico EdU/DAPI scatterplots. For each S-phase cell the time points at which replication origins are fired are modeled by a non-homogeneous Poisson Process (NHPP). Shifted gamma distributions are assumed for durations of cell cycle phases (G1, S and G2 M), Depending on the rate of DNA synthesis being an increasing or decreasing function, simulated EdU/DAPI bivariate graphs show predominance of cells in left (early-S) or right (late-S) side of the horseshoe distribution. Assuming NHPP rate estimated from independent experiments, simulated EdU/DAPI graphs are nearly indistinguishable from those experimentally observed. This finding proves consistency between the S-phase DNA-replication rate based on molecular-scale analyses, and cell population kinetics ascertained from EdU/DAPI scatterplots and demonstrates that DNA replication rate at entrance to S is relatively slow compared with its rather abrupt termination during S to G2 transition. Our approach opens a possibility of similar modeling to study the effect of anticancer drugs on DNA replication/cell cycle progression and also to quantify other kinetic events that can be measured during S-phase.

A chromatin structure-based model accurately predicts DNA replication timing in human cells

The metazoan genome is replicated in precise cell lineage‐specific temporal order. However, the mechanism controlling this orchestrated process is poorly understood as no molecular mechanisms have been identified that actively regulate the firing sequence of genome replication. Here, we develop a mechanistic model of genome replication capable of predicting, with accuracy rivaling experimental repeats, observed empirical replication timing program in humans. In our model, replication is initiated in an uncoordinated (time‐stochastic) manner at well‐defined sites. The model contains, in addition to the choice of the genomic landmark that localizes initiation, only a single adjustable parameter of direct biological relevance: the number of replication forks. We find that DNase‐hypersensitive sites are optimal and independent determinants of DNA replication initiation. We demonstrate that the DNA replication timing program in human cells is a robust emergent phenomenon that, by its very nature, does not require a regulatory mechanism determining a proper replication initiation firing sequence.

GC-rich DNA elements enable replication origin activity in the methylotrophic yeast Pichia pastoris

The well-studied DNA replication origins of the model budding and fission yeasts are A/T-rich elements. However, unlike their yeast counterparts, both plant and metazoan origins are G/C-rich and are associated with transcription start sites. Here we show that an industrially important methylotrophic budding yeast, Pichia pastoris, simultaneously employs at least two types of replication origins--a G/C-rich type associated with transcription start sites and an A/T-rich type more reminiscent of typical budding and fission yeast origins. We used a suite of massively parallel sequencing tools to map and dissect P. pastoris origins comprehensively, to measure their replication dynamics, and to assay the global positioning of nucleosomes across the genome. Our results suggest that some functional overlap exists between promoter sequences and G/C-rich replication origins in P. pastoris and imply an evolutionary bifurcation of the modes of replication initiation.

Inferring the spatiotemporal DNA replication program from noisy data

We generalize a stochastic model of DNA replication to the case where replication-origin-initiation rates vary locally along the genome and with time. Using this generalized model, we address the inverse problem of inferring initiation rates from experimental data concerning replication in cell populations. Previous work based on curve fitting depended on arbitrarily chosen functional forms for the initiation rate, with free parameters that were constrained by the data. We introduce a nonparametric method of inference that is based on Gaussian process regression. The method replaces specific assumptions about the functional form of the initiation rate with more general prior expectations about the smoothness of variation of this rate, along the genome and in time. Using this inference method, we recover, with high precision, simulated replication schemes from noisy data that are typical of current experiments.

The dynamics of genome replication using deep sequencing

Eukaryotic genomes are replicated from multiple DNA replication origins. We present complementary deep sequencing approaches to measure origin location and activity in Saccharomyces cerevisiae. Measuring the increase in DNA copy number during a synchronous S-phase allowed the precise determination of genome replication. To map origin locations, replication forks were stalled close to their initiation sites; therefore, copy number enrichment was limited to origins. Replication timing profiles were generated from asynchronous cultures using fluorescence-activated cell sorting. Applying this technique we show that the replication profiles of haploid and diploid cells are indistinguishable, indicating that both cell types use the same cohort of origins with the same activities. Finally, increasing sequencing depth allowed the direct measure of replication dynamics from an exponentially growing culture. This is the first time this approach, called marker frequency analysis, has been successfully applied to a eukaryote. These data provide a high-resolution resource and methodological framework for studying genome biology.

Analysis of replication timing using synchronized budding yeast cultures

Eukaryotic DNA replication exhibits at once extraordinary fidelity and substantial plasticity. The importance of the apparent presence of a replication temporal program on a population level has been the subject of intense debate of late. Such debate has been, to a great extent, facilitated by methods that permit the description and analysis of replication dynamics in various model organisms, both globally and at a single-molecule level. Each of these methods provides a unique view of the replication process, and also presents challenges and questions in the interpretation of experimental observations. Thus, wider applications of these methods in different genetic backgrounds and in different organisms would doubtless enable us to better understand the execution and regulation of chromosomal DNA synthesis as well as its impact on genome maintenance.

Accelerated growth in the absence of DNA replication origins

DNA replication initiates at defined sites called origins, which serve as binding sites for initiator proteins that recruit the replicative machinery. Origins differ in number and structure across the three domains of life and their properties determine the dynamics of chromosome replication. Bacteria and some archaea replicate from single origins, whereas most archaea and all eukaryotes replicate using multiple origins. Initiation mechanisms that rely on homologous recombination operate in some viruses. Here we show that such mechanisms also operate in archaea. We use deep sequencing to study replication in Haloferax volcanii and identify four chromosomal origins of differing activity. Deletion of individual origins results in perturbed replication dynamics and reduced growth. However, a strain lacking all origins has no apparent defects and grows significantly faster than wild type. Origin-less cells initiate replication at dispersed sites rather than at discrete origins and have an absolute requirement for the recombinase RadA, unlike strains lacking individual origins. Our results demonstrate that homologous recombination alone can efficiently initiate the replication of an entire cellular genome. This raises the question of what purpose replication origins serve and why they have evolved.

Three wise centromere functions: see no error, hear no break, speak no delay

The main function of the centromere is to promote kinetochore assembly for spindle microtubule attachment. Two additional functions of the centromere, however, are becoming increasingly clear: facilitation of robust sister-chromatid cohesion at pericentromeres and advancement of replication of centromeric regions. The combination of these three centromere functions ensures correct chromosome segregation during mitosis. Here, we review the mechanisms of the kinetochore-microtubule interaction, focusing on sister-kinetochore bi-orientation (or chromosome bi-orientation). We also discuss the biological importance of robust pericentromeric cohesion and early centromere replication, as well as the mechanisms orchestrating these two functions at the microtubule attachment site.

High-resolution replication profiles define the stochastic nature of genome replication initiation and termination

Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.

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Deep sequencing reveals a high-resolution view of genome replication dynamics

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Genome-wide modeling and single-cell imaging reveal stochastic origin activity

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Origin activity determines the location of replication termination events

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Termination events are widely distributed across the whole genome

Human genome replication proceeds through four chromatin states

Advances in genomic studies have led to significant progress in understanding the epigenetically controlled interplay between chromatin structure and nuclear functions. Epigenetic modifications were shown to play a key role in transcription regulation and genome activity during development and differentiation or in response to the environment. Paradoxically, the molecular mechanisms that regulate the initiation and the maintenance of the spatio-temporal replication program in higher eukaryotes, and in particular their links to epigenetic modifications, still remain elusive. By integrative analysis of the genome-wide distributions of thirteen epigenetic marks in the human cell line K562, at the 100 kb resolution of corresponding mean replication timing (MRT) data, we identify four major groups of chromatin marks with shared features. These states have different MRT, namely from early to late replicating, replication proceeds though a transcriptionally active euchromatin state (C1), a repressive type of chromatin (C2) associated with polycomb complexes, a silent state (C3) not enriched in any available marks, and a gene poor HP1-associated heterochromatin state (C4). When mapping these chromatin states inside the megabase-sized U-domains (U-shaped MRT profile) covering about 50% of the human genome, we reveal that the associated replication fork polarity gradient corresponds to a directional path across the four chromatin states, from C1 at U-domains borders followed by C2, C3 and C4 at centers. Analysis of the other genome half is consistent with early and late replication loci occurring in separate compartments, the former correspond to gene-rich, high-GC domains of intermingled chromatin states C1 and C2, whereas the latter correspond to gene-poor, low-GC domains of alternating chromatin states C3 and C4 or long C4 domains. This new segmentation sheds a new light on the epigenetic regulation of the spatio-temporal replication program in human and provides a framework for further studies in different cell types, in both health and disease.

Previous studies revealed spatially coherent and biological-meaningful chromatin mark combinations in human cells. Here, we analyze thirteen epigenetic mark maps in the human cell line K562 at 100 kb resolution of MRT data. The complexity of epigenetic data is reduced to four chromatin states that display remarkable similarities with those reported in fly, worm and plants. These states have different MRT: (C1) is transcriptionally active, early replicating, enriched in CTCF; (C2) is Polycomb repressed, mid-S replicating; (C3) lacks of marks and replicates late and (C4) is a late-replicating gene-poor HP1 repressed heterochromatin state. When mapping these states inside the 876 replication U-domains of K562, the replication fork polarity gradient observed in these U-domains comes along with a remarkable epigenetic organization from C1 at U-domain borders to C2, C3 and ultimately C4 at centers. The remaining genome half displays early replicating, gene rich and high GC domains of intermingled C1 and C2 states segregating from late replicating, gene poor and low GC domains of concatenated C3 and/or C4 states. This constitutes the first evidence of epigenetic compartmentalization of the human genome into replication domains likely corresponding to autonomous units in the 3D chromatin architecture.

Stochastic association of neighboring replicons creates replication factories in budding yeast

Inside the nucleus, DNA replication is organized at discrete sites called replication factories, consisting of DNA polymerases and other replication proteins. Replication factories play important roles in coordinating replication and in responding to replication stress. However, it remains unknown how replicons are organized for processing at each replication factory. Here we address this question using budding yeast. We analyze how individual replicons dynamically organized a replication factory using live-cell imaging and investigate how replication factories were structured using super-resolution microscopy. Surprisingly, we show that the grouping of replicons within factories is highly variable from cell to cell. Once associated, however, replicons stay together relatively stably to maintain replication factories. We derive a coherent genome-wide mathematical model showing how neighboring replicons became associated stochastically to form replication factories, which was validated by independent microscopy-based analyses. This study not only reveals the fundamental principles promoting replication factory organization in budding yeast, but also provides insight into general mechanisms by which chromosomes organize sub-nuclear structures.

DNA replication timing

Patterns of replication within eukaryotic genomes correlate with gene expression, chromatin structure, and genome evolution. Recent advances in genome-scale mapping of replication kinetics have allowed these correlations to be explored in many species, cell types, and growth conditions, and these large data sets have allowed quantitative and computational analyses. One striking new correlation to emerge from these analyses is between replication timing and the three-dimensional structure of chromosomes. This correlation, which is significantly stronger than with any single histone modification or chromosome-binding protein, suggests that replication timing is controlled at the level of chromosomal domains. This conclusion dovetails with parallel work on the heterogeneity of origin firing and the competition between origins for limiting activators to suggest a model in which the stochastic probability of individual origin firing is modulated by chromosomal domain structure to produce patterns of replication. Whether these patterns have inherent biological functions or simply reflect higher-order genome structure is an open question.

A variable fork rate affects timing of origin firing and S phase dynamics in Saccharomyces cerevisiae

Activation (in the following referred to as firing) of replication origins is a continuous and irreversible process regulated by availability of DNA replication molecules and cyclin-dependent kinase activities, which are often altered in human cancers. The temporal, progressive origin firing throughout S phase appears as a characteristic replication profile, and computational models have been developed to describe this process. Although evidence from yeast to human indicates that a range of replication fork rates is observed experimentally in order to complete a timely S phase, those models incorporate velocities that are uniform across the genome. Taking advantage of the availability of replication profiles, chromosomal position and replication timing, here we investigated how fork rate may affect origin firing in budding yeast. Our analysis suggested that patterns of origin firing can be observed from a modulation of the fork rate that strongly correlates with origin density. Replication profiles of chromosomes with a low origin density were fitted with a variable fork rate, whereas for the ones with a high origin density a constant fork rate was appropriate. This indeed supports the previously reported correlation between inter-origin distance and fork rate changes. Intriguingly, the calculated correlation between fork rate and timing of origin firing allowed the estimation of firing efficiencies for the replication origins. This approach correctly retrieved origin efficiencies previously determined for chromosome VI and provided testable prediction for other chromosomal origins. Our results gain deeper insights into the temporal coordination of genome duplication, indicating that control of the replication fork rate is required for the timely origin firing during S phase.

Kinetochores coordinate pericentromeric cohesion and early DNA replication by Cdc7-Dbf4 kinase recruitment

Centromeres play several important roles in ensuring proper chromosome segregation. Not only do they promote kinetochore assembly for microtubule attachment, but they also support robust sister chromatid cohesion at pericentromeres and facilitate replication of centromeric DNA early in S phase. However, it is still elusive how centromeres orchestrate all these functions at the same site. Here, we show that the budding yeast Dbf4-dependent kinase (DDK) accumulates at kinetochores in telophase, facilitated by the Ctf19 kinetochore complex. This promptly recruits Sld3-Sld7 replication initiator proteins to pericentromeric replication origins so that they initiate replication early in S phase. Furthermore, DDK at kinetochores independently recruits the Scc2-Scc4 cohesin loader to centromeres in G1 phase. This enhances cohesin loading and facilitates robust pericentromeric cohesion in S phase. Thus, we have found the central mechanism by which kinetochores orchestrate early S phase DNA replication and robust sister chromatid cohesion at microtubule attachment sites.

Quantitative, genome-wide analysis of eukaryotic replication initiation and termination

Many fundamental aspects of DNA replication, such as the exact locations where DNA synthesis is initiated and terminated, how frequently origins are used, and how fork progression is influenced by transcription, are poorly understood. Via the deep sequencing of Okazaki fragments, we comprehensively document replication fork directionality throughout the S. cerevisiae genome, which permits the systematic analysis of initiation, origin efficiency, fork progression, and termination. We show that leading-strand initiation preferentially occurs within a nucleosome-free region at replication origins. Using a strain in which late origins can be induced to fire early, we show that replication termination is a largely passive phenomenon that does not rely on cis-acting sequences or replication fork pausing. The replication profile is predominantly determined by the kinetics of origin firing, allowing us to reconstruct chromosome-wide timing profiles from an asynchronous culture.

Location, location, location: it's all in the timing for replication origins

The differential replication timing of eukaryotic replication origins has long been linked with epigenetic regulation of gene expression and more recently with genome stability and mutation rates; however, the mechanism has remained obscure. Recent studies have shed new light by identifying novel factors that determine origin timing in yeasts and mammalian cells and implicate the spatial organization of origins within nuclear territories in the mechanism. These new insights, along with recent findings that several initiation factors are limiting relative to licensed origins, support and shape an emerging model for replication timing control. The mechanisms that control the spatial organization of replication origins have potential impacts for genome regulation beyond replication.

The spatiotemporal program of replication in the genome of Lachancea kluyveri

We generated a genome-wide replication profile in the genome of Lachancea kluyveri and assessed the relationship between replication and base composition. This species diverged from Saccharomyces cerevisiae before the ancestral whole genome duplication. The genome comprises eight chromosomes among which a chromosomal arm of 1 Mb has a G + C-content much higher than the rest of the genome. We identified 252 active replication origins in L. kluyveri and found considerable divergence in origin location with S. cerevisiae and with Lachancea waltii. Although some global features of S. cerevisiae replication are conserved: Centromeres replicate early, whereas telomeres replicate late, we found that replication origins both in L. kluyveri and L. waltii do not behave as evolutionary fragile sites. In L. kluyveri, replication timing along chromosomes alternates between regions of early and late activating origins, except for the 1 Mb GC-rich chromosomal arm. This chromosomal arm contains an origin consensus motif different from other chromosomes and is replicated early during S-phase. We showed that precocious replication results from the specific absence of late firing origins in this chromosomal arm. In addition, we found a correlation between GC-content and distance from replication origins as well as a lack of replication-associated compositional skew between leading and lagging strands specifically in this GC-rich chromosomal arm. These findings suggest that the unusual base composition in the genome of L. kluyveri could be linked to replication.

Multiscale analysis of genome-wide replication timing profiles using a wavelet-based signal-processing algorithm

In this protocol, we describe the use of the LastWave open-source signal-processing command language (http://perso.ens-lyon.fr/benjamin.audit/LastWave/) for analyzing cellular DNA replication timing profiles. LastWave makes use of a multiscale, wavelet-based signal-processing algorithm that is based on a rigorous theoretical analysis linking timing profiles to fundamental features of the cell's DNA replication program, such as the average replication fork polarity and the difference between replication origin density and termination site density. We describe the flow of signal-processing operations to obtain interactive visual analyses of DNA replication timing profiles. We focus on procedures for exploring the space-scale map of apparent replication speeds to detect peaks in the replication timing profiles that represent preferential replication initiation zones, and for delimiting U-shaped domains in the replication timing profile. In comparison with the generally adopted approach that involves genome segmentation into regions of constant timing separated by timing transition regions, the present protocol enables the recognition of more complex patterns of the spatio-temporal replication program and has a broader range of applications. Completing the full procedure should not take more than 1 h, although learning the basics of the program can take a few hours and achieving full proficiency in the use of the software may take days.

Mathematical modeling of genome replication

Eukaryotic DNA replication is initiated from multiple sites on the chromosome, but little is known about the global and local regulation of replication. We present a mathematical model for the spatial dynamics of DNA replication, which offers insight into the kinetics of replication in different types of organisms. Most biological experiments involve average quantities over large cell populations (typically >10(7) cells) and therefore can mask the cell-to-cell variability present in the system. Although the model is formulated in terms of a population of cells, using mathematical analysis we show that one can obtain signatures of stochasticity in individual cells from averaged quantities. This work generalizes the result by Retkute et al. [Phys. Rev. Lett. 107, 068103 (2011)] to a broader set of parameter regimes.

Conservation of replication timing reveals global and local regulation of replication origin activity

DNA replication initiates from defined locations called replication origins; some origins are highly active, whereas others are dormant and rarely used. Origins also differ in their activation time, resulting in particular genomic regions replicating at characteristic times and in a defined temporal order. Here we report the comparison of genome replication in four budding yeast species: Saccharomyces cerevisiae, S. paradoxus, S. arboricolus, and S. bayanus. First, we find that the locations of active origins are predominantly conserved between species, whereas dormant origins are poorly conserved. Second, we generated genome-wide replication profiles for each of these species and discovered that the temporal order of genome replication is highly conserved. Therefore, active origins are not only conserved in location, but also in activation time. Only a minority of these conserved origins show differences in activation time between these species. To gain insight as to the mechanisms by which origin activation time is regulated we generated replication profiles for a S. cerevisiae/S. bayanus hybrid strain and find that there are both local and global regulators of origin function.

Inferring where and when replication initiates from genome-wide replication timing data

Based on an analogy between DNA replication and one dimensional nucleation-and-growth processes, various attempts to infer the local initiation rate I(x,t) of DNA replication origins from replication timing data have been developed in the framework of phase transition kinetics theories. These works have all used curve-fit strategies to estimate I(x,t) from genome-wide replication timing data. Here, we show how to invert analytically the Kolmogorov-Johnson-Mehl-Avrami model and extract I(x,t) directly. Tests on both simulated and experimental budding-yeast data confirm the location and firing-time distribution of replication origins.

A quantitative model of the initiation of DNA replication in Saccharomyces cerevisiae predicts the effects of system perturbations

Background

Eukaryotic cell proliferation involves DNA replication, a tightly regulated process mediated by a multitude of protein factors. In budding yeast, the initiation of replication is facilitated by the heterohexameric origin recognition complex (ORC). ORC binds to specific origins of replication and then serves as a scaffold for the recruitment of other factors such as Cdt1, Cdc6, the Mcm2-7 complex, Cdc45 and the Dbf4-Cdc7 kinase complex. While many of the mechanisms controlling these associations are well documented, mathematical models are needed to explore the network’s dynamic behaviour. We have developed an ordinary differential equation-based model of the protein-protein interaction network describing replication initiation.

Results

The model was validated against quantified levels of protein factors over a range of cell cycle timepoints. Using chromatin extracts from synchronized Saccharomyces cerevisiae cell cultures, we were able to monitor the in vivo fluctuations of several of the aforementioned proteins, with additional data obtained from the literature. The model behaviour conforms to perturbation trials previously reported in the literature, and accurately predicts the results of our own knockdown experiments. Furthermore, we successfully incorporated our replication initiation model into an established model of the entire yeast cell cycle, thus providing a comprehensive description of these processes.

Conclusions

This study establishes a robust model of the processes driving DNA replication initiation. The model was validated against observed cell concentrations of the driving factors, and characterizes the interactions between factors implicated in eukaryotic DNA replication. Finally, this model can serve as a guide in efforts to generate a comprehensive model of the mammalian cell cycle in order to explore cancer-related phenotypes.