Mathematical modelling of eukaryotic DNA replication

Restricting the level of the proteins essential for the regulation of the initiation step of replication extends the chronological lifespan and reproductive potential in budding yeast

Aging is defined as a progressive decline in physiological integrity, leading to impaired biological function, including fertility, and rising vulnerability to death. Disorders of DNA replication often lead to replication stress and are identified as factors influencing the aging rate. In this study, we aimed to reveal how the cells that lost strict control of the formation of crucial for replication initiation a pre-initiation complex impact the cells' physiology and aging. As strains with the lower pre-IC control (lowPICC) we used, Saccharomyces cerevisiae heterozygous strains having only one functional copy of genes, encoding essential replication proteins such as Cdc6, Dbf4, Sld3, Sld7, Sld2, and Mcm10. The lowPICC strains exhibited a significant reduction in the respective genes' mRNA levels, causing cell cycle aberrations and doubling time extensions. Additionally, the reduced expression of the lowPICC genes led to an aberrant DNA damage response, affected cellular and mitochondrial DNA content, extended the lifespan of post-mitotic cells, and increased the yeast's reproductive potential. Importantly, we also demonstrated a strong negative correlation between the content of cellular macromolecules (RNA, proteins, lipids, polysaccharides) and aging. The data presented here will likely contribute to the future development of therapies for treating various human diseases.

A Decade of Discovery-Eukaryotic Replisome Disassembly at Replication Termination

The eukaryotic replicative helicase (CMG complex) is assembled during DNA replication initiation in a highly regulated manner, which is described in depth by other manuscripts in this Issue. During DNA replication, the replicative helicase moves through the chromatin, unwinding DNA and facilitating nascent DNA synthesis by polymerases. Once the duplication of a replicon is complete, the CMG helicase and the remaining components of the replisome need to be removed from the chromatin. Research carried out over the last ten years has produced a breakthrough in our understanding, revealing that replication termination, and more specifically replisome disassembly, is indeed a highly regulated process. This review brings together our current understanding of these processes and highlights elements of the mechanism that are conserved or have undergone divergence throughout evolution. Finally, we discuss events beyond the classic termination of DNA replication in S-phase and go over the known mechanisms of replicative helicase removal from chromatin in these particular situations.

Rpd3 regulates single-copy origins independently of the rDNA array by opposing Fkh1-mediated origin stimulation

The faithful replication of eukaryotic genomes requires balancing the replication capacities of different genomic regions, such as repetitive versus single-copy genetic elements, which may compete for limiting replication resources, possibly leading to replication stress and genome instability. We examined the function of histone deacetylases Rpd3 and Sir2 in balancing replication between unique genome sequences and the multicopy ribosomal DNA genes. Our findings support prior conclusions that Sir2 directly suppresses early firing of rDNA origins, thereby enabling balanced replication of the genome. We further show that Rpd3’s function in delaying firing of later-firing, single-copy origins is independent of Sir2 and rDNA load. Instead, Rpd3 appears to oppose the Fkh1/2 origin activation pathway by regulating binding of the origin-stimulator Fkh1.

Eukaryotic chromosomes are organized into structural and functional domains with characteristic replication timings, which are thought to contribute to epigenetic programming and genome stability. Differential replication timing results from epigenetic mechanisms that positively and negatively regulate the competition for limiting replication initiation factors. Histone deacetylase Sir2 negatively regulates initiation of the multicopy (∼150) rDNA origins, while Rpd3 histone deacetylase negatively regulates firing of single-copy origins. However, Rpd3’s effect on single-copy origins might derive indirectly from a positive function for Rpd3 in rDNA origin firing shifting the competitive balance. Our quantitative experiments support the idea that origins compete for limiting factors; however, our results show that Rpd3’s effect on single-copy origin is independent of rDNA copy-number and of Sir2’s effects on rDNA origin firing. Whereas RPD3 deletion and SIR2 deletion alter the early S phase dynamics of single-copy and rDNA origin firings in opposite fashion, unexpectedly only RPD3 deletion suppresses overall rDNA origin efficiency across S phase. Increased origin activation in rpd3Δ requires Fkh1/2, suggesting that Rpd3 opposes Fkh1/2-origin stimulation, which involves recruitment of Dbf4-dependent kinase (DDK). Indeed, Fkh1 binding increases at Rpd3-regulated origins in rpd3Δ cells in G1, supporting a mechanism whereby Rpd3 influences initiation timing of single-copy origins directly through modulation of Fkh1-origin binding. Genetic suppression of a DBF4 hypomorphic mutation by RPD3 deletion further supports the conclusion that Rpd3 impedes DDK recruitment by Fkh1, revealing a mechanism of Rpd3 in origin regulation.

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.

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.

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.

Replicon: a software to accurately predict DNA replication timing in metazoan cells

Eukaryotic DNA replication follows a strict temporal program where genomic loci are replicated at precise times during the S phase of the cell cycle. Yet, the mechanism in control of the timing program in metazoan cells is poorly understood. In a recent publication, the authors proposed an intuitive stochastic model of DNA replication and showed that it predicts replication timing with an accuracy approaching the level of experimental biological repeats. Here, we discuss an extended software implementation of the mechanistic model: Replicon. This package allows interested researchers to predict the global replication timing program in human cells from chromatin data.

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.

DNA replication and spindle checkpoints cooperate during S phase to delay mitosis and preserve genome integrity

Deoxyribonucleic acid (DNA) replication and chromosome segregation must occur in ordered sequence to maintain genome integrity during cell proliferation. Checkpoint mechanisms delay mitosis when DNA is damaged or upon replication stress, but little is known on the coupling of S and M phases in unperturbed conditions. To address this issue, we postponed replication onset in budding yeast so that DNA synthesis is still underway when cells should enter mitosis. This delayed mitotic entry and progression by transient activation of the S phase, G2/M, and spindle assembly checkpoints. Disabling both Mec1/ATR- and Mad2-dependent controls caused lethality in cells with deferred S phase, accompanied by Rad52 foci and chromosome missegregation. Thus, in contrast to acute replication stress that triggers a sustained Mec1/ATR response, multiple pathways cooperate to restrain mitosis transiently when replication forks progress unhindered. We suggest that these surveillance mechanisms arose when both S and M phases were coincidently set into motion by a unique ancestral cyclin-Cdk1 complex.

Epigenetic landscape for initiation of DNA replication

The key genetic process of DNA replication is initiated at specific sites referred to as replication origins. In eukaryotes, origins of DNA replication are not specified by a defined nucleotide sequence. Recent studies have shown that the structural context and topology of DNA sequence, chromatin features, and its transcriptional activity play an important role in origin choice. During differentiation and development, significant changes in chromatin organization and transcription occur, influencing origin activity and choice. In the last few years, a number of different genome-wide studies have broadened the understanding of replication origin regulation. In this review, we discuss the epigenetic factors and mechanisms that modulate origin choice and firing.

From simple bacterial and archaeal replicons to replication N/U-domains

The Replicon Theory proposed 50 years ago has proven to apply for replicons of the three domains of life. Here, we review our knowledge of genome organization into single and multiple replicons in bacteria, archaea and eukarya. Bacterial and archaeal replicator/initiator systems are quite specific and efficient, whereas eukaryotic replicons show degenerate specificity and efficiency, allowing for complex regulation of origin firing time. We expand on recent evidence that ~50% of the human genome is organized as ~1,500 megabase-sized replication domains with a characteristic parabolic (U-shaped) replication timing profile and linear (N-shaped) gradient of replication fork polarity. These N/U-domains correspond to self-interacting segments of the chromatin fiber bordered by open chromatin zones and replicate by cascades of origin firing initiating at their borders and propagating to their center, possibly by fork-stimulated initiation. The conserved occurrence of this replication pattern in the germline of mammals has resulted over evolutionary times in the formation of megabase-sized domains with an N-shaped nucleotide compositional skew profile due to replication-associated mutational asymmetries. Overall, these results reveal an evolutionarily conserved but developmentally plastic organization of replication that is driving mammalian genome evolution.

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.

Back to the origin: reconsidering replication, transcription, epigenetics, and cell cycle control

In bacteria, replication is a carefully orchestrated event that unfolds the same way for each bacterium and each cell division. The process of DNA replication in bacteria optimizes cell growth and coordinates high levels of simultaneous replication and transcription. In metazoans, the organization of replication is more enigmatic. The lack of a specific sequence that defines origins of replication has, until recently, severely limited our ability to define the organizing principles of DNA replication. This question is of particular importance as emerging data suggest that replication stress is an important contributor to inherited genetic damage and the genomic instability in tumors. We consider here the replication program in several different organisms including recent genome-wide analyses of replication origins in humans. We review recent studies on the role of cytosine methylation in replication origins, the role of transcriptional looping and gene gating in DNA replication, and the role of chromatin's 3-dimensional structure in DNA replication. We use these new findings to consider several questions surrounding DNA replication in metazoans: How are origins selected? What is the relationship between replication and transcription? How do checkpoints inhibit origin firing? Why are there early and late firing origins? We then discuss whether oncogenes promote cancer through a role in DNA replication and whether errors in DNA replication are important contributors to the genomic alterations and gene fusion events observed in cancer. We conclude with some important areas for future experimentation.

Replication dynamics: biases and robustness of DNA fiber analysis

The factors that govern replication programs are still poorly identified in metazoans, especially in mammalian cells. Thanks to molecular combing, the dynamics of DNA replication can be assessed at the genome-scale level from the cumulative analysis of single DNA fibers. This technique notably enables measurement of replication fork speed and fork asymmetry and that of distances separating either initiation or termination events. The results presented here aim to evaluate requirements critical to accurate measurement of replication parameters by molecular combing. We show that sample size, fiber length and DNA counterstaining are crucial to gain robust information concerning replication dynamics. Our results thus provide a methodological frame to investigate the DNA replication program through molecular combing analyses.

Megabase replication domains along the human genome: relation to chromatin structure and genome organisation

In higher eukaryotes, the absence of specific sequence motifs, marking the origins of replication has been a serious hindrance to the understanding of (i) the mechanisms that regulate the spatio-temporal replication program, and (ii) the links between origins activation, chromatin structure and transcription. In this chapter, we review the partitioning of the human genome into megabased-size replication domains delineated as N-shaped motifs in the strand compositional asymmetry profiles. They collectively span 28.3% of the genome and are bordered by more than 1,000 putative replication origins. We recapitulate the comparison of this partition of the human genome with high-resolution experimental data that confirms that replication domain borders are likely to be preferential replication initiation zones in the germline. In addition, we highlight the specific distribution of experimental and numerical chromatin marks along replication domains. Domain borders correspond to particular open chromatin regions, possibly encoded in the DNA sequence, and around which replication and transcription are highly coordinated. These regions also present a high evolutionary breakpoint density, suggesting that susceptibility to breakage might be linked to local open chromatin fiber state. Altogether, this chapter presents a compartmentalization of the human genome into replication domains that are landmarks of the human genome organization and are likely to play a key role in genome dynamics during evolution and in pathological situations.

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.

Regulation of DNA replication within the immunoglobulin heavy-chain locus during B cell commitment

The temporal order of replication of mammalian chromosomes appears to be linked to their functional organization, but the process that establishes and modifies this order during cell differentiation remains largely unknown. Here, we studied how the replication of the Igh locus initiates, progresses, and terminates in bone marrow pro-B cells undergoing B cell commitment. We show that many aspects of DNA replication can be quantitatively explained by a mechanism involving the stochastic firing of origins (across the S phase and the Igh locus) and extensive variations in their firing rate (along the locus). The firing rate of origins shows a high degree of coordination across Igh domains that span tens to hundreds of kilobases, a phenomenon not observed in simple eukaryotes. Differences in domain sizes and firing rates determine the temporal order of replication. During B cell commitment, the expression of the B-cell-specific factor Pax5 sharply alters the temporal order of replication by modifying the rate of origin firing within various Igh domains (particularly those containing Pax5 binding sites). We propose that, within the Igh C_H-3′RR domain, Pax5 is responsible for both establishing and maintaining high rates of origin firing, mostly by controlling events downstream of the assembly of pre-replication complexes.

Each time a mammalian cell duplicates its genome in preparation for cell division it activates thousands of so called “DNA origins of replication.” The timely and complete duplication of the genome depends on careful orchestration of origin activation, which is modified when cells differentiate to perform a specific function. We currently lack a universally accepted model of origin regulation that can explain the replication dynamics in complex eukaryotes. Here, we studied the mouse immunoglobulin heavy-chain locus, one of the antibody-encoding portions of the genome, where origins change activity when antibody-producing B cells differentiate in the bone marrow. We show that multiple aspects of DNA replication initiation, progression, and termination can be explained mathematically by the interplay between randomly firing origins and two independent variables: the speed of progression of replication forks and the firing rate of origins along the locus. The rate of origin firing varies extensively along the locus during B cell differentiation and, thus, is a dominant factor in establishing the temporal order of replication. A differentiation factor called Pax5 can alter the temporal order of replication by modifying the rate of origin firing across various parts of the locus.

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.

Optimal placement of origins for DNA replication

DNA replication is an essential process in biology and its timing must be robust so that cells can divide properly. Random fluctuations in the formation of replication starting points, called origins, and the subsequent activation of proteins lead to variations in the replication time. We analyze these stochastic properties of DNA and derive the positions of origins corresponding to the minimum replication time. We show that under some conditions the minimization of replication time leads to the grouping of origins, and relate this to experimental data in a number of species showing origin grouping.

Evidence for sequential and increasing activation of replication origins along replication timing gradients in the human genome

Genome-wide replication timing studies have suggested that mammalian chromosomes consist of megabase-scale domains of coordinated origin firing separated by large originless transition regions. Here, we report a quantitative genome-wide analysis of DNA replication kinetics in several human cell types that contradicts this view. DNA combing in HeLa cells sorted into four temporal compartments of S phase shows that replication origins are spaced at 40 kb intervals and fire as small clusters whose synchrony increases during S phase and that replication fork velocity (mean 0.7 kb/min, maximum 2.0 kb/min) remains constant and narrowly distributed through S phase. However, multi-scale analysis of a genome-wide replication timing profile shows a broad distribution of replication timing gradients with practically no regions larger than 100 kb replicating at less than 2 kb/min. Therefore, HeLa cells lack large regions of unidirectional fork progression. Temporal transition regions are replicated by sequential activation of origins at a rate that increases during S phase and replication timing gradients are set by the delay and the spacing between successive origin firings rather than by the velocity of single forks. Activation of internal origins in a specific temporal transition region is directly demonstrated by DNA combing of the IGH locus in HeLa cells. Analysis of published origin maps in HeLa cells and published replication timing and DNA combing data in several other cell types corroborate these findings, with the interesting exception of embryonic stem cells where regions of unidirectional fork progression seem more abundant. These results can be explained if origins fire independently of each other but under the control of long-range chromatin structure, or if replication forks progressing from early origins stimulate initiation in nearby unreplicated DNA. These findings shed a new light on the replication timing program of mammalian genomes and provide a general model for their replication kinetics.

Eukaryotic chromosomes replicate from multiple replication origins that fire at different times in S phase. The mechanisms that specify origin position and firing time and coordinate origins to ensure complete genome duplication are unclear. Previous studies proposed either that origins are arranged in temporally coordinated groups or fire independently of each other in a stochastic manner. Here, we have performed a quantitative analysis of human genome replication kinetics using a combination of DNA combing, which reveals local patterns of origin firing and replication fork progression on single DNA molecules, and massive sequencing of newly replicated DNA, which reveals the population-averaged replication timing profile of the entire genome. We show that origins are activated synchronously in large regions of uniform replication timing but more gradually in temporal transition regions and that the rate of origin firing increases as replication progresses. Large regions of unidirectional fork progression are abundant in embryonic stem cells but rare in differentiated cells. We propose a model in which replication forks progressing from early origins stimulate initiation in nearby unreplicated DNA in a manner that explains the shape of the replication timing profile. These results provide a fundamental insight into the temporal regulation of mammalian genome replication.

Do replication forks control late origin firing in Saccharomyces cerevisiae?

Recent studies of eukaryotic DNA replication timing profiles suggest that the time-dependent rate of origin firing, I(t), has a universal shape, which ensures a reproducible replication completion time. However, measurements of I(t) are based on population averages, which may bias the shape of the I(t) because of imperfect cell synchrony and cell-to-cell variability. Here, we measure the population-averaged I(t) profile from synchronized Saccharomyces cerevisiae cells using DNA combing and we extract the single-cell I(t) profile using numerical deconvolution. The single cell I(t) and the population-averaged I(t) extracted from DNA combing and replication timing profiles are similar, indicating a genome scale invariance of the replication process, and excluding cell-to-cell variability in replication time as an explanation for the shape of I(t). The single cell I(t) correlates with fork density in wild-type cells, which is specifically loosened in late S phase in the clb5Δ mutant. A previously proposed numerical model that reproduces the wild-type I(t) profile, could also describe the clb5Δ mutant I(t) once modified to incorporate the decline in CDK activity and the looser dependency of initiation on fork density in the absence of Clb5p. Overall, these results suggest that the replication forks emanating from early fired origins facilitate origin firing in later-replicating regions.

Gene regulation: implications of histone dispersal patterns for epigenetics

Histones are widely believed to carry regulatory information across cell generations. A recent study suggests limits to this model by measuring dispersal of ancestral histones in yeast.

Dynamics of DNA replication in yeast

We present a mathematical model for the spatial dynamics of DNA replication. Using this model we determine the probability distribution for the time at which each chromosomal position is replicated. From this we show, contrary to previous reports, that mean replication time curves cannot be used to directly determine origin parameters. We demonstrate that the stochastic nature of replication dynamics leaves a clear signature in experimentally measured population average data, and we show that the width of the activation time probability distribution can be inferred from this data. Our results compare favorably with experimental measurements in Saccharomyces cerevisae.

Replication origins and timing of temporal replication in budding yeast: how to solve the conundrum?

Similarly to metazoans, the budding yeast Saccharomyces cereviasiae replicates its genome with a defined timing. In this organism, well-defined, site-specific origins, are efficient and fire in almost every round of DNA replication. However, this strategy is neither conserved in the fission yeast Saccharomyces pombe, nor in Xenopus or Drosophila embryos, nor in higher eukaryotes, in which DNA replication initiates asynchronously throughout S phase at random sites. Temporal and spatial controls can contribute to the timing of replication such as Cdk activity, origin localization, epigenetic status or gene expression. However, a debate is going on to answer the question how individual origins are selected to fire in budding yeast. Two opposing theories were proposed: the "replicon paradigm" or "temporal program" vs. the "stochastic firing". Recent data support the temporal regulation of origin activation, clustering origins into temporal blocks of early and late replication. Contrarily, strong evidences suggest that stochastic processes acting on origins can generate the observed kinetics of replication without requiring a temporal order. In mammalian cells, a spatiotemporal model that accounts for a partially deterministic and partially stochastic order of DNA replication has been proposed. Is this strategy the solution to reconcile the conundrum of having both organized replication timing and stochastic origin firing also for budding yeast? In this review we discuss this possibility in the light of our recent study on the origin activation, suggesting that there might be a stochastic component in the temporal activation of the replication origins, especially under perturbed conditions.

Evaluating genome-scale approaches to eukaryotic DNA replication

Mechanisms regulating where and when eukaryotic DNA replication initiates remain a mystery. Recently, genome-scale methods have been brought to bear on this problem. The identification of replication origins and their associated proteins in yeasts is a well-integrated investigative tool, but corresponding data sets from multicellular organisms are scarce. By contrast, standardized protocols for evaluating replication timing have generated informative data sets for most eukaryotic systems. Here, I summarize the genome-scale methods that are most frequently used to analyse replication in eukaryotes, the kinds of questions each method can address and the technical hurdles that must be overcome to gain a complete understanding of the nature of eukaryotic replication origins.

Modeling genome-wide replication kinetics reveals a mechanism for regulation of replication timing

Microarrays are powerful tools to probe genome-wide replication kinetics. The rich data sets that result contain more information than has been extracted by current methods of analysis. In this paper, we present an analytical model that incorporates probabilistic initiation of origins and passive replication. Using the model, we performed least-squares fits to a set of recently published time course microarray data on Saccharomyces cerevisiae. We extracted the distribution of firing times for each origin and found that the later an origin fires on average, the greater the variation in firing times. To explain this trend, we propose a model where earlier-firing origins have more initiator complexes loaded and a more accessible chromatin environment. The model demonstrates how initiation can be stochastic and yet occur at defined times during S phase, without an explicit timing program. Furthermore, we hypothesize that the initiators in this model correspond to loaded minichromosome maintenance complexes. This model is the first to suggest a detailed, testable, biochemically plausible mechanism for the regulation of replication timing in eukaryotes.

S-phase progression in mammalian cells: modelling the influence of nuclear organization

The control of DNA replication is of fundamental importance as cell proliferation demands that identical copies of the genetic material are passed to the two daughter cells that form during mitosis. These genetic copies are generated in the preceding S phase, where the entire DNA complement of the mother cell must be copied exactly once. As part of this process, it is known that different regions of mammalian genomes are replicated at specific times of a temporally defined replication programme. The key feature of this programme is that active genes in euchromatin are replicated before inactive ones in heterochromatin. This separation of S phase into periods where different classes of chromatin are duplicated is important in maintaining changes in gene expression that define individual cell types. Recent attempts to understand the structure of the S-phase timing programme have focused on the use of genome-wide strategies that inevitably use DNA isolated from large cell populations for analysis. However, this approach provides a composite view of events that occur within a population without knowledge of the cell-to-cell variability across the population. In this review, we attempt to combine information generated using genome-wide and single cell strategies in order to develop a coherent molecular understanding of S-phase progression. During this integration, we have explored how available information can be introduced into a modelling environment that best describes S-phase progression in mammalian cells.