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We added firing factors that are free to diffuse in the covolume left by the chain and that can bind to proximal p-oris to initiate replication, move along the chromosomes with the replication forks and be released when two fork merges. As shown in Figure 2 a,b for Xenopus embryo and S. These works illustrate that untangling spatio-temporal correlations in replication kinetics is challenging. For example in S. Recently, profiling of replication fork directionality obtained by Okazaki fragment sequencing have suggested that early firing origins located at the border of Topologically Associating Domains TADs trigger a cascade of secondary initiation events propagating through the TAD Petryk et al.

Early and late replicating domains were associated with nuclear compartments of open and closed chromatin Ryba et al. In human, replication timing U-domains 0. Understanding to which extent spatio-temporal correlations of the replication program can be explained by the diffusion of firing factors in the tertiary chromatin structure specific to each eukaryotic organism is a challenging issue for future work. Each model simulation allows the reconstruction of the full replication kinetics during one S-phase.

Chromosome initial replication state is described by the distribution of p-oris along each chromosomes. For Xenopus embryo, p-ori positions are randomly determined at the beginning of each simulation following two possible scenarios:. Within each segment, the position of the origin is chosen randomly in order to avoid spurious synchronization effects.


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For yeast, the p-ori positions are identical in each S-phase simulations and correspond to experimentally determined positions reported in OriDB Siow et al. The simulation starts with a fixed number N D T of firing factors that are progressively made available as described in Results. A random number is generated, and if it is inferior to this probability, an unreplicated p-ori is chosen at random, two diverging forks are created at this locus and the number of free firing factors decreases by 1.

Finally, every fork is propagated by a length v d t resulting in an increase amount of DNA marked as replicated and possibly to the passivation of some p-oris. If two forks meet they are removed and the number of free firing factors increases by 1. Forks that reach the end of a chromosome are discarded. Simulation ends when all DNA has been replicated, which define the replication time. Replication kinetics simulation for the 3D model follows the same steps as in the well-mixed model except that the probability that a free firing factor activates an unreplicated p-ori depends on their distance d obtained from a molecular dynamic simulation performed in parallel to the replication kinetics simulation.

The details of the interaction between the diffusing firing factors and the p-oris is illustrated in Figure 2—figure supplement 1. For each set of parameters of the well-mixed and 3D models, we reported the mean curves obtained over a number of independent simulations large enough so that the noisy fluctuations of the mean I S t are small compared to the average bell-shaped curve. The complete set of parameters for each simulation series is provided in Supplementary file 1.

The scripts used to extract yeast I t from the experimental data of Alvino et al. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "The eukaryotic bell-shaped temporal rate of DNA replication origin firing emanates from a balance between origin activation and passivation" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kevin Struhl as the Senior Editor. The reviewers have opted to remain anonymous. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.


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  • Based on the three positive reviews, it is possible that this model can by published in eLife , but there are some issues that two of the reviewers raise that require a response. Once a response is received, the paper will be re-considered. This appealing paper advances a new hypothesis to explain the observed, apparently quite general phenomenon in eukaryotic replication that the initiation rate of origin firing relative to the amount of unreplicated DNA decreases at the end of S-phase after having increased substantially throughout the first part of S-phase.

    There is agreement on the mechanism of the increase, but three different groups one of which includes two of the present authors have advanced three different hypotheses subdiffusive motion, a dependence on replication fork density of firing factor affinity for p-oris , or inhomogeneous firing probabilities. The present paper proposes a fourth, that the limiting factor is the finite average spacing between potential origins p-oris and makes a case that this new hypothesis is both simple and natural.

    The evidence presented is a mix of heuristic argument, simulation, and a limited comparison of experimental data. The authors further look at a 3d simulation of the diffusion process in a simple model where all origins are treated on an equal footing and find a qualitative agreement in the I t curves. The paper thus gives a simple model that advances our understanding of the replication process, adding a reasonable dynamical model to explain kinetics, and providing at least some experimental support-probably not enough to be completely convincing on its own but enough to make others take the hypothesis seriously and inspire further experimental tests.

    It is thus a nice advance. In that reference, though, Figure 3D shows only that the minimum average distance between fired origins decreases to 3kb. Put another way, the authors argue in the Discussion section second paragraph that their modeling implies that all p-oris are the same.

    Identification of mammalian replication origins

    But in the S. It may be that the model set forth here does a good job explaining the I t dependence but not the full I x,t dependence, where x is the genome position. However, there is also evidence that chromatin looping can inhibit the firing of neighboring origins. Both effects could be present, suggesting that untangling spatiotemporal correlations might be subtle.

    Is this correct? If so, it is surprising, as activation of late-firing origins are suppressed or delayed in HU, and according to Figure 1a, one might expect less origins to be passivated with slower replication forks in HU. The authors need to comment on this.

    The authors need to discuss potential reasons for this. Based on the authors' model that the localization of origins and recycling of replication factors can explain most of DNA replication kinetics, the authors need to discuss how the presence of replication foci would affect origin usage and replication kinetics. This paper should be cited and discussed to compare it to the proposed model. We used as a proxy for the number of potential origins in Xenopus embryo the highest density 0.

    Assuming that a potential origin corresponds to a dimer of MCM hexamers, this experimental quantification provides an estimate of one p-ori every 3 kbp i. Note that in the work of Loveland et al. The 1D simulations as well as the 3D simulations indeed do not consider any heterogeneity between potential origins properties. Hence, neglecting origin passivation, the median firing times for all the origins are identical. Any inhomogeneity in I x,t in our simulations thus reflects the inhomogeneity in the distribution of the potential origins in the genome, and not the heterogeneity of origin strengths.

    We are sorry if our presentation suggested that all yeast origins behave the same. Interestingly, this heterogeneity between origins is captured by the Multiple-Initiator Model MIM where origin firing time distribution is modeled by the number of MCM complexes bound at the origin Yang et al. In these models, MCM and ORC have the same status as our p-oris, they are potential origins with identical firing properties.

    However, Gindin et al. These two modeling works illustrate that indeed untangling spatio-temporal correlations in replication kinetics is challenging. In that respect, 3D modeling explicitly taking into account the transport of firing factors will allow us to quantify the contribution of physicochemistry to replication spatio-temporal correlations and in turn underline the requirement for specific biological mechanisms.

    In our model, during the second part of S-phase when most firing factors are free, the dynamics of activation of p-oris is controlled by the productive-interaction rate k on between a free firing factor and a p-ori so that a reduced replication speed will indeed result in firing of most late p-oris and thus a very low frequency of origin passivation. However, Alvino et al. Up to a rescaling of time, the replication kinetics of our model is governed by the ratio between replication fork speed and k on neglecting here the possible contribution of the activation dynamics of firing factors.

    Up to a rescaling of time, the replication kinetics of our model is governed by the ratio between replication fork speed and the productive-interaction rate k on neglecting here the possible contribution of the activation dynamics of firing factors. Hence, our model can capture the main observation of Alvino et al. We agree that dubious origins are not expected to fire as frequently as Confirmed and Likely origins. A number of scenarios can contribute to the requirement for a larger number of potential origins than the number of Confirmed and Likely origins.

    In the model we used a value of 1. The modeling in this work is performed under the assumption of a well-mixed system. It thus does not address the effect of the presence of replication foci. Replication foci would locally enhance the concentration in firing factors once released from the merging of two forks. Matthew Meselson — and Franklin Stahl — devised an experiment in to test which of these models correctly represents DNA replication Figure They grew E.

    This labeled the parental DNA.

    Archaeology of Eukaryotic DNA Replication

    The E. The cells were harvested and the DNA was isolated. DNA grown in 15 N would be expected to form a band at a higher density position than that grown in 14 N. Meselson and Stahl noted that after one generation of growth in 14 N, the single band observed was intermediate in position in between DNA of cells grown exclusively in 15 N or 14 N.

    This suggested either a semiconservative or dispersive mode of replication. Some cells were allowed to grow for one more generation in 14 N and spun again. These results could only be explained if DNA replicates in a semiconservative manner. Therefore, the other two models were ruled out.

    As a result of this experiment, we now know that during DNA replication, each of the two strands that make up the double helix serves as a template from which new strands are copied. The resulting DNA molecules have the same sequence and are divided equally into the two daughter cells. DNA replication has been well studied in bacteria primarily because of the small size of the genome and the mutants that are available. This means that approximately nucleotides are added per second. The process is quite rapid and occurs with few errors.

    DNA replication uses a large number of proteins and enzymes Table The addition of these nucleotides requires energy. This energy is present in the bonds of three phosphate groups attached to each nucleotide a triphosphate nucleotide , similar to how energy is stored in the phosphate bonds of adenosine triphosphate ATP Figure The initiation of replication occurs at specific nucleotide sequence called the origin of replication, where various proteins bind to begin the replication process.

    The origin of replication is approximately base pairs long and is rich in adenine-thymine AT sequences. Some of the proteins that bind to the origin of replication are important in making single-stranded regions of DNA accessible for replication. Chromosomal DNA is typically wrapped around histones in eukaryotes and archaea or histone-like proteins in bacteria , and is supercoiled, or extensively wrapped and twisted on itself.

    This packaging makes the information in the DNA molecule inaccessible. However, enzymes called topoisomerases change the shape and supercoiling of the chromosome. An enzyme called helicase then separates the DNA strands by breaking the hydrogen bonds between the nitrogenous base pairs. Recall that AT sequences have fewer hydrogen bonds and, hence, have weaker interactions than guanine-cytosine GC sequences.

    These enzymes require ATP hydrolysis. As the DNA opens up, Y-shaped structures called replication forks are formed. Two replication forks are formed at the origin of replication, allowing for bidirectional replication and formation of a structure that looks like a bubble when viewed with a transmission electron microscope; as a result, this structure is called a replication bubble.

    The DNA near each replication fork is coated with single-stranded binding proteins to prevent the single-stranded DNA from rewinding into a double helix. Because this sequence allows the start of DNA synthesis, it is appropriately called the primer. The primer is five to 10 nucleotides long and complementary to the parental or template DNA. During elongation in DNA replication, the addition of nucleotides occurs at its maximal rate of about nucleotides per second.

    This continuously synthesized strand is known as the leading strand. It does so until it bumps into the previously synthesized strand and then it moves back again Figure Okazaki fragments are named after the Japanese research team and married couple Reiji and Tsuneko Okazaki , who first discovered them in The strand with the Okazaki fragments is known as the lagging strand, and its synthesis is said to be discontinuous.

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