ArticlePloS one2012
Modeling inhomogeneous DNA replication kinetics.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- RepliSage: a stochastic graph-based framework for 3D chromatin modeling across the cell cycle.Nucleic acids research · 2026Article
- Model-based inference of cell cycle dynamics captures alterations of the DNA replication programme.PLoS computational biology · 2025Article
- Modeling the Dynamics of Eukaryotic DNA Synthesis in Remembrance of Tunde Ogunnaike.Industrial & engineering chemistry research · 2023Article
- Article
- Stochasticity of replication forks' speeds plays a key role in the dynamics of DNA replication.PLoS computational biology · 2019Article
- Molecular Mechanisms of DNA Replication and Repair Machinery: Insights from Microscopic Simulations.Advanced theory and simulations · 2019Article
- Peaks cloaked in the mist: the landscape of mammalian replication origins.The Journal of cell biology · 2015Review
- Replisome stall events have shaped the distribution of replication origins in the genomes of yeasts.Nucleic acids research · 2013Article
- DNA replication timing.Cold Spring Harbor perspectives in biology · 2013Review
- Multiscale analysis of genome-wide replication timing profiles using a wavelet-based signal-processing algorithm.Nature protocols · 2013Article
- Replication timing and its emergence from stochastic processes.Trends in genetics : TIG · 2012Review
- Regulation of DNA replication within the immunoglobulin heavy-chain locus during B cell commitment.PLoS biology · 2012Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In eukaryotic organisms, DNA replication is initiated at a series of chromosomal locations called origins, where replication forks are assembled proceeding bidirectionally to replicate the genome. The distribution and firing rate of these origins, in conjunction with the velocity at which forks progress, dictate the program of the replication process. Previous attempts at modeling DNA replication in eukaryotes have focused on cases where the firing rate and the velocity of replication forks are homogeneous, or uniform, across the genome. However, it is now known that there are large variations in origin activity along the genome and variations in fork velocities can also take place. Here, we generalize previous approaches to modeling replication, to allow for arbitrary spatial variation of initiation rates and fork velocities. We derive rate equations for left- and right-moving forks and for replication probability over time that can be solved numerically to obtain the mean-field replication program. This method accurately reproduces the results of DNA replication simulation. We also successfully adapted our approach to the inverse problem of fitting measurements of DNA replication performed on single DNA molecules. Since such measurements are performed on specified portion of the genome, the examined DNA molecules may be replicated by forks that originate either within the studied molecule or outside of it. This problem was solved by using an effective flux of incoming replication forks at the model boundaries to represent the origin activity outside the studied region. Using this approach, we show that reliable inferences can be made about the replication of specific portions of the genome even if the amount of data that can be obtained from single-molecule experiments is generally limited.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.