Abstract
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.
Highlights
DNA replication starts at specific locations in the chromosome called replication origins
High-throughput methods have allowed the measurement of replication times as a function of chromosomal position for the whole genome [4]
These experiments yield average replication times over large cell populations and can mask the cell-tocell variability present in the system [5]; to date single cell and single molecule studies are not able to measure the kinetics of whole genome replication [5,6]
Summary
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. High-throughput methods have allowed the measurement of replication times as a function of chromosomal position for the whole genome [4]. We introduce an analytical model of eukaryotic DNA replication which fully takes into account the stochastic nature of both origin activation and the licensing process. Using a simple two-origin chromosome, we illustrate how replication time curves from measurements are influenced by the stochasticity of origin activation as well as by the possibility that licensing fails, reinforcing results we obtained previously by direct simulations [8]
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