Projects per year
The replication of DNA is initiated at particular sites on the genome called replication origins (ROs). Understanding the constraints that regulate the distribution of ROs across different organisms is fundamental for quantifying the degree of replication errors and their downstream consequences. Using a simple probabilistic model we generate a set of predictions on the extreme sensitivity of error rates to the distribution of ROs, and how this distribution must therefore be tuned for genomes of vastly different sizes. As genome size changes from Megabases to Gigabases we predict that regularity of RO spacing is lost, that large gaps between ROs dominate error rates but are heavily constrained by the mean stalling distance of replication forks, and that for genomes spanning ~100 Megabases to ~10 Gigabases errors become increasingly inevitable but their number remains very small (three or less). Our theory predicts that the number of errors becomes significantly higher for genome sizes greater than ~10 Gigabases. We test these predictions against datasets in yeast, Arabidopsis, Drosophila and human, and also through direct experimentation on two different human cell lines. Agreement of theoretical predictions with experiment and datasets is found in all cases, resulting in a picture of great simplicity, whereby the density and positioning of ROs explain the replication error rates for the entire range of eukaryotes for which data is available. The theory highlights three domains of error rates: negligible (yeast), tolerable (metazoan) and high (some plants), with the human genome at the extreme end of the middle domain.
|Number of pages||10|
|Journal||Proceedings of the National Academy of Sciences|
|Early online date||14 Sept 2016|
|Publication status||Published - 27 Sept 2016|
- genome length
- replication error
- Poisson distribution
- mathematical modeling
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- 2 Finished
Strategic Award: Wellcome Trust Technology Platform
Blow, J., Lamond, A. & Owen-Hughes, T.
1/01/13 → 30/09/18
Understanding the Cellular Response to Replication Inhibition (Senior Investigator Award)
1/09/12 → 31/08/21