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PNAS Plus: Inevitability and containment of replication errors for eukaryotic genome lengths spanning megabase to gigabase

机译:PNAS Plus:跨兆碱基到千兆碱基的真核基因组长度的必然性和复制错误的遏制

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摘要

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 are 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.
机译:DNA的复制始于基因组上称为复制起点(ROs)的特定位点。理解调节RO在不同生物体中分布的限制因素是量化复制错误及其下游后果的基础。使用简单的概率模型,我们就错误率对RO的分布的极端敏感性以及如何针对非常不同大小的基因组调整此分布产生了一组预测。随着基因组大小从兆碱基到千兆字节的变化,我们预测RO间隔将丢失,RO之间的大间隙占主导地位,但错误率受复制叉的平均停滞距离的严重限制,并且对于跨越〜100兆碱基的基因组约10个千兆字节,错误变得越来越不可避免,但错误数量仍然很小(三个或更少)。我们的理论预测,当基因组大小大于10个千兆位酶时,错误的数量会大大增加。我们针对酵母,拟南芥,果蝇和人类中的数据集测试了这些预测,并且还通过对两种不同的人类细胞系进行直接实验来测试这些预测。在所有情况下都发现理论预测与实验和数据集相吻合,从而产生了极为简单的图景,由此可知,RO的密度和位置解释了可获得数据的整个真核生物范围的复制错误率。该理论强调了错误率的三个域:可忽略的(酵母),可忍受的(metazoan)和高(某些植物),而人类基因组位于中间域的最末端。

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