论文标题
真核DNA复制中复制起源间距的随机模型
Stochastic Models for Replication Origin Spacings in Eukaryotic DNA Replication
论文作者
论文摘要
我们认为真核DNA复制，尤其是复制起源在此过程中的作用。我们专注于“主动”的起源 - 也就是说，在通过其他起源的复制叉阅读之前触发自己的过程。与从随机矩阵理论中获得的某些概率分布相比，我们最初考虑了这些主动复制起源的间距。我们看到来自某些随机矩阵集合中相邻特征值之间的间距如何具有对主动起源之间的间距进行建模的一些潜力。使用均匀的稀疏，可以进一步增强这种适用性，这起到相关特征值间距和指数（泊松式）间距之间的连续变形。我们将该过程建模为一个修改后的2D泊松过程，并具有添加的排除规则，以根据其在染色体上的位置和触发时间相对于其他起源而识别活性点。我们看到如何将其简化为随机的几何问题，并在分析上表明，无论它们之间有多少非活动点，都不太可能在一起。特别是，我们看到这些主动源是如何线性排斥的。然后，我们看到来自各种DNA数据集的数据如何与模型的模拟匹配。我们看到，尽管DNA数据中有多样性，但将数据与模型进行了比较，可以洞悉各种生物体的复制起源分布。
We consider eukaryotic DNA replication and in particular the role of replication origins in this process. We focus on origins which are `active' - that is, trigger themselves in the process before being read by the replication forks of other origins. We initially consider the spacings of these active replication origins in comparison to certain probability distributions of spacings taken from random matrix theory. We see how the spacings between neighbouring eigenvalues from certain collections of random matrices has some potential for modelling the spacing between active origins. This suitability can be further augmented with the use of uniform thinning which acts as a continuous deformation between correlated eigenvalue spacings and exponential (Poissonian) spacings. We model the process as a modified 2D Poisson process with an added exclusion rule to identify active points based on their position on the chromosome and trigger time relative to other origins. We see how this can be reduced to a stochastic geometry problem and show analytically that two active origins are unlikely to be close together, regardless of how many non-active points are between them. In particular, we see how these active origins repel linearly. We then see how data from various DNA datasets match with simulations from our model. We see that whilst there is variety in the DNA data, comparing the data with the model provides insight into the replication origin distribution of various organisms.
