School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK.
Mathematics Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK.
J Math Biol. 2020 Mar;80(4):1039-1076. doi: 10.1007/s00285-019-01448-y. Epub 2019 Nov 14.
Telomeres are repetitive DNA sequences located at the ends of chromosomes. During cell division, an incomplete copy of each chromosome's DNA is made, causing telomeres to shorten on successive generations. When a threshold length is reached replication ceases and the cell becomes 'senescent'. In this paper, we consider populations of telomeres and, from discrete models, we derive partial differential equations which describe how the distribution of telomere lengths evolves over many generations. We initially consider a population of cells each containing just a single telomere. We use continuum models to compare the effects of various mechanisms of telomere shortening and rates of cell division during normal ageing. For example, the rate (or probability) of cell replication may be fixed or it may decrease as the telomeres shorten. Furthermore, the length of telomere lost on each replication may be constant, or may decrease as the telomeres shorten. Where possible, explicit solutions for the evolution of the distribution of telomere lengths are presented. In other cases, expressions for the mean of the distribution are derived. We extend the models to describe cell populations in which each cell contains a distinct subpopulation of chromosomes. As for the simpler models, constant telomere shortening leads to a linear reduction in telomere length over time, whereas length-dependent shortening results in initially rapid telomere length reduction, slowing at later times. Our analysis also reveals that constant telomere loss leads to a Gaussian (normal) distribution of telomere lengths, whereas length-dependent loss leads to a log-normal distribution. We show that stochastic models, which include a replication probability, also lead to telomere length distributions which are skewed.
端粒是位于染色体末端的重复 DNA 序列。在细胞分裂过程中,每个染色体的 DNA 都会复制不完全,导致端粒在连续的几代中缩短。当达到一个阈值长度时,复制停止,细胞变得“衰老”。在本文中,我们考虑端粒群体,并从离散模型中推导出描述端粒长度在多次世代中如何演变的偏微分方程。我们最初考虑一个含有单个端粒的细胞群体。我们使用连续体模型来比较各种端粒缩短机制和正常衰老过程中细胞分裂速度的影响。例如,细胞复制的速率(或概率)可以是固定的,也可以随着端粒缩短而降低。此外,每次复制丢失的端粒长度可能是恒定的,也可能随着端粒缩短而降低。在可能的情况下,我们给出了端粒长度分布演变的显式解。在其他情况下,我们推导出了分布均值的表达式。我们将模型扩展到描述每个细胞都包含独特染色体亚群的细胞群体。与更简单的模型一样,恒定的端粒缩短会导致端粒长度随时间线性减少,而依赖长度的缩短会导致端粒长度在初始时迅速减少,随后减慢。我们的分析还表明,恒定的端粒损失会导致端粒长度呈高斯(正态)分布,而依赖长度的损失会导致对数正态分布。我们表明,包括复制概率在内的随机模型也会导致端粒长度分布呈偏态。