Stochastic branching models for the telomeres dynamics in a model including telomerase activity

Athanase BenetosDCAC, Coralie FritschSIMBA, IECL, Emma HortonIRIMAS, ARCHIMEDE, PASTA, Lionel LenotreIRIMAS, ARCHIMEDE, PASTA, Simon ToupanceDCAC, Denis VillemonaisSIMBA, IECL, IUF
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Abstract

Telomeres are repetitive sequences of nucleotides at the end of chromosomes, whose evolution over time is intrinsically related to biological ageing. In most cells, with each cell division, telomeres shorten due to the so-called end replication problem, which can lead to replicative senescence and a variety of age-related diseases. On the other hand, in certain cells, the presence of the enzyme telomerase can lead to the lengthening of telomeres, which may delay or prevent the onset of such diseases but can also increase the risk of cancer.In this article, we propose a stochastic representation of this biological model, which takes into account multiple chromosomes per cell, the effect of telomerase, different cell types and the dependence of the distribution of telomere length on the dynamics of the process. We study theoretical properties of this model, including its long-term behaviour. In addition, we investigate numerically the impact of the model parameters on biologically relevant quantities, such as the Hayflick limit and the Malthusian parameter of the population of cells.
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端粒酶活性模型中端粒动态的随机分支模型
端粒是染色体末端核苷酸的重复序列,其随时间的演变与生物衰老有着内在联系。在大多数细胞中,每次细胞分裂后,端粒都会因所谓的末端复制问题而缩短,这可能导致复制衰老和各种与衰老相关的疾病。另一方面,在某些细胞中,端粒酶的存在会导致端粒的延长,这可能会推迟或预防这类疾病的发生,但也可能会增加患癌症的风险。在这篇文章中,我们提出了这一生物模型的随机表示方法,其中考虑到了每个细胞的多条染色体、端粒酶的作用、不同的细胞类型以及端粒长度分布对过程动态的依赖性。我们研究了这一模型的理论特性,包括其长期行为。此外,我们还研究了模型参数对生物学相关量(如海弗里克极限和细胞数量的马尔萨斯参数)的影响。
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