Exact site frequency spectra of neutrally evolving tumors: A transition between power laws reveals a signature of cell viability
Exact site frequency spectra of neutrally evolving tumors: A transition between power laws reveals a signature of cell viability
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DOI：
10.1016/j.tpb.2021.09.004
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发表时间：
2021-10-16
影响因子：
1.4
通讯作者：
Foo, Jasmine
中科院分区：
文献类型：
--
作者：
Gunnarsson, Einar Bjarki;Leder, Kevin;Foo, Jasmine
位点频谱（SFS）是一种流行的基因组数据汇总统计数据。虽然经历中性突变的恒定规模群体的 SFS 已在群体遗传学中得到广泛研究，但快速增长的癌症基因组数据引起了人们对指数增长群体范围的兴趣。最近的理论结果通常涉及特殊或限制情况，例如仅考虑具有无限下降线的细胞，假设确定性肿瘤生长，或采取长时间或大量群体限制。在这项工作中，我们推导出根据随机分支过程进化的细胞群的预期 SFS 的精确表达式，首先针对具有无限下降线的细胞，然后针对总群体，在固定时间（固定时间谱）或群体达到一定大小（固定大小谱）的随机时间进行评估。我们发现，虽然突变率线性地缩放了总种群的 SFS，但细胞出生率和细胞死亡率改变了小频率端的频谱形状，随着细胞活力的降低，引起 1/j(2) 幂律频谱和 1/j 频谱之间的转变。我们表明，这种见解原则上可以用于仅使用位点频谱来估计细胞死亡率和细胞出生率之间的比率以及突变率。尽管讨论是从肿瘤动力学角度进行的，但我们的结果适用于任何呈指数增长的经历中性突变的个体群体。 (C) 2021 Elsevier Inc. 保留所有权利。
The site frequency spectrum (SFS) is a popular summary statistic of genomic data. While the SFS of a constant-sized population undergoing neutral mutations has been extensively studied in population genetics, the rapidly growing amount of cancer genomic data has attracted interest in the spectrum of an exponentially growing population. Recent theoretical results have generally dealt with special or limiting cases, such as considering only cells with an infinite line of descent, assuming deterministic tumor growth, or taking large-time or large-population limits. In this work, we derive exact expressions for the expected SFS of a cell population that evolves according to a stochastic branching process, first for cells with an infinite line of descent and then for the total population, evaluated either at a fixed time (fixed-time spectrum) or at the stochastic time at which the population reaches a certain size (fixed-size spectrum). We find that while the rate of mutation scales the SFS of the total population linearly, the rates of cell birth and cell death change the shape of the spectrum at the small-frequency end, inducing a transition between a 1/j(2) power-law spectrum and a 1/j spectrum as cell viability decreases. We show that this insight can in principle be used to estimate the ratio between the rate of cell death and cell birth, as well as the mutation rate, using the site frequency spectrum alone. Although the discussion is framed in terms of tumor dynamics, our results apply to any exponentially growing population of individuals undergoing neutral mutations. (C) 2021 Elsevier Inc. All rights reserved.