Evolutionary dynamics in hematopoiesis Cells accumulate mutations as we age, and these mutations can be a source of diseases such as cancer. How cells containing mutations evolve, are maintained, and proliferate within the body has not been well characterized. Using a quantitative framework, Watson et al. applied population genetic theory to estimate mutation accumulation in cells in blood from sequencing data derived from nearly 50,000 healthy individuals (see the Perspective by Curtis). By evaluating how mutations differ between blood cell populations, a phenomenon known as clonal hematopoiesis, the researchers could observe how recurrent mutations can drive certain clonal lineages to high frequencies within an individual. The risk of specific mutations, some of which are associated with leukemias, rising to high frequencies may therefore be a function of cellular selection and the age at which the mutation originated. Science, this issue p. 1449; see also p. 1426 Blood sequencing data from ~50,000 individuals reveals how mutation, genetic drift, and fitness differences shape the diversity of healthy blood. Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance remains largely unknown. Blood sequencing data from ~50,000 individuals reveal how mutation, genetic drift, and fitness shape the genetic diversity of healthy blood (clonal hematopoiesis). We show that positive selection, not drift, is the major force shaping clonal hematopoiesis, provide bounds on the number of hematopoietic stem cells, and quantify the fitness advantages of key pathogenic variants, at single-nucleotide resolution, as well as the distribution of fitness effects (fitness landscape) within commonly mutated driver genes. These data are consistent with clonal hematopoiesis being driven by a continuing risk of mutations and clonal expansions that become increasingly detectable with age.

中文翻译：

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克隆造血的进化动力学和适应性景观

造血细胞的进化动力学随着年龄的增长而积累突变，这些突变可能是癌症等疾病的来源。含有突变的细胞如何在体内进化、维持和增殖尚未得到很好的表征。Watson 等人使用定量框架。应用群体遗传理论根据来自近 50,000 名健康个体的测序数据估计血液细胞中的突变积累（参见柯蒂斯的观点）。通过评估血细胞群之间的突变如何不同，这种现象被称为克隆造血，研究人员可以观察反复发生的突变如何将某些克隆谱系驱动到个体内的高频率。特定突变的风险，其中一些与白血病有关，因此，上升到高频率可能是细胞选择和突变起源年龄的函数。科学，这个问题 p。第1449章 另见第 1426 来自约 50,000 个人的血液测序数据揭示了突变、遗传漂移和健康差异如何塑造健康血液的多样性。随着年龄的增长，在健康组织中获得的体细胞突变是癌症风险的主要决定因素。变异是否赋予适应性优势或偶然上升到可检测的频率仍然很大程度上未知。来自约 50,000 个人的血液测序数据揭示了突变、遗传漂移和健康如何塑造健康血液（克隆造血）的遗传多样性。我们表明，正选择，而不是漂移，是塑造克隆造血的主要力量，为造血干细胞的数量提供了界限，并以单核苷酸分辨率量化关键致病变异的适应性优势，以及常见突变驱动基因内的适应性效应（适应性景观）的分布。这些数据与由突变和克隆扩增的持续风险驱动的克隆造血一致，随着年龄的增长，这些突变和克隆扩增变得越来越容易检测到。