BackgroundThe lifelong accumulation of somatic mutations underlies age-related phenotypes and cancer. Mutagenic forces are thought to shape the genome of aging cells in a tissue-specific way. Whole genome analyses of somatic mutation patterns, based on both types and genomic distribution of variants, can shed light on specific processes active in different human tissues and their effect on the transition to cancer.ResultsTo analyze somatic mutation patterns, we compile a comprehensive genetic atlas of somatic mutations in healthy human cells. High-confidence variants are obtained from newly generated and publicly available whole genome DNA sequencing data from single non-cancer cells, clonally expanded in vitro. To enable a well-controlled comparison of different cell types, we obtain single genome data (92% mean coverage) from multi-organ biopsies from the same donors. These data show multiple cell types that are protected from mutagens and display a stereotyped mutation profile, despite their origin from different tissues. Conversely, the same tissue harbors cells with distinct mutation profiles associated to different differentiation states. Analyses of mutation rate in the coding and non-coding portions of the genome identify a cell type bearing a unique mutation pattern characterized by mutation enrichment in active chromatin, regulatory, and transcribed regions.ConclusionsOur analysis of normal cells from healthy donors identifies a somatic mutation landscape that enhances the risk of tumor transformation in a specific cell population from the kidney proximal tubule. This unique pattern is characterized by high rate of mutation accumulation during adult life and specific targeting of expressed genes and regulatory regions.

中文翻译：

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全基因组 DNA 测序提供了健康人类细胞中体细胞突变的图谱，并确定了易患肿瘤的细胞类型

背景体细胞突变的终生积累是与年龄相关的表型和癌症的基础。诱变力被认为以组织特异性方式塑造衰老细胞的基因组。体细胞突变模式的全基因组分析，基于变异的类型和基因组分布，可以阐明在不同人体组织中活跃的特定过程及其对癌症转变的影响。结果为了分析体细胞突变模式，我们编制了一个全面的遗传图谱健康人体细胞中的体细胞突变。高可信度变异是从新生成的、公开可用的、来自单个非癌细胞的全基因组 DNA 测序数据中获得的，在体外进行了克隆扩增。为了能够对不同细胞类型进行良好控制的比较，我们从同一捐赠者的多器官活检中获得了单基因组数据（平均覆盖率为 92%）。这些数据显示多种细胞类型不受诱变剂的影响，并显示出固定的突变谱，尽管它们来自不同的组织。相反，同一组织中的细胞具有与不同分化状态相关的不同突变谱。基因组编码和非编码部分的突变率分析确定了一种具有独特突变模式的细胞类型，其特征在于活性染色质、调节和转录区域的突变富集。结论我们对来自健康供体的正常细胞的分析确定了一种体细胞突变增加了来自肾脏近端小管的特定细胞群中肿瘤转化风险的景观。