Computational evaluation of the causal role of somatic mutations in human aging

项目摘要 虽然基因组不稳定性长期以来一直被认为是衰老的主要原因之一， 已知每个细胞基因组改变的实际数量及其对衰老生物体的影响， 尤其是人类。在这里提出的研究中，我将采用单细胞方法来识别最常见的 体细胞突变的类型，即，碱基替换，小INDELS，拷贝数变异，基因组结构 变异和反转录转位，在人类B淋巴细胞作为年龄的函数。首要目标是 为了评估这些DNA突变在人类衰老过程中积累的功能效应， 这也将作为研究体细胞突变及其 其他细胞类型的影响。这在以前是无法验证的，因为它不可能 通过对来自该组织的大量DNA进行测序来分析组织中的随机体细胞突变（突变是低- 丰富），我将通过利用新的单细胞全基因组测序（SCWGS）方案来实现这一目标 我们开发的。在这个项目中，我将集中在人类B淋巴细胞从不同年龄的个人， 大约30到100多年，并确定不同类型的基因组频率和位置， 来自每个个体的多个细胞中的突变（目标1）。初步结果显示， 随着年龄的增长，碱基替换突变和CNV的数量增加，其中大量的这些突变发生在B细胞中， 潜在功能的基因组区域。因此，在目标2中，我将预测 使用机器学习方法和整合网络， 分析.最后，在目标3中，我将根据经验检验这些预测， 影响B细胞对刺激的反应能力。因此，为了验证长期存在的基因组不稳定性假设， 作为衰老的因果因素，我将在四个水平上确定单细胞中与年龄相关的突变：（1） 单个细胞中的突变、突变谱和基因组分布;（2） 单个突变，即，外显子中的非同义突变和基因调控区中的突变;（3） 共同影响基因调控网络的突变;以及（4）突变负荷与B之间的关系 细胞激活状态。总而言之，拟议项目的结果将首次揭示 体细胞突变对细胞功能的直接功能影响。

Project Abstract Although genome instability has long been considered as one of the major causal factors of aging, little is known about the actual number of genome alterations per cell and their effects on aging organisms, most notably humans. In the research proposed here I will take a single cell approach to identify the most common types of somatic mutations, i.e., base substitutions, small INDELS, copy number variation, genome structural variation and retrotranspositions, in human B lymphocytes as a function of age. The overarching goal is then to estimate functional effects of these DNA mutations accumulated during human aging in this particular cell type, which will also serve as a model for studying somatic mutations and their consequences in other cell types. This could never be tested before, because it was never possible to analyze random somatic mutations in a tissue by sequencing bulk DNA from that tissue (mutations are low- abundant), I will achieve this goal by utilizing a new, single-cell, whole genome sequencing (SCWGS) protocol that we developed. In this project I will focus on human B lymphocytes from individuals varying in age from about 30 to over 100 years and determine the genome-wide frequency and location of the different types of mutations in multiple cells from each individual (Aim 1). Preliminary results already show a significant increase of both base substitution mutations and CNVs with age, with a substantial number of these mutations in B cell genomic regions that are potentially functional. Hence, in Aim 2 I will predict the actual functional effects of these potentially functional, age-related mutations using machine learning approaches and integrative network analysis. Finally, in Aim 3 I will empirically test these predictions as to whether the mutation loads observed affect B cell's ability of response to stimulus. Hence, to test the long-standing hypothesis of genome instability as a causal factor in aging ,I will determine age-related mutations in single cells at four levels: (1) number of mutations, mutation spectra and genome distribution in individual cells; (2) potential functional effects of individual mutations, i.e., non-synonymous mutations in exons and mutations in gene regulatory regions; (3) mutations collectively affecting the gene regulatory network; and (4) relationship between mutation load and B cell activation status. In summary, the results of the proposed project will, for the first time uncover possible direct functional effects of somatic mutations on cellular function.