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

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.