Multiomic methods for the characterization of cellular aging

PROJECT SUMMARY Age-related diseases are together the leading causes of death in the United States, and drugs targeting basic mechanisms of aging have recently entered clinical trials. Single cell sequencing has enabled unprecedented resolution in the study of cell types implicated during aging, contributing to our study of age-related

diseases. Yet, critical deficiencies remain in our experimental and computational toolbox, limiting our ability to study cellular aging in two fundamental ways: (1) A hallmark of cellular aging is stochastic epigenetic drift, where cells gradually accumulate errors in their cytosine methylation and histone modification profiles, leading

to cell-type specific aging phenotypes, such as loss of plasticity in stem cell populations. It is unclear how errors accumulated at the chromatin level propagate to RNA transcription and splicing and how these errors impact observed aging-related phenomenon, such as cellular senescence. This gap in knowledge is due, in

part, to the lack of formal definitions and actionable models for measuring epigenetic and transcriptomic dysregulation. (2) The accumulation of senescent cells, i.e. cells that have entered irreversible cell cycle arrest, in our tissues as we age has been widely appreciated as a driver of aging. Yet, there are few studies of

the relationship between epigenetic and transcriptomic noise and cellular senescence, partly because of the aforementioned lack of analysis tools, and partly because senescent cells, which are usually present at small proportions even in aging tissue, are difficult to isolate and characterize. In this project, we will develop

methods to estimate intrinsic noise, as it was classically defined by Elowitz, Levine, Siggia, and Swain (2022), from single cell sequencing data. Across tissues and cell types, our preliminary studies show that intrinsic noise measures the accumulation of error at the per-cell and per-gene level. We will develop computational

methods for the measurement of intrinsic biological noise at the levels of chromatin accessibility, gene expression, and transcript splicing. Synergistically, we will perform experiments on which the new methods will be applied to investigate the relationship between intrinsic cellular noise and cellular senescence, and address

essential questions in cellular aging, senescence, and anti-aging drug therapy. Our central hypothesis is that epigenetic, transcriptional, and splicing noise provides both a quantitative profile of cellular aging and a critical new perspective for understanding gene (dys)regulation, senescence, and tissue aging in a cell type specific

manner. Preliminary results support this hypothesis and suggest that our methods will be of interest to the broader research community with the potential for wide adoption.