Studying the Regulatory Dynamics with Single-cell Multiomics

New York Genome Center, New York NY

Investigators

Abstract

Project Summary/Abstract A multitude of epigenomic variables and mechanisms contribute to cell-type-specific gene expression programs, and the spatiotemporal dynamics of these complex gene regulatory machinery laid the foundations for diverse biological processes, particularly in development, disease, and aging. Single-cell genomics technologies allowed capturing the static snapshots, such as transcriptomic or epigenomic states of the cells; while it remained challenging to study the temporal dynamics of the cell’s state transition processes. We hypothesized that the regulatory dynamics are shaped by the balance between “writing” and “erasing” of epigenomic variables, and thus can be inferred from measuring the linked molecular layers that maintain regulatory equilibriums by the development of single-cell multiomics technologies. Studying the regulatory dynamics of cell state transition is particularly challenging in aging brains: aging of the brain involves complex cellular and molecular changes, including variations in molecular signatures of certain cell types, changes in cell population compositions, and declined communications between neuron cells in this tissue with the most sophisticated cellular composition and spatial organizations. Aging contributes to many diseases that affect all organ systems and is the greatest risk factor for multiple diseases, including neurodegeneration and cancers. Understanding the fundamental biology of aging is essential for the development of clinical interventions. But current omics analysis of aging can only capture the static pictures of individual modalities, which cannot differentiate well-maintained components (young) from those who are about to lose fidelity (pre-decay) nor record the complex relationships between different molecule types. In this proposal, we aim to fundamentally transform our approaches to studying the principles of cell state transition, focusing on the mouse aging brain as a model system, by developing innovative single-cell genomics technologies for joint analysis of the cell’s regulatory dynamics and transcriptional states. Firstly, we will develop a set of single-cell multiomics tools for integrated analysis of the rates of forward and reverse reactions in maintaining the cell’s regulatory states, including epigenome (DNA methylation and active demethylation) and DNA damages (oxidative damages and base excision repair) with the transcriptional states. Next, we will develop a technology for the detection of colocalized regulatory elements and their epigenetic states jointly with transcriptomes from single cells, to evaluate the cell’s regulatory functionality. Finally, we will develop a modularized platform for tissue-scale high-definition 3-D spatial registration of single cells (AMBER) and then combine it with these single-cell multiomics tools to reconstruct the whole tissue structure with multimodal molecular profiles. We will apply our methods to investigate the molecular changes of aging in nervous systems with 3-D spatial information from mouse models, and believe our approach is broadly applicable to studying regulatory dynamics across various biological systems both in health and diseases.