Advances in single-cell omics and multiomics for high-resolution molecular profiling

초록

Single-cell omics technologies have revolutionized molecular profiling by providing high-resolution insights into cellular heterogeneity and complexity. Traditional bulk omics approaches average signals from heterogeneous cell populations, thereby obscuring important cellular nuances. Single-cell omics studies enable the analysis of individual cells and reveal diverse cell types, dynamic cellular states, and rare cell populations. These techniques offer unprecedented resolution and sensitivity, enabling researchers to unravel the molecular landscape of individual cells. Furthermore, the integration of multimodal omics data within a single cell provides a comprehensive and holistic view of cellular processes. By combining multiple omics dimensions, multimodal omics approaches can facilitate the elucidation of complex cellular interactions, regulatory networks, and molecular mechanisms. This integrative approach enhances our understanding of cellular systems, from development to disease. This review provides an overview of the recent advances in single-cell and multimodal omics for high-resolution molecular profiling. We discuss the principles and methodologies for representatives of each omics method, highlighting the strengths and limitations of the different techniques. In addition, we present case studies demonstrating the applications of single-cell and multimodal omics in various fields, including developmental biology, neurobiology, cancer research, immunology, and precision medicine. Each cell is a bustling city of genetic material and proteins, but traditional methods often blur the individuality of each cell by averaging the data. Single-cell omics techniques, however, allow us to focus on individual cells, revealing the rich variety of cell types, states, and rare populations that make up our tissues and organs. In this review, researchers delve into the details of single-cell omics and multi-modal omics. They explore on how to isolate cells, add unique barcodes to keep track of them, and then analyze their genetic and molecular content. The integration of data across different molecular dimensions is a leap forward in the field, and it paves the way for future discoveries that could transform medicine. The potential implications of this research are vast, offering hope for more precise and personalized medical treatments in the future.This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

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