Methods and applications for single-cell and spatial multi-omics

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the i...

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Bibliographic Details
Published in:Nature reviews. Genetics 2023-08, Vol.24 (8), p.494-515
Main Authors: Vandereyken, Katy, Sifrim, Alejandro, Thienpont, Bernard, Voet, Thierry
Format: Article
Language:English
Subjects:
631/1647/2017
631/1647/2210
631/208/212/2019
631/337/100
631/337/475
Agriculture
Animal Genetics and Genomics
Biology
Biomedical and Life Sciences
Biomedicine
Cancer Research
Cells
Gene Function
Genetics
Genome
Genomes
Human Genetics
Information processing
Metabolome
Mitochondrial DNA
Molecular modelling
Multiomics
Principles
Proteome - genetics
Proteomes
Proteomics
Review
Review Article
Single-Cell Analysis
Transcriptome
Transcriptomes
Transcriptomics
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Summary:The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future. In this Review, the authors discuss the latest advances in profiling multiple molecular modalities from single cells, including genomic, transcriptomic, epigenomic and proteomic information. They describe the diverse strategies for separately analysing different modalities, how the data can be computationally integrated, and approaches for obtaining spatially resolved data.
ISSN:1471-0056
1471-0064
1471-0064
DOI:10.1038/s41576-023-00580-2