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

Methods and applications for single-cell and spatial multi-omics.
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DOI:
10.1038/s41576-023-00580-2
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发表时间:
2023-08
影响因子:
42.7
通讯作者:
Voet, Thierry
Voet, Thierry
中科院分区:
生物学1区
文献类型:
--
作者:
Vandereyken, Katy;Sifrim, Alejandro;Thienpont, Bernard;Voet, Thierry

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对单细胞基因组、表观基因组、转录组、蛋白质组和/或代谢组的联合分析正在改变我们对健康和疾病细胞生物学的理解。在不到十年的时间里,该领域发生了巨大的技术革命,使人们对控制发育、生理学和发病机制的细胞内和细胞间分子机制之间的相互作用有了重要的新见解。在这篇综述中,我们重点介绍了快速发展的单细胞和空间多组学技术(也称为多模式组学方法)领域的进展,以及整合这些分子层信息所需的计算策略。我们展示它们对基础细胞生物学和转化研究的影响,讨论当前的挑战并展望未来。在这篇综述中,作者讨论了分析单细胞多种分子模式的最新进展,包括基因组、转录组、表观基因组和蛋白质组信息。他们描述了单独分析不同模态的不同策略、如何通过计算集成数据以及获取空间解析数据的方法。
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.
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