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表观基因组单细胞测序应用的进展与挑战。

Advances and challenges in epigenomic single-cell sequencing applications.

机构信息

Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, NIHR Oxford BRU, University of Oxford, OX3 7LD, UK.

ATDBio, Oxford Science Park, Robert Robinson Ave, Oxford, OX4 4GA, UK.

出版信息

Curr Opin Chem Biol. 2020 Aug;57:17-26. doi: 10.1016/j.cbpa.2020.01.013. Epub 2020 Apr 15.

Abstract

Understanding multicellular physiology and pathobiology requires analysis of the relationship between genotype, chromatin organisation and phenotype. In the multi-omics era, many methods exist to investigate biological processes across the genome, transcriptome, epigenome, proteome and metabolome. Until recently, this was only possible for populations of cells or complex tissues, creating an averaging effect that may obscure direct correlations between multiple layers of data. Single-cell sequencing methods have removed this averaging effect, but computational integration after profiling distinct modalities separately may still not completely reflect underlying biology. Multiplexed assays resolving multiple modalities in the same cell are required to overcome these shortcomings and have the potential to deliver unprecedented understanding of biology and disease.

摘要

要了解多细胞生理学和病理生物学,就需要分析基因型、染色质组织和表型之间的关系。在多组学时代,有许多方法可以研究基因组、转录组、表观基因组、蛋白质组和代谢组中的生物过程。直到最近,这还只能针对细胞群体或复杂组织进行,这种平均效应可能会掩盖多个数据层之间的直接相关性。单细胞测序方法消除了这种平均效应,但在分别分析不同模式后进行计算整合,仍可能无法完全反映潜在的生物学。需要能够在同一细胞中解析多种模式的多重分析来克服这些缺点,并有可能以前所未有的方式理解生物学和疾病。

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