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通过多重单细胞 RNA-Seq 解码神经元多样化。

Decoding Neuronal Diversification by Multiplexed Single-cell RNA-Seq.

机构信息

RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa 230-0045, Japan.

RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Nihon University, College of Bioresource Sciences, Laboratory of Veterinary Radiology, Fujisawa, Kanagawa 252-0880, Japan.

出版信息

Stem Cell Reports. 2021 Apr 13;16(4):810-824. doi: 10.1016/j.stemcr.2021.02.006. Epub 2021 Mar 11.

Abstract

Cellular reprogramming is driven by a defined set of transcription factors; however, the regulatory logic that underlies cell-type specification and diversification remains elusive. Single-cell RNA-seq provides unprecedented coverage to measure dynamic molecular changes at the single-cell resolution. Here, we multiplex and ectopically express 20 pro-neuronal transcription factors in human dermal fibroblasts and demonstrate a widespread diversification of neurons based on cell morphology and canonical neuronal marker expressions. Single-cell RNA-seq analysis reveals diverse and distinct neuronal subtypes, including reprogramming processes that strongly correlate with the developing brain. Gene mapping of 20 exogenous pro-neuronal transcription factors further unveiled key determinants responsible for neuronal lineage specification and a regulatory logic dictating neuronal diversification, including glutamatergic and cholinergic neurons. The multiplex scRNA-seq approach is a robust and scalable approach to elucidate lineage and cellular specification across various biological systems.

摘要

细胞重编程由一组定义明确的转录因子驱动;然而,细胞类型特化和多样化的调控逻辑仍然难以捉摸。单细胞 RNA-seq 提供了前所未有的覆盖范围,可以在单细胞分辨率下测量动态分子变化。在这里,我们在人真皮成纤维细胞中多路复用和异位表达 20 种原神经转录因子,并基于细胞形态和典型神经元标记物的表达证明了神经元的广泛多样化。单细胞 RNA-seq 分析揭示了不同的神经元亚型,包括与发育中的大脑强烈相关的重编程过程。20 种外源原神经转录因子的基因图谱进一步揭示了负责神经元谱系特化的关键决定因素和决定神经元多样化的调控逻辑,包括谷氨酸能和胆碱能神经元。多路复用 scRNA-seq 方法是一种强大且可扩展的方法,可阐明各种生物系统中的谱系和细胞特化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5026/8072034/b7d1180abdf2/gr1.jpg

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