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一份人类骨骼肌组织的参考单细胞转录组图谱揭示了分叉的肌肉干细胞群体。

A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations.

作者信息

De Micheli Andrea J, Spector Jason A, Elemento Olivier, Cosgrove Benjamin D

机构信息

Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, 14853, USA.

Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.

出版信息

Skelet Muscle. 2020 Jul 6;10(1):19. doi: 10.1186/s13395-020-00236-3.

Abstract

Single-cell RNA-sequencing (scRNA-seq) facilitates the unbiased reconstruction of multicellular tissue systems in health and disease. Here, we present a curated scRNA-seq dataset of human muscle samples from 10 adult donors with diverse anatomical locations. We integrated ~ 22,000 single-cell transcriptomes using Scanorama to account for technical and biological variation and resolved 16 distinct populations of muscle-resident cells using unsupervised clustering of the data compendium. These cell populations included muscle stem/progenitor cells (MuSCs), which bifurcated into discrete "quiescent" and "early-activated" MuSC subpopulations. Differential expression analysis identified transcriptional profiles altered in the activated MuSCs including genes associated with aging, obesity, diabetes, and impaired muscle regeneration, as well as long non-coding RNAs previously undescribed in human myogenic cells. Further, we modeled ligand-receptor cell-communication interactions and observed enrichment of the TWEAK-FN14 pathway in activated MuSCs, a characteristic signature of muscle wasting diseases. In contrast, the quiescent MuSCs have enhanced expression of the EGFR receptor, a recognized human MuSC marker. This work provides a new benchmark reference resource to examine human muscle tissue heterogeneity and identify potential targets in MuSC diversity and dysregulation in disease contexts.

摘要

单细胞RNA测序(scRNA-seq)有助于在健康和疾病状态下对多细胞组织系统进行无偏重建。在此,我们展示了一个经过整理的scRNA-seq数据集,该数据集来自10名成年供体、具有不同解剖位置的人类肌肉样本。我们使用Scanorama整合了约22,000个单细胞转录组,以考虑技术和生物学变异,并通过对数据汇总进行无监督聚类解析出16个不同的肌肉驻留细胞群体。这些细胞群体包括肌肉干/祖细胞(MuSCs),它们又分为离散的“静止”和“早期激活”MuSC亚群。差异表达分析确定了激活的MuSCs中改变的转录谱,包括与衰老、肥胖、糖尿病和肌肉再生受损相关的基因,以及人类成肌细胞中以前未描述的长链非编码RNA。此外,我们对配体-受体细胞通讯相互作用进行建模,并观察到激活的MuSCs中TWEAK-FN14通路的富集,这是肌肉萎缩疾病的一个特征性标志。相比之下,静止的MuSCs增强了EGFR受体的表达,EGFR是一种公认的人类MuSC标志物。这项工作提供了一个新的基准参考资源,用于研究人类肌肉组织的异质性,并确定疾病背景下MuSC多样性和失调的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02d9/7336639/28be82f446b3/13395_2020_236_Fig1_HTML.jpg

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