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转录组基因特征可衡量肌营养不良症中的卫星细胞活性。

Transcriptomic gene signatures measure satellite cell activity in muscular dystrophies.

作者信息

Engquist Elise N, Greco Anna, Joosten Leo A B, van Engelen Baziel G M, Banerji Christopher R S, Zammit Peter S

机构信息

King's College London, Randall Centre for Cell and Molecular Biophysics, New Hunt's House, Guy's Campus, London SE1 1UL, UK.

Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen 6525 GA, the Netherlands.

出版信息

iScience. 2024 May 8;27(6):109947. doi: 10.1016/j.isci.2024.109947. eCollection 2024 Jun 21.

Abstract

The routine need for myonuclear turnover in skeletal muscle, together with more sporadic demands for hypertrophy and repair, are performed by resident muscle stem cells called satellite cells. Muscular dystrophies are characterized by muscle wasting, stimulating chronic repair/regeneration by satellite cells. Here, we derived and validated transcriptomic signatures for satellite cells, myoblasts/myocytes, and myonuclei using publicly available murine single cell RNA-Sequencing data. Our signatures distinguished disease from control in transcriptomic data from several muscular dystrophies including facioscapulohumeral muscular dystrophy (FSHD), Duchenne muscular dystrophy, and myotonic dystrophy type I. For FSHD, the expression of our gene signatures correlated with direct counts of satellite cells on muscle sections, as well as with increasing clinical and pathological severity. Thus, our gene signatures enable the investigation of myogenesis in bulk transcriptomic data from muscle biopsies. They also facilitate study of muscle regeneration in transcriptomic data from human muscle across health and disease.

摘要

骨骼肌中肌核周转的常规需求,以及对肥大和修复的更多偶发性需求,由称为卫星细胞的驻留肌肉干细胞来执行。肌肉营养不良的特征是肌肉萎缩,刺激卫星细胞进行慢性修复/再生。在这里,我们利用公开可用的小鼠单细胞RNA测序数据,推导并验证了卫星细胞、成肌细胞/肌细胞和肌核的转录组特征。我们的特征在包括面肩肱型肌营养不良(FSHD)、杜氏肌营养不良和I型强直性肌营养不良在内的几种肌肉营养不良的转录组数据中区分了疾病和对照。对于FSHD,我们基因特征的表达与肌肉切片上卫星细胞的直接计数相关,也与临床和病理严重程度的增加相关。因此,我们的基因特征能够在来自肌肉活检的大量转录组数据中研究肌生成。它们还便于在健康和疾病状态下人类肌肉的转录组数据中研究肌肉再生。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/656a/11150970/bd4a68dcecba/fx1.jpg

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