Ge Zilu, Tang Hong, Lyu Jingtong, Zhou Binghua, Yang Mingyu, Tang Kanglai, Chen Wan
Department of Orthopedics/Sports Medicine Center, State Key Laboratory of Trauma, Burn and Combined Injury, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China.
Ann Transl Med. 2020 Mar;8(6):335. doi: 10.21037/atm.2020.02.149.
Rotator cuff tendinopathy (RCT) is a common musculoskeletal disorder in the shoulder, whose underlying mechanism is unknown. Long non-coding RNAs (lncRNAs) are involved in the development of various diseases, but little is known about their potential roles in RCT.
In this study, we profiled lncRNAs and mRNAs involved in RCT in comparison with the normal tendon (NT) by RNA sequencing (RNA-Seq), to identify potential therapeutic targets. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway, competing endogenous RNA (ceRNA), and co-expression network construction were used to identify the potential functions of these RNAs. Three lncRNAs and three mRNAs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).
In total, 419 lncRNAs and 1,541 mRNAs were differentially expressed between the RCT and NT groups with a fold change of >2 and P of <0.01. The GO and KEGG pathway analyses showed that the differentially expressed mRNAs were mainly enriched in complement activation and involved in the citrate cycle. The ceRNA network showed the interaction of differentially expressed RNAs, comprising 139 lncRNAs, 126 mRNAs, and 35 miRNAs. , , , , , and were validated by PCR. We constructed a co-expressed network of these validated RNAs.
We preliminarily analyzed the profile of lncRNAs and mRNAs in RCT. The bioinformatic analysis revealed several potential therapeutic targets for RCT.
肩袖肌腱病（RCT）是肩部常见的肌肉骨骼疾病，其潜在机制尚不清楚。长链非编码RNA（lncRNA）参与多种疾病的发生发展，但它们在RCT中的潜在作用知之甚少。
在本研究中，我们通过RNA测序（RNA-Seq）对RCT中涉及的lncRNA和mRNA与正常肌腱（NT）进行分析，以确定潜在的治疗靶点。利用基因本体论（GO）、京都基因与基因组百科全书（KEGG）通路、竞争性内源RNA（ceRNA）以及共表达网络构建来确定这些RNA的潜在功能。通过定量逆转录-聚合酶链反应（qRT-PCR）验证了3种lncRNA和3种mRNA。
RCT组和NT组之间共有419种lncRNA和1541种mRNA差异表达，变化倍数>2且P<0.01。GO和KEGG通路分析表明，差异表达的mRNA主要富集于补体激活，并参与柠檬酸循环。ceRNA网络显示了差异表达RNA之间的相互作用，包括139种lncRNA、126种mRNA和35种miRNA。通过PCR验证了……、……、……、……、……和……。我们构建了这些验证RNA的共表达网络。
我们初步分析了RCT中lncRNA和mRNA的表达谱。生物信息学分析揭示了RCT的几个潜在治疗靶点。
