Transcriptome sequencing reveals aerobic exercise training-associated lncRNAs for improving Parkinson's disease

转录组 生物 有氧运动 医学 小桶
作者
Xiang Zhang,Yachun Wang,Zhenqiang Zhao,Xinxu Chen,Wen Li,Xiating Li
出处
期刊:3 biotech [Springer Science+Business Media]
卷期号:10 (11): 498-
标识
DOI:10.1007/s13205-020-02483-z
摘要

The present study aimed to evaluate the effect of aerobic exercise training (AET) on the performance of mice with Parkinson’s disease (PD) and to explore the molecular mechanism of AET-associated long noncoding RNAs (lncRNAs) in PD treatment. The results showed that the behaviors of PD mice were significantly improved after 4 weeks of AET. The substantia nigra pars compacta of PD mice showed scattered large multipolar cells and surrounding neutrophils after AET. In addition, a total of 62 differentially expressed lncRNAs (DE-lncRNAs) were identified between the AET group and the PD group, including 55 up-regulated and 7 down-regulated DE-lncRNAs in the AET group. Furthermore, the target genes of DE-lncRNAs, including LOC102633466, LOC102637865, and LOC102638670, were mainly involved in ECM-receptor interaction, the Wnt pathway and the PI3K/AKT/mTOR pathway. Quantitative real-time polymerase chain reaction showed that these three DE-lncRNAs were significantly up-regulated in the AET group than in the PD group. The lncRNA–miRNA–mRNA ceRNA network suggested that these 3 DE-lncRNAs may improve PD via the ceRNA mechanism. In conclusion, this study suggests that aerobic exercise improves motor performance of PD mice and provides a foundation for further studies on the molecular mechanism of lncRNAs in treating PD.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
NexusExplorer应助林黛玉采纳,获得10
1秒前
1秒前
领导范儿应助long83961258采纳,获得10
2秒前
斯文败类应助哈哈哈采纳,获得10
3秒前
WELL123发布了新的文献求助10
3秒前
Dr.L发布了新的文献求助50
3秒前
Akim应助风中乐松采纳,获得10
4秒前
无花果应助偏偏意气用事采纳,获得10
4秒前
5秒前
6秒前
6秒前
6秒前
7秒前
二两白茶发布了新的文献求助10
10秒前
庸人自扰完成签到,获得积分10
10秒前
long83961258发布了新的文献求助10
10秒前
续集发布了新的文献求助10
11秒前
123发布了新的文献求助10
11秒前
小材人完成签到,获得积分20
11秒前
小刘发布了新的文献求助10
12秒前
mz发布了新的文献求助10
15秒前
汉堡包应助听弦采纳,获得10
15秒前
蝶恋花发布了新的文献求助10
15秒前
WELL123完成签到,获得积分20
15秒前
16秒前
17秒前
zhuiyu完成签到,获得积分10
17秒前
金晓完成签到,获得积分20
17秒前
beichuanheqi应助张一二二二采纳,获得30
17秒前
18秒前
19秒前
酷酷码完成签到,获得积分10
19秒前
等你发布了新的文献求助10
20秒前
小刘完成签到,获得积分10
21秒前
研友_Ljqal8发布了新的文献求助200
21秒前
22秒前
兀拉拉完成签到,获得积分10
22秒前
22秒前
图图应助long83961258采纳,获得10
22秒前
24秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Ergodic Theory 200
A monograph of the genera Conocybe and Pholiotina in Europe 200
Clinical Observation and Analysis of Transient Postoperative CA-125 Elevation in a Patient with Sigmoid Colon Adenocarcinoma 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3836785
求助须知:如何正确求助?哪些是违规求助? 3379022
关于积分的说明 10507257
捐赠科研通 3098893
什么是DOI,文献DOI怎么找? 1706622
邀请新用户注册赠送积分活动 821120
科研通“疑难数据库(出版商)”最低求助积分说明 772445