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艾灸治疗下老年小鼠的数字基因表达谱分析

Digital Gene Expression Profiling Analysis of Aged Mice under Moxibustion Treatment.

作者信息

Liu Nan, Jiang Yunyao, Xing Min, Zhao Baixiao, Hou Jincai, Lim Minyee, Huang Jian, Luo Xue, Han Li

机构信息

School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing 10029, China.

Institute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China.

出版信息

Evid Based Complement Alternat Med. 2018 May 2;2018:4767328. doi: 10.1155/2018/4767328. eCollection 2018.

Abstract

Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55%) were clean reads. Five differentially expressed genes with an adjusted value < 0.05 and |log⁡2(fold  change)| > 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.

摘要

衰老与死亡、生理功能的渐进性衰退以及疾病风险的增加密切相关,这些疾病包括癌症、动脉硬化、心脏病、高血压和神经退行性疾病。据报道,艾灸可以治疗300多种疾病,包括与衰老相关的问题,并且可以改善免疫功能和生理功能。在本研究中,对接受或未接受艾灸治疗的老年小鼠进行了数字基因表达谱分析,并通过基因本体论和通路分析推测了艾灸对老年小鼠的作用机制。通过数字基因表达分析获得了近1.45亿条原始读数,其中约1.4亿条(96.55%)为有效读数。在对照组和艾灸组之间鉴定出5个差异表达基因,其校正后P值<0.05且|log₂(倍数变化)|>1。它们分别是Gm6563、Gm8116、Rps26-ps1、Nat8f4和Igkv3-12。通过GOseq R软件包进行基因本体论分析,并对与翻译、mRNA从细胞核输出、mRNA转运、核体、乙酰转移酶活性等相关的差异表达基因进行功能注释。使用京都基因与基因组百科全书数据库进行通路分析,核糖体是最显著富集的通路术语。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c9c5/5954890/11f815a3c7c2/ECAM2018-4767328.001.jpg

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