中国神经再生研究(英文版)

中国神经再生研究(英文版) ›› 2019, Vol. 14 ›› Issue (6): 1099-1104.doi: 10.4103/1673-5374.250632

• 原著:周围神经损伤修复保护与再生 • 上一篇    

周围神经退变与再生中许旺细胞微阵列研究的大数据分析

  

  • 出版日期:2019-06-15 发布日期:2019-06-15
  • 基金资助:

    韩国政府韩国国家研究基金会基础科学研究计划（2018R1D1A1B07040282）；2018年庆熙大学资助

Comparative study of microarray and experimental data on Schwann cells in peripheral nerve degeneration and regeneration: big data analysis

Ulfuara Shefa 1 , Junyang Jung 1, 2   

  1. 1 Department of Biomedical Science, Graduate School, Kyung Hee University, Dongdaemun-gu, Seoul, Republic of Korea
    2 Department of Anatomy and Neurobiology, College of Medicine, Kyung Hee University, Dongdaemun-gu, Seoul, Republic of Korea
  • Online:2019-06-15 Published:2019-06-15
  • Contact: Junyang Jung, MD, PhD, jjung@khu.ac.kr.
  • Supported by:

    This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2018R1D1A1B07040282; to JJ) and a grant from Kyung Hee University in 2018 (KHU-20181065; to JJ).

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摘要：

许旺细胞作为周围神经纤维的鞘细胞,在周围神经再生中发挥不可或缺的作用。此次进行的微阵列研究是生物信息学研究的一部分，主要关注许旺细胞。微阵列数据显示出，许旺细胞中几个基因表达增加（倍数变化），但在基于mRNA水平的实验研究中这些基因表达则弱表达。相反，一些在微阵列数据中弱表达的基因，在基于mRNA水平的实验研究中则高表达；这些基因可能是干预许旺细胞的未来靶基因。在此次基于PubMed/NCBI, Google Scholar, Google数据库的微阵列大数据研究中，确定了1016个上调和下调表达的基因与许旺细胞相关。但基于mRNA水平的实验研究则未见。此次大数据分析基于对所有微阵列数据的比较分析得出结论：微阵列可以是用于预测许旺细胞不同基因的表达和强度的有用工具。

orcid: 0000-0003-3946-5406 (Junyang Jung)

关键词: 许旺细胞, 大数据分析, 周围神经变性, 周围神经再生, MI-croarray, 匹配基因, 神经再生

Abstract:

A Schwann cell has regenerative capabilities and is an important cell in the peripheral nervous system. This microarray study is part of a bioinformatics study that focuses mainly on Schwann cells. Microarray data provide information on differences between microarray-based and experiment-based gene expression analyses. According to microarray data, several genes exhibit increased expression (fold change) but they are weakly expressed in experimental studies (based on morphology, protein and mRNA levels). In contrast, some genes are weakly expressed in microarray data and highly expressed in experimental studies; such genes may represent future target genes in Schwann cell studies. These studies allow us to learn about additional genes that could be used to achieve targeted results from experimental studies. In the current big data study by retrieving more than 5000 scientific articles from PubMed or NCBI, Google Scholar, and Google, 1016 (up- and downregulated) genes were determined to be related to Schwann cells. However, no experiment was performed in the laboratory; rather, the present study is part of a big data analysis. Our study will contribute to our understanding of Schwann cell biology by aiding in the identification of genes. Based on a comparative analysis of all microarray data, we conclude that the microarray could be a good tool for predicting the expression and intensity of different genes of interest in actual experiments.

Key words: Schwann cells, big data analysis, peripheral nerve degeneration, peripheral nerve regeneration, microarray, matched genes, promising genes, gene ranking