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Chen L, Li J, Zhang YH, Feng K, Wang S, Zhang Y, Huang T, Kong X, Cai YD. Identification of gene expression signatures across different types of neural stem cells with the Monte-Carlo feature selection method. J Cell Biochem 2017; 119:3394-3403. [PMID: 29130544 DOI: 10.1002/jcb.26507] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Accepted: 11/09/2017] [Indexed: 02/03/2023]
Abstract
Adult neural stem cells (NSCs) are a group of multi-potent, self-renewing progenitor cells that contribute to the generation of new neurons and oligodendrocytes. Three subtypes of NSCs can be isolated based on the stages of the NSC lineage, including quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs). Although it is widely accepted that these three groups of NSCs play different roles in the development of the nervous system, their molecular signatures are poorly understood. In this study, we applied the Monte-Carlo Feature Selection (MCFS) method to identify the gene expression signatures, which can yield a Matthews correlation coefficient (MCC) value of 0.918 with a support vector machine evaluated by ten-fold cross-validation. In addition, some classification rules yielded by the MCFS program for distinguishing above three subtypes were reported. Our results not only demonstrate a high classification capacity and subtype-specific gene expression patterns but also quantitatively reflect the pattern of the gene expression levels across the NSC lineage, providing insight into deciphering the molecular basis of NSC differentiation.
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Affiliation(s)
- Lei Chen
- Schoolof Life Sciences, Shanghai University, Shanghai, P.R. China.,College of Information Engineering, Shanghai Maritime University, Shanghai, P.R. China
| | - JiaRui Li
- Schoolof Life Sciences, Shanghai University, Shanghai, P.R. China
| | - Yu-Hang Zhang
- Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P.R. China
| | - KaiYan Feng
- Department of Computer Science, Guangdong AIB Polytechnic, Guangzhou, Guangdong, P.R. China
| | - ShaoPeng Wang
- Schoolof Life Sciences, Shanghai University, Shanghai, P.R. China
| | - YunHua Zhang
- Anhui province key lab of Farmland Ecological Conversation and Pollution Prevention, School of Resources and Environment, Anhui Agricultural University, Hefei, P.R. China
| | - Tao Huang
- Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P.R. China
| | - Xiangyin Kong
- Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P.R. China
| | - Yu-Dong Cai
- Schoolof Life Sciences, Shanghai University, Shanghai, P.R. China
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