Analysis of Gene Expression Profiles in the Human Brain Stem, Cerebellum and Cerebral Cortex.
Analysis of Gene Expression Profiles in the Human Brain Stem, Cerebellum and Cerebral Cortex.
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人脑干、小脑和大脑皮层基因表达谱分析
DOI：
10.1371/journal.pone.0159395
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Cai YD
中科院分区：
文献类型：
--
作者：
Chen L;Chu C;Zhang YH;Zhu C;Kong X;Huang T;Cai YD
人脑是人体中最神秘的组织之一。我们对人类大脑的了解是有限的，这是由于其结构的复杂性以及大脑区域与身体其他组织之间连接的微观性质。在这项研究中，我们分析了三个大脑区域的基因表达谱-脑干，小脑和大脑皮层-以确定在人类这些不同的大脑区域之间差异表达的基因，并通过比较不同个体的表达特征来获得一系列稳健的，区域特异性的，差异表达的基因。特征选择方法，特别是最小冗余最大相关性和增量特征选择，被用来分析基因表达谱。顺序最小优化，一种机器学习算法，被用来检查所选择的基因的效用。我们还进行了文献检索，我们讨论了几个高排名的基因，包括NR 2 E1，DAO和LRRC 7的重要生理功能的实验证据，我们给我们的基因（TFAP 2B）尚未调查或实验验证的分析。总的来说，我们的研究结果将提高我们预测和理解与大脑区域化和功能相关的基因的能力。
The human brain is one of the most mysterious tissues in the body. Our knowledge of the human brain is limited due to the complexity of its structure and the microscopic nature of connections between brain regions and other tissues in the body. In this study, we analyzed the gene expression profiles of three brain regions—the brain stem, cerebellum and cerebral cortex—to identify genes that are differentially expressed among these different brain regions in humans and to obtain a list of robust, region-specific, differentially expressed genes by comparing the expression signatures from different individuals. Feature selection methods, specifically minimum redundancy maximum relevance and incremental feature selection, were employed to analyze the gene expression profiles. Sequential minimal optimization, a machine-learning algorithm, was employed to examine the utility of selected genes. We also performed a literature search, and we discuss the experimental evidence for the important physiological functions of several highly ranked genes, including NR2E1, DAO, and LRRC7, and we give our analyses on a gene (TFAP2B) that have not been investigated or experimentally validated. As a whole, the results of our study will improve our ability to predict and understand genes related to brain regionalization and function.