Building an RNA Sequencing Transcriptome of the Central Nervous System.
Building an RNA Sequencing Transcriptome of the Central Nervous System.
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DOI：
10.1177/1073858415610541
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发表时间：
2016-12
期刊：
影响因子：
--
通讯作者：
Wu JQ
中科院分区：
文献类型：
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作者：
Dong X;You Y;Wu JQ
中枢神经系统（CNS）的组成和功能极其复杂。除了数百种神经元亚型外，其他细胞类型，包括神经胶质细胞（星形胶质细胞，少突胶质细胞和小胶质细胞）和血管细胞（内皮细胞和周细胞）也在CNS功能中发挥重要作用。这种异质性使得CNS中基因转录的研究具有挑战性。转录组学研究，即分析所有基因的表达水平和结构，对于解释CNS的功能元件和理解CNS的分子组成是必不可少的。基因表达谱芯片技术是大规模基因表达谱分析的主要方法。然而，近年来发展的RNA测序（RNA-Seq）技术与微阵列相比具有许多优势，并且能够构建CNS和其他系统的更定量、准确和全面的转录组。新基因、不同的选择性剪接事件和非编码RNA的发现显著地扩展了基因表达谱的复杂性，并将帮助我们理解复杂的神经回路。本文就RNA-Seq技术在哺乳动物中枢神经系统转录组构建中的步骤和优势进行了讨论，并对组织样本和特定细胞类型构建RNA-Seq转录组的样本采集方法和最新进展进行了综述。
The composition and function of the central nervous system (CNS) is extremely complex. In addition to hundreds of subtypes of neurons, other cell types, including glia (astrocytes, oligodendrocytes, and microglia) and vascular cells (endothelial cells and pericytes) also play important roles in CNS function. Such heterogeneity makes the study of gene transcription in CNS challenging. Transcriptomic studies, namely the analyses of the expression levels and structures of all genes, are essential for interpreting the functional elements and understanding the molecular constituents of the CNS. Microarray has been a predominant method for large-scale gene expression profiling in the past. However, RNA-sequencing (RNA-Seq) technology developed in recent years has many advantages over microarrays, and has enabled building more quantitative, accurate, and comprehensive transcriptomes of the CNS and other systems. The discovery of novel genes, diverse alternative splicing events, and noncoding RNAs has remarkably expanded the complexity of gene expression profiles and will help us to understand intricate neural circuits. Here, we discuss the procedures and advantages of RNA-Seq technology in mammalian CNS transcriptome construction, and review the approaches of sample collection as well as recent progress in building RNA-Seq-based transcriptomes from tissue samples and specific cell types.