The neuronal genome of Caenorhabditis elegans.
The neuronal genome of Caenorhabditis elegans.
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DOI：
10.1895/wormbook.1.161.1
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发表时间：
2013-08-13
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影响因子：
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通讯作者：
Hobert, Oliver
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作者：
Hobert, Oliver
秀丽隐杆线虫的〜100 Mb基因组代码约为20,000个蛋白质编码基因，其中许多是神经系统功能所需的，由成人雌雄同体中的302个神经元组成，成年男性中的383个神经元组成。除了管家基因外，差异化神经元被认为表达了数百个甚至数千个定义其功能特性的基因。这些基因代码为离子通道，G蛋白偶联受体，神经递质合成酶，转运蛋白和受体，神经肽及其受体，细胞粘附分子，运动蛋白，信号分子等。这种基因已被称为“终末分化基因”或“效应基因”。末端分化基因不同组合的差异表达定义了不同的神经元类型。本文提供了超过2,800个推定的终末分化基因的纲要。许多基因家族分析揭示的一个普遍主题是许多与神经元功能相关的基因家族的线虫特异性扩张，包括例如许多类型的离子通道家族，感觉受体和神经递质受体。这里提供的基因列表可以实现多种目的。它们可以用作单个基因家族的快速参考指南，也可以用于开采具有神经系统功能可能功能的基因的大型数据集（例如表达数据集）。它们还可以作为未来项目的起点。例如，对神经系统中这些基因经常复杂的表达模式的调节的全面了解最终将解释神经系统的构建方式。
The ~100 MB genome of C. elegans codes for ~20,000 protein-coding genes many of which are required for the function of the nervous system, composed of 302 neurons in the adult hermaphrodite and of 383 neurons in the adult male. In addition to housekeeping genes, a differentiated neuron is thought to express many hundreds if not thousands of genes that define its functional properties. These genes code for ion channels, G-protein-coupled receptors, neurotransmitter-synthesizing enzymes, transporters and receptors, neuropeptides and their receptors, cell adhesion molecules, motor proteins, signaling molecules and many others. Collectively such genes have been referred to as "terminal differentiation genes" or "effector genes". The differential expression of distinct combinations of terminal differentiation genes define different neuron types. This paper provides a compendium of more than 2,800 putative terminal differentiation genes. One pervasive theme revealed by the analysis of many gene families is the nematode-specific expansions of many neuron function-related gene families, including, for example, many types of ion channel families, sensory receptors and neurotransmitter receptors. The gene lists provided here can serve multiple purposes. They can serve as quick reference guides for individual gene families or they can be used to mine large datasets (e.g., expression datasets) for genes with likely functions in the nervous system. They also serve as a starting point for future projects. For example, a comprehensive understanding of the regulation of the often complex expression patterns of these genes in the nervous system will eventually explain how nervous systems are built.