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Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment

机译:从微阵列数据构建基因网络可识别与年龄相关的空间学习障碍中的关键网络模块和几个候选中心基因

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摘要

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in “learning and memory” related functions and pathways. Subsequent differential network analysis of this “learning and memory” module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning.
机译:随着人类年龄的增长,许多人的大脑功能都会下降,包括空间学习障碍。这项研究旨在更好地了解与年龄相关的空间学习障碍(ASLI)的分子机制。我们使用在加权基因共表达网络分析(WGCNA)中实施的数学建模方法,从上下文中的一组探索性数据集中创建和比较了年轻人(学习无障碍)和衰老(主要是学习障碍)大脑的基因网络模型。 ASLI。主要目标是使用这些数据来克服以前在传统元和通路分析中观察到的某些局限性,并基于基因的共表达关系来鉴定新的ASLI相关基因及其网络。这项分析确定了一组年轻的网络模块,每个模块都高度丰富了在广泛但不同的GO功能类别或生物学途径中起作用的基因。有趣的是,分析指出了一个模块,该模块高度丰富了在“学习和记忆”相关功能和途径中起作用的基因。随后对老年(主要是学习障碍)大鼠和年轻学习未受损大鼠进行“学习和记忆”模块的差分网络分析,使我们能够鉴定出一组新的ASLI候选中心基因。这些基因中的某些在由独立的年轻和老年验证数据集生成的网络中显示出显着的可重复性。这些中枢基因与网络中的其他基因高度共表达,不仅表现出差异表达,而且在年龄和学习障碍中也表现出差异共表达和差异连通性。这些中枢基因的已知功能表明它们在关键途径(包括激酶和磷酸酶信号传导),与各种离子通道有关的功能以及在维持与突触可塑性和记忆形成有关的神经元完整性中起关键作用。两者合计,它们提供了新的见解,并为导致与年龄相关的学习障碍(包括空间学习)的分子机制产生了新的假设。

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