Gene Networks Show Associations with Seed Region Connectivity
Gene Networks Show Associations with Seed Region Connectivity
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DOI：
10.1002/hbm.23579
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发表时间：
2017-06-01
影响因子：
4.8
通讯作者：
Greenwood, Celia M. T.
中科院分区：
文献类型：
--
作者：
Forest, Marie;Iturria-Medina, Yasser;Greenwood, Celia M. T.
成人大脑连接的主要模式是在发育过程中通过瞬时表达的基因协调网络建立的；然而，神经网络在整个生命过程中仍然具有可塑性。目前的研究假设，关键种子区的结构连通性可能会对其连接的靶标产生影响，这反映在这些靶区的基因表达上。为了验证这一假设，对来自Allen人脑图谱的两个大脑的数据进行了分析，这些数据既有基因表达，也有DW-MRI。根据DW-MRI数据估计结构连通性，并使用网络拓扑驱动的方法，即加权基因共表达网络分析(WGCNA)，在大脑中聚类具有相似表达模式的基因。然后使用组指数套索模型来预测基因簇表达摘要作为种子区域结构连接性模式的函数。在几个基因簇中，位于脑干、间脑和海马结构的大脑区域被发现对这些表达摘要具有显著的预测能力。这些与连接相关的簇富含与突触信号和大脑可塑性相关的基因。此外，使用基于种子区域的连通性为理解基因表达和连通性之间的关系提供了一个新的视角。(C)2017威利期刊公司。
Primary patterns in adult brain connectivity are established during development by coordinated networks of transiently expressed genes; however, neural networks remain malleable throughout life. The present study hypothesizes that structural connectivity from key seed regions may induce effects on their connected targets, which are reflected in gene expression at those targeted regions. To test this hypothesis, analyses were performed on data from two brains from the Allen Human Brain Atlas, for which both gene expression and DW-MRI were available. Structural connectivity was estimated from the DW-MRI data and an approach motivated by network topology, that is, weighted gene coexpression network analysis (WGCNA), was used to cluster genes with similar patterns of expression across the brain. Group exponential lasso models were then used to predict gene cluster expression summaries as a function of seed region structural connectivity patterns. In several gene clusters, brain regions located in the brain stem, diencephalon, and hippocampal formation were identified that have significant predictive power for these expression summaries. These connectivity-associated clusters are enriched in genes associated with synaptic signaling and brain plasticity. Furthermore, using seed region based connectivity provides a novel perspective in understanding relationships between gene expression and connectivity. (C) 2017 Wiley Periodicals, Inc.