Inference of Functional Networks of Condition-Specific Response--A Case Study Of Quiescence In Yeast
Inference of Functional Networks of Condition-Specific Response--A Case Study Of Quiescence In Yeast
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条件特异性响应功能网络的推断--酵母静止的案例研究
DOI：
10.1142/9789812836939_0006
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发表时间：
2008
影响因子：
--
通讯作者：
Diego Martínez
中科院分区：
文献类型：
--
作者：
Sushmita Roy;T. Lane;M. Werner;Diego Martínez
分析应激环境条件下的条件特异性行为可以深入了解导致不同健康和病变细胞状态的机制。从特定于条件的表达式数据推断出的功能网络（表示统计依赖关系的边）可以提供关于不同条件下的保守和特定行为的细粒度、网络级信息。在本文中，我们研究了一种新的微阵列纲要，用于测量两种独特的静止期酵母细胞群，静止期和非静止期的基因表达。我们做出了以下贡献：(a)开发了一种新的算法来推断以无向概率图模型、马尔可夫随机场为模型的功能网络，(b)推断静态、非静态细胞和指数细胞的功能网络，(c)比较推断的网络以识别这些细胞之间的共同和不同过程。我们发现非静止细胞和指数细胞都比静止细胞有更多的基因本体富集。与静态细胞相比，指数细胞与非静态细胞共享更多的过程，突出了静态细胞的新特性和相对较少的研究。对推断子图的分析确定了在静止和非静止细胞中丰富的过程，以及每种细胞类型特有的过程。最后，SNF1对静止至关重要，它只发生在静止的网络枢纽中，而非静止的网络枢纽则富含人类疾病同源物。
Analysis of condition-specific behavior under stressful environmental conditions can provide insight into mechanisms causing different healthy and diseased cellular states. Functional networks (edges representing statistical dependencies) inferred from condition-specific expression data can provide fine-grained, network level information about conserved and specific behavior across different conditions. In this paper, we examine novel microarray compendia measuring gene expression from two unique stationary phase yeast cell populations, quiescent and non-quiescent. We make the following contributions: (a) develop a new algorithm to infer functional networks modeled as undirected probabilistic graphical models, Markov random fields, (b) infer functional networks for quiescent, non-quiescent cells and exponential cells, and (c) compare the inferred networks to identify processes common and different across these cells. We found that both non-quiescent and exponential cells have more gene ontology enrichment than quiescent cells. The exponential cells share more processes with non-quiescent than with quiescent, highlighting the novel and relatively under-studied characteristics of quiescent cells. Analysis of inferred subgraphs identified processes enriched in both quiescent and non-quiescent cells as well processes specific to each cell type. Finally, SNF1, which is crucial for quiescence, occurs exclusively among quiescent network hubs, while non-quiescent network hubs are enriched in human disease causing homologs.