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Coexpression networks based on natural variation in human gene expression at baseline and under stress .

机译:共表达网络基于自然变化的人类基因表达的基线和压力下。

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摘要

Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress.;First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility. These analyses showed that human coexpression networks based on natural variation may offer information on gene functions and interactions.;We then examined the extent to which networks change upon stress. We studied changes in expression levels and gene relationships induced by two stresses: endoplasmic reticulum (ER) stress and exposure to ionizing radiation (IR). Using large datasets, we found between 30---70% of genes change expression upon stress. In contrast, the majority (between 65---95%) of gene relationships are maintained as assessed using statistical, network and machine learning methods. However, a subset of genes altered relationships upon stress. These genes tended to be critical for the cellular response to the specific stress examined. For example, BIP and CHOP altered relationships in ER stress; p21, GADD45A and CCNB1 altered relationships in IR stress. Some genes with altered relationships have not been implicated in ER or IR stress or do not change expression; these are genes that may be critical but remain unexplored. We provide evidence implicating two such genes, INHBE and SLC3A2, in the response to ionizing radiation. Our results suggest that the majority of gene relationships are maintained upon stress, but those genes with altered relationships tend to be critical to the stress response.
机译:基因在网络中相互作用以协调细胞过程。在这里,我们使用了基于基因表达中自然变化的共表达网络来研究人类基因的功能和相互作用。我们问这些网络如何响应压力而变化。首先,我们研究了基线时的人类共表达网络。我们通过鉴定来自三个独立样本的295个个体的永生化B细胞中890万个基因对的表达水平的相关性,构建了网络。由此产生的网络使我们能够推断生物过程之间的相互作用。我们使用网络来预测人类特征较差的基因的功能,并提供了一些实验支持。检查涉及疾病的基因后,我们发现IFIH1(一种糖尿病易感性基因)与YES1相互作用,从而影响葡萄糖的转运。易患相同疾病的基因在网络中非随机聚集,这表明该网络可用于识别影响疾病易感性的候选基因。这些分析表明,基于自然变异的人类共表达网络可能提供有关基因功能和相互作用的信息。;然后我们研究了网络在压力下变化的程度。我们研究了由两种压力引起的表达水平和基因关系的变化:内质网(ER)压力和电离辐射(IR)。使用大型数据集,我们发现30 --- 70%的基因在压力下会改变表达。相比之下,使用统计,网络和机器学习方法评估时,大多数基因关系(介于65 --- 95%之间)得以维持。然而,基因的一个子集在压力下改变了关系。这些基因往往对细胞对特定压力的反应至关重要。例如,BIP和CHOP改变了内质网应激的关系。 p21,GADD45A和CCNB1改变了IR应激的关系。某些具有改变关系的基因尚未与ER或IR应激有关,也没有改变表达。这些基因可能很关键,但尚未开发。我们提供证据表明在电离辐射的响应中涉及两个这样的基因,INHBE和SLC3A2。我们的结果表明,大多数基因关系在压力下得以维持,但那些具有改变的关系的基因往往对压力反应至关重要。

著录项

  • 作者

    Nayak, Renuka.;

  • 作者单位

    University of Pennsylvania.;

  • 授予单位 University of Pennsylvania.;
  • 学科 Biology Genetics.;Engineering System Science.;Biology Bioinformatics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 674 p.
  • 总页数 674
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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