微rna-转录因子网络大尺度数学模型中传感器回路介导的基因剂量补偿建模

Man-Sai Acón-Chan, Francisco Siles Canales, R. Mora-Rodríguez
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引用次数: 0

摘要

在之前的工作中,我们开发了一个生物计算平台,用于自动构建microrna -转录因子(TF)调控网络的数学模型,以研究基因剂量补偿。我们假设基因剂量补偿通过下调一组核心补偿基因的表达来维持具有高水平染色体改变的肿瘤细胞的活力。在这里,我们报告了这些补偿候选者根据其染色体位置形成簇,并且它们共享与mirna和tf相互作用的大规模网络的连接。虽然前馈回路的初始模型不显示基因剂量补偿,但我们通过只包括实验验证的相互作用的传感器回路来简化模型。传感器回路允许基因感知并对其自身表达的波动做出反应。该模型显示基因剂量补偿MYC和STAT3,但这两个基因的遗传调控可以扩展到共同调节其他补偿基因的表达。这些结果有助于确定基因剂量补偿网络,对特定节点的操作有可能成为特异性靶向非整倍体癌细胞的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Gene Dosage Compensation Mediated by Sensor Loops in Large-Scale Mathematical Models of Microrna-Transcription Factor Networks
In a previous work we developed a biocomputational platform to automatically construct mathematical models of microRNA-transcription factor (TF) regulatory network to study gene dosage compensation. We hypothesized that gene dosage compensation maintains the viability of tumoral cells with high levels of chromosomal alterations by down regulating the expression of a core group of compensated genes. Here we report that those compensated candidates form clusters according to their chromosomal locations and they share the connections of a large-scale network of putative interactions with miRNAs and TFs. Although initial models of feed-forward loops do not show gene dosage compensation, we simplified the model by including only sensor loops of experimentally validated interactions. A sensor loop allows a gene to sense and react to fluctuations of its own expression. The resulting model shows gene dosage compensation for MYC and STAT3 but the genetic regulation of these two genes can be extended to co-regulate the expression of other compensated genes. These results contribute to the identification of a network of gene dosage compensation, which manipulation of specific nodes has the potential to become a novel approach to specifically target aneuploid cancer cells.
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