Inferring Gene Regulatory Networks from a Population of Yeast Segregants
Inferring Gene Regulatory Networks from a Population of Yeast Segregants
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DOI：
10.1038/s41598-019-52275-6
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发表时间：
2019-02-04
影响因子：
4.6
通讯作者：
Zhang, Min
中科院分区：
文献类型：
--
作者：
Chen, Chen;Zhang, Dabao;Zhang, Min
构建基因调控网络对于揭示复杂性状的遗传结构和理解疾病的机制至关重要。基于酵母的基因表达和单核苷酸多态性数据，采用两阶段惩罚最小二乘法构建了基因调控网络。通过对一组替代变量的最优预测，在第一阶段建立了一个大型结构方程组，然后在第二阶段对调节效应进行一致的选择。利用这种方法，我们确定了富含基因本体类别的子网络，揭示了控制这些生物途径的定向调节机制。我们对基于表达的数量性状位点的定位和分析揭示了生物通路中基因表达的已知改变，该改变导致对磷脂网络中伴生通路基因的调节作用。此外，我们确定了这些富含基因本体的子网络中的节点，这些子网络由反式表达数量性状位点驱动的转录因子协调控制。总之，将记录的转录因子调控关联与使用数量性状位点数据的结构方程系统定义的子网络相结合，是描述生物学途径的转录控制的有效手段。
Constructing gene regulatory networks is crucial to unraveling the genetic architecture of complex traits and to understanding the mechanisms of diseases. On the basis of gene expression and single nucleotide polymorphism data in the yeast, Saccharomyces cerevisiae, we constructed gene regulatory networks using a two-stage penalized least squares method. A large system of structural equations via optimal prediction of a set of surrogate variables was established at the first stage, followed by consistent selection of regulatory effects at the second stage. Using this approach, we identified subnetworks that were enriched in gene ontology categories, revealing directional regulatory mechanisms controlling these biological pathways. Our mapping and analysis of expression-based quantitative trait loci uncovered a known alteration of gene expression within a biological pathway that results in regulatory effects on companion pathway genes in the phosphocholine network. In addition, we identify nodes in these gene ontology-enriched subnetworks that are coordinately controlled by transcription factors driven by trans-acting expression quantitative trait loci. Altogether, the integration of documented transcription factor regulatory associations with subnetworks defined by a system of structural equations using quantitative trait loci data is an effective means to delineate the transcriptional control of biological pathways.