Bioinformatics and Computational Biology Research Center, Shiraz University of Medical Sciences, Shiraz P.O. Box 71336-54361, Iran.
Department of Biology, Temple University, Philadelphia, PA 19122, USA.
Biomolecules. 2020 Jun 3;10(6):850. doi: 10.3390/biom10060850.
Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.
通过表达谱分析研究基因产物之间的关系是系统生物学中的一种常用方法。许多研究已经将结果推广到中心法则信息流的不同层次，并假设转录本和蛋白质表达水平之间存在相关性。然而，基因产物的各种相互作用（即激活和抑制）与其表达谱之间的关系尚未得到广泛研究。事实上，根据差异表达基因寻找任何扰动是常见的方法，而分析表达变化对信号通路活性的影响往往被忽略。在这项研究中，我们研究了基因表达的显著变化是否必然导致信号通路失调。我们使用四个常用且全面的数据库，提取了所有相关的基因表达数据以及直接连接基因对之间的所有关系。我们旨在评估表达水平以及基因对之间因果关系的一致性或符号一致性的比例。通过与随机不相关的基因对进行比较，我们说明了信号网络是不协调的，与记录的表达谱不一致。最后，我们证明为了推断受扰的信号通路，我们需要考虑基因产物表达数据之外的关系类型，特别是在转录本水平。我们断言，通过差异表达基因识别富集的生物学过程在尝试推断失调的途径时是有限的。
