Abstract
BackgroundDespite the high yearly prevalence of Influenza, the pathogenesis mechanism and involved genes have not been fully known. Finding the patterns and mapping the complex interactions between different genes help us to find the possible biomarkers and treatment targets.MethodsHerein, weighted gene co-expression network analysis (WGCNA) was employed to construct a co-expression network among genes identified by microarray analysis of the pediatric influenza-infected samples.ResultsThree of the 38 modules were found as the most related modules to influenza infection. At a functional level, we found that the genes in these modules regulate the immune responses, protein targeting, and defense to virus. Moreover, the analysis of differentially expressed genes disclosed 719 DEGs between the normal and infected subjects. The comprehensive investigation of genes in the module involved in immune system and viral defense (yellow module) revealed that SP110, HERC5, SAMD9L, RTP4, C19orf66, HELZ2, EPSTI1, and PHF11 which were also identified as DEGs (except C19orf66) have the potential to be as the biomarkers and also drug targeting for the treatment of pediatric influenza.ConclusionsThe WGCN analysis revealed co-expressed genes which were involved in the innate immune system and defense to virus. The differentially expressed genes in the identified modules can be considered for designing drug targets. Moreover, modules can help to find pathogenesis routes in the future.
Highlights
Despite the high yearly prevalence of Influenza, the pathogenesis mechanism and involved genes have not been fully known
Weighted gene co-expression network construction and modules identification To exploration the required criterion for weighted gene co-expression network analysis (WGCNA), the scale-free topology fit index was calculated for various softthresholding power
To determine the biologically meaningful modules, all modules were submitted into the STRING and ones which their proteins were highly connected, were selected
Summary
Despite the high yearly prevalence of Influenza, the pathogenesis mechanism and involved genes have not been fully known. The prevalence amount of type A is more than other influenza types in the world. The burden of seasonal influenza virus caused the infection of 3–5 million cases with severe illness symptoms [1]. Influenza viruses affect the human life more than other respiratory illnesses. The pathogenesis of Influenza has not been yet well understood since it depends on the immune system and viral determinants. The previous infection or vaccination causes the cellular immunity which affected the efficacy of infection with various seasonal, Microarray is a high-throughput technique has the ability of simultaneous measuring of thousands of gene expressions and so generating tremendous data. In order to general and detailed evaluation of the biological phenomena in each study, the special and sometimes complicated statistical analysis is required [3, 4]
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