توصيفگر ها :
گاوهاي شيري , بيماري يون , شبكه هم بيان ژني وزن دار , شبكه هاي lncRNA-mRNA-TF , شبكه هاي PPIs , RNA-Seq , ژن هاي هاب , ژن هاي هاب-هاب , ماژول مورد توافق
چكيده انگليسي :
Johne’s disease (JD) is a chronic infection of ruminants that burdens dairy herds with a significant economic loss. The pathogenesis of the disease has not been revealed clearly due to its complex nature. In order to achieve deeper biological insights into molecular mechanisms involved in JD, a system biology approach was used in the current study. As far as is known this is the first study that considers lncRNAs, TFs and mRNAs, simultaneously, to construct an integrated gene regulatory network involved in JD. RNA-Seq Analysis was performed on two datasets related to JD. The created expression matrices were applied to construct co-expression networks using weighted gene co-expression network analysis (WGCNA). After detection of co-expression modules using WGCNA, preservation analysis was done on the resulted modules. Then, functional enrichment analysis was performed to identify gene ontology terms in each module. Since non-preserved modules have altered connectivity patterns in normal samples compared to infected ones, they can indicate sets of genes influenced by the disease. Therefore, hub, hub-hub, TF, lncRNA genes and their targets were identified in the non-preserved modules and integrated networks of lncRNA-mRNA-TF were constructed in these modules. In the first dataset, 21 modules out of 47 non-preserved modules showed significant biological processes associated with immune system and JD. Among them, five non-preserved modules including green, royalblue, purple, darkturquoise, and white were considered the most related modules to JD based on their hub and hub-hub genes and biological processes. Some of JD related pathways in these modules comprise “positive regulation of cytokine-mediated signaling pathway,” “T cell differentiation,” “neutrophil activation,” and “defense response.” Furthermore, several genes were identified in these modules, including APLP2, VDR, SLC11A1, MAPK8IP1, TLR4, CORO1A, IRF1, and BLA-DQB, which are potentially associated with JD pathogenesis. In the second dataset, six modules out of 15 non-preserved modules had significant biological processes associated with JD. The brown module was introduced as the most important one because of having the highest number of significant terms related to JD and hub and hub-hub genes involved in the disease. Biological processes including “cytokine-mediated signaling pathway,” “inflammatory response,” “positive regulation of apoptotic process,” “regulation of interferon-gamma production” and “cytokine secretion” are among the associated processes with JD in this module. Furthermore, in this study for the first time a computational pipeline was proposed in order to authenticate reproducibility of modules of one dataset in another one. The presented approach enabled us to identify and confirm non-preserved consensus modules in two datasets. Eight out of 21 non-preserved consensus modules owned significant biological processes related to JD. The sienna3 module as the most important non-preserved consensus module was enriched in the biological processes such as “cytokine-mediated signaling pathway,” “inflammatory response,” “response to interleukin-1,” “response to interferon-gamma,” and “regulation of B cell proliferation.” Several genes of this module that can be potential candidates for JD pathogenesis are BLA-DQB, TLR2, ADIPOR1, TREM1, NFKB1, and IRF1. This study expanded our knowledge of molecular mechanisms involved in JD, the identified hub and hub-hub genes can serve as breeding and diagnostic targets, and the presented pipeline enabled us to achieve more valid results.
