Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

Construction and Analysis of ceRNA Networks Reveal the Key Genes Associated with Bovine Herpesvirus Type 1 Infection

Background

Virus infection can cause the changes of lncRNA expression levels to regulate the interaction between virus and host, but the relationship between BHV-1 infection and lncRNA has not been reported.

Methods

In this study, in order to reveal the molecular mechanism of RNA in BoHV-1 infection, the Madin-Darby bovine kidney (MDBK) cells were infected with BoHV-1, transcriptome sequencing were performed by next-generation sequencing at 18 h or 24 h or 33 h of viral infection and then based on the competitive endogenous RNA (ceRNA) theory, lncRNA-miRNA-mRNA networks were constructed using these high-throughput sequencing data. The network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed for functional annotation and exploration of ncRNA ceRNAs in BoHV-1 infection.

Results

The results showed that 48 lncRNAs, 123 mRNAs and 20 miRNAs as differentially expressed genes, and the mitogen activated protein kinase (MAPK) pathway and calcium signaling pathway were significantly enriched in the ceRNA network. Some differentially expressed lncRNA genes were randomly selected for verification by RT-qPCR, and the results showed that their expression trend was consistent with the results of transcriptome sequencing data.

Conclusion

This study revealed that BoHV-1 infection can affect the expression of RNAs in MDBK cells and the regulation of ceRNA network to carry out corresponding biological functions in the host, but further experimental studies are still necessary to prove the hub genes function in ceRNA network and the molecular mechanism in BoHV-1 infection.

Exploring the Novel Computational Drug Target and Associated Key Pathways of Oral Cancer

Oral cancer (OC) is a serious health concern that has a high fatality rate. The oral cavity has seven kinds of OC, including the lip, tongue, and floor of the mouth, as well as the buccal, hard palate, alveolar, retromolar trigone, and soft palate. The goal of this study is to look into new biomarkers and important pathways that might be used as diagnostic biomarkers and therapeutic candidates in OC. The publicly available repository the Gene Expression Omnibus (GEO) was to the source for the collection of OC-related datasets. GSE74530, GSE23558, and GSE3524 microarray datasets were collected for analysis. Minimum cut-off criteria of |log fold-change (FC)| > 1 and adjusted p < 0.05 were applied to calculate the upregulated and downregulated differential expression genes (DEGs) from the three datasets. After that only common DEGs in all three datasets were collected to apply further analysis. Gene ontology (GO) and pathway analysis were implemented to explore the functional behaviors of DEGs. Then protein−protein interaction (PPI) networks were built to identify the most active genes, and a clustering algorithm was also implemented to identify complex parts of PPI. TF-miRNA networks were also constructed to study OC-associated DEGs in-depth. Finally, top gene performers from PPI networks were used to apply drug signature analysis. After applying filtration and cut-off criteria, 2508, 3377, and 670 DEGs were found for GSE74530, GSE23558, and GSE3524 respectively, and 166 common DEGs were found in every dataset. The GO annotation remarks that most of the DEGs were associated with the terms of type I interferon signaling pathway. The pathways of KEGG reported that the common DEGs are related to the cell cycle and influenza A. The PPI network holds 88 nodes and 492 edges, and CDC6 had the highest number of connections. Four clusters were identified from the PPI. Drug signatures doxorubicin and resveratrol showed high significance according to the hub genes. We anticipate that our bioinformatics research will aid in the definition of OC pathophysiology and the development of new therapies for OC.