Screening of key biomarkers in osteoporosis: Evidence from bioinformatic analysis

OBJECTIVE

To analyze the expression characteristics of osteoporosis-related genes by bioinformatics and elucidate the pathogenesis of osteoporosis.

METHODS

The differentially expressed genes (DEGs), microRNA (miRNA), and genes with differentially methylated regions (DMRS) in promoters were identified. The protein-protein interaction (PPI) network was constructed and performed. The Clue Gene Ontology analysis and miRNA-mRNA (messenger RNA) regulatory network were constructed using Cytoscape.

RESULTS

Fifty-nine DEGs, 10 differential miRNAs, and 2083 genes with DMRs were screened out. The Proteasome-Modulator (PSMD) family proteins and estrogen receptor 1 (ESR1) are vital for the PPI analysis of DEGs. The interaction network of the Smad3 protein showed that the degree of connection to ESR1, PSMD11, and transcription factor 4 (TCF4) is very high. Homo sapiens (hsa)-miR-106b-5p was differential and regulated TCF4 through building the miRNA-mRNA regulatory network. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of DEGs focused on vascular smooth muscle contraction, thyroid hormone signaling pathway, and estrogen signaling pathway. The Gene Ontology (GO) function analysis of genes with DMRs in promoters was primarily concentrated in the cell differentiation, positive regulation of CDP-diacylglycerol-serine O-phosphatidyltransferase activity, and positive regulation of C-palmitoyltransferase activity. The KEGG enrichment of genes with DMRs in promoters largely focused on glycerol phospholipid metabolism, histidine metabolism, Adenosine 5'-monophosphate-activated protein kinase signaling pathway, Hedgehog signaling pathway, and mRNA surveillance pathway.

CONCLUSION

Hsa-miRNA-106b-5p regulates bone formation and the pathogenesis of osteoporosis by controlling TCF4, and methylation modification of TCF4 can also affect the pathogenesis of osteoporosis.

mintRULS: Prediction of miRNA–mRNA Target Site Interactions Using Regularized Least Square Method

Identification of miRNA–mRNA interactions is critical to understand the new paradigms in gene regulation. Existing methods show suboptimal performance owing to inappropriate feature selection and limited integration of intuitive biological features of both miRNAs and mRNAs. The present regularized least square-based method, mintRULS, employs features of miRNAs and their target sites using pairwise similarity metrics based on free energy, sequence and repeat identities, and target site accessibility to predict miRNA-target site interactions. We hypothesized that miRNAs sharing similar structural and functional features are more likely to target the same mRNA, and conversely, mRNAs with similar features can be targeted by the same miRNA. Our prediction model achieved an impressive AUC of 0.93 and 0.92 in LOOCV and LmiTOCV settings, respectively. In comparison, other popular tools such as miRDB, TargetScan, MBSTAR, RPmirDIP, and STarMir scored AUCs at 0.73, 0.77, 0.55, 0.84, and 0.67, respectively, in LOOCV setting. Similarly, mintRULS outperformed other methods using metrics such as accuracy, sensitivity, specificity, and MCC. Our method also demonstrated high accuracy when validated against experimentally derived data from condition- and cell-specific studies and expression studies of miRNAs and target genes, both in human and mouse.

MicroRNA Targeting

MicroRNAs (miRNAs) are small noncoding elements that play essential roles in the posttranscriptional regulation of biochemical processes. miRNAs recognize and target multiple mRNAs; therefore, investigating miRNA dysregulation is an indispensable strategy to understand pathological conditions and to design innovative drugs. Targeting miRNAs in diseases improve outcomes of several therapeutic strategies thus, this present study highlights miRNA targeting methods through experimental assays and bioinformatics tools. The first part of this review focuses on experimental miRNA targeting approaches for elucidating key biochemical pathways. A growing body of evidence about the miRNA world reveals the fact that it is not possible to uncover these molecules' structural and functional characteristics related to the biological processes with a deterministic approach. Instead, a systemic point of view is needed to truly understand the facts behind the natural complexity of interactions and regulations that miRNA regulations present. This task heavily depends both on computational and experimental capabilities. Fortunately, several miRNA bioinformatics tools catering to nonexperts are available as complementary wet-lab approaches. For this purpose, this work provides recent research and information about computational tools for miRNA targeting research.

Functional role of miR‑155 in physiological and pathological processes of liver injury (Review)

There are several types of liver injury, including alcohol‑induced liver injury, drug‑induced liver injury, infectious liver injury, cirrhosis, liver ischemia/reperfusion injury and liver failure. In recent years, accumulated data have demonstrated that microRNAs (miRNAs/miRs) may be involved in the occurrence and development of a variety of systemic diseases, such as immune diseases, tumors and nervous system diseases. miR‑155 is a key miRNA, which has been studied extensively and has been shown to target different genes. In the present review, the potential effects and mechanisms of miR‑155 on the physiological and pathological processes of liver injury were reviewed from the perspective of cell stress, inflammation and activation of fibrosis. In addition, the potential benefits of miR‑155 as a therapeutic target and predictor of liver injury were summarized.

Knockdown of miR-125b-5p inhibits the proliferation and invasion of gastric carcinoma cells by targeting RYBP

Gastric carcinoma, one of the most aggressive and lethal human malignancies, is associated with poor prognosis despite progress in therapeutic strategies. This study examined the potential function and mechanism of action of microRNA-125b-5p (miR-125b-5p) in the pathogenesis of gastric carcinoma. We recognized that miR-125b-5p was elevated in gastric carcinoma, and its decreased expression was associated with a better prognosis. Loss-of-function assays showed that miR-125b-5p suppression inhibited the proliferative and invasive abilities of gastric cancer cells. Furthermore, RING1 and YY1-binding protein (RYBP) was found to be target gene for miR-125b-5p action; miR-125b-5p negatively regulates RYBP expression. According to the results of rescue experiments, RYBP downregulation partially counteracted the miR-125b-5p silence-mediated inhibitory function in gastric cancer progression. Collectively, these data elucidated the molecular mechanisms of the miR-125b-5p/RYBP axis in gastric cancer invasion and growth.

MiR-141-3p downregulation promotes tube formation, migration, invasion and inhibits apoptosis in hypoxia-induced human umbilical vein endothelial cells by targeting Notch2

Vascular endothelial cell damage is regarded as the carrier in the progression of the pathological changes of preeclampsia (PE) from the placenta to maternal organs. MicroRNA (miR)-141-3p was aberrantly expressed during PE pathogenesis. We investigated the role of miR-141-3p in regulating the biological behaviors of endothelial cells in PE. Human umbilical vein endothelial cells (HUVECs) were isolated from the human umbilical cords and cultured under hypoxia condition to establish PE models. The binding of miR-141-3p and Notch2 was confirmed by dual-luciferase reporter assay. HUVECs were transfected with miR-141-3p inhibitor and siRNA-Notch2. The viability, vascularization capability, migration, and invasion of HUVECs were evaluated by MTT, tube formation, and Transwell assays. Cell apoptosis was measured via flow cytometry. The expressions of miR-141-3p, Notch2, Bcl-2, Bax and cleaved caspase-3 were assessed by qRT-PCR or Western blot. MiR-141-3p expression was upregulated in the HUVECs isolated from PE tissues and hypoxia-induced HUVECs. Hypoxia treatment inhibited viability, tube formation, migration, and invasion, and promoted apoptosis in HUVECS, as well as increased Bax and cleaved caspase-3 expressions and decreased Bcl-2 expression. Downregulating miR-141-3p expression promoted viability, tube formation, migration and invasion, and inhibited apoptosis in HUVECs, counteracting the effect of hypoxia on HUVECs. MiR-141-3p directly targeted Notch2. Silencing Notch2 reversed the promoting effect of downregulated miR-141-3p expression on HUVECs. In conclusion, downregulating miR-141-3p expression during hypoxia promotes tube formation, migration, and invasion and inhibits apoptosis in HUVECs by targeting Notch2.

ChiRA: an integrated framework for chimeric read analysis from RNA-RNA interactome and RNA structurome data

BACKGROUND

With the advances in next-generation sequencing technologies, it is possible to determine RNA-RNA interaction and RNA structure predictions on a genome-wide level. The reads from these experiments usually are chimeric, with each arm generated from one of the interaction partners. Owing to short read lengths, often these sequenced arms ambiguously map to multiple locations. Thus, inferring the origin of these can be quite complicated. Here we present ChiRA, a generic framework for sensitive annotation of these chimeric reads, which in turn can be used to predict the sequenced hybrids.

RESULTS

Grouping reference loci on the basis of aligned common reads and quantification improved the handling of the multi-mapped reads in contrast to common strategies such as the selection of the longest hit or a random choice among all hits. On benchmark data ChiRA improved the number of correct alignments to the reference up to 3-fold. It is shown that the genes that belong to the common read loci share the same protein families or similar pathways. In published data, ChiRA could detect 3 times more new interactions compared to existing approaches. In addition, ChiRAViz can be used to visualize and filter large chimeric datasets intuitively.

CONCLUSION

ChiRA tool suite provides a complete analysis and visualization framework along with ready-to-use Galaxy workflows and tutorials for RNA-RNA interactome and structurome datasets. Common read loci built by ChiRA can rescue multi-mapped reads on paralogous genes without requiring any information on gene relations. We showed that ChiRA is sensitive in detecting new RNA-RNA interactions from published RNA-RNA interactome datasets.

miRNA-Coordinated Schizophrenia Risk Network Cross-Talk With Cardiovascular Repair and Opposed Gliomagenesis

Background

Schizophrenia risk genes are widely investigated, but a systemic analysis of miRNAs contributing to schizophrenia is lacking.

Methods

Schizophrenia-associated genetic loci profiles were derived from a genome-wide association study (GWAS) from the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) dataset. Experimentally confirmed relationships between miRNAs and their target genes were retrieved from a miRTarBase. A competitive gene set association analysis for miRNA-target regulations was conducted by the Multi-marker Analysis of GenoMic Annotation (MAGMA) and further validated by literature-based functional pathway analysis using Pathway Studio. The association between the targets of three miRNAs and schizophrenia was further validated using a GWAS of antipsychotic treatment responses.

Results

Three novel schizophrenia-risk miRNAs, namely, miR-208b-3p, miR-208a-3p, and miR-494-5p, and their targetomes converged on calcium voltage-gated channel subunit alpha1 C (CACNA1C) and B-cell lymphoma 2 (BCL2), and these are well-known contributors to schizophrenia. Both miR-208a-3p and miR-208b-3p reduced the expression of the RNA-binding protein Quaking (QKI), whose suppression commonly contributes to demyelination of the neurons and to ischemia/reperfusion injury. On the other hand, both QKI and hsa-miR-494-5p were involved in gliomagenesis.

Conclusion

Presented results point at an orchestrating role of miRNAs in the pathophysiology of schizophrenia. The sharing of regulatory networks between schizophrenia and other pathologies may explain higher cardiovascular mortality and lower odds of glioma previously reported in psychiatric patients.

Predicting miRNA-lncRNA interactions and recognizing their regulatory roles in stress response of plants

It has been found that each non-coding RNA (ncRNA) can act not only through its target gene, but also interact with each other to act on biological traits, and this interaction is more common. Many studies focus mainly on the analysis of microRNA(miRNA) and message RNA (mRNA) interactions. In this study, we investigated miRNA and long non-coding RNA (lncRNA) interactions using support vector regression (SVR) for prediction of new target genes in Arabidopsis thaliana and identify some regulatory roles in stress response. The networks of miRNA-mRNA, miRNA-lncRNA and miRNA-mRNA-lncRNA were constructed. They were further analyzed and interpreted in R. We showed that miRNA with low sequence number, targeted lncRNA with high sequence number and miRNA with high sequence number targeted lncRNA with low sequence number. The experimental results showed that there is a regulatory relationship between miRNA-lncRNA. New RNA targets were predicted using SVR with new gene expression mechanism and the stress related functions were annotated.