Integrated miRNA and mRNA Expression Profiling to Identify mRNA Targets of Dysregulated miRNAs in Pulmonary Tuberculosis

Zhang, Xing; Zhu, Min; Hu, Xiaolong

doi:10.2217/epi-2018-0028

Cited by 15 publications

(8 citation statements)

References 33 publications

(41 reference statements)

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“…15,16 miRNA is a type of noncoding RNA between 22 and 24 nucleotide (nt). 17 Acting as a negative regulator of gene expression, miR-NAs are predicted to target 60% of all human protein-coding genes and involved in many biological processes, including proliferative responses and inflammatory/immune responses. 18 Several studies have investigated the altered miRNA in RSV-infected airway epithelial cells and the role of the altered miRNAs has recently been highlighted.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Respiratory syncytial virus infection‐induced mucus secretion by down‐regulation of miR‐34b/c‐5p expression in airway epithelial cells

Yang

Xiao

et al. 2020

J Cellular Molecular Medi

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Section: Introductionmentioning

confidence: 99%

“…miRNA is a type of noncoding RNA between 22 and 24 nucleotide (nt) 17 . Acting as a negative regulator of gene expression, miRNAs are predicted to target 60% of all human protein‐coding genes and involved in many biological processes, including proliferative responses and inflammatory/immune responses 18 .…”

Section: Introductionmentioning

confidence: 99%

Respiratory syncytial virus infection‐induced mucus secretion by down‐regulation of miR‐34b/c‐5p expression in airway epithelial cells

Yang

Xiao

et al. 2020

J Cellular Molecular Medi

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“…miRNAs are epigenetic regulators that post-transcriptionally regulate the expression of protein-coding genes [35]. They have emerged as novel regulators in various biological processes and pathogenic conditions such as in ammation, cancer and infectious diseases [36].…”

Section: Discussionmentioning

confidence: 99%

Whole-Transcriptome RNA Sequencing Reveals the Molecular Responses and C eRNA Regulatory Network under Simulated Long-term Spaceflight Composite Stress in Hippocampus

Yin

Liu

et al. 2022

Preprint

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To systematically evaluate the affect of simulated long-term spaceflight composite stress (LSCS) in hippocampus and to gain more insights into the transcriptomic landscape and molecular mechanism, we performed whole-transcriptome sequencing based on the control group (Ctrl) and the simulated long-term spaceflight composite stress group (LSCS) from six hippocampus of rats. Subsequently, differential expression analysis was performed on the Ctrl and LSCS groups, followed by enrichment analysis and functional interaction prediction analysis to investigate gene-regulatory circuits in LSCS. In addition, competitive endogenous RNA (ceRNA) network was constructed to gain insights into genetic interaction. The result showed that 276 differentially expressed messenger RNAs (DEmRNAs), 139 differentially expressed long non-coding RNAs (DElncRNAs), 103 differentially expressed circular RNAs (DEcircRNAs), and 52 differentially expressed microRNAs (DEmiRNAs) were found in LSCS samples compared with the controls, which were then subjected to enrichment analysis of Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to find potential functions. PI3K-Akt signaling pathway and MAPK signaling pathway may play fundamental roles in the pathogenesis of LSCS. A ceRNA network was constructed with the predicted 340 DE pairs, which revealed the interaction roles of 220 DEmiRNA-DEmRNA pairs, 76 DEmiRNA-DElncRNA pairs, and 44 DEmiRNA-DEcircRNA pairs. Further, Thrombospondins2 was found to be a key target among those ceRNAs. Overall, we conducted for the first time a full transcriptomic analysis of the response of hippocampus to the LSCS that involved a potential ceRNA network, thus providing a basis to study the underlying mechanism of the LSCS.

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“…Based on the ceRNA (competing endogenous RNA) regulatory mechanisms (Salmena et al, 2011), the miRNA targets (miRNA-mRNA or miRNA-circRNA targets) were predicted, and then circRNA-mRNA regulation pairs were predicted according with the guilty by association method (Zhang et al, 2017;Zhang, Zhu & Hu, 2018). At the same time, the correlation of regulation relation to expression value was calculated.…”

Section: Cerna Network Analysismentioning

confidence: 99%

Identification and comparison of circular RNAs in preeclampsia

Ping

Shen

et al. 2021

PeerJ

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Background Preeclampsia (PE) is a pregnancy-specific syndrome, belongs to the gestational hypertension diseases category and is considered among the causes of maternal and perinatal mortality and morbidity. However, the pathogenesis of PE is still vague. Methods In the present study, the circular RNA (circRNA) expression patterns of normal pregnant women and PE patients were investigated using whole RNA sequencing. Results A total of 151 differential expressed circRNAs were identified including 121 upregulated and 30 downregulated ones. Functional and pathway enrichment analysis was conducted on the differentially expressed circRNAs using Gene Ontology and KEGG databases. The results of this analysis indicated that several crucial biological processes and pathways were enriched in PE patients. circRNA–microRNA (miRNA) interaction analysis indicated that the reported differentially expresse circRNAs may be associated with some regulatory functions through miRNAs in PE patients. Two ceRNAs networks were constructed according to the targeting relationship between circRNAs/miRNAs and miRNAs/mRNAs. One sub-network contained one upregulated circRNA, four downregulated miRNAs and five upregulated mRNAs, and another sub-network contained 10 downregulated circRNAs, 21 upregulated miRNAs and 15 downregulated mRNAs. Conclusion CircRNA expression patterns have been investigated and this analysis revealed their potential regulatory mechanisms in PE patients. We constructed the ceRNAs (competing endogenous RNA) to reveal the potential molecular roles of dysregulated circRNAs in the PE patients using RNA sequencing data. circRNA_13301 was the only one upregulated circRNA in ceRNA being targeted by four miRNAs.

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Integrated miRNA and mRNA Expression Profiling to Identify mRNA Targets of Dysregulated miRNAs in Pulmonary Tuberculosis

Cited by 15 publications

References 33 publications

Respiratory syncytial virus infection‐induced mucus secretion by down‐regulation of miR‐34b/c‐5p expression in airway epithelial cells

Respiratory syncytial virus infection‐induced mucus secretion by down‐regulation of miR‐34b/c‐5p expression in airway epithelial cells

Whole-Transcriptome RNA Sequencing Reveals the Molecular Responses and C eRNA Regulatory Network under Simulated Long-term Spaceflight Composite Stress in Hippocampus

Identification and comparison of circular RNAs in preeclampsia

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