Integrated microRNA and mRNA Expression Profiling Identifies Novel Targets and Networks Associated with Ebstein’s Anomaly

Little is known about abundance level changes of circulating microRNAs (miRNAs) and messenger RNAs (mRNA) in patients with Ebstein’s anomaly (EA). Here, we performed an integrated analysis to identify the differentially abundant miRNAs and mRNA targets and to identify the potential therapeutic targets that might be involved in the mechanisms underlying EA. A large panel of human miRNA and mRNA microarrays were conducted to determine the genome-wide expression profiles in the blood of 16 EA patients and 16 age and gender-matched healthy control volunteers (HVs). Differential abundance level of single miRNA and mRNA was validated by Real-Time quantitative PCR (RT-qPCR). Enrichment analyses of altered miRNA and mRNA abundance levels were identified using bioinformatics tools. Altered miRNA and mRNA abundance levels were observed between EA patients and HVs. Among the deregulated miRNAs and mRNAs, 76 miRNAs (49 lower abundance and 27 higher abundance, fold-change of ≥2) and 29 mRNAs (25 higher abundance and 4 lower abundance, fold-change of ≥1.5) were identified in EA patients compared to HVs. Bioinformatics analysis identified 37 pairs of putative miRNA-mRNA interactions. The majority of the correlations were detected between the lower abundance level of miRNA and higher abundance level of mRNA, except for let-7b-5p, which showed a higher abundance level and their target gene, SCRN3, showed a lower abundance level. Pathway enrichment analysis of the deregulated mRNAs identified 35 significant pathways that are mostly involved in signal transduction and cellular interaction pathways. Our findings provide new insights into a potential molecular biomarker(s) for the EA that may guide the development of novel targeting therapies.

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Evaluation of molecular pathogenesis of colon cancer in Kerala using high-throughput expression, signaling pathways, and network analyses.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e16065 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e16065-e16065

Author(s):

Prasanth Ariyannur ◽

Pavithran Keechilat ◽

Roopa Paulose ◽

Damodaran M Vasudevan

Keyword(s):

Network Analysis ◽

Signaling Pathways ◽

High Throughput ◽

Expression Profiles ◽

Colon Adenocarcinoma ◽

Fold Change ◽

Molecular Pathogenesis ◽

Pathway Enrichment Analysis ◽

Network Analyses ◽

Significant Difference

e16065 Background: The molecular pathogenesis of colon adenocarcinoma (COAD) is attributed to large molecular changes such as Chromosomal Instability and high somatic copy number variation or defective DNA mismatch repair and consequent microsatellite instability (MSI). The prevalence of this type of cancer is increasing in the state of Kerala, India. A detailed study of the signaling pathways could lead to a better understanding of the central molecular pathological changes and potential biomarkers particular to this population. Methods: High throughput somatic expression analysis using Nanostring PanCancer pathway panel assay was performed. Differentially expressed (DE) genes were selected and KEGG pathway enrichment analysis was performed for assessment of canonical signaling pathways. Expression profiles were compared against the public database, Colon Adenocarcinoma cohort of the Cancer Genome Atlas (TCGA-COAD), using the Genome Expression Profiling Interactive Analysis (GEPIA). Protein-protein interaction network analysis was done using Cytoscape. DE genes were compared against immune cell infiltration in the TCGA-COAD from Tumor Immune Estimation Resource (TIMER) databases. Results: Nanostring assay was performed in 10 Tumor-Normal paired FFPE samples of stage II/III colon adenocarcinoma. Out of > 700 genes, significant difference in expression was found in 83 genes (FDR adjusted p -value < 0.01) with fold-change |fc(log2)| of at least one. Fold-change |fc(log2)| ≥ 2 was found in 19/83 genes. Network analysis clustered 13 out of 17 upregulated genes. Superimposition of the current data on TCGA study showed that among the three genes, four (MET, MCM2, ETV4 and MMP7), were common. DE Genes which were not significant in TCGA COAD study such as INHBA, COL1A1, COL11A1, COMP, SFRP4, SPP1, IL11, LIF, WT1 and DDIT4, were found to be significant in the current study. A few of the unique genes identified in the current study were found to have significant correlation with antigen presenting cells infiltration in the TCGA-COAD studies. Conclusions: Many DE genes from the study population were found to be different from previous large cohort studies in other population. This may suggest a different pathogenesis of COAD in this population, warranting a detailed study on the pathogenesis.

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Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

10.21203/rs.3.rs-21667/v1 ◽

2020 ◽

Author(s):

Ling Zhang ◽

Lu Gao ◽

Yu Zhao ◽

Xuelei Ma

Keyword(s):

Survival Analysis ◽

Protein Interactions ◽

Sequence Data ◽

Gene Prediction ◽

Expression Profiles ◽

Enrichment Analysis ◽

Integrated Analysis ◽

Pathway Enrichment Analysis ◽

Tissue Samples ◽

Cerna Network

Abstract The ceRNA network has been demonstrated to play crucial roles in multiple biological processes and the development of neoplasms, which have the potential to become diagnostic and prognosis markers and therapeutic targets. In this work, we comparing the expression profiles between sarcoma identified differentially expressed genes (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas and normal tissue samples in GEO datasets. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to investigate the major functions of the overlapping DEGs. Then, lncRNA-miRNA interactions and miRNA-mRNA interactions were predicted, and a ceRNA regulatory network was constructed. In addition, the mRNAs included in ceRNA network were used to construct the protein-protein interactions network, and the survival analysis of sarcomas was performed according to the biomarkers included in the ceRNA network. According to the RNA sequence data from GEO dataset, 1296 DEGs were identified in sarcoma samples by combining the GO and Pathway enrichment analysis, 338 DELs were discovered after re-annotating the probes, and 36 DEGs were ascertained through intersecting two different expression miRNAs sets. Further, 448 miRNA-mRNA interactions and 454 miRNA-lncRNA interactions were obtained through target gene prediction, and then, we constructed a lncRNA-miRNA-mRNA ceRNA network containing 9 miRNAs, 69 lncRNAs and 113 mRNAs. PPI network showed that the hub up-regulated nodes include IGF1, PRKCB and GNAI3, and the hub down-regulated nodes include AR, CYCS and PPP1CB. Survival analysis revealed that the expression levels of 12 RNAs involved in the ceRNA network were associated with overall survival of sarcoma patients. Our study showed that the ceRNA network in sarcomas based on that lncRNA could serve as ceRNA and discovered the potential indicators for prognosis of sarcoma patients.

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Integrated Analysis of the lncRNA/circRNA-miRNA-mRNA Expression Profiles Reveals Novel Insights Into Potential Mechanisms in Response to Root-knot Nematodes in Peanut

10.21203/rs.3.rs-968829/v1 ◽

2021 ◽

Author(s):

Ping Xu ◽

Hui Li ◽

Xiaohua Wang ◽

Ge Zhao ◽

Xiaofei Lu ◽

...

Keyword(s):

Expression Profiles ◽

Reduction Process ◽

Synthesis Process ◽

Integrated Analysis ◽

Pathway Enrichment Analysis ◽

Root Knot Nematode ◽

Root Knot Nematodes ◽

Oxidation Reduction ◽

The World

Abstract BackgroundThe high content of oil and protein makes peanut the main oil and edible crop in the world. Root-knot nematode forms root-knot by infecting peanut roots, which lead to poor development of peanut roots and seriously restricts the yield of peanut in the world. With the release of peanut genome, a large number of genetic loci controlling peanut root-knot nematode have been detected, but the molecular mechanism of root-knot nematode is still unclear. ResultsThe whole transcriptome RNA-seq was used to reveal the divergent response to root-knot nematode stress in peanut roots. A total of 430 mRNAs, 111 miRNAs, 4453 lncRNAs and 123 circRNAs were identified differential expression between infected and no-infected peanut, respectively. To understand the potential mechanisms in response to root-knot nematodes in peanut roots, the expression profiles of lncRNA/circRNA-miRNA-mRNA network were constructed. A total of 10 lncRNAs, 4 circRNAs, 5 miRNAs and 13 mRNAs can regularly the expression of mRNA during root-knot nematodes stress by forming competing endogenous RNA and participate in oxidation-reduction process and other various biological metabolism pathways in peanut. The results gained will reveal the role of ceRNAs of peanut in response to root-knot nematodes.ConclusionThe GO classification and KEGG pathway enrichment analysis of core regulatory networks revealing the ceRNAs participate in oxidation-reduction, peroxidase activity, lignin synthesis in xylem and flavonoid synthesis process. Overall, those results could gain the knowledge of the role of no-coding RNAs in response to root-knot nematodes.

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Transcriptome Analysis and miRNA Target Profiling at Various Stages of Root-Knot Nematode Meloidogyne incognita Development for Identification of Potential Regulatory Networks

International Journal of Molecular Sciences ◽

10.3390/ijms22147442 ◽

2021 ◽

Vol 22 (14) ◽

pp. 7442

Author(s):

Vimalraj Mani ◽

Awraris Derbie Assefa ◽

Bum-Soo Hahn

Keyword(s):

Life Cycle ◽

Heat Shock ◽

Meloidogyne Incognita ◽

Mirna Target ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Integrated Analysis ◽

Qrt Pcr ◽

Mrna Targets ◽

Related Proteins

Root-knot nematodes (RKNs) are a group of plant-parasitic nematodes that cause damage to various plant species and extensive economical losses. In this study, we performed integrated analysis of miRNA and mRNA expression data to explore the regulation of miRNA and mRNA in RKNs. In particular, we aimed to elucidate the mRNA targets of Meloidogyne incognita miRNAs and variations of the RKN transcriptome during five stages of its life cycle. Stage-wise RNA sequencing of M. incognita resulted in clean read numbers of 56,902,902, 50,762,456, 40,968,532, 47,309,223, and 51,730,234 for the egg, J2, J3, J4, and female stages, respectively. Overall, stage-dependent mRNA sequencing revealed that 17,423 genes were expressed in the transcriptome of M. incognita. The egg stage showed the maximum number of transcripts, and 12,803 gene transcripts were expressed in all stages. Functional Gene Ontology (GO) analysis resulted in three main GO classes: biological process, cellular components, and molecular function; the detected sequences were longer than sequences in the reference genome. Stage-wise selected fragments per kilobase of transcript per million mapped reads (FPKM) values of the top 10 stage-specific and common mRNAs were used to construct expression profiles, and 20 mRNAs were validated through quantitative real-time PCR (qRT-PCR). Next, we used three target prediction programs (miRanda, RNAhybrid, and PITA) to obtain 2431 potential target miRNA genes in RKNs, which regulate 8331 mRNAs. The predicted potential targets of miRNA were generally involved in cellular and metabolic processes, binding of molecules in the cell, membranes, and organelles. Stage-wise miRNA target analysis revealed that the egg stage contains heat shock proteins, transcriptional factors, and DNA repair proteins, whereas J2 includes DNA replication, heat shock, and ubiquitin-conjugating pathway-related proteins; the J3 and J4 stages are represented by the major sperm protein domain and translation-related proteins, respectively. In the female stage, we found proteins related to the maintenance of molybdopterin-binding domain-containing proteins and ubiquitin-mediated protein degradation. In total, 29 highly expressed stage-specific mRNA-targeting miRNAs were analyzed using qRT-PCR to validate the sequence analysis data. Overall, our findings provide new insights into the molecular mechanisms occurring at various developmental stages of the RKN life cycle, thus aiding in the identification of potential control strategies.

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Identification of candidate genes and proteins in aging skeletal muscle (sarcopenia) using gene expression and structural analysis

PeerJ ◽

10.7717/peerj.5239 ◽

2018 ◽

Vol 6 ◽

pp. e5239 ◽

Cited By ~ 11

Author(s):

Gita Shafiee ◽

Yazdan Asgari ◽

Akbar Soltani ◽

Bagher Larijani ◽

Ramin Heshmat

Keyword(s):

Gene Expression ◽

Skeletal Muscle ◽

Ribosome Biogenesis ◽

Expression Profiles ◽

Enrichment Analysis ◽

Lipid Storage ◽

Integrated Analysis ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Men And Women

Sarcopenia is an age-related disease characterized by the loss of muscle mass and muscle function. A proper understanding of its pathogenesis and mechanisms may lead to new strategies for diagnosis and treatment of the disease. This study aims to discover the underlying genes, proteins, and pathways associated with sarcopenia in both genders. Integrated analysis of microarray datasets has been performed to identify differentially expressed genes (DEGs) between old and young skeletal muscles. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then performed to uncover the functions of the DEGs. Moreover, a protein–protein interaction (PPI) network was constructed based on the DEGs. We have identified 41,715 DEGs, including 19 downregulated and 41,696 upregulated ones, in men. Among women, 3,015 DEGs have been found, with 2,874 of them being upregulated and 141 downregulated genes. Among the top up-regulated and downregulated genes, the ribosome biogenesis genes and genes involved in lipid storage may be closely related to aging muscles in men and women respectively. Also, the DEGs were enriched in the pathways including those of ribosome and Peroxisome proliferator-activated receptor (PPAR) in men and women, respectively. In the PPI network, Neurotrophic Receptor Tyrosine Kinase 1 (NTRK1), Cullin 3 (CUL3) and P53 have been identified as significant hub proteins in both genders. Using the integrated analysis of multiple gene expression profiles, we propose that the ribosome biogenesis genes and those involved in lipid storage would be promising markers for sarcopenia in men and women, respectively. In the reconstructed PPI network, neurotrophic factors expressed in skeletal muscle are essential for motoneuron survival and muscle fiber innervation during development. Cullin E3 ubiquitin ligase (Cul3) is an important component of the ubiquitin–proteasome system—it regulates the proteolysis. P53 is recognized as a central regulator of the cell cycle and apoptosis. These proteins, which have been identified as the most significant hubs, may be involved in aging muscle and sarcopenia.

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Identification of Significant Genes And Pathways In ARDS Via Bioinformatical Analysis

10.21203/rs.3.rs-457902/v1 ◽

2021 ◽

Author(s):

Weina Lu ◽

Ran Ji

Keyword(s):

Cellular Response ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Receptor Interaction ◽

Integrated Analysis ◽

Pathway Enrichment Analysis ◽

Signal Pathways ◽

Ppi Network ◽

Hub Genes

Abstract Background and Aims: Acute respiratory distress syndrome (ARDS) is one of the most common acute thoracopathy with complicated pathogenesis in ICU. The study is to explore the differentially expressed genes (DEGs) in the lung tissue and underlying altering mechanisms in ARDS.Methods: Gene expression profiles of GSE2411 and GSE130936 were available from GEO database, both of them included in GPL 339. Then, an integrated analysis of these genes was performed, including gene ontology (GO) and KEGG pathway enrichment analysis, protein-protein interaction (PPI) network construction, Transcription Factors (TFs) forecasting, and their expression in varied organs.Results: A total of 39 differential expressed genes were screened from the datasets, including 39 up-regulated genes and 0 down-regulated genes. The up-regulated genes were mainly enriched in the biological process, such as immune system process, innate immune response, inflammatory response, cellular response to interferon-beta and also involved in some signal pathways, including cytokine-cytokine receptor interaction, salmonella infection, legionellosis, chemokine, and Toll-like receptor signal pathway. GBP2, IFIT2 and IFIT3 were identified as hub genes in the lung by PPI network analysis with MCODE plug-in, as well as GO and KEGG re-enrichment. All of the three hub genes were regulated by the predictive common TFs, including STAT1, E2F1, IRF1, IRF2, and IRF9. Conclusions: This study implied that hub gene GBP2, IFIT2 and IFIT3, which might be regulated by STAT1, E2F1, IRF1, IRF2, or IRF9, played significant roles in ARDS. They could be potential diagnostic or therapeutic targets for ARDS patients.

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Identification of significant alteration genes, pathways and TFs induced by LPS in ARDS via bioinformatical analysis

BMC Infectious Diseases ◽

10.1186/s12879-021-06578-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Weina Lu ◽

Ran Ji

Keyword(s):

Expression Profiles ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Receptor Interaction ◽

Integrated Analysis ◽

Pathway Enrichment Analysis ◽

Signal Pathways ◽

Ppi Network ◽

Hub Genes ◽

Protein Protein Interaction

Abstract Background and aims Acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) is one of the most common acute thoracopathy with complicated pathogenesis in ICU. The study is to explore the differentially expressed genes (DEGs) in the lung tissue and underlying altering mechanisms in ARDS. Methods Gene expression profiles of GSE2411 and GSE130936 were available from GEO database, both of them included in GPL339. Then, an integrated analysis of these genes was performed, including gene ontology (GO) and KEGG pathway enrichment analysis in DAVID database, protein–protein interaction (PPI) network construction evaluated by the online database STRING, Transcription Factors (TFs) forecasting based on the Cytoscape plugin iRegulon, and their expression in varied organs in The Human Protein Atlas. Results A total of 39 differential expressed genes were screened from the two datasets, including 39 up-regulated genes and 0 down-regulated genes. The up-regulated genes were mainly enriched in the biological process, such as immune system process, innate immune response, inflammatory response, and also involved in some signal pathways, including cytokine–cytokine receptor interaction, Salmonella infection, Legionellosis, Chemokine, and Toll-like receptor signal pathway with an integrated analysis. GBP2, IFIT2 and IFIT3 were identified as hub genes in the lung by PPI network analysis with MCODE plug-in, as well as GO and KEGG re-enrichment. All of the three hub genes were regulated by the predictive common TFs, including STAT1, E2F1, IRF1, IRF2, and IRF9. Conclusions This study implied that hub gene GBP2, IFIT2 and IFIT3, which might be regulated by STAT1, E2F1, IRF1, IRF2, or IRF9, played significant roles in ARDS. They could be potential diagnostic or therapeutic targets for ARDS patients.

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