scholarly journals Identification of the TF-miRNA-mRNA Co-regulatory Networks Involved in Sepsis

2021 ◽  
Author(s):  
Xiaoqian Luo ◽  
Weina Lu ◽  
Jianfeng Zhao ◽  
Jun Hu ◽  
Enjiang Chen ◽  
...  
Keyword(s):  
Expression Analysis ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Genes ◽  
Medical Condition ◽  
Differentially Expressed ◽  
Biological Targets ◽  
Differentially Expressed Mirnas

Abstract BackgroundSepsis is a life-threatening medical condition caused by a dysregulated host response to infection. Recent studies have found that the expression of miRNAs is associated with the pathogenesis of sepsis and septic shock. Our study aimed to reveal which miRNAs may be involved in the dysregulated immune response in sepsis and how these miRNAs interact with transcription factors (TFs) using a computational approach with in vitro validation studies. MethodsTo determine the network of TFs, miRNAs and target genes involved in sepsis, GEO datasets GSE94717 and GSE131761 were used to identify differentially expressed miRNAs and DEGs. TargetScan and miRWalk databases were used to predict biological targets that overlap with the identified DEGs of differentially expressed miRNAs. The TransmiR database was used to predict the differential miRNA TFs that overlap with the identified DEGs. The TF-miRNA-mRNA network was constructed and visualized. Finally, qRT-PCR was used to verify the expression of TFs and miRNA in HUVECs. ResultBetween the healthy and sepsis groups, there were 146 upregulated and 98 downregulated DEGs in the GSE131761 dataset, and there were 1 upregulated and 183 downregulated DEMs in the GSE94717 dataset. A regulatory network of the TF-miRNA-target genes was established. According to the experimental results, RUNX3 was found to be downregulated while MAPK14 was upregulated, which corroborates the result of the computational expression analysis. In a HUVECs model, miR-19b-1-5p and miR-5009-5p were found to be significantly downregulated. Other TFs and miRNAs did not correlate with our bioinformatics expression analysis. ConclusionWe constructed a TF-miRNA-target gene regulatory network and identified potential treatment targets RUNX3, MAPK14, miR-19b-1-5p and miR-5009-5p. This information provides an initial basis for understanding the complex sepsis regulatory mechanisms.

scholarly journals Identification of New miRNA-mRNA Networks in the Development of Non-syndromic Cleft Lip With or Without Cleft Palate

2021 ◽  
Vol 9 ◽  
Author(s):  
Chengyi Fu ◽  
Shu Lou ◽  
Guirong Zhu ◽  
Liwen Fan ◽  
Xin Yu ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Cleft Palate ◽  
Negative Correlation ◽  
Cell Apoptosis ◽  
Cleft Lip ◽  
Target Genes ◽  
Craniofacial Development ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Objective: To identify new microRNA (miRNA)-mRNA networks in non-syndromic cleft lip with or without cleft palate (NSCL/P).Materials and Methods: Overlapping differentially expressed miRNAs (DEMs) were selected from cleft palate patients (GSE47939) and murine embryonic orofacial tissues (GSE20880). Next, the target genes of DEMs were predicted by Targetscan, miRDB, and FUNRICH, and further filtered through differentially expressed genes (DEGs) from NSCL/P patients and controls (GSE42589), MGI, MalaCards, and DECIPHER databases. The results were then confirmed by in vitro experiments. NSCL/P lip tissues were obtained to explore the expression of miRNAs and their target genes.Results: Let-7c-5p and miR-193a-3p were identified as DEMs, and their overexpression inhibited cell proliferation and promoted cell apoptosis. PIGA and TGFB2 were confirmed as targets of let-7c-5p and miR-193a-3p, respectively, and were involved in craniofacial development in mice. Negative correlation between miRNA and mRNA expression was detected in the NSCL/P lip tissues. They were also associated with the occurrence of NSCL/P based on the MGI, MalaCards, and DECIPHER databases.Conclusions: Let-7c-5p-PIGA and miR-193a-3p-TGFB2 networks may be involved in the development of NSCL/P.

scholarly journals Genome-Wide microRNA Profiling Using Oligonucleotide Microarray Reveals Regulatory Networks of microRNAs in Nicotiana benthamiana During Beet Necrotic Yellow Vein Virus Infection

Viruses ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 310 ◽  
Author(s):  
Junying Liu ◽  
Huiyan Fan ◽  
Ying Wang ◽  
Chenggui Han ◽  
Xianbing Wang ◽  
...  
Keyword(s):  
Nicotiana Benthamiana ◽  
Regulatory Networks ◽  
Target Genes ◽  
Tobacco Rattle Virus ◽  
Yellow Vein ◽  
Differentially Expressed ◽  
Virus Induced Gene Silencing ◽  
Developmental Defects ◽  
Differentially Expressed Mirnas ◽  
Species Specific

Beet necrotic yellow vein virus (BNYVV) infections induce stunting and leaf curling, as well as root and floral developmental defects and leaf senescence in Nicotiana benthamiana. A microarray analysis with probes capable of detecting 1596 candidate microRNAs (miRNAs) was conducted to investigate differentially expressed miRNAs and their targets upon BNYVV infection of N. benthamiana plants. Eight species-specific miRNAs of N. benthamiana were identified. Comprehensive characterization of the N. benthamiana microRNA profile in response to the BNYVV infection revealed that 129 miRNAs were altered, including four species-specific miRNAs. The targets of the differentially expressed miRNAs were predicted accordingly. The expressions of miR164, 160, and 393 were up-regulated by BNYVV infection, and those of their target genes, NAC21/22, ARF17/18, and TIR, were down-regulated. GRF1, which is a target of miR396, was also down-regulated. Further genetic analysis of GRF1, by Tobacco rattle virus-induced gene silencing, assay confirmed the involvement of GRF1 in the symptom development during BNYVV infection. BNYVV infection also induced the up-regulation of miR168 and miR398. The miR398 was predicted to target umecyanin, and silencing of umecyanin could enhance plant resistance against viruses, suggesting the activation of primary defense response to BNYVV infection in N. benthamiana. These results provide a global profile of miRNA changes induced by BNYVV infection and enhance our understanding of the mechanisms underlying BNYVV pathogenesis.

scholarly journals Construction of miRNA-target networks using microRNA profiles of CVB3-infected HeLa cells

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hai Lan Yao ◽  
Mi Liu ◽  
Wen Jun Wang ◽  
Xin Ling Wang ◽  
Juan Song ◽  
...  
Keyword(s):  
Hela Cells ◽  
Regulatory Networks ◽  
Cellular Differentiation ◽  
High Throughput Sequencing ◽  
Target Genes ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Mirna Regulation ◽  
Cvb3 Infection ◽  
Differentially Expressed Mirnas

AbstractMicroRNAs (miRNAs) play an important role in regulating gene expression in multiple biological processes and diseases. Thus, to understand changes in miRNA during CVB3 infection, specific miRNA expression profiles were investigated at 3 h, 6 h, and 9 h postinfection in HeLa cells by small-RNA high-throughput sequencing. Biological implications of 68 differentially expressed miRNAs were analyzed through GO and KEGG pathways. Interaction networks between 34 known highly differentially expressed miRNAs and targets were constructed by mirDIP and Navigator. The predicted targets showed that FAM135A, IKZF2, PLAG1, ZNF148, PHC3, LCOR and DYRK1A, which are associated with cellular differentiation and transcriptional regulation, were recognized by 8 miRNAs or 9 miRNAs through interactional regulatory networks. Seven target genes were confirmed by RT-qPCR. The results showed that the expression of DYRK1A, FAM135A, PLAG1, ZNF148, and PHC3 were obviously inhibited at 3 h, 6 h, and 9 h postinfection. The expression of LCOR did not show a significant change, and the expression of IKZF2 increased gradually with prolonged infection time. Our findings improve the understanding of the pathogenic mechanism of CVB3 infection on cellular differentiation and development through miRNA regulation, which has implications for interventional approaches to CVB3-infection therapy. Our results also provide a new method for screening target genes of microRNA regulation in virus-infected cells.

Global Gene Expression Analysis Demonstrates that Transforming Growth Factor β1 (TGF-β1) Signals Exclusively through Receptor Complexes Involving TGF-β Receptor I and Identifies Numerous Targets of TGF-β Signaling.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2178-2178
Author(s):  
Goran Karlsson ◽  
Yingchun Liu ◽  
Marie-José Goumans ◽  
Jonas Larsson ◽  
Ju-Seog Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Target Genes ◽  
Global Gene Expression ◽  
Differentially Expressed ◽  
Global Gene Expression Analysis ◽  
Β Receptor ◽  
Tgf Β1

Abstract In the hematopoietic system, TGF-β1 is one of the most potent extrinsic regulators, affecting both early progenitors and committed cells. At the top of the hematopoietic hierarchy, TGF-β1 maintains hematopoietic stem cells (HSCs) in quiescence in vitro through transcriptional regulation of genes encoding proteins important in the cell cycle. We have shown that TGF-β receptor I (TβRI) −/− HSCs exhibit increased proliferative capacity in vitro and that TβRII−/− mice develop a multifocal autoimmune disease, mainly mediated by T-cells (Larsson et al, 2003, Levéen et al 2002). The mechanisms of TGF-β signaling in hematopoietic cells are poorly understood and many target genes of TGF-β signaling remain elusive. In this study we have used global gene expression analysis to investigate whether all TGF-β signaling is mediated by TβRI and II. Furthermore, we asked what target genes are affected upon TGF-β stimulation in normal and TGF-β signaling deficient murine embryonic fibroblasts (MEFs). MEFs were grown with and without TGF-β1 stimulation and proliferation, transcriptional responses and expression analysis were performed. We demonstrate through Western Blot analysis, luciferase reporter assays and cell expansion experiments how these cells lack functional TβRI. Additionally, transcriptional assays show that no other Smad activity is triggered by TGF-β1 stimulation. Furthermore, we demonstrate through quantitative RT-PCR that the inhibitor of differentiation family of genes, known targets of TGF-β signaling, are not affected by TGF-β1 in TβRI−/− MEFs, while wt cells downregulate these genes 4–8.5 fold in response to stimulation. In order to completely exclude alternative receptors outside the TGF-β superfamily and signaling pathways activated through TβRII alone, we performed global gene expression profiling on TGF-β1 stimulated TβRI−/− MEFs with unstimulated TβRI deficient cells as reference. Very few (0.05 %) of the more than 37,000 spots on the microarray had a >2 fold differential expression in the two experiments conducted. Similar experiments performed on wt cells resulted in differential expression of between 2.6–3.9 % of the genes printed. From this data we conclude that no signaling affecting gene expression occur in the absence of TβRI in these cells. Additionally we present transcriptional profiles of MEF cell lines that either are normal or are TβRI deficient. By means of cDNA microarray technology, we have identified genes that were differentially expressed when TβRI deficient fibroblasts were compared to wt cells stimulated with TGF-β1. Our results create a data base of 461 significantly differentially expressed (p<0.01) target genes of TGF-β signaling. These include genes potentially responsible for the growth arrest induced by TGF-β1, like Gadd45g, Gas5, Id1, Id2 and Id3. However, the most significantly enriched number of differentially expressed genes are involved in protein folding and chaperone activities (Hspa9a, Hsp105, Hspe1, Hsp60, Cct2, Cct3, Cct8, Tcp1 and Dnaja1. Studies to identify TGF-β signaling responsive genes in HSCs are in progress.

scholarly journals Identification and validation of key miRNAs and miRNA–mRNA regulatory network associated with uterine involution in postpartum Kazakh sheep

2021 ◽  
Vol 64 (1) ◽  
pp. 119-129
Author(s):  
Heng Yang ◽  
Lin Fu ◽  
Qifeng Luo ◽  
Licai Li ◽  
Fangling Zheng ◽  
...  
Keyword(s):  
Mirna Target ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Gene Prediction ◽  
Biological Effects ◽  
Differentially Expressed ◽  
Illumina Hiseq ◽  
Go Annotation ◽  
Uterine Involution ◽  
Differentially Expressed Mirnas

Abstract. MicroRNAs (miRNAs) are widely expressed in different mammalian tissues and exert their biological effects through corresponding target genes. miRNA target genes can be rapidly and efficiently identified and screened by combining bioinformatics prediction and experimental validation. To investigate the possible molecular regulatory mechanisms involving miRNAs during uterine involution in postpartum ewes, we used Illumina HiSeq sequencing technology to screen for the number and characteristics of miRNAs in faster uterine involution and normal uterine involution group. A total of 118 differentially expressed miRNAs, including 33 known miRNAs and 85 new miRNAs, were identified in the hypothalamic library, whereas 54 miRNAs, including 5 known miRNAs and 49 new miRNAs, were identified in the uterine library. Screening with four types of gene prediction software revealed 73 target genes associated with uterine involution, and subsequently, GO annotation and KEGG pathway analysis were performed. The results showed that, in the hypothalamic–uterine axis, uterine involution in postpartum ewes might primarily involve two miRNA-target gene pairs, namely, miRNA-200a–PTEN and miRNA-133–FGFR1, which can participate in GnRH signal transduction in the upstream hypothalamus and in the remodeling process at the downstream uterus, through the PI3K–AKT signaling pathway to influence the recovery of the morphology and functions of the uterus during the postpartum period in sheep. Therefore, identification of differentially expressed miRNAs in this study fills a gap in the research related to miRNAs in uterine involution in postpartum ewes and provides an important reference point for a comprehensive understanding of the molecular mechanisms underlying the regulation of postpartum uterine involution in female livestock.

Identification and Characterization of New Microrna Biomarkers and Target Genes in Drug-Insensitive CD34+ CML Stem/Progenitor Cells Using Global Comparative RNA-Seq Analyses

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1567-1567
Author(s):  
Hanyang Lin ◽  
Jonathan Zeng ◽  
Katharina Rothe ◽  
Jens Ruschmann ◽  
Oleh Petriv ◽  
...  
Keyword(s):  
Progenitor Cells ◽  
Mirna Target ◽  
Target Genes ◽  
Expression Profiles ◽  
Therapeutic Targets ◽  
Mapk Signaling ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Cd34 Cells ◽  
Differentially Expressed Mirnas

Abstract Therapeutic targeting of BCR-ABL with selective ABL tyrosine kinase inhibitors (TKIs) has led to a significant survival benefit for early phase CML. However, TKI monotherapies are rarely curative, with persistence of leukemic stem cells, emergence of resistance and relapses remaining as challenges. To identify differentially expressed and new miRNAs in CD34+ CML stem/progenitor cells that might serve as potential biomarkers and/or therapeutic targets, we have performed Illumina Deep Sequencing to obtain absolute miRNA expression profiles of highly purified CD34+ cells obtained at newly diagnosed stage from six CML patients. Three of the patients were classified retrospectively, after imatinib (IM) therapy, as IM-responders and three as IM-nonresponders. CD34+ cells isolated from five normal bone marrow (NBM) samples were similarly analyzed as controls. Bioconductor DESeq2 analysis revealed 63 differentially expressed miRNAs between CML and NBM samples (adjusted P<0.05). Most differentially expressed miRNAs identified were down-regulated in CML compared to NBM, while 17 were up-regulated. Interestingly, 12 miRNAs were found to be differentially expressed between the IM-responders and IM-nonresponders. In addition, 34 novel miRNAs were identified in the CD34+ CML stem/progenitor cells. We next validated the sequencing data in a larger cohort of samples. CD34+ cells from IM-responders (n=12), IM-nonresponders (n=10) and normal individuals (n=11) were analyzed using a high-throughput qPCR microfluidics device. These studies confirmed the differential expression in CD34+ CML cells of 32 of the 63 miRNAs (adjusted P<0.05), including an increased level of oncomirs miR-155 and miR-17-92, and a decreased level of tumor suppressors miR-145, miR-151, and miR-452. Importantly, significant changes in some of these miRNAs were detected in CD34+ cells from CML patients (n=60) after three months of nilotinib (NL) treatment compared to the same patient samples before the treatment: expression of 18 miRNAs were normalized after NL therapy, whereas 10 showed little change. To further identify potential miRNA target genes, RNA-seq analysis was performed on the same RNA samples to correlate miRNA profiles with corresponding mRNA expression changes. Bioconductor RmiR analysis was performed to match miRNA target genes whose expression was inversely correlated with the expression of deregulated miRNAs based on three of six prediction algorithms (mirBase, TargetScan, miRanda, tarBase, mirTarget2, and PicTar). We have identified 1,210 differentially expressed mRNAs that are predicted targets of the deregulated miRNAs in the comparison of CML and NBM data. Interestingly, only seven differentially expressed genes were predicted targets of the deregulated miRNAs identified in a comparison of IM-responders and IM-nonresponders. Most of the predicted target genes are involved in cell cycle regulation, MAPK signaling and TGF-beta signaling pathways according to DAVID Bioinformatics Resources analysis, which clusters predicted target genes to known KEGG pathways. To elucidate the biological significance of the differentially expressed miRNAs in TKI-insensitive CML stem/progenitor cells, a number of functional assays were performed. An initial screen of eight miRNAs, selected for their novelty and CML-related potential target genes, was performed by transiently transfecting CML cells with miRNA mimics or inhibitors, and chemically synthesized RNAs which mimic or inhibit mature endogenous miRNAs. Four of the eight miRNA mimics/inhibitors transfected cells displayed significant growth disadvantages and enhanced sensitivity to TKI treatments based on trypan-blue exclusion, thymidine incorporation, apoptosis, and colony-forming cell assays. Q-RT-PCR analysis further showed reduced expression of their predicted target genes in cells transfected with miRNA mimics. Taken together, we have identified aberrant, differentially expressed miRNAs and their target genes in TKI-insensitive CML stem/progenitor cells that may serve as useful biomarkers to predict clinical response of CML patients to TKI therapy and ultimately lead to identification of new therapeutic targets for improved treatment options in CML. Disclosures No relevant conflicts of interest to declare.

Integration of small RNAs, degradome, and transcriptome sequencing in Populus × euramericana “Neva” provides insights into the allelopathic interference of para-hydroxybenzoic acid

2020 ◽  
Vol 50 (4) ◽  
pp. 422-437 ◽  
Author(s):  
Guoting Liang ◽  
Jing Guo ◽  
Shuyong Zhang ◽  
Guangcan Zhang
Keyword(s):  
Small Rnas ◽  
Mirna Target ◽  
Target Genes ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Hydroxybenzoic Acid ◽  
Differentially Expressed Mirnas ◽  
Leaves And Roots

Allelopathy is a hot topic of research; however, little is known regarding microRNA (miRNA) expression profiles in plants in response to allelochemicals. In this study, we combined the analyses of the transcriptome, small RNAs (sRNAs), and the degradome to identify key regulatory miRNA-targeted circuits under para-hydroxybenzoic acid (pHBA) stress. A total of 739 and 673 miRNAs were identified in leaves and roots, respectively. Of those, 214 and 148 miRNAs were significantly differentially expressed and identified as pHBA-responsive miRNAs in leaves and roots, respectively. The target genes for the pHBA-responsive miRNAs are involved in signal transduction, response to stress, and secondary metabolite pathways. Furthermore, an integrated analysis of the miRNA–target expression profiles was used to screen the 60 differentially expressed target genes from the 46 differentially expressed miRNAs in the leaves and the 51 differentially expressed target genes from the 36 differentially expressed miRNAs in roots. This integrated analysis revealed 17 and 30 pairs of miRNA targets in the leaves and roots, respectively, which had negatively correlated expression profiles. According to a real-time quantitative polymerase chain reaction (PCR) analysis, 14 miRNA–target pairs also exhibited negative correlations. Moreover, four coexpression regulatory networks were constructed based on the profiles of the differentially expressed miRNA–target pairs. These results suggest that comprehensive analyses of transcriptomes, sRNAs, and the degradome provide a useful platform for investigating the molecular mechanism underlying the pHBA-induced stress response in plants.

The high expression of miR-564 in patients with systemic lupus erythematosus promotes differentiation and maturation of DC cells by negatively regulating TP53 expression in vitro

Lupus ◽  
2021 ◽  
pp. 096120332110203
Author(s):  
Ziyue Teng ◽  
Xiaoying Lin ◽  
Chunyan Luan ◽  
Yixuan Sun ◽  
Xiaolan Li
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Dendritic Cells ◽  
Lupus Erythematosus ◽  
Target Genes ◽  
Differentially Expressed ◽  
Systemic Lupus ◽  
Differentially Expressed Mirnas ◽  
And Migration ◽  
Si Rna

Background miRNA is involved in the occurrence and progression of systemic lupus erythematosus (SLE), but the regulatory effect of miRNA on dendritic cells in SLE patients is still unclear. Material and methods Bioinformatics methods were used to analyze the differentially expressed miRNA and its target genes in SLE patients. In vitro experiments were conducted to explore the effects and mechanisms of differentially expressed miRNAs in SLE patients on the differentiation and maturation of monocyte-derived dendritic cells. Results Bioinformatics analysis showed that miR-564 was up-regulated in SLE patients, and TP53 was the core target gene of miR-564. The expression level of miR-564 showed a rising trend during the differentiation and maturation of monocytes into Mo-DC cells. The differentiation, maturation and proliferation of Mo-DC cells were significantly inhibited by transfection with miR-564 antagomir. The expression of TP53 is negatively regulated by miR-564. In rescue experiments, the proliferation and migration of DC cells were significantly restored by co-transfection of miR-564 antagomir and TP53 si-RNA. Conclusion Highly expressed miR-564 promotes the maturation, proliferation of Mo-DC cells by negatively regulating the expression of TP53.

scholarly journals A combined microRNA and target protein-based panel for predicting the probability and severity of uraemic vascular calcification: a translational study

2020 ◽  
Author(s):  
Chia-Ter Chao ◽  
Hsiang-Yuan Yeh ◽  
You-Tien Tsai ◽  
Chih-Kang Chiang ◽  
Huei-Wen Chen
Keyword(s):  
Vascular Calcification ◽  
Target Genes ◽  
Ex Vivo ◽  
Target Protein ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Target Proteins ◽  
Differentially Expressed Mirnas

Abstract Aims  Vascular calcification (VC) increases the future risk of cardiovascular events in uraemic patients, but effective therapies are still unavailable. Accurate identification of those at risk of developing VC using pathogenesis-based biomarkers is of particular interest and may facilitate individualized risk stratification. We aimed to uncover microRNA (miRNA)-target protein-based biomarker panels for evaluating uraemic VC probability and severity. Methods and results  We created a three-tiered in vitro VC model and an in vivo uraemic rat model receiving high phosphate diet to mimic uraemic VC. RNAs from the three-tiered in vitro and in vivo uraemic VC models underwent miRNA and mRNA microarray, with results screened for differentially expressed miRNAs and their target genes as biomarkers. Findings were validated in original models and additionally in an ex vivo VC model and human cells, followed by functional assays of identified miRNAs and target proteins, and tests of sera from end-stage renal disease (ESRD) and non-dialysis-dependent chronic kidney disease (CKD) patients without and with VC. Totally 122 down-regulated and 119 up-regulated miRNAs during calcification progression were identified initially; further list narrowing based on miRNA–mRNA pairing, anti-correlation, and functional enrichment left 16 and 14 differentially expressed miRNAs and mRNAs. Levels of four miRNAs (miR-10b-5p, miR-195, miR-125b-2-3p, and miR-378a-3p) were shown to decrease throughout all models tested, while one mRNA (SULF1, a potential target of miR-378a-3p) exhibited the opposite trend concurrently. Among 96 ESRD (70.8% with VC) and 59 CKD patients (61% with VC), serum miR-125b2-3p and miR-378a-3p decreased with greater VC severity, while serum SULF1 levels increased. Adding serum miR-125b-2-3p, miR-378a-3p, and SULF1 into regression models for VC substantially improved performance compared to using clinical variables alone. Conclusion  Using a translational approach, we discovered a novel panel of biomarkers for gauging the probability/severity of uraemic VC based on miRNAs/target proteins, which improved the diagnostic accuracy.

scholarly journals miRDRN—miRNA disease regulatory network: a tool for exploring disease and tissue-specific microRNA regulatory networks

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7309
Author(s):  
Hsueh-Chuan Liu ◽  
Yi-Shian Peng ◽  
Hoong-Chien Lee
Keyword(s):  
Web Service ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Genes ◽  
Gene Annotation ◽  
Biological Pathways ◽  
Tissue Specific ◽  
Cellular Processes ◽  
Disease Pair

Background MicroRNA (miRNA) regulates cellular processes by acting on specific target genes, and cellular processes proceed through multiple interactions often organized into pathways among genes and gene products. Hundreds of miRNAs and their target genes have been identified, as are many miRNA-disease associations. These, together with huge amounts of data on gene annotation, biological pathways, and protein–protein interactions are available in public databases. Here, using such data we built a database and web service platform, miRNA disease regulatory network (miRDRN), for users to construct disease and tissue-specific miRNA-protein regulatory networks, with which they may explore disease related molecular and pathway associations, or find new ones, and possibly discover new modes of drug action. Methods Data on disease-miRNA association, miRNA-target association and validation, gene-tissue association, gene-tumor association, biological pathways, human protein interaction, gene ID, gene ontology, gene annotation, and product were collected from publicly available databases and integrated. A large set of miRNA target-specific regulatory sub-pathways (RSPs) having the form (T, G1, G2) was built from the integrated data and stored, where T is a miRNA-associated target gene, G1 (G2) is a gene/protein interacting with T (G1). Each sequence (T, G1, G2) was assigned a p-value weighted by the participation of the three genes in molecular interactions and reaction pathways. Results A web service platform, miRDRN (http://mirdrn.ncu.edu.tw/mirdrn/), was built. The database part of miRDRN currently stores 6,973,875 p-valued RSPs associated with 116 diseases in 78 tissue types built from 207 diseases-associated miRNA regulating 389 genes. miRDRN also provides facilities for the user to construct disease and tissue-specific miRNA regulatory networks from RSPs it stores, and to download and/or visualize parts or all of the product. User may use miRDRN to explore a single disease, or a disease-pair to gain insights on comorbidity. As demonstrations, miRDRN was applied: to explore the single disease colorectal cancer (CRC), in which 26 novel potential CRC target genes were identified; to study the comorbidity of the disease-pair Alzheimer’s disease-Type 2 diabetes, in which 18 novel potential comorbid genes were identified; and, to explore possible causes that may shed light on recent failures of late-phase trials of anti-AD, BACE1 inhibitor drugs, in which genes downstream to BACE1 whose suppression may affect signal transduction were identified.

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