miRNA Regulatory Network Research Articles

Integrated Analysis of miRNA and mRNA Regulation Network in Hypertension.

Hypertension is the most common chronic disease. Early diagnosis is helpful for early medical intervention. The miRNAs and the messenger RNAs (mRNAs) network may be valuable disease diagnosis markers. We aimed to explore the diagnostic value of the miRNA-mRNA network for hypertension patients. Data of miRNAs and mRNAs expression were obtained from the Gene Expression Omnibus database. The weighted gene co-expression network analysis was performed to screen hypertension-related gene modules, and these genes undergone functional enrichment analysis using "clusterProfiler" package. Differential expression analysis was applied on miRNAs expression profiles using "limma" package. TargetScanHuman and miRDB databases were used to select target mRNAs. Cytoscape software was used to visualize the miRNA-mRNA regulation network. P value < 0.05 was considered statistically significant after t test. There were 123 screened mRNAs which were enriched in 161 Gene ontology (GO) terms and 14 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Thirty-five differentially expressed miRNAs (DEMs) are found in the GSE75670. Totally 36 miRNA-mRNA pairs were obtained after the integrated analysis, and three mRNAs and the hsa-miRNA-5589-5p were identified as key joints. Hub genes, KIAA0513, ARID3A and LRPAP1, and key hsa-miRNA-5589-5p are potential diagnostic biomarkers for hypertension. Our findings are promising in the clinical application, conducive to early detection and prompt intervention of hypertension.

Identification of the potential ferroptosis key genes in lung cancer with bone metastasis.

To identify the potential key genes of ferroptosis in the pathogenesis of lung cancer with bone metastasis (LCBM) by bioinformatics analysis to provide new targets for treating LCBM and an indicator for early monitoring. We first obtained differentially expressed genes (DEGs) associated with ferroptosis from the Gene Expression Omnibus (GEO) database. MiRWalk 2.0 was used to predict the key microRNAs (miRNAs) and construct related gene-miRNA interaction networks. The functional enrichment analysis of key miRNAs was performed using the miEAA database. Finally, the clinical data of 105 lung cancer patients were retrospectively analyzed, and logistic regression analysis was conducted to assess the relationship between serum alkaline phosphatase (ALP), neuron-specific enolase (NSE), and bone metastasis in lung cancer patients, and a receiver operating characteristic (ROC) curve was drawn. We identified 15 ferroptosis-related genes that were differentially expressed in lung cancer bone metastasis. GO and KEGG enrichment analyses suggested that these genes may affect the oxidative stress response, hypoxia response, rough endoplasmic reticulum, mitochondrial outer membrane, iron-sulfur cluster binding, virus receptor activity, central carbon metabolism in cancer, the interleukin-17 (IL-17) signaling pathway, and other aspects to participate in the occurrence and development of lung cancer bone metastasis. Among the 105 lung cancer patients included in the study, 39 cases had bone metastasis, and the incidence rate was 37.14%. A high Eastern Cooperative Oncology Group (ECOG) score and serum ALP and NSE overexpression were associated with bone metastasis in patients with lung cancer. By assessing the risk of bone metastasis in patients with lung cancer, we found that the Area Under Curves (AUCs) of serum ALP and NSE alone and combined were >0.70. The differentially expressed ferroptosis-related genes and predicted miRNA regulatory network in lung cancer bone metastasis and the related functional enrichment analysis provide new targets for the treatment of lung cancer bone metastasis. At the same time, from a serological perspective, it was found that early monitoring of serum ALP and NSE expression in patients with lung cancer could be considered to assess the risk of bone metastasis in the future.

A Potential Immune-Related miRNAs Regulatory Network and Corresponding Diagnostic Efficacy in Schizophrenia.

Immune-related pathways actively participate in the progression of schizophrenia (SCZ), however, roles of immune-related miRNAs in SCZ are still unclear. A microarray expression study was conducted to explored roles of immune-related genes in SCZ. Functional enrichment analysis by using "clusterProfiler" was used to identify molecular alterations of SCZ. Protein-protein interaction (PPI) network was constructed and helped core molecular factors identification. Based on The Cancer Genome Atlas (TCGA) database, clinical significances of hub immune-related genes in cancers were also been explored. Then, correlation analyses were used to determine immune-related miRNAs. We further validated that hsa-miR-1299 could be an effective diagnostic biomarker for SCZ via analyzing multi-cohorts' data and quantitative real-time PCR (qRT-PCR). A total of 455 mRNAs and 70 miRNAs that were differentially expressed between SCZ and control samples. Functional enrichment analysis based on differentially expressed genes (DEGs) hinted that immune-related pathways were significantly correlated with SCZ. Furthermore, a total of 35 immune-related genes that involved in disease onset and showed significant co-expressed relationships. Hub immune-related gene CCL4 and CCL22 are valuable in tumor diagnosis and survival prediction. Furthermore, we also identified 22 immune-related miRNAs that play important roles in this disease. An immune-related miRNAs-mRNAs regulatory network was constructed to provide miRNAs regulatory roles in SCZ. Core miRNAs expression status of hsa-miR-1299 were also validated in another cohort, which suggested its diagnostic performance for SCZ. Our study reports the downregulation of some miRNAs in the process of SCZ are important. Shared genomics characteristics between SCZ and cancers also provide novel insights for cancers. A significant alteration of hsa-miR-1299 expression is effective as biomarker for the diagnosis of SCZ, suggesting that this miRNA could be a specific biomarker.

Whole transcriptome analysis of trifoliate orange (Poncirus trifoliata (L.) Raf.) under osmotic stress

Trifoliate orange (Poncirus trifoliata (L.) Raf.) is a conventional citrus rootstock, and its resistance to abiotic stress is critical to citriculture. By using high-throughput RNA sequencing, this study unfolded the whole transcriptome expression profile of trifoliate orange seedlings under osmotic stress (-1.56 MPa) mediated by polyethylene glycol. Based on the morphologic observation and physiological measurements, the seedlings were subjected to remarkable water deficit under 1.5, 6 and 24 h of osmotic stress (OS1.5, OS6 and OS24) but recovered after 4 h of re-watering (RE4). Totally, 9756/11,791, 327/435, 69/95 and 181/102 differentially expressed (DE) protein-coding mRNAs, long non-coding (lnc)RNA, circular (circ)RNA and micro (mi)RNA were identified in leaf/root at 0 h of osmotic stress (OS0), OS1.5, OS6 and OS24 and RE4. With over representation analysis for the DEmRNAs of OS1.5/OS0, OS6/OS0, OS24/OS0 and RE4/OS24, there were 70/95 enriched Gene Ontology terms and 16/28 Kyoto Encyclopedia of Genes and Genomes pathways in leaf/root, thereby displaying diverse biological processes, molecular functions and pathways. With k-means cluster analysis, eight DEmRNA clusters with different expression patterns were classified. In addition, some important molecular players in abscisic acid signaling, mitogen-activated protein kinase cascade, proline biosynthesis and polyamine synthesis were revealed and discussed. Ptrif.0009s2070 was identified as the ortholog of RD29B in trifoliate orange, which is the landmark gene under water deficit and ABA treatment. The targets of DElncRNAs and miRNA and the source genes of DEcircRNAs were identified through bioinformatics approaches. Last, competing endogenous RNA (lncRNA/circRNA/mRNA)-miRNA regulatory network with 503/138 nodes including 30/4 hub miRNAs and 497/108 connections and were constructed in leaf/root. Our results benefit the understanding in osmotic stress response and abiotic stress-resistance gene mining in trifoliate orange.

Poplar coma morphogenesis and miRNA regulatory networks by combining ovary tissue sectioning and deep sequencing

Poplar coma, commonly referred to as "seed hairs", is a tuft of trichomes attached to the seed coat that helps seed dispersal. However, they can also trigger health impacts for humans, including sneezing, shortness of breath, and skin irritation. Despite efforts to study the regulatory mechanism of herbaceous trichome formation, poplar coma remains poorly understood. In this study, we showed that the epidermal cells of the funiculus and placenta are the origin of poplar coma based on observations of paraffin sections. Small RNA (sRNA) and degradome libraries were also constructed at three stages of poplar coma development, including initiation and elongation stages. Based on 7,904 miRNA-target pairs identified by small RNA and degradome sequencing, we constructed a miRNA-transcript factor and a stage-specific miRNA regulatory network. By combining paraffin section observation and deep sequencing, our research will provide greater insight into the molecular mechanisms of poplar coma development.

Well-Aligned Track-Accelerated Tripedal DNA Walker for Photoelectrochemical Recognition of Dual-miRNAs Based on Molecular Logic Gates.

Post-transcriptional regulators, microRNAs (miRNAs), are involved in the occurrence and progression of various diseases. However, due to the complexity of disease-related miRNA regulatory networks, the typing and identification of miRNAs have remained challenging. Herein, a linear ladder-like DNA nanoarchitecture (LDN) was constructed to promote the movement efficiency of the tripedal DNA walker (T-walker), which was combined with the DNA-based logic gates and the PTCDA@PDA/CdS/WO3 photoelectrode to develop a novel biosensor for the detection of dual-miRNAs. Two miRNAs, miR-122 and miR-21, were used as targets to operate the logic module, while its output, trigger strands (TSs), initiated a catalytic hairpin assembly (CHA) reaction to form a T-walker. By using LDN as the track, the T-walker efficiently unfolded hairpin 4, which further hybridized with the alkaline phosphatase-modified hairpin 5 (AP-H5). The remaining AP can catalyze the ascorbic acid 2-phosphate (AAP) into ascorbic acid (AA), an ideal electron donor, thus resulting in a photocurrent change. The photocurrent signals of both AND and OR gates displayed a linear relationship with the logarithm of dual-miRNA concentrations with detection limits of 10.1 and 13.6 fM, respectively. Moreover, the intelligent and rational design of DNA tracks gives impetus to create a well-organized sensing interface with wide application in clinical diagnosis and cancer monitoring.

Analysis of common genetic variation across targets of microRNAs dysregulated both in ASD and epilepsy reveals negative correlation.

Genetic overlap involving rare disrupting mutations may contribute to high comorbidity rates between autism spectrum disorders and epilepsy. Despite their polygenic nature, genome-wide association studies have not reported a significant contribution of common genetic variation to comorbidity between both conditions. Analysis of common genetic variation affecting specific shared pathways such as miRNA dysregulation could help to elucidate the polygenic mechanisms underlying comorbidity between autism spectrum disorders and epilepsy. We evaluated here the role of common predisposing variation to autism spectrum disorders and epilepsy across target genes of 14 miRNAs selected through bibliographic research as being dysregulated in both disorders. We considered 4,581 target genes from various in silico sources. We described negative genetic correlation between autism spectrum disorders and epilepsy across variants located within target genes of the 14 miRNAs selected (p = 0.0228). Moreover, polygenic transmission disequilibrium test on an independent cohort of autism spectrum disorders trios (N = 233) revealed an under-transmission of autism spectrum disorders predisposing alleles within miRNAs' target genes across autism spectrum disorders trios without comorbid epilepsy, thus reinforcing the negative relationship at the common genetic variation between both traits. Our study provides evidence of a negative relationship between autism spectrum disorders and epilepsy at the common genetic variation level that becomes more evident when focusing on the miRNA regulatory networks, which contrasts with observed clinical comorbidity and results from rare variation studies. Our findings may help to conceptualize the genetic heterogeneity and the comorbidity with epilepsy in autism spectrum disorders.

Identification of hub genes and potential molecular mechanisms related to radiotherapy sensitivity in rectal cancer based on multiple datasets

BackgroundRadiotherapy resistance is the main cause of low tumor regression for locally advanced rectum adenocarcinoma (READ). The biomarkers correlated to radiotherapy sensitivity and potential molecular mechanisms have not been completely elucidated.MethodsA mRNA expression profile and a gene expression dataset of READ (GSE35452) were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) between radiotherapy responder and non-responder of READ were screened out. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for DEGs were performed. Random survival forest analysis was used to identified hub genes by randomForestSRC package. Based on CIBERSORT algorithm, Genomics of Drug Sensitivity in Cancer (GDSC) database, Gene set variation analysis (GSVA), enrichment analysis (GSEA), nomogram, motif enrichment and non-coding RNA network analyses, the associations between hub genes and immune cell infiltration, drug sensitivity, specific signaling pathways, prognosis prediction and TF – miRNA regulatory and ceRNA network were investigated. The expressions of hub genes in clinical samples were displayed with the online Human Protein Atlas (HPA).ResultsIn total, 544 up-regulated and 575 down-regulated DEGs in READ were enrolled. Among that, three hubs including PLAGL2, ZNF337 and ALG10 were identified. These three hub genes were significantly associated with tumor immune infiltration, different immune-related genes and sensitivity of chemotherapeutic drugs. Also, they were correlated with the expression of various disease-related genes. In addition, GSVA and GSEA analysis revealed that different expression levels of PLAGL2, ZNF337 and ALG10 affected various signaling pathways related to disease progression. A nomogram and calibration curves based on three hub genes showed excellent prognosis predictive performance. And then, a regulatory network of transcription factor (ZBTB6) - mRNA (PLAGL2) and a ceRNA network of miRNA (has-miR-133b) - lncRNA were established. Finally, the results from HPA online database demonstrated the protein expression levels of PLAGL2, ZNF337 and ALG10 varied widely in READ patients.ConclusionThese findings indicated that up-regulation of PLAGL2, ZNF337 and ALG10 in READ associated with radiotherapy response and involved in multiple process of cellular biology in tumor. They might be potential predictive biomarkers for radiotherapy sensitivity and prognosis for READ.

Aberrant Methylation of the Imprinted C19MC and MIR371-3 Clusters in Patients with Non-Small Cell Lung Cancer

Epigenetic mechanisms have emerged as an important contributor to tumor development through the modulation of gene expression. Our objective was to identify the methylation profile of the imprinted C19MC and MIR371-3 clusters in patients with non-small cell lung cancer (NSCLC) and to find their potential target genes, as well as to study their prognostic role. DNA methylation status was analyzed in a NSCLC patient cohort (n = 47) and compared with a control cohort including COPD patients and non-COPD subjects (n = 23) using the Illumina Infinium Human Methylation 450 BeadChip. Hypomethylation of miRNAs located on chromosome 19q13.42 was found to be specific for tumor tissue. We then identified the target mRNA-miRNA regulatory network for the components of the C19MC and MIR371-3 clusters using the miRTargetLink 2.0 Human tool. The correlations of miRNA-target mRNA expression from primary lung tumors were analyzed using the CancerMIRNome tool. From those negative correlations identified, we found that a lower expression of 5 of the target genes (FOXF2, KLF13, MICA, TCEAL1 and TGFBR2) was significantly associated with poor overall survival. Taken together, this study demonstrates that the imprinted C19MC and MIR371-3 miRNA clusters undergo polycistronic epigenetic regulation leading to deregulation of important and common target genes with potential prognostic value in lung cancer.

Expression Profile of Selected Genes Involved in Na+ Homeostasis and In Silico miRNA Identification in Medicago sativa and Medicago arborea under Salinity Stress

The accumulation of ions due to increased salinity in the soil is one of the major abiotic stressors of cultivated plants that negatively affect their productivity. The model plant, Medicago truncatula, is the only Medicago species that has been extensively studied, whereas research into increased salinity adaptation of two important forage legumes, M. sativa and M. arborea, has been limited. In the present study, the expression of six genes, namely SOS1, SOS3, NHX2, AKT, AVP and HKT1 was monitored to investigate the manner in which sodium ions are blocked and transferred to the various plant parts. In addition, in silico miRNA analysis was performed to identify miRNAs that possibly control the expression of the genes studied. The following treatments were applied: (1) salt stress, with initial treatment of 50 mM NaCl and gradual acclimatization every 10 days, (2) salt shock, with continuous application of 100 mM NaCl concentration and (3) no application of NaCl. Results showed that M. arborea appeared to overexpress and activate all available mechanisms of resistance in conditions of increased salinity, while M. sativa acted in a more targeted way, overexpressing the HKT1 and AKT genes that contribute to the accumulation of sodium ions, particularly in the root. Regarding miRNA in silico analysis, five miRNAs with significant complementarity to putative target genes, AKT1, AVP and SOS3 were identified and served as a first step in investigating miRNA regulatory networks. Further miRNA expression studies will validate these results. Our findings contribute to the understanding of the molecular mechanisms underlying salt-responsiveness in Medicago and could be used in the future for generating salt-tolerant genotypes in crop improvement programs.

Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity

Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein-protein interactions network, module analysis, target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.

Identification of Key Diagnostic Markers and Immune Infiltration in Osteoarthritis.

Osteoarthritis (OA) is a worldwide chronic disease of the articulating joints. An increasing body of data demonstrates the immune system's involvement in osteoarthritis. The molecular mechanisms of OA are still unclear. This study aimed to search for OA immunerelated hub genes and determine appropriate diagnostic markers to help the detection and treatment of the disease. Gene expression data were downloaded from the GEO database. Firstly, we analyzed and identified the differentially expressed genes (DEGs) using R packages. Meanwhile, ssGSEA was used to determine the activation degree of immune-related genes (IRGs), and WGCNA analysis was applied to search for co-expressed gene modules associated with immune cells. Then, critical networks and hub genes were found in the PPI network. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analyzed the biological functions of genes. The ability of the hub genes to differentiate OA from controls was assessed by the area under the ROC curve. A miRNA and transcription factor (TF) regulatory network was constructed according to their relationship with hub genes. Finally, the validation of hub genes was carried out by qPCR. In total, 353 DEGs were identified in OA patients compared with controls, including 222 upregulated and 131 downregulated genes. WGCNA successfully identified 34 main functional modules involved in the pathogenesis of OA. The most crucial functional module involved in OA included 89 genes. 19 immune-related genes were obtained by overlapping DEGs with the darkgrey module. The String database was constructed using the protein-protein interaction (PPI) network of 19 target genes, and 7 hub genes were identified by MCODE. ROC curve showed that 7 hub genes were potential biomarkers of OA. The expression levels of hub genes were validated by qPCR, and the results were consistent with those from bioinformatic analyses. Immune-related hub genes, including TYROBP, ITGAM, ITGB2, C1QC, MARCO, C1QB, and TLR8, may play critical roles in OA development. ITGAM had the highest correction on immune cells.

Potential upstream lncRNA-miRNA-mRNA regulatory network of the ferroptosis-related gene SLC7A11 in renal cell carcinoma.

SLC7A11 is a key regulator of ferroptosis, which mediates cysteine uptake for glutathione biosynthesis and maintains redox homeostasis. Emerging evidence has shown that SLC7A11 is upregulated in many human tumors. Nevertheless, the prognosis and posttranslational regulatory mechanism of SLC7A11 in renal cell carcinoma (RCC) remains obscure. The Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), and The Cancer Genome Atlas (TCGA) databases were used to analyze the difference in SLC7A11 expression between malignant and normal tissues. Furthermore, the GEPIA, the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN), and starBase databases were used to conduct the survival analyses. For correlation analysis, the UALCAN and starBase databases were employed. The Tumor Immune Estimation Resource (TIMER) database was used to approximate the abundance of immune infiltration. We confirmed that SLC7A11 was upregulated in most human cancers, including 3 types of RCC. SLC7A11 overexpression was linked to poor prognosis of individuals with kidney renal clear cell carcinoma (KIRC), kidney chromophobe cell carcinoma (KICH), and kidney renal papillary cell carcinoma (KIRP). SLC7A11 expression was also linked to immune cell infiltration levels. After performing a comprehensive analysis of the regulatory mechanisms of SLC7A11 expression, the results depicted a potential noncoding (ncRNA)-messenger RNA (mRNA) axis, incorporating SNHG6-miR-26a-5p-SLC7A11 networks in KICH, CASC19/CYTOR/LINC00997-miR-27b-3pSLC7A11 networks in KIRC, and CASC19/CYTOR/PVT1-miR27b-3p-SLC7A11 networks in KIRP as partially responsible for the functions of SLC7A11 in RCC. SLC7A11 expression was positively linked to infiltrated immune cells and their matching marker sets in 3 types of RCC, including CD8+ and myeloid dendritic cells. Our research elucidated the crucial functions and the upstream long noncoding RNA (lncRNA)-microRNA (miRNA) regulatory network of SLC7A11 in RCC. Importantly, SLC7A11 can be used as a potential prognostic biomarker for 3 types of RCC and to determine the infiltration of immune cells in malignant tissues.

Recent allopolyploidy alters Spartina microRNA expression in response to xenobiotic-induced stress.

Environmental contamination by xenobiotics represents a major threat for natural ecosystems and public health. In response, xenobiotic detoxification is a fundamental trait of organisms for developmental plasticity and stress tolerance, but the underlying molecular mechanisms remain poorly understood in plants. To decipher this process, we explored the consequences of allopolyploidy on xenobiotic tolerance in the genus Spartina Schreb. Specifically, we focused on microRNAs (miRNAs) owing to their central function in the regulation of gene expression patterns, including responses to stress. Small RNA-Seq was conducted on the parents S. alterniflora and S. maritima, their F1 hybrid S. x townsendii and the allopolyploid S. anglica under phenanthrene-induced stress (phe), a model Polycyclic Aromatic Hydrocarbon (PAH) compound. Differentially expressed miRNAs in response to phe were specifically identified within species. In complement, the respective impacts of hybridization and genome doubling were detected, through changes in miRNA expression patterns between S. x townsendii, S. anglica and the parents. The results support the impact of allopolyploidy in miRNA-guided regulation of plant response to phe. In total, we identified 17 phe-responsive miRNAs in Spartina among up-regulated MIR156 and down-regulated MIR159. We also describe novel phe-responsive miRNAs as putative Spartina-specific gene expression regulators in response to stress. Functional validation using Arabidopsis (L.) Heynh. T-DNA lines inserted in homologous MIR genes was performed, and the divergence of phe-responsive miRNA regulatory networks between Arabidopsis and Spartina was discussed.

A Complex Heterogeneous Network Model of Disease Regulated by Noncoding RNAs: A Case Study of Unstable Angina Pectoris.

MicroRNAs (miRNAs) are important types of noncoding RNAs, and there is a lack of holistic and systematic understanding of the functions they play in disease. We proposed a research strategy, including two parts network analysis and network modelling, to analyze, model, and predict the regulatory network of miRNAs from a network perspective, using unstable angina pectoris as an example. In the network analysis section, we proposed the WGCNA & SimCluster method using both correlation and similarity to find hub miRNAs, and validation on two datasets showed better results than the methods using correlation or similarity alone. In the network modelling section, we used six knowledge graph or graph neural network models for link prediction of three types of edges and multilabel classification of two types of nodes. Comparative experiments showed that the RotatE model was a good model for link prediction, while the RGCN model was the best model for multilabel classification. Potential target genes were predicted for hub miRNAs and validation of hub miRNA-target gene interactions, target genes as biomarkers and target gene functions were performed using a three-step validation approach. In conclusion, our study provides a new strategy to analyze and model miRNA regulatory networks.

Computational Biology and Machine Learning Approaches Identify Rubber Tree (Hevea brasiliensis Muell. Arg.) Genome Encoded MicroRNAs Targeting Rubber Tree Virus 1

Tapping panel dryness (TPD), a complex physiological syndrome associated with the rubber tree (Hevea brasiliensis Muell. Arg.), causes cessation of latex drainage upon tapping and thus threatens rubber production. Rubber tree virus 1 (RTV1) is a novel positive-sense single-stranded RNA virus from the Betaflexiviridae (genus Capillovirus), which has been established to cause TPD. MicroRNAs (miRNAs) play an important role in the interplay between viruses and host cells. In this study, we identified the rubber tree genome-encoded miRNAs and their therapeutic targets against RTV1. We applied computational algorithms to predict target binding sites of rubber tree miRNAs potentially targeting RTV1 RNA genome. Mature rubber-tree miRNAs are retrieved from the miRBase database and are used for hybridization of the RTV1 genome. A total of eleven common rubber-tree miRNAs were identified based on consensus genomic positions. The consensus of four algorithms predicted the hybridization sites of the hbr-miR396a and hbr-miR398 at common genomic loci (6676 and 1840), respectively. A miRNA-regulatory network of rubber tree was constructed with the RTV1— ORFs using Circos, is illustrated to analyze therapeutic targets. Overall, this study provides the first computational evidence of the reliable miRNA–mRNA interaction between specific rubber tree miRNAs and RTV1 genomic RNA transcript. Therefore, the predicted data offer valuable evidence for the development of RTV1-resistant rubber tree in the future. Our work suggests that similar computational host miRNA prediction strategies are warranted for identification of the miRNA targets in the other viral genomes.

Development of dynamical network biomarkers for regulation in Epstein-Barr virus positive peripheral T cell lymphoma unspecified type.

Background: This study was performed to identify key regulatory network biomarkers including transcription factors (TFs), miRNAs and lncRNAs that may affect the oncogenesis of EBV positive PTCL-U. Methods: GSE34143 dataset was downloaded and analyzed to identify differentially expressed genes (DEGs) between EBV positive PTCL-U and normal samples. Gene ontology and pathway enrichment analyses were performed to illustrate the potential function of the DEGs. Then, key regulators including TFs, miRNAs and lncRNAs involved in EBV positive PTCL-U were identified by constructing TF-mRNA, lncRNA-miRNA-mRNA, and EBV encoded miRNA-mRNA regulatory networks. Results: A total of 96 DEGs were identified between EBV positive PTCL-U and normal tissues, which were related to immune responses, B cell receptor signaling pathway, chemokine activity. Pathway analysis indicated that the DEGs were mainly enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. Based on the TF network, hub TFs were identified regulate the target DEGs. Afterwards, a ceRNA network was constructed, in which miR-181(a/b/c/d) and lncRNA LINC01744 were found. According to the EBV-related miRNA regulatory network, CXCL10 and CXCL11 were found to be regulated by EBV-miR-BART1-3p and EBV-miR-BHRF1-3, respectively. By integrating the three networks, some key regulators were found and may serve as potential network biomarkers in the regulation of EBV positive PTCL-U. Conclusion: The network-based approach of the present study identified potential biomarkers including transcription factors, miRNAs, lncRNAs and EBV-related miRNAs involved in EBV positive PTCL-U, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of EBV positive PTCL-U.

Construction of a novel miRNA regulatory network and identification of target genes in gestational diabetes mellitus by integrated analysis.

Backgrounds: Given the roles of microRNA (miRNA) in human diseases and the high incidence of gestational diabetes mellitus (GDM), the aim of the study was to examine miRNA signatures and crucial pathways, as well as possible biomarkers for GDM diagnosis. Methods: We conducted a two-stage study to explore functional miRNA and those target genes. Twelve participants (6 GDM and 6 non-GDM) were first enrolled and performed RNA sequencing analysis. The overlapped candidate genes were further screened in combination with differentially expressed genes (DEGs) of GEO datasets (GSE87295, GSE49524 and GSE19649) and potential target genes of DEMs. Candidate genes, critical pathways, small molecular compounds and regulatory networks were identified using bioinformatic analysis. The potential candidate genes were then investigated using the GEO dataset (GSE103552) of 19 participants in the validation stage (11 GDM and 8 non-GDM women). Results: Briefly, blood samples were sequenced interrogating 50 miRNAs, including 20 upregulated and 30 downregulated differentially expressed microRNAs(DEMs) in our internal screening dataset. After screening GEO databases, 123 upregulated and 70 downregulated genes were overlapped through DEGs of GEO datasets and miRNA-target genes. MiR-29b-1-5p-TGFB2, miR-142-3p-TGFB2, miR-9-5p-FBN2, miR-212-5p-FBN2, miR-542-3p-FBN1, miR-9-5p-FBN1, miR-508-3p-FBN1, miR-493-5p-THBS1, miR-29b-3p-COL4A1, miR-432-5p-COL5A2, miR-9-5p-TGFBI, miR-486-3p-SLC7A5 and miR-6515-5p-SLC1A5 were revealed as thirteen possible regulating pathways by integrative analysis. Conclusion: Overall, thirteen candidate miRNA-target gene regulatory pathways representing potentially novel biomarkers of GDM diseases were revealed. Ten chemicals were identified as putative therapeutic agents for GDM. This study examined a series of DEGs that are associated with epigenetic alternations of miRNA through an integrated approach and gained insight into biological pathways in GDM. Precise diagnosis and therapeutic targets of GDM would be further explored through putative genes in the future.

Systems biology approach reveals a common molecular basis for COVID-19 and non-alcoholic fatty liver disease (NAFLD)

BackgroundPatients with non-alcoholic fatty liver disease (NAFLD) may be more susceptible to coronavirus disease 2019 (COVID-19) and even more likely to suffer from severe COVID-19. Whether there is a common molecular pathological basis for COVID-19 and NAFLD remains to be identified. The present study aimed to elucidate the transcriptional alterations shared by COVID-19 and NAFLD and to identify potential compounds targeting both diseases.MethodsDifferentially expressed genes (DEGs) for COVID-19 and NAFLD were extracted from the GSE147507 and GSE89632 datasets, and common DEGs were identified using the Venn diagram. Subsequently, we constructed a protein–protein interaction (PPI) network based on the common DEGs and extracted hub genes. Then, we performed gene ontology (GO) and pathway analysis of common DEGs. In addition, transcription factors (TFs) and miRNAs regulatory networks were constructed, and drug candidates were identified.ResultsWe identified a total of 62 common DEGs for COVID-19 and NAFLD. The 10 hub genes extracted based on the PPI network were IL6, IL1B, PTGS2, JUN, FOS, ATF3, SOCS3, CSF3, NFKB2, and HBEGF. In addition, we also constructed TFs–DEGs, miRNAs–DEGs, and protein–drug interaction networks, demonstrating the complex regulatory relationships of common DEGs.ConclusionWe successfully extracted 10 hub genes that could be used as novel therapeutic targets for COVID-19 and NAFLD. In addition, based on common DEGs, we propose some potential drugs that may benefit patients with COVID-19 and NAFLD.

The combination of SMRT sequencing and Illumina sequencing highlights organ-specific and age-specific expression patterns of miRNAs in Sika Deer.

Due to the lack of high-quality Sika Deer (Cervus nippon) transcriptome and sRNAome across multiple organs or development stages, it is impossible to comprehensively analyze the mRNA and miRNA regulatory networks related to growth, development and immunity response. In this study, we used single molecule-real time sequencing (SMRT-seq) and Illumina sequencing methods to generate transcriptome and sRNAome from ten tissues and four age groups of Sika Deer to help us understand molecular characteristics and global miRNA expression profiles. The results showed that a total of 240,846 consensus transcripts were generated with an average length of 2,784 bp. 4,329 Transcription factors (TFs), 109,000 Simple Sequence Repeats (SSRs) and 18,987 Long non-coding RNAs (LncRNAs) were identified. Meanwhile, 306 known miRNAs and 143 novel miRNAs were obtained. A large number of miRNAs showed organ-specific and age-specific differential expression patterns. In particular, we found that the organ-specific miRNAs were enriched in the brain, some of which shared only between the brain and adrenal. These miRNAs were involved in maintaining specific functions within the brain and adrenal. By constructing miRNA96mRNA interaction networks associated with Sika Deer immunity, we found that miRNAs (miR-148a, miR-26a, miR-214, let-7b, etc.) and mRNAs (CD6, TRIM38, C3, CD163, etc.) might play an important role in the immune response of Sika Deer spleen. Together, our study generated an improved transcript annotation for Sika Deer by SMRT-seq and revealed the role of miRNA in regulating the growth, development and immunity response of Sika Deer.