A database of experimentally verified microRNAs and miRNA target genes in human, mouse, rat, and other metazoan genomes. In addition to known miRNA targets, three computational tools previously developed, such as miRanda, RNAhybrid and TargetScan, were applied for identifying miRNA targets in 3'-UTR of genes. In order to reduce the false positive prediction of miRNA targets, several criteria are supported for filtering the putative miRNA targets. Furthermore, miRNA expression profiles can provide valuable clues for investigating the properties of miRNAs, such tissue specificity and differential expression in cancer/normal cell. Therefore, we performed the Q-PCR experiments for monitoring the expression profiles of 224 human miRNAs in eighteen major normal tissues in human. The cross-reference between the miRNA expression profiles and the expression profiles of its target genes can provide effective viewpoint to understand the regulatory functions of the miRNA.

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. UCbase & miRfunc is a database of (i) human, mouse and rat microRNAs and (ii) Ultraconserved elements providing information about function, expression and correlation between these classes of non-coding RNAs and the disorders related to their aberrant expression. The genomics interface allows the user to explore where whole-genome collections of miRNAs and UCRs are located with respect to annotation sets such as band, disorders and known genes. The Blast interface provides a web tool for matching miRNAs/UCRs elements against any given sequence and providing specific functional information on the results. 481 Ultraconserved sequences (UCRs) longer than 200 bases were discovered in the genomes of human, mouse and rat. These are DNA sequences showing 100 percent identity among the human, mouse and rat genomes. UCRs are frequently located at genomic regions involved in cancer, differentially expressed in human leukemias and carcinomas and in some instances regulated by microRNAs (miRNAs), the most extensively studied category of non-coding RNAs (ncRNAs). Here we present the first database which links UCRs and miRNAs with the related human disorders and genomic properties.

This data package contains dataset on microRNA sequences and families with annotations and dataset on human genes and their miRNA annotations.

ObjectiveSince circRNA can be utilized as a potential diagnostic marker for cancer, to explore the regulatory mechanism of colorectal cancer (CRC) using bioinformatics, the public database of circRNA was mined.MethodsCRC differentially expressed miRNAs were screened in the Cancer Genome Atlas (TCGA) database, CRC differentially expressed circRNAs were searched in the Gene Expression Omnibus (GEO) database, the two databases were combined to identify CRC differentially expressed mRNAs, and a circRNA-miRNA‒mRNA regulatory network was constructed by combining a plurality of target prediction databases to identify key genes. The upstream circRNA and regulatory axis of the key genes were identified for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis to explore the biological functions of circRNA in CRC using the regulatory axis.ResultsAfter the screening of the GSE21815 dataset, a total of 22 differentially expressed circRNAs were obtained, with 12 upregulated and 10 downregulated genes. Similarly, the GSE126094 dataset yielded 104 differentially expressed circRNAs, comprising 56 upregulated and 48 downregulated genes. Among the differentially expressed circRNAs, five were identified, with VDAC3 and SETD2 showing downregulated expression, while RAD23B, RPPH1, and MYBL2 exhibited upregulated expression. Following the selection process, five DEcircRNAs, eight target miRNAs, and 105 target DEmRNAs were identified. The protein-protein interaction (PPI) network revealed close relationships among the mRNAs, with E2F2, E2F3, CCND1, TNRC6A, and KAT2B identified as key genes. Notably, CCND1 emerged as a critical gene in the PPI network. Through the upregulation of has-circ-0087862, which binds to miR-892b, the translation inhibition of CCND1 by miR-892b was attenuated, leading to enhanced CCND1 expression. Functional enrichment analysis indicated that CCND1 was involved in protein binding and positive regulation of cellular processes, among other functions.ConclusionThe differentially expressed genes (DEGs) in CRC markedly affected the survival time of patients. CircRNAs could be utilized as diagnostic markers of CRC, and the key genes in CRC could be screened out by bioinformatics, which would be helpful to understand the drug targets for the treatment of human immunodeficiency virus (HIV)-related CRC patients.

399 tumors profiled using Agilent miRNA microarrays (Product Number G4872A, design ID 046064). The arrays are based on miRBase release 19.0 and 2006 human miRNAs are represented. 150 ng total RNA was used as input.

In the present study we analyzed miRNA and mRNA expression profiles in human peripheral blood lymphocytes (PBLs) incubated in microgravity condition simulated by a ground-based Rotating Wall Vessel (RWV) bioreactor. Our results show that 42 miRNAs were differentially expressed in MMG-incubated PBLs compared with 1g-incubated ones. Among these miR-9-5p miR-9-3p miR-155-5p miR-150-3p and miR-378-3p were the most dysregulated. To improve the detection of functional miRNA-mRNA pairs we performed gene expression profiles on the same samples assayed for miRNA profiling and we integrated miRNA and mRNA expression data. The functional classification of miRNA-correlated genes evidenced significant enrichments in the biological processes of immune/inflammatory response signal transduction regulation of response to stress regulation of programmed cell death and regulation of cell proliferation. We identified the correlation between miR-9-3p miR-155-5p miR-150-3p and miR-378-3p expression with that of genes involved in immune/inflammatory response (eg. IFNG and IL17F) apoptosis (eg. PDCD4 and PTEN) and cell proliferation (eg. NKX3-1 and GADD45A). Experimental assays of cell viability and apoptosis induction validated the results obtained by bioinformatics analyses demonstrating that in human PBLs the exposure to reduced gravitational force increases the frequency of apoptosis and decreases cell proliferation. microRNA expression profiling were carried out on total RNA extracted from PBLs of twelve healthy donors at the end of 24h-incubation time in MMG and in 1g conditions. Analyses were performed by using the Human miRNA Microarray kit (V2) (Agilent Technologies) that allows the detection of 723 known human (miRBase v.10.1) and 76 human viral miRNAs. By comparing the expression profile of MMG-incubated vs. 1g-incubated PBLs of the same donor we found 42 differentially expressed miRNAs 25 up-regulated and 17 down-regulated.

The aim of this study was to identity in silico the relationships among microRNAs (miRNAs) and genes encoding transcription factors, ubiquitylation, DNA methylation, and histone modifications in systemic lupus erythematosus (SLE). To identify miRNA dysregulation in SLE, we used miR2Disease and PhenomiR for information about miRNAs exhibiting differential regulation in disease and other biological processes, and HMDD for information about experimentally supported human miRNA-disease association data from genetics, epigenetics, circulating miRNAs, and miRNA-target interactions. This information was incorporated into the miRNA analysis. High-throughput sequencing revealed circulating miRNAs associated with kidney damage in patients with SLE. As the main finding of our in silico analysis of miRNAs differentially expressed in SLE and their interactions with disease-susceptibility genes, post-translational modifications, and transcription factors; we highlight 226 miRNAs associated with genes and processes. Moreover, we highlight that alterations of miRNAs such as hsa-miR-30a-5p, hsa-miR-16-5p, hsa-miR-142-5p, and hsa-miR-324-3p are most commonly associated with post-translational modifications. In addition, altered miRNAs that are most frequently associated with susceptibility-related genes are hsa-miR-16-5p, hsa-miR-374a-5p, hsa-miR-34a-5p, hsa-miR-31-5p, and hsa-miR-1-3p.

*Human mir-923 appears to be a frgament of the 28S rRNA, so is removed from the microRNA database;Human mir-768 overlaps an annotated snoRNA, HBII-239. Phylogenetic analysis in all vertebrates supports the snoRNA annotation, with poor conservation of the reported mature miRNA sequence,it is therefore removed from the microRNA database.

Human miRNA tissue atlas. Database showing distribution of miRNA expression across human tissues.

A database of manually curated dSNPs on the 3''UTRs of human genes from available publications in PubMed. The advanced web interface allows users to perform proximity searches between miRNA target sites and dSNPs by gene name, miRbase ID, target prediction algorithm, disease, and any nucleotide distance between dSNPs and miRNA target sites. The web interface displays detailed sequence views showing the relationship between dSNPs, miRNA target sites, and SNPs. An interactive visualization tool shows the chromosomal distribution of dSNPs, miRNA target sites (from TargetScan), and SNPs. miRdSNP provides a comprehensive data source of dSNPs and robust tools to capture their spacial relationship with miRNA target sites on the 3''UTRs of human genes. miRdSNP enables researchers to further explore the molecular mechanism of gene dysregulation for dSNPs at posttranscriptional level.

Using a bioinformatic analysis of human miRNA potential interactions with the SARS-CoV-2’s genome, we examined the potential miRNA target sites in 7 coronavirus genomes that include SARS-CoV-2, MERS-CoV, SARS-CoV, and 4 non-pathogenic coronaviruses. (Data Set 1).

Our approach was to examine and compare 3 pathogenic and 4 non-pathogenic strains of HCoVs. The HCoVs' RNA genomes of pathogenic strains were SARS-CoV-2 (NC_045512.2), SARS-CoV (NC_004718.3), MERS-CoV (NC_019843.3). The non-pathogenic strains were HCoV-OC43 (KU131570.1), HCoV-229E (NC_002645.1), HCoV-HKU1 (KF686346.1), and HCoV-NL63 (NC_005831.2). These coronaviruses were tested against the set of 896 confident mature human miRNA sequences that were obtained from the miRBbase v2.21 using the RNA22 v2 microRNA target discovery tool web-server. In order to reduce the false discovery rate of the MTS predictions, the most strict parameters were applied to the default computation workflow using a specificity of 92% versus a sensitivity of 22%.

In Data set 2, using the miRDIP database with only top 1% of the most probable targets considered, we analyzed the potential targets of miRNA that could be bound to either the pathogenic, the non-pathogenic or both groups of HCoVs.

In Data set 3, using miRNAFold webserver we identified 10 pre-miRNA sequences in the SARS-CoV-2 RNA sequence that could potentially enter the human RNAi pathway.

The graphical summary of our working hypothesis is provided in the graphical abstract.

Database serving as a tool for microRNA target prediction. The HOCTAR procedure is based on the integration of expression profiling and sequence-based miRNA target recognition softwares. HOCTAR database (db) is the first and unique database to use transcriptomic data to score putative miRNA targets looking at the expression behaviour of their host genes, and it includes and re-analyzes all miRNA target predictions generated by softwares such as miRanda, TargetScan and PicTar. The HOCTARdb contains the prediction target lists for 290 human intragenic miRNAs and also provides tentative assignments of miRNA function based on Gene Ontology analyses of their predicted targets. There are two ways to interrogate HOCTARdb: (i) by selecting a miRNA using either an alphabetically sorted pull-down menu in the microRNA query, or (ii) by typing a target gene symbol (HUGO Gene Name-approved) in the Target Gene Name query.

MicroRNAs (miRNAs), approximately 22-nucleotide non-coding RNA molecules, regulate a variety of pivotal physiological or pathological processes, including embryonic development and tumorigenesis. To obtain comprehensive expression profiles of miRNAs in human embryos, we characterized miRNA expression in weeks 4-6 of human embryonic development using miRNA microarrays and identified 50 human-embryo-specific miRNAs (HES-miRNAs). Furthermore, we selected three non-conserved or primate-specific miRNAs, hsa-miR-638, -720, and -1280, and examined their expression levels in various normal and tumor tissues. The results show that expression of most miRNAs is extremely low during early human embryonic development. In addition, the expression of some non-conserved or primate-specific miRNAs is significantly different between tumor and the corresponding normal tissue samples, suggesting that the miRNAs are closely related to the pathological processes of various tumors. This study presents the first comprehensive overview of miRNA expression during human embryonic development and offers immediate evidence of the relationship between human early embryonic development and tumorigenesis.

ViTa is a database which collects virus data from miRBase and ICTV, VirGne, VBRC.., etc, including known miRNAs on virus and supporting predicted host miRNA targets by miRanda and TargetScan. ViTa also rovide effective annotations, including human miRNA expression, virus infected tissues, annotation of virus and comparisons.

The present study concerns the effects of 21 days of sustained recumbence (bedrest) and hypoxia alone and in combination on skeletal muscle microRNA expression. 14 male subjects participated in 3 experimental campaigns in a counterbalanced fashion: normoxic bedrest (NBR) hypoxic bedrest (HBR) and hypoxic ambulatory confinement (HAMB) both hypoxic conditions with FO2 = 0.141 and PIO2 = 90 xc2 xb1 0.4 mmHg equivalent to an altitude of xe2 x89 x88 4000 m). Each intervention (bedrest or ambulatory confinement) lasted 21 days and the interventions were separated by a 4-month wash-out/recovery period. The order in which each subject undertook the interventions is denoted Intervention_order Throughout both bedrest interventions each subject remained in a horizontal position at all times. He was allowed one pillow for the head and to occasionally lean on an elbow while eating or being transferred to a gurney. Muscular exercise was prohibited. During the HAMB confinement each subject was allowed to move freely within the hypoxic area. To mimic a normal level of physical activity subjects performed 30 minutes of low-to-moderate-intensity exercise twice daily. Muscle samples from Vastus lateralis.

Brain ischemia induces systemic immunosuppression and increases a host's susceptibility to infection. MicroRNAs (miRNAs) are molecular switches in immune cells, but the alterations of miRNAs in human immune cells in response to brain ischemia and their impact on immune defense remain elusive. Natural killer (NK) cells are critical for early host defenses against pathogens. In this study, we identified reduced counts, cytokine production, and cytotoxicity in human peripheral blood NK cells obtained from patients with acute ischemic stroke. The extent of NK cell loss of number and activity was associated with infarct volume. MicroRNA sequencing analysis revealed that brain ischemia significantly altered miRNA expression profiles in circulating NK cells, in which miRNA-451a and miRNA-122-5p were dramatically upregulated. Importantly, inhibition of miR-451a or miR-122-5p augmented the expression of activation-associated receptors in NK cells. These results provide the first evidence that brain ischemia alters miRNA signatures in human NK cells.

This is the Raw Data Files of the sequencing data. And the original datas about the Differentially_Expressed_miRNAs, GO Analysis Results (miRNA Targets),miRNA_Targets_Prediction,novel_miRNAs_predicted_by_miRDeep2, and Pathway Analysis Results (miRNA Targets).

BACKGROUND: Ionizing radiation (IR) can be extremely harmful for human cells since an improper DNA-damage response (DDR) to IR can contribute to carcinogenesis initiation. Perturbations in DDR pathway can originate from alteration in the functionality of the microRNA-mediated gene regulation being microRNAs (miRNAs) small noncoding RNA that act as post-transcriptional regulators of gene expression. In this study we gained insight into the role of miRNAs in the regulation of DDR to IR under microgravity a condition of weightlessness experienced by astronauts during space missions which could have a synergistic action on cells increasing the risk of radiation exposure. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed miRNA expression profile of human peripheral blood lymphocytes (PBL) incubated for 4 and 24 h in normal gravity (1 g) and in modeled microgravity (MMG) during the repair time after irradiation with 0.2 and 2Gy of gamma-rays. Our results show that MMG alters miRNA expression signature of irradiated PBL by decreasing the number of radio-responsive miRNAs. Moreover let-7i miR-7 miR-7-1 miR-27a miR-144 miR-200a miR-598 miR-650 are deregulated by the combined action of radiation and MMG. Integrated analyses of miRNA and mRNA expression profiles carried out on PBL of the same donors identified significant miRNA-mRNA anti-correlations of DDR pathway. Gene Ontology analysis reports that the biological category of Response to DNA damage is enriched when PBL are incubated in 1 g but not in MMG. Moreover some anti-correlated genes of p53-pathway show a different expression level between 1 g and MMG. Functional validation assays using luciferase reporter constructs confirmed miRNA-mRNA interactions derived from target prediction analyses. CONCLUSIONS/SIGNIFICANCE: On the whole by integrating the transcriptome and microRNome we provide evidence that modeled microgravity can affects the DNA-damage response to IR in human PBL.

We reconstructed miRNA regulatory networks for 38 tissues from the Genotype-Tissue Expression project (GTEx) using two different prior networks, one obtained with target predictions from TargetScan and one with target predictions from miRanda.

We used these networks to investigate gene expression and regulation by miRNAs across these tissues. In the RData file, we share the following objects:

• exp: a 16,161 by 9,435 data frame including normalized expression data for each sample.

• expTS: a 16,161 by 38 matrix including the tissue-specificity scores for each gene in each tissue.

• netT: a 10,391,523 by 41 data frame that includes the miRNA regulatory networks. The column "miRNA" includes the name of the regulating miRNA, the column "Gene" includes the target gene (HGNC symbol), and the column "Prior" the prior regulatory network based on target predictions from TargetScan, with 1 for edges that are canonical and 0 for edges that are non-canonical. The remaining 38 columns contain the PUMA network edge weights for each of the 38 tissues.

• netT_TS: a 10,391,523 by 38 matrix that includes the tissue-specificity scores of the miRNA regulatory networks that were modeled on the TargetScan prior. Edges are not labelled, but edge order corresponds to the edges in "netT".

• netM: a 10,391,523 by 41 data frame that includes the miRNA regulatory networks. The column "miRNA" includes the name of the regulating miRNA, the column "Gene" includes the target gene (HGNC symbol), and the column "Prior" the prior regulatory network based on target predictions from miRanda, with 1 for edges that are canonical and 0 for edges that are non-canonical. The remaining 38 columns contain the PUMA network edge weights for each of the 38 tissues.

• netM_TS: a 10,391,523 by 38 matrix that includes the tissue-specificity scores of the miRNA regulatory networks that were modeled on the miRanda prior. Edges are not labelled, but edge order corresponds to the edges in "netT".

• samples: a 9,435 by 2 data frame that includes sample identifiers (matching the identifiers in "exp") and the tissue to which these samples belong.

• mirnames: a 694 by 3 data frame that contains miRNA names of regulators and their matching target miRNA names. The first column "base_miRNA" contains the "base" miRNA, the name of the miRNA without any extensions. The second column "reg_miRNA" contains the 643 regulator miRNA, which may have -3P/-5P extensions, and which matches the miRNAs that are present as regulators in the networks. The third columns "tar_miRNA" contains the 621 target miRNAs, which may have numbered suffix extensions, and for which we have expression data available.

microRNA data integration portal to find microRNAs that target a gene, or genes targeted by a microRNA, in Homo sapiens. Software to integrate prediction databases to elucidate accurate microRNA:target relationships. Used for human microRNA prediction studies.