miRBase: microRNA sequences, targets and gene nomenclature.

The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at http://microrna.sanger.ac.uk/

SNP analysis reveals an evolutionary acceleration of the human-specific microRNAs

MicroRNAs are one class of important gene regulators at the post-transcriptional level by binding to the 3’UTRs of target mRNAs. It has been reported that human microRNAs are evolutionary conserved and show lower single nucleotide polymorphisms (SNPs) than their flanking regions. However, in this study, we report that the human-specific microRNAs show a higher SNP density than both the conserved microRNAs and other control regions, suggesting rapid evolution and positive selection has occurred in these regions. Furthermore, we observe that the human-specific microRNAs show greater SNPs minor allele frequency and the SNPs in the human-specific microRNAs show fewer effects on the stability of the microRNA secondary structure, indicating that the SNPs in the human-specific microRNAs tend to be less deleterious. Finally, two microRNAs hsa-mir-423 (SNP: rs6505162), hsa-mir-608 (SNP: rs4919510) and 288 target genes that have apparently been under recent positive selection are identified. These findings will improve our understanding of the functions, evolution, and population disease susceptibility of human microRNAs

The expansion of the metazoan microRNA repertoire

BACKGROUND: MicroRNAs have been identified as crucial regulators in both animals and plants. Here we report on a comprehensive comparative study of all known miRNA families in animals. We expand the MicroRNA Registry 6.0 by more than 1000 new homologs of miRNA precursors whose expression has been verified in at least one species. Using this uniform data basis we analyze their evolutionary history in terms of individual gene phylogenies and in terms of preservation of genomic nearness across species. This allows us to reliably identify microRNA clusters that are derived from a common transcript. RESULTS: We identify three episodes of microRNA innovation that correspond to major developmental innovations: A class of about 20 miRNAs is common to protostomes and deuterostomes and might be related to the advent of bilaterians. A second large wave of innovations maps to the branch leading to the vertebrates. The third significant outburst of miRNA innovation coincides with placental (eutherian) mammals. In addition, we observe the expected expansion of the microRNA inventory due to genome duplications in early vertebrates and in an ancestral teleost. The non-local duplications in the vertebrate ancestor are predated by local (tandem) duplications leading to the formation of about a dozen ancient microRNA clusters. CONCLUSION: Our results suggest that microRNA innovation is an ongoing process. Major expansions of the metazoan miRNA repertoire coincide with the advent of bilaterians, vertebrates, and (placental) mammals

Genomic Organization of Zebrafish microRNAs

<p>Abstract</p> <p>Background</p> <p>microRNAs (miRNAs) are small (~22 nt) non-coding RNAs that regulate cell movement, specification, and development. Expression of miRNAs is highly regulated, both spatially and temporally. Based on direct cloning, sequence conservation, and predicted secondary structures, a large number of miRNAs have been identified in higher eukaryotic genomes but whether these RNAs are simply a subset of a much larger number of noncoding RNA families is unknown. This is especially true in zebrafish where genome sequencing and annotation is not yet complete.</p> <p>Results</p> <p>We analyzed the zebrafish genome to identify the number and location of proven and predicted miRNAs resulting in the identification of 35 new miRNAs. We then grouped all 415 zebrafish miRNAs into families based on seed sequence identity as a means to identify possible functional redundancy. Based on genomic location and expression analysis, we also identified those miRNAs that are likely to be encoded as part of polycistronic transcripts. Lastly, as a resource, we compiled existing zebrafish miRNA expression data and, where possible, listed all experimentally proven mRNA targets.</p> <p>Conclusion</p> <p>Current analysis indicates the zebrafish genome encodes 415 miRNAs which can be grouped into 44 families. The largest of these families (the miR-430 family) contains 72 members largely clustered in two main locations along chromosome 4. Thus far, most zebrafish miRNAs exhibit tissue specific patterns of expression.</p

miRBase Tracker : keeping track of microRNA annotation changes

Since 2002, information on individual microRNAs (miRNAs), such as reference names and sequences, has been stored in miRBase, the reference database for miRNA annota- tion. As a result of progressive insights into the miRNome and its complexity, miRBase underwent addition and deletion of miRNA records, changes in annotated miRNA se- quences and adoption of more complex naming schemes over time. Unfortunately, miRBase does not allow straightforward assessment of these ongoing miRNA annota- tion changes, which has resulted in substantial ambiguity regarding miRNA identity and sequence in public literature, in target prediction databases and in content on various commercially available analytical platforms. As a result, correct interpretation, compari- son and integration of miRNA study results are compromised, which we demonstrate here by assessing the impact of ignoring sequence annotation changes. To address this problem, we developed miRBase Tracker (www.mirbasetracker.org), an easy-to-use on- line database that keeps track of all historical and current miRNA annotation present in the miRBase database. Three basic functionalities allow researchers to keep their miRNA annotation up-to-date, reannotate analytical miRNA platforms and link published results with outdated annotation to the latest miRBase release. We expect miRBase Tracker to increase the transparency and annotation accuracy in the field of miRNA research. Database URL: www.mirbasetracker.or

The effect of microRNA-375 overexpression, an inhibitor of Helicobacter pylori-induced carcinogenesis, on lncRNA SOX2OT

Background: Helicobacter pylori is a major human pathogenic bacterium in gastric mucosa. Although the association between gastric cancer and H. pylori has been well-established, the molecular mechanisms underlying H. pylori-induced carcinogenesis are still under investigation. MicroRNAs (miRNAs) are small noncoding RNAs that modulate gene expression at the posttranscriptional level. Recently, studies have revealed that miRNAs are involved in immune response and host cell response to bacteria. Also, microRNA-375 (miR-375) is a key regulator of epithelial properties that are necessary for securing epithelium-immune system crosstalk. It has been recently reported that miR-375 acts as an inhibitor of H. pylori-induced gastric carcinogenesis. There are few reports on miRNA-mediated targeting long noncoding RNAs (lncRNAs). Objectives: This study aimed to examine the possible effect of miR-375 as an inhibitor of H. pylori-induced carcinogenesis on the expression of lncRNA SOX2 overlapping transcript (SOX2OT) and SOX2, a master regulator of pluripotency of cancer stem cells. Materials and Methods: In a model cell line, NT-2 was transfected with the constructed expression vector pEGFP-C1 contained miR- 375. The RNA isolations and cDNA synthesis were performed after 48 hours of transformation. Expression of miR-375 and SOX2OT and SOX2 were quantified using real-time polymerase chain reaction and compared with control cells transfected with pEGFP-C1-Mock clone. Cell cycle modification was also compared after transfections using the flow cytometry analysis. Results: Following ectopic expression of miR-375, SOX2OT and SOX2 expression analysis revealed a significant decrease in their expression level (P < 0.05) in NT-2 cells compared to the control. Cell cycle analysis following ectopic expression of miR-375 in the NT-2 cells using propidium iodine staining revealed significant extension in sub-G1 cell cycle. Conclusions: This is the first report to show down-regulation of SOX2OT and SOX2 following induced expression of miR-375. This findingmaysuggest expression regulation potential between different classes of ncRNAs, for example between miR-375andSOX2OT. This data not only extends our understanding of possible ncRNA interactions in cancers but also may open novel investigation lines towards elucidation of molecular mechanisms controlling H. pylori inflammation and carcinogenesis. © 2016, Ahvaz Jundishapur University of Medical Sciences

Establishment of a integrative multi-omics expression database CKDdb in the context of chronic kidney disease (CKD)

Complex human traits such as chronic kidney disease (CKD) are a major health and financial burden in modern societies. Currently, the description of the CKD onset and progression at the molecular level is still not fully understood. Meanwhile, the prolific use of high-throughput omic technologies in disease biomarker discovery studies yielded a vast amount of disjointed data that cannot be easily collated. Therefore, we aimed to develop a molecule-centric database featuring CKD-related experiments from available literature publications. We established the Chronic Kidney Disease database CKDdb, an integrated and clustered information resource that covers multi-omic studies (microRNAs, genomics, peptidomics, proteomics and metabolomics) of CKD and related disorders by performing literature data mining and manual curation. The CKDdb database contains differential expression data from 49395 molecule entries (redundant), of which 16885 are unique molecules (non-redundant) from 377 manually curated studies of 230 publications. This database was intentionally built to allow disease pathway analysis through a systems approach in order to yield biological meaning by integrating all existing information and therefore has the potential to unravel and gain an in-depth understanding of the key molecular events that modulate CKD pathogenesis

miRNAs as Regulators of Antidiabetic Effects of Fucoidans

open access articleDiabetes mellitus is a metabolic disease with a high mortality rate worldwide. MicroRNAs (miRNAs), and other small noncoding RNAs, serve as endogenous gene regulators through binding to specific sequences in RNA and modifying gene expression toward up- or down-regulation. miRNAs have become compelling therapeutic targets and play crucial roles in regulating the process of insulin resistance. Fucoidan has shown potential function as an a-amylase inhibitor, which may be beneficial in the management of type 2 diabetes mellitus. In recent years, many studies on fucoidan focused on the decrease in blood glucose levels caused by ingesting low-glucose food or glucose-lowering components. However, the importance of miRNAs as regulators of antidiabetic effects was rarely recognized. Hence, this review emphasizes the antidiabetic mechanisms of fucoidan through regulation of miRNAs. Fucoidan exerts a vital antidiabetic effect by regulation of miRNA expression and thus provides a novel biological target for future research

Post-transcriptional knowledge in pathway analysis increases the accuracy of phenotypes classification

Motivation: Prediction of phenotypes from high-dimensional data is a crucial task in precision biology and medicine. Many technologies employ genomic biomarkers to characterize phenotypes. However, such elements are not sufficient to explain the underlying biology. To improve this, pathway analysis techniques have been proposed. Nevertheless, such methods have shown lack of accuracy in phenotypes classification. Results: Here we propose a novel methodology called MITHrIL (Mirna enrIched paTHway Impact anaLysis) for the analysis of signaling pathways, which has built on top of the work of Tarca et al., 2009. MITHrIL extends pathways by adding missing regulatory elements, such as microRNAs, and their interactions with genes. The method takes as input the expression values of genes and/or microRNAs and returns a list of pathways sorted according to their deregulation degree, together with the corresponding statistical significance (p-values). Our analysis shows that MITHrIL outperforms its competitors even in the worst case. In addition, our method is able to correctly classify sets of tumor samples drawn from TCGA. Availability: MITHrIL is freely available at the following URL: http://alpha.dmi.unict.it/mithril

An Introduction to RNA Databases

We present an introduction to RNA databases. The history and technology behind RNA databases is briefly discussed. We examine differing methods of data collection and curation, and discuss their impact on both the scope and accuracy of the resulting databases. Finally, we demonstrate these principals through detailed examination of four leading RNA databases: Noncode, miRBase, Rfam, and SILVA.Comment: 27 pages, 10 figures, 1 tables. Submitted as a chapter for "An introduction to RNA bioinformatics" to be published by "Methods in Molecular Biology