Human pre-miRNA Research Articles

The Human Pre-miRNA Distance Distribution for Exploring Disease Association.

MicroRNAs (miRNAs), playing an important role in cell differentiation, development, gene regulation, and apoptosis, have attracted much attention in recent years. miRNAs were shown to be involved in the mechanisms of various diseases, and certainly, they can be employed as useful disease biomarkers. The phylogenetic tree analysis of miRNA biomarkers is a useful tool to investigate the association between various diseases as well as the association between viruses and disease. In addition to the phylogenetic tree analysis, a more advanced study is to use the miRNA distance distribution to evaluate the similarity of the miRNA biomarkers. The mature miRNA distance distribution based on mature miRNA sequences has been derived. The averages of the pairwise distances of miRNA biomarkers for several associated diseases were shown to be smaller than the overall mean of all miRNAs, which indicates the high similarity of miRNA biomarkers for associated diseases. In addition to the mature miRNA, the precursor miRNA (pre-miRNA) may be more useful to explore the similarity of miRNAs because the mature miRNA duplex is released from the pre-miRNA. Therefore, in this study, the distance distributions based on human pre-miRNA stem-loop sequences were derived. The 1917 human miRNA stem-loop sequences in the miRBase dataset were used to derive the pre-miRNA distance distribution, and this is the first study to provide the distance distribution based on the human pre-miRNAs. The similarity of miRNA biomarkers for several associated diseases or vaccines was examined using the derived distribution, and the results show that the similarity of pre-miRNA biomarkers may be a feasible way to help explore the disease association.

Characterization of Viral miRNAs during Adenovirus 14 Infection and Their Differential Expression in the Emergent Strain Adenovirus 14p1

Human adenoviruses (HAdV) express either one or two virus-associated RNAs (VA RNAI or VA RNAII). The structure of VA RNA resembles human precursor microRNAs (pre-miRNA), and, like human pre-miRNA, VA RNA can be processed by DICER into small RNAs that resemble human miRNA. VA RNA-derived miRNA (mivaRNA) can mimic human miRNA post-transcriptional gene repression by binding to complementary sequences in the 3′ UTR of host mRNA. HAdV14 is a member of the B2 subspecies of species B adenovirus, and the emergent strain HAdV14p1 is associated with severe respiratory illness that can lead to acute respiratory distress syndrome. Utilizing small RNA sequencing, we identified four main mivaRNAs generated from the HAdV14/p1 VA RNA gene, two from each of the 5′ and 3′ regions of the terminal stem. There were temporal expression changes in the abundance of 5′ and 3′ mivaRNAs, with 3′ mivaRNAs more highly expressed early in infection and 5′ mivaRNAs more highly expressed later in infection. In addition, there are differences in expression between the emergent and reference strains, with HAdV14 expressing more mivaRNAs early during infection and HAdV14p1 having higher expression later during infection. HAdV14/p1 mivaRNAs were also shown to repress gene expression in a luciferase gene reporter system. Our results raise the question as to whether differential expression of mivaRNAs during HAdV14p1 infection could play a role in the increased pathogenesis associated with the emergent strain.

Multi-branch Convolutional Neural Network for Identification of Small Non-coding RNA genomic loci

Genomic regions that encode small RNA genes exhibit characteristic patterns in their sequence, secondary structure, and evolutionary conservation. Convolutional Neural Networks are a family of algorithms that can classify data based on learned patterns. Here we present MuStARD an application of Convolutional Neural Networks that can learn patterns associated with user-defined sets of genomic regions, and scan large genomic areas for novel regions exhibiting similar characteristics. We demonstrate that MuStARD is a generic method that can be trained on different classes of human small RNA genomic loci, without need for domain specific knowledge, due to the automated feature and background selection processes built into the model. We also demonstrate the ability of MuStARD for inter-species identification of functional elements by predicting mouse small RNAs (pre-miRNAs and snoRNAs) using models trained on the human genome. MuStARD can be used to filter small RNA-Seq datasets for identification of novel small RNA loci, intra- and inter- species, as demonstrated in three use cases of human, mouse, and fly pre-miRNA prediction. MuStARD is easy to deploy and extend to a variety of genomic classification questions. Code and trained models are freely available at gitlab.com/RBP_Bioinformatics/mustard.

A Potassium Ion-Dependent RNA Structural Switch Regulates Human Pre-miRNA 92b Maturation

MicroRNAs (miRNAs) are an important set of oligonucleotide sequences with a biogenesis that involves Dicer-mediated cleavage as a critical step. Dicer cleaves the precursor miRNA (pre-miRNA) stem-loop structure to produce the mature miRNA. Using bioinformatics analysis, we discovered the presence of putative G-quadruplex (GQ)-forming sequences in about 16% of pre-miRNAs. We report the existence of a GQ as an alternative to the canonical stem-loop structure in the clinically important human pre-miRNA 92b. GQ formation led to unwinding of the stem-loop structure imparting resistance to Dicer-mediated cleavage both invitro and invivo. A potential K(+) ion-dependent equilibrium between GQ and the stem-loop structure has the ability to regulate the Dicer-mediated maturation of pre-miRNA 92b, which consequently affects target gene silencing. These findings unravel a new mechanism of regulation in pre-miRNA maturation, albeit at the RNA structure level.

The relationship between pre-mir-146a G/C polymorphism and risk of gastric cancer in patients with gastric cancer in Ardabil province, Iran

Background: MicroRNAs (miRNAs) are endogenous non-protein-coding short RNAs of 21-23 nucleotides (Kim, 2005; Bartel, 2004).polymorphism in human pre-mir-146a has been recently implicated in human cancers. Gastric cancer (GC) is the most of common cancers, and is especially common in Ardabil province, located in North-West Iran. Single nucleotide polymorphism (SNP)is the most common type of genetic variation in the human genome .polymorphisms in human pre-mi RNA genome lesion modify the processing and/or target selection of human mi RNAs, which are implicated in cell cycle regulation , and thereby play critical roles in carcinogenesis. Pre-mir-146a G/C polymorphism designated rs2910164 is located on chromosome 5, in the stem region opposite to the mature pre-mir-146a sequence. Methods: We performed a hospital-based, case-control study using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method in 100 individuals (50 gastric cancer patients and 50 age and sex matched cancer – free controls). The frequency of genotypes was 9(18%), 17(34%), and 24(48%) among cases and 3(6%), 14(28%), and 33(66%) among controls for C/C, G/C, and G/G, respectively. The 147bp amplified fragment was digested by Sac1 (Thermo science co.). An uncut fragment indicates allele G. However, substitution of C allele by G allele tends to create a Sac1 restriction site. Therefore, C allele is observed by 122bp and 25bp digested products. If the quantity of restriction enzyme used is inadequate, the homozygous may be detected as heterozygote, therefore, some sequenced samples were chosen for evaluating the accuracy of digestion. All the statistical analyses were performed using spss software. Results: The frequencies of pre-miR-146a G/C genotypes in the case groups were significantly different from those in the control groups although clinically CC genotype in patients with gastric cancer incidence was higher than the control groups (18% versus 6%), so this difference was statistically significant (p=0.038). Conclusions: In this study, between the polymorphism of G/C hsa-mir-146a and the risk of gastric cancer in Ardabil province, a significant relationship was found.

Derivation and characterization of Dicer- and microRNA-deficient human cells.

We have used genome editing to generate inactivating deletion mutations in all three copies of the dicer (hdcr) gene present in the human cell line 293T. As previously shown in murine ES cells lacking Dicer function, hDcr-deficient 293T cells are severely impaired for the production of mature microRNAs (miRNAs). Nevertheless, RNA-induced silencing complexes (RISCs) present in these hDcr-deficient cells are readily programmed by transfected, synthetic miRNA duplexes to repress mRNAs bearing either fully or partially complementary targets, including targets bearing incomplete seed homology to the introduced miRNA. Using these hDcr-deficient 293T cells, we demonstrate that human pre-miRNA processing can be effectively rescued by ectopic expression of the Drosophila Dicer 1 protein, but only in the presence of the PB isoform of Loquacious (Loqs-PB), the fly homolog of the hDcr cofactor TRBP. In contrast, Drosophila Dicer 2, even in the presence of its cofactors Loqs-PD and R2D2, was unable to support human pre-miRNA processing. Interestingly, although ectopic Drosophila Dicer 1/Loqs-PB or hDcr both rescued pre-miRNA processing effectively in these hDcr-deficient cells, there were significant differences in the ratio of the miRNA isoforms that were produced, especially in the case of miR-30 family members, and we also noted differences in the relative expression level of miRNAs vs. passenger strands for a subset of human miRNAs. These data demonstrate that the mechanisms underlying the accurate processing of pre-miRNAs are largely, but not entirely, conserved between mammalian and insect cells.

Improved and Promising Identification of Human MicroRNAs by Incorporating a High-Quality Negative Set.

MicroRNA (miRNA) plays an important role as a regulator in biological processes. Identification of (pre-) miRNAs helps in understanding regulatory processes. Machine learning methods have been designed for pre-miRNA identification. However, most of them cannot provide reliable predictive performances on independent testing data sets. We assumed this is because the training sets, especially the negative training sets, are not sufficiently representative. To generate a representative negative set, we proposed a novel negative sample selection technique, and successfully collected negative samples with improved quality. Two recent classifiers rebuilt with the proposed negative set achieved an improvement of ~6 percent in their predictive performance, which confirmed this assumption. Based on the proposed negative set, we constructed a training set, and developed an online system called miRNApre specifically for human pre-miRNA identification. We showed that miRNApre achieved accuracies on updated human and non-human data sets that were 34.3 and 7.6 percent higher than those achieved by current methods. The results suggest that miRNApre is an effective tool for pre-miRNA identification. Additionally, by integrating miRNApre, we developed a miRNA mining tool, mirnaDetect, which can be applied to find potential miRNAs in genome-scale data. MirnaDetect achieved a comparable mining performance on human chromosome 19 data as other existing methods.

Loop-miRs: active microRNAs generated from single-stranded loop regions

MicroRNAs (miRNAs) are key mediators of post-transcriptional gene regulation. The miRNA precursors are processed by the endonucleases Drosha and Dicer into a duplex, bound to an Argonaute protein and unwound into two single-stranded miRNAs. Although alternative ways to generate miRNAs have been discovered, e.g. pre-miRNA cleavage by Ago2 or cleavage products of snoRNAs or tRNAs, all known pathways converge on a double-stranded RNA duplex. Exogenous single-stranded siRNAs (ss-siRNAs) can elicit an effective RNA interference reaction; recent studies have identified chemical modifications increasing their stability and activity. Here, we provide first evidence that endogenous, unmodified, single-stranded RNA sequences are generated from single-stranded loop regions of human pre-miRNA hairpins, the so called loop-miRs. Luciferase assays and immunoprecipitation validate loop-miR activity and incorporation into RNA-induced silencing complexes. This study identifies endogenous miRNAs that are generated from single-stranded regions; hence, it provides evidence that precursor-miRNAs can give rise to three distinct endogenous miRNAs: the guide strand, the passenger strand and the loop-miR.

A novel over-sampling method and its application to miRNA prediction

MicroRNAs (miRNAs) are short (~22nt) non-coding RNAs that play an indispensable role in gene regulation of many biological processes. Most of current computational, comparative, and non-comparative methods commonly classify human precursor micro- RNA (pre-miRNA) hairpins from both genome pseudo hairpins and other non-coding RNAs (ncRNAs). Although there were a few approaches achieving promising results in applying class imbalance learning methods, this issue has still not solved completely and successfully yet by the existing methods because of imbalanced class distribution in the datasets. For example, SMOTE is a famous and general over-sampling method addressing this problem, however in some cases it cannot improve or sometimes reduces classification performance. Therefore, we developed a novel over-sampling method named incre-mental- SMOTE to distinguish human pre-miRNA hairpins from both genome pseudo hairpins and other ncRNAs. Experimental results on pre-miRNA datasets from Batuwita et al. showed that our method achieved better Sensitivity and G-mean than the control (no over- sampling), SMOTE, and several successsors of modified SMOTE including safe-level-SMOTE and border-line-SMOTE. In addition, we also applied the novel method to five imbalanced benchmark datasets from UCI Machine Learning Repository and achieved improvements in Sensitivity and G-mean. These results suggest that our method outperforms SMOTE and several successors of it in various biomedical classification problems including miRNA classification.

Dynamic evolution of mir-17–92 gene cluster and related miRNA gene families in vertebrates

mir-17-92 gene cluster is widely distributed in vertebrates and plays an important role in regulating multiple biological processes. Its dysregulation may be associated with risk of some human cancers. The microRNA (miRNA) members are identified in the three gene families: mir-17, mir-19 and mir-25. Herein we attempted to understand the evolutionary processes and patterns in vertebrates. The three miRNA gene families showed difference in distribution, number of miRNA genes and clustered miRNA genes in the five animal species. Compared to other related gene clusters, mir-17-92 cluster was well-conserved and had more abundant roles in multiple biological processes. These clustered miRNAs showed inconsistent nucleotide divergence patterns across different animal species, even between homologous miRNA genes. Simultaneously, they also indicated inconsistent expression patterns although they were co-transcribed as a polycistronic transcript. Phylogenetic tree based on human pre-miRNA sequences showed that mir-19 gene family was an older miRNA species, while tree based on miRNA gene cluster indicated evolutionary positions of different animal species. The study shows dynamic evolution of the mir-17-92 gene cluster and related miRNA gene families across vertebrates, which may be derived from potential functional implication. miRNA gene cluster should be a better phylogenetic marker than a single miRNA gene to reveal functional and evolutionary relationships.

Pre-microRNA and Mature microRNA in Human Mitochondria

BackgroundBecause of the central functions of the mitochondria in providing metabolic energy and initiating apoptosis on one hand and the role that microRNA (miRNA) play in gene expression, we hypothesized that some miRNA could be present in the mitochondria for post-transcriptomic regulation by RNA interference. We intend to identify miRNA localized in the mitochondria isolated from human skeletal primary muscular cells.Methodology/Principal FindingsTo investigate the potential origin of mitochondrial miRNA, we in-silico searched for microRNA candidates in the mtDNA. Twenty five human pre-miRNA and 33 miRNA aligments (E-value<0.1) were found in the reference mitochondrial sequence and some of the best candidates were chosen for a co-localization test. In situ hybridization of pre-mir-302a, pre-let-7b and mir-365, using specific labelled locked nucleic acids and confocal microscopy, demonstrated that these miRNA were localized in mitochondria of human myoblasts. Total RNA was extracted from enriched mitochondria isolated by an immunomagnetic method from a culture of human myotubes. The detection of 742 human miRNA (miRBase) were monitored by RT-qPCR at three increasing mtRNA inputs. Forty six miRNA were significantly expressed (2nd derivative method Cp>35) for the smallest RNA input concentration and 204 miRNA for the maximum RNA input concentration. In silico analysis predicted 80 putative miRNA target sites in the mitochondrial genome (E-value<0.05).Conclusions/SignificanceThe present study experimentally demonstrated for the first time the presence of pre-miRNA and miRNA in the human mitochondria isolated from skeletal muscular cells. A set of miRNA were significantly detected in mitochondria fraction. The origin of these pre-miRNA and miRNA should be further investigate to determine if they are imported from the cytosol and/or if they are partially processed in the mitochondria.

Structural profiles of human miRNA families from pairwise clustering

MicroRNAs (miRNAs) are a group of small, approximately 21 nt long, riboregulators inhibiting gene expression at a post-transcriptional level. Their most distinctive structural feature is the foldback hairpin of their precursor pre-miRNAs. Even though each pre-miRNA deposited in miRBase has its secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures. http://genome.ku.dk/resources/mirclust

Computational identification of novel microRNA homologs in the chimpanzee genome

MicroRNAs are important negative regulators of gene expression in higher eukaryotes. The miRNA repertoire of the closest human animal relative, the chimpanzee ( Pan troglodytes), is largely unknown. In this study, we focused on computational search of novel miRNA homologs in chimpanzee. We have searched and analyzed the chimp homologs of the human pre-miRNA and mature miRNA sequences. Based on a homology search of the chimpanzee genome with human miRNA precursor sequences as queries, we identified 639 chimp miRNA genes, including 529 novel chimp miRNAs. 91.8% of chimp mature miRNAs and 60.3% of precursors are 100% identical to their human orthologs. The pre-miRNA secondary structures, miRNA families, and clusters are also highly conserved. We also found certain sequence differences in pre-miRNAs and even mature miRNAs that occurred after the divergence of the two species. Some of these differences (especially in mature miRNAs) could have caused species-specific changes in the expression levels of their target genes which in turn could have resulted in phenotypic variation between human and chimp.

Bioinformatic discovery of microRNA precursors from human ESTs and introns

BackgroundMicroRNAs (miRNAs) function in many physiological processes, and their discovery is beneficial for further studying their physiological functions. However, many of the miRNAs predicted from genomic sequences have not been experimentally validated to be authentic expressed RNA transcripts, thereby decreasing the reliability of miRNA discovery. To overcome this problem, we examined expressed transcripts – ESTs and intronic sequences – to identify novel miRNAs as well as their target genes.ResultsTo facilitate our approach, we developed our scanning method using criteria based on the features of 207 known human pre-miRNAs to discriminate miRNAs from random sequences. We identified 208 candidate hairpins in human ESTs and human reference gene intronic sequences, 52 of which are known pre-miRNAs. The discovery pipeline performance was further assessed using 130 newly updated pre-miRNA and randomly selected sequences. We achieved sensitivity of 85% (110/130) and overall specificity of 49.7% using this method. Because miRNAs are evolutionarily conserved regulators of gene expression, it is expected that their host genes and target genes should have respective phylogenetic orthologs. Our results confirmed that, in certain mammals, the host genes carrying the same miRNAs are orthologs, as previously reported. Moreover, this observation is also the case for some of the miRNA target genes.ConclusionWe have predicted 208 human pre-miRNA candidates and over 10,000 putative human target genes. Using sequence information from ESTs and introns ensures that the predicted pre-miRNA candidates are expressed and the combined expression transcription information from ESTs and introns makes our prediction results more decisive with regard to expressed pre-miRNAs.

Polymorphisms in human pre-miRNAs

MicroRNAs constitute a growing class of non-coding RNAs that are thought to regulate gene expression via translational repression. MicroRNAs are initially transcribed as several hundred-nucleotide pri-miRNAs and are then processed to ∼60-nucleotide hairpin pre-miRNAs. We hypothesized that polymorphisms in both pre-miRNA and mature microRNA modify various biological processes by influencing the processing and/or target selection of microRNAs. In the present study, we sequenced 173 human pre-miRNA genome regions in 96 subjects and found 10 polymorphisms in the 10 pre-miRNA hairpin regions. Although most of these polymorphisms seem to have no effect on microRNA processing, we identified a C to A polymorphism in the mature miR-30c-2 sequence. This polymorphism may alter target selection and thus exert profound biological effects. To the best of our knowledge, this is the first report of polymorphisms in pre-miRNAs.

Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs.

MicroRNAs (miRNAs) are initially expressed as long transcripts that are processed in the nucleus to yield approximately 65-nucleotide (nt) RNA hairpin intermediates, termed pre-miRNAs, that are exported to the cytoplasm for additional processing to yield mature, approximately 22-nt miRNAs. Here, we demonstrate that human pre-miRNA nuclear export, and miRNA function, are dependent on Exportin-5. Exportin-5 can bind pre-miRNAs specifically in vitro, but only in the presence of the Ran-GTP cofactor. Short hairpin RNAs, artificial pre-miRNA analogs used to express small interfering RNAs, also depend on Exportin-5 for nuclear export. Together, these findings define an additional cellular cofactor required for miRNA biogenesis and function.