In silico identification of conserved microRNAs and their target transcripts from expressed sequence tags of three earthworm species

MicroRNAs are a recently identified class of small regulatory RNAs that target more than 30% protein-coding genes. Elevating evidence shows that miRNAs play a critical role in many biological processes, including developmental timing, tissue differentiation, and response to chemical exposure. In this study, we applied a computational approach to analyze expressed sequence tags, and identified 32 miRNAs belonging to 22 miRNA families, in three earthworm species Eisenia fetida, Eisenia andrei, and Lumbricus rubellus. These newly identified earthworm miRNAs possess a difference of 2-4 nucleotides from their homologous counterparts in Caenorhabditis elegans. They also share similar features with other known animal miRNAs, for instance, the nucleotide U being dominant in both mature and pre-miRNA sequences, particularly in the first position of mature miRNA sequences at the 5' end. The newly identified earthworm miRNAs putatively regulate mRNA genes that are involved in many important biological processes and pathways related to development, growth, locomotion, and reproduction as well as response to stresses, particularly oxidative stress. Future efforts will focus on experimental validation of their presence and target mRNA genes to further elucidate their biological functions in earthworms.     

Identification of evolutionarily conserved Momordica charantia microRNAs using computational approach and its utility in phylogeny analysis

Momordica charantia (bitter gourd, bitter melon) is a monoecious Cucurbitaceae with anti-oxidant, anti-microbial, anti-viral and anti-diabetic potential. Molecular studies on this economically valuable plant are very essential to understand its phylogeny and evolution. MicroRNAs (miRNAs) are conserved, small, non-coding RNA with ability to regulate gene expression by bind the 3′ UTR region of target mRNA and are evolved at different rates in different plant species. In this study we have utilized homology based computational approach and identified 27 mature miRNAs for the first time from this bio-medically important plant. The phylogenetic tree developed from binary data derived from the data on presence/absence of the identified miRNAs were noticed to be uncertain and biased. Most of the identified miRNAs were highly conserved among the plant species and sequence based phylogeny analysis of miRNAs resolved the above difficulties in phylogeny approach using miRNA. Predicted gene targets of the identified miRNAs revealed their importance in regulation of plant developmental process. Reported miRNAs held sequence conservation in mature miRNAs and the detailed phylogeny analysis of pre-miRNA sequences revealed genus specific segregation of clusters.     

Computational identification of 48 potato microRNAs and their targets

MicroRNAs (miRNAs) are a new family of small RNA molecules known in animals and plants, whose conservation among species suggests that they bear conserved biological functions. So far, little is known about miRNA in Solanum tuberosum species. Using previously known miRNAs from Arabidopsis, rice and other plant species against expressed sequence tags (ESTs), genomic survey sequence (GSS) and nucleotide databases, we identified 48 potential miRNAs in S. tuberosum. These potato miRNAs may regulate 186 potential targets, which are involved in floral, leaf, root, and stem development, signal transduction, metabolism pathways, and stress responses. To validate the prediction of miRNAs in potato, we performed a RT-PCR analysis and found that potato miRNAs have diverse expression patterns during development.     

Exosome based miRNA delivery strategy for disease treatment

miRNA, which is a common non-coding RNA, can target various m RNAs to regulate their physiological activities. Therefore, mi RNAs play an important role in various physiological and pathological processes,and so they have been proposed as a powerful tool to treat different diseases efficiently. However, the characteristic of mi RNA degradation in vivo limits its further clinical application. Exosomes have the advantage of crossing the biological barrier and achieving long-distance communication ...     

Predicting microRNA biological functions based on genes discriminant analysis

Although thousands of microRNAs (miRNAs) have been identified in recent experimental efforts, it remains a challenge to explore their specific biological functions through molecular biological experiments. Since those members from same family share same or similar biological functions, classifying new miRNAs into their corresponding families will be helpful for their further functional analysis. In this study, we initially built a vector space by characterizing the features from miRNA sequences and structures according to their miRBase family organizations. Then we further assigned miRNAs into its specific miRNA families by developing a novel genes discriminant analysis (GDA) approach in this study. As can be seen from the results of new families from GDA, in each of these new families, there was a high degree of similarity among all members of nucleotide sequences. At the same time, we employed 10-fold cross-validation machine learning to achieve the accuracy rates of 68.68%, 80.74%, and 83.65% respectively for the original miRNA families with no less than two, three, and four members. The encouraging results suggested that the proposed GDA could not only provide a support in identifying new miRNAs’ families, but also contributing to predicting their biological functions.     

Enhanced extraction efficiency of miRNA from cells by addition of Triton X-100

The determination of microRNA (miRNA) levels in biomaterials has become important for understanding their biological functions and for the diagnosis of various diseases. An effective extraction method is needed for maximizing the recovery of miRNAs from cells, while minimizing RNA degradation during the extraction because miRNAs present only approximately 0.01 % of total RNA. In this study, we used Triton X-100 (TX-100) to improve the extraction efficiency of miRNAs with TRIzol® reagent, which is a commonly used commercial microRNA isolation kit. The concentration of TX-100 and the incubation time after the addition of TX-100 were optimized to maximize the extraction efficiency. The extraction recovery by a combination of TX-100 and TRIzol® reagent was approximately 1.9-fold greater than that by the TRIzol® reagent alone. We have established a very effective extraction method for the extraction of low-abundance miRNAs in biological samples for the determination of miRNA levels in biomaterials.     

Analysis of the NCI-60 dataset for cancer-related microRNA and mRNA using expression profiles

BackgroundRecent studies have indicated that microRNA (miRNA) may play an oncogenic or tumor suppressor role in human cancer. To study the regulatory role of miRNAs in tumorigenesis, an integrated platform has been set up to provide a user friendly interface for query. The main advantage of the present platform is that all the miRNA target genes’ information and disease records are drawn from experimentally verified or high confidence records.ResultsMiRNA target gene results are annotated with reference to the disease gene as well as the pathway database. The correlation strength between miRNA and target gene expression profile is quantified by computing the correlation coefficient using the NCI-60 expression profiling data. Comprehensive analysis of the NCI-60 data found that the cumulative percentage of negative correlation coefficients for cleavage regulation is slightly higher than its positive counterpart; which indicated that the mRNA degradation mechanism is slightly dominant. In addition, the RNAHybrid and TargetScans scores are computed which potentially served as quantitative estimators for miRNA–mRNA binding events.Three scores are defined for each miRNA–mRNA pair, which are based on the disease gene and pathway information. These three scores allow user to sort out high confidence cancer-related miRNA–mRNA pairs.Statistical tests were applied to investigate the relations of three chromosomal features, i.e., CpG island, fragile site, and miRNA cluster, with cancer-related miRNAs. A web-based interface has been set up for query, which can be accessed at: http://ppi.bioinfo.asia.edu.tw/mirna_target/ConclusionsThe main advantage of the present platform on miRNA–mRNA targeting information is that all the target genes’ information and disease records are experimentally verified. Although this may limit the number of miRNA–mRNA relationships, the results provided here are more solid and have fewer false positive events. Certain novel cancer-related miRNA–mRNA pairs are identified and confirmed in the literature. Fisher's exact test suggests that CpG island and fragile site associated miRNAs tend to associate with cancer formation. In summary, the present platform provides an easy means of investigating cancer-related miRNAs.     

Computational classification of microRNAs in next-generation sequencing data

MicroRNAs (miRNAs) have been shown to play an important regulatory role in plants and animals. A large number of known and novel miRNAs can be uncovered from next-generation sequencing (NGS) experiments that measure the complement of a given cell’s small RNAs under various conditions. Here, we present an algorithm based on radial basis functions for the identification of potential miRNA precursor structures. Computationally assessing features of known human miRNA precursors, such as structural linearity, normalized minimum folding energy, and nucleotide pairing frequencies, this model robustly differentiates between miRNAs and other types of non-coding RNAs. Without relying on cross species conservation, the method also identifies non-conserved precursors and achieves high sensitivity. The presented method can be used routinely for the identification of known and novel miRNAs present in NGS experiments.     

DNA methylation-regulated microRNA pathways in ovarian serous cystadenocarcinoma: A meta-analysis

Epigenetic regulation has been linked to the initiation and progression of cancer. Aberrant expression of microRNAs (miRNAs) is one such mechanism that can activate or silence oncogenes (OCGs) and tumor suppressor genes (TSGs) in cells. A growing number of studies suggest that miRNA expression can be regulated by methylation modification, thus triggering cancer development. However, there is no comprehensive in silico study concerning miRNA regulation by direct DNA methylation in cancer. Ovarian serous cystadenocarcinoma (OSC) was therefore chosen as a tumor model for the present work.Twelve batches of OSC data, with at least 35 patient samples in each batch, were obtained from The Cancer Genome Atlas (TCGA) database. The Spearman rank correlation coefficient (SRCC) was used to quantify the correlation between the CpG DNA methylation level and miRNA expression level. Meta-analysis was performed to reduce the effects of biological heterogeneity among different batches. MiRNA-target interactions were also inferred by computing SRCC and meta-analysis to assess the correlation between miRNA expression and cancer-associated gene expression and the interactions were further validated by a query against the miRTarBase database.A total of 26 potential epigenetic-regulated miRNA genes that can target OCGs or TSGs in OSC were found to show biological relevance between DNA methylation and miRNA gene expression. Furthermore, some of the identified DNA-methylated miRNA genes; for instance, the miR-200 family, were previously identified as epigenetic-regulated miRNAs and correlated with poor survival of ovarian cancer. We also found that several miRNA target genes, BTG3, NDN, HTRA3, CDC25A, and HMGA2 were also related to the poor outcomes in ovarian cancer.The present study proposed a systematic strategy to construct highly confident epigenetic-regulated miRNA pathways for OSC. The findings are validated and are in line with the literature. The inclusion of direct DNA methylated miRNA events may offer another layer of explanation that along with genetics can give a better understanding of the carcinogenesis process.     

Capillary electrophoresis methods for microRNAs assays: A review

MicroRNAs (miRNAs) are short noncoding RNAs that conduct important roles in many cellular processes such as development, proliferation, differentiation, and apoptosis. In particular, circulating miRNAs have been proposed as biomarkers for cancer, diabetes, cardiovascular disease, and other illnesses. Therefore, determination of miRNA expression levels in various biofluids is important for the investigation of biological processes in health and disease and for discovering their potential as new biomarkers and drug targets. Capillary electrophoresis (CE) is emerging as a useful analytical tool for analyzing miRNA because of its simple sample preparation steps and efficient resolution of a diverse size range of compounds. In particular, CE with laser-induced fluorescence detection is a promising and relatively rapidly developing tool with the potential to provide high sensitivity and specificity in the analysis of miRNAs. This paper covers a short overview of the recent developments and applications of CE systems in miRNA studies in biological and biomedical areas.     

Genome-wide computational identification of microRNAs and their targets in the deep-branching eukaryote Giardia lamblia

Using a combined computational program, we identified 50 potential microRNAs (miRNAs) in Giardia lamblia, one of the most primitive unicellular eukaryotes. These miRNAs are unique to G. lamblia and no homologues have been found in other organisms; miRNAs, currently known in other species, were not found in G. lamblia. This suggests that miRNA biogenesis and miRNA-mediated gene regulation pathway may evolve independently, especially in evolutionarily distant lineages. A majority (43) of the predicted miRNAs are located at one single locus; however, some miRNAs have two or more copies in the genome. Among the 58 miRNA genes, 28 are located in the intergenic regions whereas 30 are present in the anti-sense strands of the protein-coding sequences. Five predicted miRNAs are expressed in G. lamblia trophozoite cells evidenced by expressed sequence tags or RT-PCR. Thirty-seven identified miRNAs may target 50 protein-coding genes, including seven variant-specific surface proteins (VSPs). Our findings provide a clue that miRNA-mediated gene regulation may exist in the early stage of eukaryotic evolution, suggesting that it is an important regulation system ubiquitous in eukaryotes.     

An in-silico approach to study the possible interactions of miRNA between human and SARS-CoV2

BackgroundThe progressive SARS-CoV2 outbreaks worldwide have evoked global investigation. Despite the numerousin-silico approaches, the virus-host relationship remains a serious concern. MicroRNAs are the small non-coding RNAs that help in regulating gene profiling. The current study utilized miRNA prediction tools along with the PANTHER classification system to demonstrate association and sequence similarities shared between miRNAs of SARS-CoV2 and human host.MethodAn in-silico approach was carried out using Vmir analyzer to predict miRNAs from SARS-CoV2 viral genomes. Predicted miRNAs from SARS-CoV2 viral genomes were used for effective hybridization sequence identification along the nucleotide similarities with human miRNAs from miRbase database. Further, it was proceeded to analyze the gene ontology using miRDB with PANTHER classification.ResultBased on the prediction and analysis, we have identified 22 potential miRNAs from five genomes of SARS-CoV2 linked with 12 human miRNAs. Analysis of human miRNAs hsa-mir-1267, hsa-mir-1-3p, hsa-mir-5683 were found shared between all the five viral SARS-CoV2 miRNAs. Further, PANTHER classification analyzed the gene-ontology being carried by these associations showed that 44 genes were involved in biological functions that includes genes specific for signaling pathway, immune complex generation, enzyme binding with effective role in the virus-host relationship.ConclusionOur analysis concludes that the genes identified in this study can be effective in analyzing the virus-host interaction. It also provides a new direction to understand viral pathogenesis with a probable new way to link, that can be used to understand and relate the miRNAs of the virus to the host conditions.