Current tools for the identification of miRNA genes and their targets

The discovery of microRNAs (miRNAs), almost 10 years ago, changed dramatically our perspective on eukaryotic gene expression regulation. However, the broad and important functions of these regulators are only now becoming apparent. The expansion of our catalogue of miRNA genes and the identification of the genes they regulate owe much to the development of sophisticated computational tools that have helped either to focus or interpret experimental assays. In this article, we review the methods for miRNA gene finding and target identification that have been proposed in the last few years. We identify some problems that current approaches have not yet been able to overcome and we offer some perspectives on the next generation of computational methods

Systematic computational analysis of potential RNA interference regulation in Toxoplasma gondii

Thesis (Master)--Izmir Institute of Technology, Molecular Biology and Genetics, Izmir, 2009Includes bibliographical references (leaves: 58-73)Text in English; Abstract: Turkish and Englishx, 79 leavesRNA-mediated silencing was first described in plants and became famous by studies in Caenorhabditis elegans. RNA interference (RNAi) is the mechanism through which an RNA interferes with the production of other RNAs in a sequence specific manner. MiRNAs are a type of RNA which originate from the genome with their active form being ss-RNAs of 21-23 nucleotides in length. They are being transcribed as primiRNAs then processed in the nucleus by Drosha to pre-miRNAs with a stem-loop structure and 70 nucleotides in length. This stem-loop containing pre-miRNAs is then processed in the cytoplasm to ds-RNA one strand of which will serve as interfering RNA. Toxoplasma gondii is a species of parasitic protozoa which causes several diseases. T.gondii emerges as a good candidate for computational efforts with its small genome size, publicly available genome files and extensive information about its gene structure, either based on experimental data or the prediction with several gene finders in parallel. Therefore, it seems important to establish the regulatory network composed of RNAi which may be beneficial for the Toxoplasma community. Within this context the pool of possible stem-loop constitutive transcripts are produced, further analysis of this pool for desired 2D structure is integrated and mapping of possible RNAi regulation to T.gondii.s genome is established. In connection with computational assessment and mapping, the derived information is provided as a database for quick lookup using a convenient web interface for experimental studies of RNAi regulation in Toxoplasma, thus reduce time and money costs in such studies

MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans

Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of gene expression. Identification of miRNAs is an important requirement for understanding the mechanisms of post-transcriptional regulation. Hundreds of miRNAs have been identified by direct cloning and computational approaches in several species. However, there are still many miRNAs that remain to be identified due to lack of either sequence features or robust algorithms to efficiently identify them. Results: We have evaluated features valuable for pre-miRNA prediction, such as the local secondary structure differences of the stem region of miRNA and non-miRNA hairpins. We have also established correlations between different types of mutations and the secondary structures of pre-miRNAs. Utilizing these features and combining some improvements of the current premiRNA prediction methods, we implemented a computational learning method SVM (support vector machine) to build a high throughput and good performance computational pre-miRNA prediction tool called MiRFinder. The tool was designed for genome-wise, pair-wise sequences from two related species. The method built into the tool consisted of two major steps: 1) genome wide search for hairpin candidates and 2) exclusion of the non-robust structures based on analysis of 18 parameters by the SVM method. Results from applying the tool for chicken/human and D. melanogaster/D. pseudoobscura pair-wise genome alignments showed that the tool can be used for genome wide pre-miRNA predictions. Conclusion: The MiRFinder can be a good alternative to current miRNA discovery software. This tool is available at http://www.bioinformatics.org/mirfinder/

Protein interactions and complexes in human microRNA biogenesis and function

Encoded in the genome of most eukaryotes, microRNAs (miRNAs) have been proposed to regulate specifically up to 90% of human genes through a process known as miRNA-guided RNA silencing. The aim of this review is to present this process as the integration of a succession of specialized molecular machines exerting well defined functions. The nuclear microprocessor complex initially recognizes and processes its primary miRNA substrate into a miRNA precursor (pre-miRNA). This structure is then exported to the cytoplasm by the Exportin-5 complex where it is presented to the pre-miRNA processing complex. Following pre-miRNA conversion into a miRNA:miRNA* duplex, this complex is assembled into a miRNA-containing ribonucleoprotein (miRNP) complex, after which the miRNA strand is selected. The degree of complementarity of the miRNA for its messenger RNA (mRNA) target guides the recruitment of the miRNP complex. Initially repressing its translation, the miRNP-silenced mRNA is directed to the P-bodies, where the mRNA is either released from its inhibition upon a cellular signal and/or actively degraded. The potency and specificity of miRNA biogenesis and function rely on the distinct protein x protein, protein x RNA and RNA:RNA interactions found in different complexes, each of which fulfill a specific function in a well orchestrated process

Crispr/Cas9 editing reveals novel mechanisms of clustered microRNA regulation and function

MicroRNAs (miRNAs) are important regulators of diverse physiological and pathophysiological processes. MiRNA families and clusters are two key features in miRNA biology. Here we explore the use of CRISPR/Cas9 as a powerful tool to delineate the function and regulation of miRNA families and clusters. We focused on four miRNA clusters composed of miRNA members of the same family, homoclusters or different families, hetero-clusters. Our results highlight different regulatory mechanisms in miRNA cluster expression. In the case of the miR-497~195 cluster, editing of miR-195 led to a significant decrease in the expression of the other miRNA in the cluster, miR-497a. Although no gene editing was detected in the miR-497a genomic locus, computational simulation revealed alteration in the three dimensional structure of the pri miR-497~195 that may affect its processing. In cluster miR- 143~145 our results imply a feed-forward regulation, although structural changes cannot be ruled out. Furthermore, in the miR-17~92 and miR-106~25 clusters no interdependency in miRNA expression was observed. Our findings suggest that CRISPR/Cas9 is a powerful gene editing tool that can uncover novel mechanisms of clustered miRNA regulation and function

Crispr/Cas9 editing reveals novel mechanisms of clustered microRNA regulation and function

MicroRNAs (miRNAs) are important regulators of diverse physiological and pathophysiological processes. MiRNA families and clusters are two key features in miRNA biology. Here we explore the use of CRISPR/Cas9 as a powerful tool to delineate the function and regulation of miRNA families and clusters. We focused on four miRNA clusters composed of miRNA members of the same family, homoclusters or different families, hetero-clusters. Our results highlight different regulatory mechanisms in miRNA cluster expression. In the case of the miR-497~195 cluster, editing of miR-195 led to a significant decrease in the expression of the other miRNA in the cluster, miR-497a. Although no gene editing was detected in the miR-497a genomic locus, computational simulation revealed alteration in the three dimensional structure of the pri miR-497~195 that may affect its processing. In cluster miR- 143~145 our results imply a feed-forward regulation, although structural changes cannot be ruled out. Furthermore, in the miR-17~92 and miR-106~25 clusters no interdependency in miRNA expression was observed. Our findings suggest that CRISPR/Cas9 is a powerful gene editing tool that can uncover novel mechanisms of clustered miRNA regulation and function

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs

Complexity of murine cardiomyocyte miRNA biogenesis, sequence variant expression and function

microRNAs (miRNAs) are critical to heart development and disease. Emerging research indicates that regulated precursor processing can give rise to an unexpected diversity of miRNA variants. We subjected small RNA from murine HL-1 cardiomyocyte cells to next generation sequencing to investigate the relevance of such diversity to cardiac biology. ∼40 million tags were mapped to known miRNA hairpin sequences as deposited in miRBase version 16, calling 403 generic miRNAs as appreciably expressed. Hairpin arm bias broadly agreed with miRBase annotation, although 44 miR* were unexpectedly abundant (>20% of tags); conversely, 33 -5p/-3p annotated hairpins were asymmetrically expressed. Overall, variability was infrequent at the 5' start but common at the 3' end of miRNAs (5.2% and 52.3% of tags, respectively). Nevertheless, 105 miRNAs showed marked 5' isomiR expression (>20% of tags). Among these was miR-133a, a miRNA with important cardiac functions, and we demonstrated differential mRNA targeting by two of its prevalent 5' isomiRs. Analyses of miRNA termini and base-pairing patterns around Drosha and Dicer cleavage regions confirmed the known bias towards uridine at the 5' most position of miRNAs, as well as supporting the thermodynamic asymmetry rule for miRNA strand selection and a role for local structural distortions in fine tuning miRNA processing. We further recorded appreciable expression of 5 novel miR*, 38 extreme variants and 8 antisense miRNAs. Analysis of genome-mapped tags revealed 147 novel candidate miRNAs. In summary, we revealed pronounced sequence diversity among cardiomyocyte miRNAs, knowledge of which will underpin future research into the mechanisms involved in miRNA biogenesis and, importantly, cardiac function, disease and therapy.This work was supported by by the Victor Chang Cardiac Research Institute and grants 573726, 573731 and 514904 from the National Health & Medical Research Council awarded to TP

MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are a family of ~22 nt small RNAs that can regulate gene expression at the post-transcriptional level. Identification of these molecules and their targets can aid understanding of regulatory processes. Recently, HTS has become a common identification method but there are two major limitations associated with the technique. Firstly, the method has low efficiency, with typically less than 1 in 10,000 sequences representing miRNA reads and secondly the method preferentially targets highly expressed miRNAs. If sequences are available, computational methods can provide a screening step to investigate the value of an HTS study and aid interpretation of results. However, current methods can only predict miRNAs for short fragments and have usually been trained against small datasets which don't always reflect the diversity of these molecules.</p> <p>Results</p> <p>We have developed a software tool, miRPara, that predicts most probable mature miRNA coding regions from genome scale sequences in a species specific manner. We classified sequences from miRBase into animal, plant and overall categories and used a support vector machine to train three models based on an initial set of 77 parameters related to the physical properties of the pre-miRNA and its miRNAs. By applying parameter filtering we found a subset of ~25 parameters produced higher prediction ability compared to the full set. Our software achieves an accuracy of up to 80% against experimentally verified mature miRNAs, making it one of the most accurate methods available.</p> <p>Conclusions</p> <p>miRPara is an effective tool for locating miRNAs coding regions in genome sequences and can be used as a screening step prior to HTS experiments. It is available at <url>http://www.whiov.ac.cn/bioinformatics/mirpara</url></p