miR-BAG: Bagging Based Identification of MicroRNA Precursors

Non-coding elements such as miRNAs play key regulatory roles in living systems. These ultra-short, ∼21 bp long, RNA molecules are derived from their hairpin precursors and usually participate in negative gene regulation by binding the target mRNAs. Discovering miRNA candidate regions across the genome has been a challenging problem. Most of the existing tools work reliably only for limited datasets. Here, we have presented a novel reliable approach, miR-BAG, developed to identify miRNA candidate regions in genomes by scanning sequences as well as by using next generation sequencing (NGS) data. miR-BAG utilizes a bootstrap aggregation based machine learning approach, successfully creating an ensemble of complementary learners to attain high accuracy while balancing sensitivity and specificity. miR-BAG was developed for wide range of species and tested extensively for performance over a wide range of experimentally validated data. Consideration of position-specific variation of triplet structural profiles and mature miRNA anchored structural profiles had a positive impact on performance. miR-BAG’s performance was found consistent and the accuracy level was observed to be >90% for most of the species considered in the present study. In a detailed comparative analysis, miR-BAG performed better than six existing tools. Using miR-BAG NGS module, we identified a total of 22 novel miRNA candidate regions in cow genome in addition to a total of 42 cow specific miRNA regions. In practice, discovery of miRNA regions in a genome demands high-throughput data analysis, requiring large amount of processing. Considering this, miR-BAG has been developed in multi-threaded parallel architecture as a web server as well as a user friendly GUI standalone version.     

Global profiling of miRNAs and the hairpin precursors: insights into miRNA processing and novel miRNA discovery

MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5′ tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences.     

Discovery of novel microRNAs in rat kidney using next generation sequencing and microarray validation

MicroRNAs (miRNAs) are small non-coding RNAs that regulate a variety of biological processes. The latest version of the miRBase database (Release 18) includes 1,157 mouse and 680 rat mature miRNAs. Only one new rat mature miRNA was added to the rat miRNA database from version 16 to version 18 of miRBase, suggesting that many rat miRNAs remain to be discovered. Given the importance of rat as a model organism, discovery of the completed set of rat miRNAs is necessary for understanding rat miRNA regulation. In this study, next generation sequencing (NGS), microarray analysis and bioinformatics technologies were applied to discover novel miRNAs in rat kidneys. MiRanalyzer was utilized to analyze the sequences of the small RNAs generated from NGS analysis of rat kidney samples. Hundreds of novel miRNA candidates were examined according to the mappings of their reads to the rat genome, presence of sequences that can form a miRNA hairpin structure around the mapped locations, Dicer cleavage patterns, and the levels of their expression determined by both NGS and microarray analyses. Nine novel rat hairpin precursor miRNAs (pre-miRNA) were discovered with high confidence. Five of the novel pre-miRNAs are also reported in other species while four of them are rat specific. In summary, 9 novel pre-miRNAs (14 novel mature miRNAs) were identified via combination of NGS, microarray and bioinformatics high-throughput technologies.     

miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, ??miRNA primer designer?? to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.     

Performance comparison and evaluation of software tools for microRNA deep-sequencing data analysis

With the development of next-generation sequencing (NGS) techniques, many software tools have emerged for the discovery of novel microRNAs (miRNAs) and for analyzing the miRNAs expression profiles. An overall evaluation of these diverse software tools is lacking. In this study, we evaluated eight software tools based on their common feature and key algorithms. Three deep-sequencing data sets were collected from different species and used to assess the computational time, sensitivity and accuracy of detecting known miRNAs as well as their capacity for predicting novel miRNAs. Our results provide useful information for researchers to facilitate their selection of the optimal software tools for miRNA analysis depending on their specific requirements, i.e. novel miRNAs discovery or miRNA expression profile analysis of sequencing data sets.     

Identification of MicroRNAs in Helicoverpa armigera and Spodoptera litura Based on Deep Sequencing and Homology Analysis

The current identification of microRNAs (miRNAs) in insects is largely dependent on genome sequences. However, the lack of available genome sequences inhibits the identification of miRNAs in various insect species. In this study, we used a miRNA database of the silkworm Bombyx mori as a reference to identify miRNAs in Helicoverpa armigera and Spodoptera litura using deep sequencing and homology analysis. Because all three species belong to the Lepidoptera, the experiment produced reliable results. Our study identified 97 and 91 conserved miRNAs in H. armigera and S. litura, respectively. Using the genome of B. mori and BAC sequences of H. armigera as references, 1 novel miRNA and 8 novel miRNA candidates were identified in H. armigera, and 4 novel miRNA candidates were identified in S. litura. An evolutionary analysis revealed that most of the identified miRNAs were insect-specific, and more than 20 miRNAs were Lepidoptera-specific. The investigation of the expression patterns of miR-2a, miR-34, miR-2796-3p and miR-11 revealed their potential roles in insect development. miRNA target prediction revealed that conserved miRNA target sites exist in various genes in the 3 species. Conserved miRNA target sites for the Hsp90 gene among the 3 species were validated in the mammalian 293T cell line using a dual-luciferase reporter assay. Our study provides a new approach with which to identify miRNAs in insects lacking genome information and contributes to the functional analysis of insect miRNAs.     

Accuracy of MicroRNA Discovery Pipelines in Non-Model Organisms Using Closely Related Species Genomes

Mapping small reads to genome reference is an essential and more common approach to identify microRNAs (miRNAs) in an organism. Using closely related species genomes as proxy references can facilitate miRNA expression studies in non-model species that their genomes are not available. However, the level of error this introduces is mostly unknown, as this is the result of evolutionary distance between the proxy reference and the species of interest. To evaluate the accuracy of miRNA discovery pipelines in non-model organisms, small RNA library data from a mosquito, Aedes aegypti, were mapped to three well annotated insect genomes as proxy references using miRanalyzer with two strict and loose mapping criteria. In addition, another web-based miRNA discovery pipeline (DSAP) was used as a control for program performance. Using miRanalyzer, more than 80% reduction was observed in the number of mapped reads using strict criterion when proxy genome references were used; however, only 20% reduction was recorded for mapped reads to other species known mature miRNA datasets. Except a few changes in ranking, mapping criteria did not make any significant differences in the profile of the most abundant miRNAs in A. aegypti when its original or a proxy genome was used as reference. However, more variation was observed in miRNA ranking profile when DSAP was used as analysing tool. Overall, the results also suggested that using a proxy reference did not change the most abundant miRNAs’ differential expression profiles when infected or non-infected libraries were compared. However, usage of a proxy reference could provide about 67% of the original outcome from more extremely up- or down-regulated miRNA profiles. Although using closely related species genome incurred some losses in the number of miRNAs, the most abundant miRNAs along with their differential expression profile would be acceptable based on the sensitivity level of each project.     

Implementation of a de novo genome-wide computational approach for updating Brachypodium miRNAs

Plant microRNAs (miRNAs) are single-stranded 20-22 nt small RNAs (sRNA) that are produced from their own genes. We have developed a de novo genome-wide approach for the computational identification of novel plant miRNAs based on the integration of the complete genome sequence with sRNA libraries. It comprises three modules - the clustering module identifies genomic regions that have two closely-located unidirectional sRNA clusters, the mirplan module explores the secondary structure of the genomic regions, and the duplex module predicts miRNA/miRNA* duplexes. We applied our approach to the Brachypodium genome and publicly available sRNA libraries and predicted 102 miRNAs. Our results extend the list of known miRNAs with 58 novel miRNAs and define the genomic loci of all predicted miRNAs. Because this approach considers specific features of plant miRNAs, it can be employed for the analysis of the genome and sRNA libraries generated for plant species to achieve systematic miRNA discovery.     

Next-Generation Sequencing Analysis of MiRNA Expression in Control and FSHD Myogenesis

Emerging evidence has demonstrated that miRNA sequences can regulate skeletal myogenesis by controlling the process of myoblast proliferation and differentiation. However, at present a deep analysis of miRNA expression in control and FSHD myoblasts during differentiation has not yet been derived. To close this gap, we used a next-generation sequencing (NGS) approach applied to in vitro myogenesis. Furthermore, to minimize sample genetic heterogeneity and muscle-type specific patterns of gene expression, miRNA profiling from NGS data was filtered with FC≥4 (log₂FC≥2) and p-value<0.05, and its validation was derived by qRT-PCR on myoblasts from seven muscle districts. In particular, control myogenesis showed the modulation of 38 miRNAs, the majority of which (34 out 38) were up-regulated, including myomiRs (miR-1, -133a, -133b and -206). Approximately one third of the modulated miRNAs were not previously reported to be involved in muscle differentiation, and interestingly some of these (i.e. miR-874, -1290, -95 and -146a) were previously shown to regulate cell proliferation and differentiation. FSHD myogenesis evidenced a reduced number of modulated miRNAs than healthy muscle cells. The two processes shared nine miRNAs, including myomiRs, although with FC values lower in FSHD than in control cells. In addition, FSHD cells showed the modulation of six miRNAs (miR-1268, -1268b, -1908, 4258, -4508- and -4516) not evidenced in control cells and that therefore could be considered FSHD-specific, likewise three novel miRNAs that seem to be specifically expressed in FSHD myotubes. These data further clarify the impact of miRNA regulation during control myogenesis and strongly suggest that a complex dysregulation of miRNA expression characterizes FSHD, impairing two important features of myogenesis: cell cycle and muscle development. The derived miRNA profiling could represent a novel molecular signature for FSHD that includes diagnostic biomarkers and possibly therapeutic targets.     

MapMi: automated mapping of microRNA loci

Background  

A large effort to discover microRNAs (miRNAs) has been under way. Currently miRBase is their primary repository, providing annotations of primary sequences, precursors and probable genomic loci. In many cases miRNAs are identical or very similar between related (or in some cases more distant) species. However, miRBase focuses on those species for which miRNAs have been directly confirmed. Secondly, specific miRNAs or their loci are sometimes not annotated even in well-covered species. We sought to address this problem by developing a computational system for automated mapping of miRNAs within and across species. Given the sequence of a known miRNA in one species it is relatively straightforward to determine likely loci of that miRNA in other species. Our primary goal is not the discovery of novel miRNAs but the mapping of validated miRNAs in one species to their most likely orthologues in other species.     

Computational identification of microRNA gene loci and precursor microRNA sequences in CHO cell lines

MicroRNAs (miRNAs) have recently entered Chinese hamster ovary (CHO) cell culture technology, due to their severe impact on the regulation of cellular phenotypes. Applications of miRNAs that are envisioned range from biomarkers of favorable phenotypes to cell engineering targets. These applications, however, require a profound knowledge of miRNA sequences and their genomic organization, which exceeds the currently available information of ~400 conserved mature CHO miRNA sequences. Based on these recently published sequences and two independent CHO-K1 genome assemblies, this publication describes the computational identification of CHO miRNA genomic loci. Using BLAST alignment, 415 previously reported CHO miRNAs were mapped to the reference genomes, and subsequently assigned to a distinct genomic miRNA locus. Sequences of the respective precursor-miRNAs were extracted from both reference genomes, folded in silico to verify correct structures and cross-compared. In the end, 212 genomic loci and pre-miRNA sequences representing 319 expressed mature miRNAs (approximately 50% of miRNAs represented matching pairs of 5' and 3' miRNAs) were submitted to the miRBase miRNA repository. As a proof-of-principle for the usability of the published genomic loci, four likely polycistronic miRNA cluster were chosen for PCR amplification using CHO-K1 and DHFR (-) genomic DNA. Overall, these data on the genomic context of miRNA expression in CHO will simplify the development of tools employing stable overexpression or deletion of miRNAs, allow the identification of miRNA promoters and improve detection methods such as microarrays.     

The impact of age,biogenesis, and genomic clustering on Drosophila microRNA evolution

The molecular evolutionary signatures of miRNAs inform our understanding of their emergence, biogenesis, and function. The known signatures of miRNA evolution have derived mostly from the analysis of deeply conserved, canonical loci. In this study, we examine the impact of age, biogenesis pathway, and genomic arrangement on the evolutionary properties of Drosophila miRNAs. Crucial to the accuracy of our results was our curation of high-quality miRNA alignments, which included nearly 150 corrections to ortholog calls and nucleotide sequences of the global 12-way Drosophilid alignments currently available. Using these data, we studied primary sequence conservation, normalized free-energy values, and types of structure-preserving substitutions. We expand upon common miRNA evolutionary patterns that reflect fundamental features of miRNAs that are under functional selection. We observe that melanogaster-subgroup-specific miRNAs, although recently emerged and rapidly evolving, nonetheless exhibit evolutionary signatures that are similar to well-conserved miRNAs and distinct from other structured noncoding RNAs and bulk conserved non-miRNA hairpins. This provides evidence that even young miRNAs may be selected for regulatory activities. More strikingly, we observe that mirtrons and clustered miRNAs both exhibit distinct evolutionary properties relative to solo, well-conserved miRNAs, even after controlling for sequence depth. These studies highlight the previously unappreciated impact of biogenesis strategy and genomic location on the evolutionary dynamics of miRNAs, and affirm that miRNAs do not evolve as a unitary class.     

Origin and evolution of human microRNAs from transposable elements

We sought to evaluate the extent of the contribution of transposable elements (TEs) to human microRNA (miRNA) genes along with the evolutionary dynamics of TE-derived human miRNAs. We found 55 experimentally characterized human miRNA genes that are derived from TEs, and these TE-derived miRNAs have the potential to regulate thousands of human genes. Sequence comparisons revealed that TE-derived human miRNAs are less conserved, on average, than non-TE-derived miRNAs. However, there are 18 TE-derived miRNAs that are relatively conserved, and 14 of these are related to the ancient L2 and MIR families. Comparison of miRNA vs. mRNA expression patterns for TE-derived miRNAs and their putative target genes showed numerous cases of anti-correlated expression that are consistent with regulation via mRNA degradation. In addition to the known human miRNAs that we show to be derived from TE sequences, we predict an additional 85 novel TE-derived miRNA genes. TE sequences are typically disregarded in genomic surveys for miRNA genes and target sites; this is a mistake. Our results indicate that TEs provide a natural mechanism for the origination miRNAs that can contribute to regulatory divergence between species as well as a rich source for the discovery of as yet unknown miRNA genes.