Prediction of both conserved and nonconserved microRNA targets in animals

MOTIVATION: MicroRNAs (miRNAs) are involved in many diverse biological processes and they may potentially regulate the functions of thousands of genes. However, one major issue in miRNA studies is the lack of bioinformatics programs to accurately predict miRNA targets. Animal miRNAs have limited sequence complementarity to their gene targets, which makes it challenging to build target prediction models with high specificity. RESULTS: Here we present a new miRNA target prediction program based on support vector machines (SVMs) and a large microarray training dataset. By systematically analyzing public microarray data, we have identified statistically significant features that are important to target downregulation. Heterogeneous prediction features have been non-linearly integrated in an SVM machine learning framework for the training of our target prediction model, MirTarget2. About half of the predicted miRNA target sites in human are not conserved in other organisms. Our prediction algorithm has been validated with independent experimental data for its improved performance on predicting a large number of miRNA down-regulated gene targets. AVAILABILITY: All the predicted targets were imported into an online database miRDB, which is freely accessible at http://mirdb.org.     

Computational approaches for microRNA studies: a review

MicroRNAs (miRNAs) are one class of tiny, endogenous RNAs that can regulate messenger RNA (mRNA) expression by targeting homologous sequences in mRNAs. Their aberrant expressions have been observed in many cancers and several miRNAs have been convincingly shown to play important roles in carcinogenesis. Since the discovery of this small regulator, computational methods have been indispensable tools in miRNA gene finding and functional studies. In this review we first briefly outline the biological findings of miRNA genes, such as genomic feature, biogenesis, gene structure, and functional mechanism. We then discuss in detail the three main aspects of miRNA computational studies: miRNA gene finding, miRNA target prediction, and regulation of miRNA genes. Finally, we provide perspectives on some emerging issues, including combinatorial regulation by miRNAs and functional binding sites beyond the 3′-untranslated region (3′UTR) of target mRNAs. Available online resources for miRNA computational studies are also provided.     

miRTour: Plant miRNA and target prediction tool

MicroRNAs (miRNAs) are important negative regulators of gene expression in plant and animals, which are endogenously produced from their own genes. Computational comparative approach based on evolutionary conservation of mature miRNAs has revealed a number of orthologs of known miRNAs in different plant species. The homology-based plant miRNA discovery, followed by target prediction, comprises several steps, which have been done so far manually. Here, we present the bioinformatics pipeline miRTour which automates all the steps of miRNA similarity search, miRNA precursor selection, target prediction and annotation, each of them performed with the same set of input sequences. AVAILABILITY: The database is available for free at http://bio2server.bioinfo.uni-plovdiv.bg/miRTour/     

Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA

MicroRNAs (miRNAs) are important regulators of gene expression. The large-scale detection and profiling of miRNAs have been accelerated with the development of high-throughput small RNA sequencing (sRNA-Seq) techniques and bioinformatics tools. However, generating high-quality comprehensive miRNA annotations remains challenging due to the intrinsic complexity of sRNA-Seq data and inherent limitations of existing miRNA prediction tools. Here, we present iwa-miRNA, a Galaxy-based framework that can facilitate miRNA annotation in plant species by combining computational analysis and manual curation. iwa-miRNA is specifically designed to generate a comprehensive list of miRNA candidates, bridging the gap between already annotated miRNAs provided by public miRNA databases and new predictions from sRNA-Seq datasets. It can also assist users in selecting promising miRNA candidates in an interactive mode, contributing to the accessibility and reproducibility of genome-wide miRNA annotation. iwa-miRNA is user-friendly and can be easily deployed as a web application for researchers without programming experience. With flexible, interactive, and easy-to-use features, iwa-miRNA is a valuable tool for the annotation of miRNAs in plant species with reference genomes. We also illustrate the application of iwa-miRNA for miRNA annotation using data from plant species with varying genomic complexity. The source codes and web server of iwa-miRNA are freely accessible at http://iwa-miRNA.omicstudio.cloud/.     

Computational identification of miRNAs,their targets and functions in three‐spined stickleback (Gasterosteus aculeatus)

An intriguing question in biology is how the evolution of gene regulation is shaped by natural selection in natural populations. Among the many known regulatory mechanisms, regulation of gene expression by microRNAs (miRNAs) is of critical importance. However, our understanding of their evolution in natural populations is limited. Studying the role of miRNAs in three‐spined stickleback, an important natural model for speciation research, may provide new insights into adaptive polymorphisms. However, lack of annotation of miRNA genes in its genome is a bottleneck. To fill this research gap, we used the genome of three‐spined stickleback to predict miRNAs and their targets. We predicted 1486 mature miRNAs using the homology‐based miRNA prediction approach. We then performed functional annotation and enrichment analysis of these targets, which identified over‐represented motifs. Further, a database resource (GAmiRdb) has been developed for dynamically searching miRNAs and their targets exclusively in three‐spined stickleback. Finally, the database was used in two case studies focusing on freshwater adaptation in natural populations. In the first study, we found 44 genomic regions overlapping with predicted miRNA targets. In the second study, we identified two SNPs altering the MRE seed site of sperm‐specific glyceraldehyde‐3‐phosphate gene. These findings highlight the importance of the GAmiRdb knowledge base in understanding adaptive evolution.     

Comparative profile of exosomal microRNAs in postmenopausal women with various bone mineral densities by small RNA sequencing

To explore the role of plasma miRNAs in exosomes in early postmenopausal women. Small RNA sequencing was implemented to clarify the expression of miRNA in plasma exosomes obtained from 15 postmenopausal women, divided into groups of osteoporosis, osteopenia, and normal bone mass based on bone mineral density. Differentially expressed miRNAs (DEMs) were identified by comparing miRNA expression profiles. Five putative miRNAs, miR-224-3p, miR-25-5p, miR-302a-3p, miR-642a-3p, and miR-766-5p were confirmed by real-time PCR; miRNA target genes were obtained from 4 databases: miRWalk, miRDB, RNA22, and TargetScan. The miRNA-mRNA- Kyoto Encyclopedia of Genes and Genomes (KEGG) networks were analyzed, and the DEMs' potential role was investigated by gene ontology terms and KEGG pathway annotation. The results suggest that characterizing plasma exosomal miRNA profiles of early postmenopausal women by small RNA sequencing could identify novel exo-miRNAs involved in bone remodeling, and miR-642a-3p maybe contribute to the prediction and diagnosis of early postmenopausal osteoporosis.     

An Integrative Meta-analysis of MicroRNAs in Hepatocellular Carcinoma

We aimed to shed new light on the roles of microRNAs （miRNAs） in liver cancer using an integrative in silico bioinformatics analysis. A new protocol for target prediction and functional analysis is presented and applied to the 26 highly differentially deregulated miRNAs in hepatocellular carcinoma. This framework comprises： （1） the overlap of prediction results by four out of five target prediction tools, including TargetScan, PicTar, miRanda, DIANA-microT and miRDB （combining machine-learning, alignment, interaction energy and statistical tests in order to minimize false positives）, （2） evidence from previous microarray analysis on the expression of these targets, （3） gene ontology （GO） and pathway enrichment analysis of the miRNA targets and their pathways and （4） linking these results to oncogenesis and cancer hallmarks. This yielded new insights into the roles of miRNAs in cancer hallmarks. Here we presented several key targets and hundreds of new targets that are significantly enriched in many new cancer-related hallmarks. In addition, we also revealed some known and new oncogenic pathways for liver cancer. These included the famous MAPK, TGFβ and cell cycle pathways. New insights were also provided into Wnt signaling, prostate cancer, axon guidance and oocyte meiosis pathways. These signaling and developmental pathways crosstalk to regulate stem cell transformation and implicate a role of miRNAs in hepatic stem cell deregulation and cancer development. By analyzing their complete interactome, we proposed new categorization for some of these miRNAs as either tumor-suppressors or oncomiRs with dual roles. Therefore some of these miRNAs may be addressed as therapeutic targets or used as therapeutic agents. Such dual roles thus expand the view of miRNAs as active maintainers of cellular homeostasis.     

miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets

Background

Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.

Results

First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.

Conclusions

MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.     

Analysis of putative miRNA function using a novel approach, GAPPS-miRTarGE

Deciphering the function of miRNA is one of the most important research subjects directed toward understanding the regulation of gene expression. Several experimental methodologies and bioinformatics programs have been developed, however, elucidating miRNA function has not been an easy task. Herein, we suggest a new method, GAPPS-miRTar^GE, which is a novel methodology for predicting miRNA function based on the proportion of mRNA targets expressed during embryonic developmental stages, the Theilers stages (TS), in mice. GAPPS-miRTar^GE is essentially a computational approach that groups miRNAs using shared expression patterns of their target genes during the 28 different TS. In this study, we present not only several examples derived from the GAPPS-miRTar^GE analyses that confirm previously known miRNA functions but also examples of function prediction for valid but functionally unknown miRNAs. Furthermore, we show that tissue-centered GAPPS-miRTar^GE, such as brain-centered or heart-centered, is useful for predicting miRNA function on a more detailed level.     

蒙古沙冬青保守microRNAs的鉴定及靶基因预测

蒙古沙冬青(Ammopiptanthus mongolicus)是生长在荒漠中的木本植物, 对于我国西北部干旱、半干旱区域的植被维护与恢复具有重要价值。蒙古沙冬青对干旱、低温等多种逆境具有较高的耐受性, 是研究林木耐受逆境生理与分子机制的合适材料。MicroRNA(miRNA)是一类长度约为21个核苷酸的内源性非编码小分子RNA, 在植物生长发育和逆境应答等生物学过程中发挥着重要的调控作用。目前, 许多植物物种的miRNAs已经获得鉴定, 但未见蒙古沙冬青miRNAs的相关报道。文章应用高通量测序和生物信息学分析方法对蒙古沙冬青幼苗保守miRNAs的类型、表达丰度以及靶基因进行了分析和预测。共鉴定了10个家族的19种保守miRNAs, 其表达丰度介于55~1920269个拷贝之间。通过在线软件psRNATarget预测了其中14个保守miRNAs的靶基因。对于这些靶基因的功能分析表明, 蒙古沙冬青的保守miRNA主要通过转录调控、激素信号途径、物质代谢和胁迫应答等生物学过程参与植物生长发育和环境响应。