microRNA-mRNA Interactions Research Articles

Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches.

Cartilage destruction in rheumatoid arthritis (RA) occurs primarily in the pannus-cartilage interface. The close contact of the synovium-cartilage interface implicates crosstalk between synovial fibroblasts and chondrocytes. The aim of this study is to explore the differentially expressed genes and novel microRNA regulations potentially implicated in the dysregulated cartilage homeostasis in joint destruction of RA. Total RNAs were extracted from human primary cultured normal and RA chondrocytes for RNA and small RNA expression profiling using next-generation sequencing. Using systematic bioinformatics analyses, we identified 463 differentially expressed genes in RA chondrocytes were enriched in biological functions related to altered cell cycle process, inflammatory response and hypoxic stimulation. Moreover, fibroblast growth factor 9 (FGF9), kynureninase (KYNU), and regulator of cell cycle (RGCC) were among the top dysregulated genes identified to be potentially affected in the RA joint microenvironment, having similar expression patterns observed in arrays of clinical RA synovial tissues from the Gene Expression Omnibus database. Additionally, among the 31 differentially expressed microRNAs and 10 candidate genes with potential microRNA-mRNA interactions in RA chondrocytes, the novel miR-140-3p-FGF9 interaction was validated in different microRNA prediction databases, and proposed to participate in the pathogenesis of joint destruction through dysregulated cell growth in RA. The findings provide new perspectives for target genes in the management of cartilage destruction in RA.

Deduction of Novel Genes Potentially Involved in Osteoblasts of Rheumatoid Arthritis Using Next-Generation Sequencing and Bioinformatic Approaches.

The role of osteoblasts in peri-articular bone loss and bone erosion in rheumatoid arthritis (RA) has gained much attention, and microRNAs are hypothesized to play critical roles in the regulation of osteoblast function in RA. The aim of this study is to explore novel microRNAs differentially expressed in RA osteoblasts and to identify genes potentially involved in the dysregulated bone homeostasis in RA. RNAs were extracted from cultured normal and RA osteoblasts for sequencing. Using the next generation sequencing and bioinformatics approaches, we identified 35 differentially expressed microRNAs and 13 differentially expressed genes with potential microRNA–mRNA interactions in RA osteoblasts. The 13 candidate genes were involved mainly in cell–matrix adhesion, as classified by the Gene Ontology. Two genes of interest identified from RA osteoblasts, A-kinase anchoring protein 12 (AKAP12) and leucin rich repeat containing 15 (LRRC15), were found to express more consistently in the related RA synovial tissue arrays in the Gene Expression Omnibus database, with the predicted interactions with miR-183-5p and miR-146a-5p, respectively. The Ingenuity Pathway Analysis identified AKAP12 as one of the genes involved in protein kinase A signaling and the function of chemotaxis, interconnecting with molecules related to neovascularization. The findings indicate new candidate genes as the potential indicators in evaluating therapies targeting chemotaxis and neovascularization to control joint destruction in RA.

Defining a microRNA-mRNA interaction map for calcineurin inhibitor induced nephrotoxicity.

Calcineurin inhibitors induce nephrotoxicity through poorly understood mechanisms thereby limiting their use in transplantation and other diseases. Here we define a microRNA (miRNA)-messenger RNA (mRNA) interaction map that facilitates exploration into the role of miRNAs in cyclosporine-induced nephrotoxicity (CIN) and the gene pathways they regulate. Using photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP), we isolated RNAs associated with Argonaute 2 in the RNA-induced silencing complex (RISC) of cyclosporine A (CsA) treated and control human proximal tubule cells and identified mRNAs undergoing active targeting by miRNAs. CsA causes specific changes in miRNAs and mRNAs associated with RISC, thereby altering post-transcriptional regulation of gene expression. Pathway enrichment analysis identified canonical pathways regulated by miRNAs specifically following CsA treatment. RNA-seq performed on total RNA indicated that only a fraction of total miRNAs and mRNAs are actively targeted in the RISC, indicating that PAR-CLIP more accurately defines meaningful targeting interactions. Our data also revealed a role for miRNAs in calcineurin-independent regulation of JNK and p38 MAPKs caused by targeting of MAP3K1. Together, our data provide a novel resource and unique insights into molecular pathways regulated by miRNAs in CIN. The gene pathways and miRNAs defined may represent novel targets to reduce calcineurin induced nephrotoxicity.

Dynamic and Modularized MicroRNA Regulation and Its Implication in Human Cancers

MicroRNA is responsible for the fine-tuning of fundamental cellular activities and human disease development. The altered availability of microRNAs, target mRNAs, and other types of endogenous RNAs competing for microRNA interactions reflects the dynamic and conditional property of microRNA-mediated gene regulation that remains under-investigated. Here we propose a new integrative method to study this dynamic process by considering both competing and cooperative mechanisms and identifying functional modules where different microRNAs co-regulate the same functional process. Specifically, a new pipeline was built based on a meta-Lasso regression model and the proof-of-concept study was performed using a large-scale genomic dataset from ~4,200 patients with 9 cancer types. In the analysis, 10,726 microRNA-mRNA interactions were identified to be associated with a specific stage and/or type of cancer, which demonstrated the dynamic and conditional miRNA regulation during cancer progression. On the other hands, we detected 4,134 regulatory modules that exhibit high fidelity of microRNA function through selective microRNA-mRNA binding and modulation. For example, miR-18a-3p, −320a, −193b-3p, and −92b-3p co-regulate the glycolysis/gluconeogenesis and focal adhesion in cancers of kidney, liver, lung, and uterus. Furthermore, several new insights into dynamic microRNA regulation in cancers have been discovered in this study.

The contribution of alternative polyadenylation to the cancer phenotype.

Eukaryotic 3'-end formation is a critical step for mRNA maturation and involves a requisite cleavage and polyadenylation event downstream of a polyadenylation signal. Recent discoveries suggest that in nearly 70% of human genes, cleavage and polyadenylation can occur at multiple locations through a process known as alternative polyadenylation (APA). Therefore, APA is a form of co-transcriptional gene regulation that has the potential to greatly expand mRNA transcript diversity. There are two general types of APA. The first includes alternative splicing events (splicing-APA) that result in changes to the coding sequence, and the second does not involve alternative splicing (tandem untranslated region-APA). The latter form of APA occurs within the same terminal exon, thereby only changing the 3'-untranslated region length and content. The role of APA in transformation and cancer is still being deciphered and has been the subject of intensive investigation by multiple groups. Here, we provide a general summary of APA and how it can differentially impact mRNA stability, translation and localization in cis. In addition, we discuss more indirect implications of APA on mRNA transcripts. The latter is based upon the concept that APA can induce the reorganization of both microRNA-mRNA and RNA-binding protein-mRNA interactions. We use these general models as a platform to describe what is known about how tumors manipulate the APA of oncogenes to further drive tumorigenesis. Finally, we briefly discuss the role that next-generation sequencing has played in identifying APA regulators and key transcripts that alter 3'-untranslated region length in cancer.

Crucial microRNAs and genes in metformin's anti-pancreatic cancer effect explored by microRNA-mRNA integrated analysis.

Despite great improvements in surgical procedures and chemotherapy, pancreatic cancer remains one of the most aggressive and fatal human malignancies, with a low 5-year survival rate. Therefore, novel therapeutic strategies for the prevention and treatment of pancreatic cancer are urgently needed. The present study aimed to investigate the mechanisms by which metformin exerts its anticancer effects on the microRNA-mRNA interactions in human pancreatic cancer. Microarray and systematic analyses revealed that the anti-pancreatic cancer effects of metformin were correlated with 3 up-regulated microRNAs and 4 of their target mRNAs. In addition, the microarray and systematic analyses ultimately demonstrated that 3 microRNAs regulated 4 key mRNAs in a sub-pathway of pancreatic cancer and then affected growth, angiogenesis, and apoptosis. This finding may provide a deeper understanding of the mechanisms by which metformin suppresses proliferation and angiogenesis and promotes apoptosis in pancreatic cancer cells. Collectively, this experiment improves the understanding of the mechanisms by which metformin suppresses pancreatic cancer and indicates that metformin, the most commonly used drug for the treatment of diabetes mellitus, may be a promising candidate agent for the treatment of pancreatic cancer.

Identification of novel genetic regulations associated with airway epithelial homeostasis using next-generation sequencing data and bioinformatics approaches.

Airway epithelial cells play important roles in airway remodeling. Understanding gene regulations in airway epithelial homeostasis may provide new insights into pathogenesis and treatment of asthma. This study aimed to combine gene expression (GE) microarray, next generation sequencing (NGS), and bioinformatics to explore genetic regulations associated with airway epithelial homeostasis. We analyzed expression profiles of mRNAs (GE microarray) and microRNAs (NGS) in normal and asthmatic bronchial epithelial cells, and identified 9 genes with potential microRNA-mRNA interactions. Of these 9 dysregulated genes, downregulation of MEF2C and MDGA1 were validated in a representative microarray (GSE43696) from the gene expression omnibus (GEO) database. Our findings suggested that upregulated mir-203a may repress MEF2C, a transcription factor, leading to decreased cellular proliferation. In addition, upregulated mir-3065-3p may repress MDGA1, a cell membrane anchor protein, resulting in suppression of cell-cell adhesion. We also found that KCNJ2, a potassium channel, was downregulated in severe asthma and may promote epithelial cell apoptosis. We proposed that aberrant regulations of mir-203a-MEF2C and mir-3065-3p-MDGA1, as well as downregulation of KCNJ2, play important roles in airway epithelial homeostasis in asthma. These findings provide new perspectives on diagnostic or therapeutic strategies targeting bronchial epithelium for asthma. The approach in this study also provides a new aspect of studying asthma.

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA interactions such as microRNA-mRNA interactions have been shown to regulate gene expression, the full extent to which RNA interactions occur in the cell is still unknown. Previous methods to study RNA interactions have primarily focused on subsets of RNAs that are interacting with a particular protein or RNA species. Here, we detail a method named Sequencing of Psoralen crosslinked, Ligated, and Selected Hybrids (SPLASH) that allows genome-wide capture of RNA interactions in vivo in an unbiased manner. SPLASH utilizes in vivo crosslinking, proximity ligation, and high throughput sequencing to identify intramolecular and intermolecular RNA base-pairing partners globally. SPLASH can be applied to different organisms including bacteria, yeast and human cells, as well as diverse cellular conditions to facilitate the understanding of the dynamics of RNA organization under diverse cellular contexts. The entire experimental SPLASH protocol takes about 5 days to complete and the computational workflow takes about 7 days to complete.

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen.

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA interactions such as microRNA-mRNA interactions have been shown to regulate gene expression, the full extent to which RNA interactions occur in the cell is still unknown. Previous methods to study RNA interactions have primarily focused on subsets of RNAs that are interacting with a particular protein or RNA species. Here, we detail a method named Sequencing of Psoralen crosslinked, Ligated, and Selected Hybrids (SPLASH) that allows genome-wide capture of RNA interactions in vivo in an unbiased manner. SPLASH utilizes in vivo crosslinking, proximity ligation, and high throughput sequencing to identify intramolecular and intermolecular RNA base-pairing partners globally. SPLASH can be applied to different organisms including bacteria, yeast and human cells, as well as diverse cellular conditions to facilitate the understanding of the dynamics of RNA organization under diverse cellular contexts. The entire experimental SPLASH protocol takes about 5 days to complete and the computational workflow takes about 7 days to complete.

Patients with bicuspid and tricuspid aortic valve exhibit distinct regional microrna signatures in mildly dilated ascending aorta.

MicroRNAs are able to modulate gene expression in a range of diseases. We focused on microRNAs as potential contributors to the pathogenesis of ascending aorta (AA) dilatation in patients with stenotic tricuspid (TAV) or bicuspid aortic valve (BAV). Aortic specimens were collected from the 'concavity' and the 'convexity' of mildly dilated AAs and of normal AAs from heart transplant donors. Aortic RNA was analyzed through PCR arrays, profiling the expression of 84 microRNAs involved in cardiovascular disease. An in silico analysis identified the potential microRNA-mRNA interactions and the enriched KEGG pathways potentially affected by microRNA changes in dilated AAs. Distinct signatures of differentially expressed microRNAs are evident in TAV and BAV patients vs. donors, as well as differences between aortic concavity and convexity in patients only. MicroRNA changes suggest a switch of SMC phenotype, with particular reference to TAV concavity. MicroRNA changes potentially affecting mechanotransduction pathways exhibit a higher prevalence in BAV convexity and in TAV concavity, with particular reference to TGF-β1, Hippo, and PI3K/Akt/FoxO pathways. Actin cytoskeleton emerges as potentially affected by microRNA changes in BAV convexity only. MicroRNAs could play distinct roles in BAV and TAV aortopathy, with possible implications in diagnosis and therapy.

Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources.

MicroRNA (miRNA) mediated silencing and repression of mRNA molecules requires complementary base pairing between the "seed" region of the miRNA and the "seed match" region of target mRNAs. While this mechanism is fairly well understood, accurate prediction of valid miRNA targets remains challenging due to factors such as imperfect sequence specificity, target site availability, and the thermodynamic stability of the mRNA structure itself. As knowledge of what genes are being targeted by each miRNA is arguably the most important facet of miRNA biology, many approaches have been developed to address the need for reliable prediction and ranking of putative targets, with most using a combination of various strategies such as evolutionary conservation, statistical inference, and distinct features of the target sequences themselves. This chapter reviews the pros and cons of a number of different prediction algorithms, showcases some databases that store experimentally validated miRNA targets, and also provides a case study that profiles some of the potential microRNA-mRNA interactions predicted by each methodology for various human genes.

Inhibition of fat cell differentiation in 3T3-L1 pre-adipocytes by all-trans retinoic acid: Integrative analysis of transcriptomic and phenotypic data

The process of adipogenesis is controlled in a highly orchestrated manner, including transcriptional and post-transcriptional events. In developing 3T3-L1 pre-adipocytes, this program can be interrupted by all-trans retinoic acid (ATRA). To examine this inhibiting impact by ATRA, we generated large-scale transcriptomic data on the microRNA and mRNA level. Non-coding RNAs such as microRNAs represent a field in RNA turnover, which is very important for understanding the regulation of mRNA gene expression. High throughput mRNA and microRNA expression profiling was performed using mRNA hybridisation microarray technology and multiplexed expression assay for microRNA quantification. After quantitative measurements we merged expression data sets, integrated the results and analysed the molecular regulation of in vitro adipogenesis. For this purpose, we applied local enrichment analysis on the integrative microRNA-mRNA network determined by a linear regression approach. This approach includes the target predictions of TargetScan Mouse 5.2 and 23 pre-selected, significantly regulated microRNAs as well as Affymetrix microarray mRNA data. We found that the cellular lipid metabolism is negatively affected by ATRA. Furthermore, we were able to show that microRNA 27a and/or microRNA 96 are important regulators of gap junction signalling, the rearrangement of the actin cytoskeleton as well as the citric acid cycle, which represent the most affected pathways with regard to inhibitory effects of ATRA in 3T3-L1 preadipocytes. In conclusion, the experimental workflow and the integrative microRNA–mRNA data analysis shown in this study represent a possibility for illustrating interactions in highly orchestrated biological processes. Further the applied global microRNA–mRNA interaction network may also be used for the pre-selection of potential new biomarkers with regard to obesity or for the identification of new pharmaceutical targets.

Visualization and Analysis of MiRNA-Targets Interactions Networks.

MicroRNAs are a class of small, noncoding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the target mRNAs, mainly leading to down-regulation or repression of the target genes. MicroRNAs are involved in diverse regulatory pathways in normal and pathological conditions. In this context, it is highly important to identify the targets of specific microRNA in order to understand the mechanism of its regulation and consequently its involvement in disease. However, the microRNA target identification is experimentally laborious and time-consuming. The in silico prediction of microRNA targets is an extremely useful approach because you can identify potential mRNA targets, reduce the number of possibilities and then, validate a few microRNA-mRNA interactions in an in vitro experimental model. In this chapter, we describe, in a simple way, bioinformatics guidelines to use miRWalk database and Cytoscape software for analyzing microRNA-mRNA interactions through their visualization as a network.

Exploration of low temperature microRNA function in an anoxia tolerant vertebrate ectotherm, the red eared slider turtle (Trachemys scripta elegans)

As a model for vertebrate long-term survival in oxygen-restricted environments, the red-eared slider turtle (Trachemys scripta elegans) can adapt at the biochemical level to survive in oxygen-free (anoxic) cold water (<10°C). This impressive ability is enabled through a coordinated suppression of energy-expensive, non-essential, cell processes. This study explored the anoxia-responsive expression of several microRNA species (miR-1a, −133, −17, −107, −148a, −21, −103, −210, −20a, −365 and −29b) in adult turtles exposed to 5h and 20h anoxia (at 5±1°C). Furthermore, since microRNA target binding is regularly defined only by microRNA-mRNA interactions at 37°C, the possibility of unique low temperature-selective microRNA targeting interactions with mRNA was explored in this ectotherm. Approximately twice as many microRNA-mRNA interactions were predicted at 5°C versus 37°C with particular enrichment of mRNA targets involved in biological processes known to be part of the stress response. Hence, the results suggest that the influence of temperature should be considered for the prediction of microRNA targets (and their follow-up) in poikilothermic animals and that interacting effects of low body temperature and anoxia on microRNA expression could potentially be important to achieve the profound metabolic rate depression that characterizes turtle hibernation underwater during the winter.

Dihydroartemisinin suppresses pancreatic cancer cells via a microRNA-mRNA regulatory network.

Despite improvements in surgical procedures and chemotherapy, pancreatic cancer remains one of the most aggressive and fatal human malignancies, with a low 5-year survival rate of only 8%. Therefore, novel strategies for prevention and treatment are urgently needed. Here, we investigated the mechanisms underlying the anti-pancreatic cancer effects dihydroartemisinin (DHA). Microarray and systematic analysis showed that DHA suppressed proliferation, inhibited angiogenesis and promoted apoptosis in two different human pancreatic cancer cell lines, and that 5 DHA-regulated microRNAs and 11 of their target mRNAs were involved in these effects via 19 microRNA-mRNA interactions. Four of these microRNAs, 9 of the mRNAs and 17 of the interactions were experimentally verified. Furthermore, we found that the anti-pancreatic caner effects of DHA in vivo involved 4 microRNAs, 9 mRNAs and 17 microRNA-mRNA interactions. These results improve the understanding of the mechanisms by which DHA suppresses proliferation and angiogenesis and promotes apoptosis in pancreatic cancer cells and indicate that DHA, an effective antimalarial drug, might improve pancreatic cancer treatments.

Proceedings of the 15th Annual UT-KBRIN Bioinformatics Summit 2016 : Cadiz, KY, USA. 8-10 April 2016.

Table of contentsI1 Proceedings of the Fifteenth Annual UT- KBRIN Bioinformatics Summit 2016Eric C. Rouchka, Julia H. Chariker, Benjamin J. Harrison, Juw Won ParkP1 CC-PROMISE: Projection onto the Most Interesting Statistical Evidence (PROMISE) with Canonical Correlation to integrate gene expression and methylation data with multiple pharmacologic and clinical endpointsXueyuan Cao, Stanley Pounds, Susana Raimondi, James Downing, Raul Ribeiro, Jeffery Rubnitz, Jatinder LambaP2 Integration of microRNA-mRNA interaction networks with gene expression data to increase experimental powerBernie J Daigle, Jr.P3 Designing and writing software for in silico subtractive hybridization of large eukaryotic genomesDeborah Burgess, Stephanie Gehrlich, John C CarmenP4 Tracking the molecular evolution of Pax geneNicholas Johnson; Chandrakanth EmaniP5 Identifying genetic differences in thermally dimorphic and state specific fungi using in silico genomic comparisonStephanie Gehrlich, Deborah Burgess, John C CarmenP6 Identification of conserved genomic regions and variation therein amongst Cetartiodactyla species using next generation sequencingKalpani De Silva, Michael P Heaton, Theodore S KalbfleischP7 Mining physiological data to identify patients with similar medical events and phenotypesTeeradache Viangteeravat, Rahul Mudunuri, Oluwaseun Ajayi, Fatih Şen, Eunice Y HuangP8 Smart brief for home health monitoringMohammad Mohebbi, Luaire Florian, Douglas J Jackson, John F NaberP9 Side-effect term matching for computational adverse drug reaction predictionsAKM Sabbir, Sally R EllingsonP10 Enrichment vs robustness: A comparison of transcriptomic data clustering metricsYuping Lu, Charles A Phillips, Michael A LangstonP11 Deep neural networks for transcriptome-based cancer classificationRahul K Sevakula, Raghuveer Thirukovalluru, Nishchal K. Verma, Yan CuiP12 Motif discovery using K-means clusteringMohammed Sayed, Juw Won ParkP13 Large scale discovery of active enhancers from nascent RNA sequencingJing Wang, Qi Liu, Yu ShyrP14 Computationally characterizing genomic pipelines and benchmarking results using GATK best practices on the high performance computing cluster at the University of KentuckyXiaofei Zhang, Sally R EllingsonP15 Development of approaches enabling the identification of abnormal gene expression from RNA-Seq in personalized oncologyNaresh Prodduturi, Gavin R Oliver, Diane Grill, Jie Na, Jeanette Eckel-Passow, Eric W KleeP16 Processing RNA-Seq data of plants infected with coffee ringspot virusMichael M Goodin, Mark Farman, Harrison Inocencio, Chanyong Jang, Jerzy W Jaromczyk, Neil Moore, Kelly SovacoolP17 Comparative transcriptomics of three Acinetobacter baumanii clinical isolates with different antibiotic resistance patternsLeon Dent, Mike Izban, Sammed Mandape, Shruti Sakhare, Siddharth Pratap, Dana MarshallP18 Metagenomic assessment of possible microbial contamination in the equine reference genome assemblyM Scotty DePriest, James N MacLeod, Theodore S KalbfleischP19 Molecular evolution of cancer driver genesChandrakanth Emani, Hanady Adam, Ethan Blandford, Joel Campbell, Joshua Castlen, Brittany Dixon, Ginger Gilbert, Aaron Hall, Philip Kreisle, Jessica Lasher, Bethany Oakes, Allison Speer, Maximilian ValentineP20 Biorepository Laboratory Information Management SystemNaga Satya V Rao Nagisetty, Rony Jose, Teeradache Viangteeravat, Robert Rooney, David Hains

A novel infection- and inflammation-associated molecular signature in peripheral blood of myasthenia gravis patients

Myasthenia gravis (MG) is a T-cell dependent autoimmune disorder of the neuromuscular junction, characterised by muscle weakness and fatigability. Autoimmunity is thought to initiate in the thymus of acetylcholine receptor (AChR)-positive MG patients; however, the molecular mechanisms linking intra-thymic MG pathogenesis with autoreactivity via the circulation to the muscle target organ are poorly understood. Using whole-transcriptome sequencing, we compared the transcriptional profile of peripheral blood mononuclear cells from AChR-early onset MG (AChR-EOMG) patients with healthy controls: 178 coding transcripts and 229 long non-coding RNAs, including 11 pre-miRNAs, were differentially expressed. Among the 178 coding transcripts, 128 were annotated of which 17% were associated with the ‘infectious disease’ functional category and 46% with ‘inflammatory disease’ and ‘inflammatory response-associated’ categories. Validation of selected transcripts by qPCR indicated that of the infectious disease-related transcripts, ETF1, NFKB2, PLK3, and PPP1R15A were upregulated, whereas CLC and IL4 were downregulated in AChR-EOMG patients; in the ‘inflammatory’ categories, ABCA1, FUS, and RELB were upregulated, suggesting a contribution of these molecules to immunological dysfunctions in MG. Data selection and validation were also based on predicted microRNA-mRNA interactions. We found that miR-612, miR-3654, and miR-3651 were increased, whereas miR-612-putative AKAp12 and HRH4 targets and the miR-3651-putative CRISP3 target were downregulated in AChR-EOMG, also suggesting altered immunoregulation. Our findings reveal a novel peripheral molecular signature in AChR-EOMG, reflecting a critical involvement of inflammatory- and infectious disease-related immune responses in disease pathogenesis.

MicroRNA in late lung development and bronchopulmonary dysplasia: the need to demonstrate causality.

MicroRNA are emerging as powerful regulators of cell differentiation and tissue and organ development. Several microRNA have been described to play a role in branching morphogenesis, a key step in early lung development. However, considerably less attention has been paid to microRNA as regulators of the process of secondary septation, which drives lung alveolarization during late lung development. Secondary septation is severely perturbed in bronchopulmonary dysplasia (BPD), a common complication of preterm birth characterized by blunted alveolarization. A number of studies to date have reported microRNA microarray screens in animal models of BPD; however, only two studies have attempted to demonstrate causality. Although the expression of miR-150 was altered in experimental BPD, a miR-150−/− knockout mouse did not exhibit appreciable protection in a BPD animal model. Similarly, while the expression of miR-489 in the lung was reduced in clinical and experimental BPD, antagomiR and over-expression approaches could not validate a role for miR-489 in the impaired alveolarization associated with experimental BPD. This mini-review aims to highlight microRNA that have been revealed by multiple microarray studies to be potential causal players in normal and pathological alveolarization. Additionally, the challenges faced in attempting to demonstrate a causal role for microRNA in lung alveolarization are discussed. These include the tremendous variability in the animal models employed, and the limitations and advantages offered by the available tools, including antagomiRs and approaches for the validation of a specific microRNA-mRNA interaction during lung alveolarization.

Identification of More Feasible MicroRNA-mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction.

MicroRNA(miRNA)–mRNA interactions are important for understanding many biological processes, including development, differentiation and disease progression, but their identification is highly context-dependent. When computationally derived from sequence information alone, the identification should be verified by integrated analyses of mRNA and miRNA expression. The drawback of this strategy is the vast number of identified interactions, which prevents an experimental or detailed investigation of each pair. In this paper, we overcome this difficulty by the recently proposed principal component analysis (PCA)-based unsupervised feature extraction (FE), which reduces the number of identified miRNA–mRNA interactions that properly discriminate between patients and healthy controls without losing biological feasibility. The approach is applied to six cancers: hepatocellular carcinoma, non-small cell lung cancer, esophageal squamous cell carcinoma, prostate cancer, colorectal/colon cancer and breast cancer. In PCA-based unsupervised FE, the significance does not depend on the number of samples (as in the standard case) but on the number of features, which approximates the number of miRNAs/mRNAs. To our knowledge, we have newly identified miRNA–mRNA interactions in multiple cancers based on a single common (universal) criterion. Moreover, the number of identified interactions was sufficiently small to be sequentially curated by literature searches.

ImiRP: a computational approach to microRNA target site mutation.

BackgroundMicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs that function as post-transcriptional regulators of messenger RNA (mRNA) through base-pairing to 6–8 nucleotide long target sites, usually located within the mRNA 3’ untranslated region. A common approach to validate and probe microRNA-mRNA interactions is to mutate predicted target sites within the mRNA and determine whether it affects miRNA-mediated activity. The introduction of miRNA target site mutations, however, is potentially problematic as it may generate new, “illegitimate sites” target sites for other miRNAs, which may affect the experimental outcome. While it is possible to manually generate and check single miRNA target site mutations, this process can be time consuming, and becomes particularly onerous and error prone when multiple sites are to be mutated simultaneously. We have developed a modular Java-based system called ImiRP (Illegitimate miRNA Predictor) to solve this problem and to facilitate miRNA target site mutagenesis.ResultsThe ImiRP interface allows users to input a sequence of interest, specify the locations of multiple predicted target sites to mutate, and set parameters such as species, mutation strategy, and disallowed illegitimate target site types. As mutant sequences are generated, ImiRP utilizes the miRBase high confidence miRNA dataset to identify illegitimate target sites in each mutant sequence by comparing target site predictions between input and mutant sequences. ImiRP then assembles a final mutant sequence in which all specified target sites have been mutated.ConclusionsImiRP is a mutation generator program that enables selective disruption of specified miRNA target sites while ensuring predicted target sites for other miRNAs are not inadvertently created. ImiRP supports mutagenesis of single and multiple miRNA target sites within a given sequence, including sites that overlap. This software will be particularly useful for studies looking at microRNA cooperativity, where mutagenesis of multiple microRNA target sites may be desired. The software is available at imirp.org and is available open source for download through GitHub (https://github.com/imirp).Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1057-y) contains supplementary material, which is available to authorized users.