Intensive research in past two decades has uncovered the presence and importance of noncoding RNAs (ncRNAs), which includes microRNAs (miRs) and long ncRNAs (lncRNAs). These two classes of ncRNAs interact to a certain extent, as some lncRNAs bind to miRs to sequester them. Such lncRNAs are collectively called ‘competing endogenous RNAs’ or ‘miRNA sponges’. In this study, we screened for lncRNAs that may act as miRNA sponges using the publicly available data sets and databases. To uncover the roles of miRNA sponges, loss-of-function experiments were conducted, which revealed the biological roles as miRNA sponges. LINC00324 is important for the cell survival by binding to miR-615-5p leading to the de-repression of its target BTG2. LOC400043 controls several biological functions via sequestering miR-28-3p and miR-96-5p, thereby changing the expressions of transcriptional regulators. Finally, we also screened for circular RNAs (circRNAs) that may function as miRNA sponges. The results were negative at least for the selected circRNAs in this study. In conclusion, miRNA sponges can be identified by applying a series of bioinformatics techniques and validated with biological experiments.

Myogenesis is a complex process required for skeletal muscle formation during embryonic development and for regeneration and growth of myofibers in adults. Accumulating evidence suggests that long non-coding RNAs (lncRNAs) play key roles in regulating cell fate decision and function in various tissues. However, the role of lncRNAs in the regulation of myogenesis remains poorly understood. In this study, we identified a novel muscle-enriched lncRNA called ‘Myolinc (AK142388)’, which we functionally characterized in the C2C12 myoblast cell line. Myolinc is predominately localized in the nucleus, and its levels increase upon induction of the differentiation. Knockdown of Myolinc impairs the expression of myogenic regulatory factors and formation of multi-nucleated myotubes in cultured myoblasts. Myolinc also regulates the expression of Filip1 in a cis-manner. Similar to Myolinc, knockdown of Filip1 inhibits myogenic differentiation. Furthermore, Myolinc binds to TAR DNA-binding protein 43 (TDP-43), a DNA/RNA-binding protein that regulates the expression of muscle genes (e.g. Acta1 and MyoD). Knockdown of TDP-43 inhibits myogenic differentiation. We also show that Myolinc−TDP-43 interaction is essential for the binding of TDP-43 to the promoter regions of muscle marker genes. Finally, we show that silencing of Myolinc inhibits skeletal muscle regeneration in adult mice. Altogether, our study identifies a novel lncRNA that controls key regulatory networks of myogenesis.

RNA editing of adenosine residues to inosine (‘A-to-I editing’) is the most common RNA modification event detectible with RNA sequencing (RNA-seq). While not directly detectable, inosine is read by next-generation sequencers as guanine. Therefore, mapping RNA-seq reads to their corresponding reference genome can detect potential editing events by identifying ‘A-to-G’ conversions. However, one must exercise caution when searching for editing sites, as A-to-G conversions also arise from sequencing errors as well as mutations. To address these complexities, several algorithms and software products have been developed to accurately identify editing events. Here, we survey currently available methods to analyze RNA editing events and introduce a new easy-to-use bioinformatics tool ‘RNAEditor’ for the detection of RNA editing events. During the development of RNAEditor, we noticed editing often happened in clusters, which we named ‘editing islands’. We developed a clustering algorithm to find editing islands and included it in RNAEditor. RNAEditor is freely available at http://rnaeditor.uni-frankfurt.de. We anticipate that RNAEditor will provide biologists with an easy-to-use tool for studying RNA editing events and the newly defined editing islands.

Owing greatly to the advancement of next-generation sequencing (NGS), the amount of NGS data is increasing rapidly. Although there are many NGS applications, one of the most commonly used techniques ‘RNA sequencing (RNA-seq)’ is rapidly replacing microarray-based techniques in laboratories around the world. As more and more of such techniques are standardized, allowing technicians to perform these experiments with minimal hands-on time and reduced experimental/operator-dependent biases, the bottleneck of such techniques is clearly visible; that is, data analysis. Further complicating the matter, increasing evidence suggests most of the genome is transcribed into RNA; however, the majority of these RNAs are not translated into proteins. These RNAs that do not become proteins are called ‘noncoding RNAs (ncRNAs)’. Although some time has passed since the discovery of ncRNAs, their annotations remain poor, making analysis of RNA-seq data challenging. Here, we examine the current limitations of RNA-seq analysis using case studies focused on the detection of novel transcripts and examination of their characteristics. Finally, we validate the presence of novel transcripts using biological experiments, showing novel transcripts can be accurately identified when a series of filters is applied. In conclusion, novel transcripts that are identified from RNA-seq must be examined carefully before proceeding to biological experiments.

Every year pathogenic organisms cause billions of dollars' worth damage to crops and livestock. In agriculture, study of plant-microbe interactions is demanding a special attention to develop management strategies for the destructive pathogen induced diseases that cause huge crop losses every year worldwide. Pseudomonas syringae is a major bacterial leaf pathogen that causes diseases in a wide range of plant species. Among its various strains, pathovar tomato strain DC3000 (PstDC3000) is asserted to infect the plant host Arabidopsis thaliana and thus, has been accepted as a model system for experimental characterization of the molecular dynamics of plant-pathogen interactions. Protein-protein interactions (PPIs) play a critical role in initiating pathogenesis and maintaining infection. Understanding the PPI network between a host and pathogen is a critical step for studying the molecular basis of pathogenesis. The experimental study of PPIs at a large scale is very scarce and also the high throughput experimental results show high false positive rate. Hence, there is a need for developing efficient computational models to predict the interaction between host and pathogen in a genome scale, and find novel candidate effectors and/or their targets.

Rationale:: Increasing evidence indicates the presence of lncRNAs in various cell types. Airn is an imprinting gene transcribed from the paternal chromosome. It is in antisense orientation to the imprinted, but maternally derived, Igf2r gene, on which Airn exerts its regulation in cis . Although Airn is highly expressed in the heart, functions aside from imprinting remain unknown. Objective:: Here, we studied the functions of Airn in the heart, especially cardiomyocytes. Methods and Results:: Silencing of Airn via siRNAs augmented cell death, vulnerability to cellular stress, and reduced cell migration. To find the cause of such phenotypes, the potential binding partners of Airn were identified via RNA pull-down followed by mass spectrometry, which indicated Igf2bp2 (insulin-like growth factor 2 mRNA-binding protein 2) and Rpa1 (replication protein A1) as potential binding partners. Further experiments showed that Airn binds to Igf2bp2 to control the translation of several genes. Moreover, silencing of Airn caused less binding of Igf2bp2 to other mRNAs and reduced translation of Igf2bp2 protein. Conclusions:: Our study uncovers a new function of Airn and demonstrates that Airn is important for the physiology of cardiomyocytes.