Bioinformatics tools and novel challenges in long non-coding RNAs (lncRNAs) functional analysis

Exploiting Long Noncoding RNAs as Pharmacological Targets to Modulate Epigenetic Diseases

Long non-coding RNAs (lncRNAs) constitute the largest class of non-coding transcripts in the human genome. Results from next-generation sequencing and bioinformatics advances indicate that the human genome contains more non-coding RNA genes than protein-coding genes. Validated functions of lncRNAs suggest that they are master regulators of gene expression and often exert their influences via epigenetic mechanisms by modulating chromatin structure. Specific lncRNAs can regulate transcription in gene clusters. Since the functions of protein-coding genes in clusters are often tied to specific pathways, lncRNAs constitute attractive pharmacological targets. Here we review the current knowledge of lncRNA functions in human cells and their roles in disease processes. We also present forward-looking perspectives on how they might be manipulated pharmacologically for the treatment of a variety of human diseases, in which regulation of gene expression by epigenetic mechanisms plays a major role.

Long non-coding RNAs in brain development, synaptic biology, and Alzheimer's disease

Long non-coding RNAs (lncRNAs), which are long transcripts without apparent protein-coding roles, interfere with gene expression and signaling events at various stages. Increasing evidence has suggested that lncRNAs function in the regulation of tissue homeostasis and under pathophysiologic conditions. In the nervous system, the expression of lncRNAs has been detected and characterized under normal physiologic conditions and in disease states. Some lncRNAs regulate brain development and synaptic plasticity. In Alzheimer's disease (AD), several lncRNAs have been demonstrated to regulate β-amyloid production/generation, synaptic impairment, neurotrophin depletion, inflammation, mitochondrial dysfunction, and stress responses. This review summarizes data on lncRNA expression and focuses on neural lncRNAs that may function in AD. Although our understanding of lncRNAs remains in its infancy, this review provides insight into the contribution of lncRNAs to AD.

p53-inducible long non-coding RNA PICART1 mediates cancer cell proliferation and migration

Long non-coding RNAs (lncRNAs) function in the development and progression of cancer, but only a small portion of lncRNAs have been characterized to date. A novel lncRNA transcript, 2.53 kb in length, was identified by transcriptome sequencing analysis, and was named p53-inducible cancer-associated RNA transcript 1 (PICART1). PICART1 was found to be upregulated by p53 through a p53-binding site at -1808 to -1783 bp. In breast and colorectal cancer cells and tissues, PICART1 expression was found to be decreased. Ectopic expression of PICART1 suppressed the growth, proliferation, migration, and invasion of MCF7, MDA-MB-231 and HCT116 cells whereas silencing of PICART1 stimulated cell growth and migration. In these cells, the expression of PICART1 suppressed levels of p-AKT (Thr308 and Ser473) and p-GSK3β (Ser9), and accordingly, β-catenin, cyclin D1 and c-Myc expression were decreased, while p21Waf/cip1 expression was increased. Together these data suggest that PICART1 is a novel p53-inducible tumor-suppressor lncRNA, functioning through the AKT/GSK3β/β-catenin signaling cascade.

HOTAIR functions as a competing endogenous RNA to regulate PTEN expression by inhibiting miR-19 in cardiac hypertrophy

Sustained cardiac hypertrophy (CH) is related to a variety of physiological as well as pathological stimuli and eventually increases the risk of heart failure. HOTAIR has been identified as a competing endogenous RNA in multiple human biological processes. Whether lncRNA-HOTAIR is involved in the progress of CH and how it works still remain unknown. Herein, we found that HOTAIR was down-regulated, while miR-19 was up-regulated in both heart tissues from TAC-operated mice in vivo and cultural cardiomyocytes treated with Ang-II in vitro by real-time PCR. Meanwhile, HOTAIR expression was negatively correlated with miR-19 in TAC-operated mice. HOTAIR overexpression reduced cell surface area and the expression of hypertrophic markers ANP, BNP, and β-MHC in response to Ang-II stimulation as well as knockdown of miR-19. The further molecular mechanisms of HOTAIR action in CH demonstrated that HOTAIR may act as a competing endogenous RNA (ceRNA) for miR-19, thereby modulating the dis-inhibition of its endogenous target PTEN and playing an important role in inhibiting CH progress. These findings reveal a novel function of LncRNAs, which conduce to an extensive understanding of CH and provide novel research directions and therapeutic options for treating this disease.

MicroRNAs at the epicenter of intestinal homeostasis

Maintaining intestinal homeostasis is a key prerequisite for a healthy gut. Recent evidence points out that microRNAs (miRNAs) act at the epicenter of the signaling networks regulating this process. The fine balance in the interaction between gut microbiota, intestinal epithelial cells, and the host immune system is achieved by constant transmission of signals and their precise regulation. Gut microbes extensively communicate with the host immune system and modulate host gene expression. On the other hand, sensing of gut microbiota by the immune cells provides appropriate tolerant responses that facilitate the symbiotic relationships. While the role of many regulatory proteins, receptors and their signaling pathways in the regulation of the intestinal homeostasis is well documented, the involvement of non-coding RNA molecules in this process has just emerged. This review discusses the most recent knowledge about the contribution of miRNAs in the regulation of the intestinal homeostasis.

LOC100287225, novel long intergenic non-coding RNA, misregulates in colorectal cancer

Colorectal cancer (CRC) is one of the most common cancers in the world; therefore, extensive research is needed to find new molecular therapeutic targets and biomarkers. LncRNA (long non-coding RNA), a new class of non-coding RNAs, has a crucial role in the onset and progression of various cancers including colorectal cancer. Research on lncRNA is still at initial stages and underlying molecular mechanisms of the vast majority of lncRNA have remained unclear. LOC100287225 is one of these novel lncRNAs (long intergenic non-coding RNA) located in the long arm of the chromosome 18. The purpose of this study was to determine the expression of LOC100287225 in colorectal tissue, and its misregulation in CRC patients. Quantitative real-time-PCR (qRT-PCR) was used to investigate the LOC100287225 expression in pairs of tumorous and adjacent tumor-free tissues of 39 colorectal cancer patients. Also, the relationship between the clinicopathology and expression of LOC100287225 was determined. QRT-PCR results revealed that not only is LOC100287225 expressed in the intestinal tissue, but has also been misregulated during tumorigenesis. Moreover, LOC100287225 RNA relative expression levels were significantly lower in tumor tissues compared with adjacent tumor-free tissues (P< 0.001). RNA expression level of LOC100287225 did not show significant correlation with clinical characteristics. In conclusion, our study demonstrated that LOC100287225 misregulation could be a potential target for gene therapy in colorectal cancer.

LncRNAs: emerging players in gene regulation and disease pathogenesis

The advent of next-generation sequencing has demonstrated that eukaryotic genomes are extremely complex than what were previously thought. Recent studies revealed that in addition to protein-coding genes, nonprotein-coding genes have allocated a large fraction of the genome. Long noncoding RNA (lncRNA) genes are classified as nonprotein-coding genes, serving as a molecular signal, decoy, guide and scaffold. They were suggested to play important roles in chromatin states, epigenetic and posttranscriptional regulation of genes. Aberrant expression of lncRNAs and changes in their structure are associated with a wide spectrum of diseases ranging from different types of cancer and neurodegeneration to ?-thalassaemia. The purpose of this study was to summarize the current progress in understanding the genomic bases and origin of lncRNAs. Moreover, this study focusses on the diverse functions of lncRNAs in normal cells as well as various types of disease to illustrate the potential impacts of lncRNAs on diverse biological processes and their therapeutic significance.

Satellite non-coding RNAs: the emerging players in cells, cellular pathways and cancer

For several decades, transcriptional inactivity was considered as one of the particular features of constitutive heterochromatin and, therefore, of its major component, satellite DNA sequences. However, more recently, succeeding evidences have demonstrated that these sequences can indeed be transcribed, yielding satellite non-coding RNAs with important roles in the organization and regulation of genomes. Since then, several studies have been conducted, trying to understand the function(s) of these sequences not only in the normal but also in cancer genomes. It is thought that the association between cancer and satncRNAs is mostly due to the influence of these transcripts in the genome instability, a hallmark of cancer. The few reports on satellite DNA transcription in cancer contexts point to its overexpression; however, this scenario may be far more complex, variable, and influenced by a number of factors and the exact role of satncRNAs in the oncogenic process remains poorly understood. The greater is the knowledge on the association of satncRNAs with cancer, the greater would be the opportunity to assist cancer treatment, either by the design of effective therapies targeting these molecules or by using them as biomarkers in cancer diagnosis, prognosis, and with predictive value.

How Our Other Genome Controls Our Epi-Genome

Eukaryotes and prokaryotes produce extracellular nanovescicles that contain RNAs and other molecules that they exploit to communicate. Recently, inter-kingdom crosstalk was demonstrated between humans and bacteria through fecal microRNAs. We suggest here how bacteria interact with humans via RNAs within membrane vesicles to alter our epigenome, thus filling the gap and closing the circle. At the same time, there are indications that there could be a wider inter-kingdom communication network that might encompass all known kingdoms. Now that the connection with our other genome has been established, we also should begin to explore the 'social' network that we have around us.

lncRNATargets: A platform for lncRNA target prediction based on nucleic acid thermodynamics

Many studies have supported that long noncoding RNAs (lncRNAs) perform various functions in various critical biological processes. Advanced experimental and computational technologies allow access to more information on lncRNAs. Determining the functions and action mechanisms of these RNAs on a large scale is urgently needed. We provided lncRNATargets, which is a web-based platform for lncRNA target prediction based on nucleic acid thermodynamics. The nearest-neighbor (NN) model was used to calculate binging-free energy. The main principle of NN model for nucleic acid assumes that identity and orientation of neighbor base pairs determine stability of a given base pair. lncRNATargets features the following options: setting of a specific temperature that allow use not only for human but also for other animals or plants; processing all lncRNAs in high throughput without RNA size limitation that is superior to any other existing tool; and web-based, user-friendly interface, and colored result displays that allow easy access for nonskilled computer operators and provide better understanding of results. This technique could provide accurate calculation on the binding-free energy of lncRNA-target dimers to predict if these structures are well targeted together. lncRNATargets provides high accuracy calculations, and this user-friendly program is available for free at http://www.herbbol.org:8001/lrt/ .

Expression and diversification analysis reveals transposable elements play important roles in the origin of Lycopersicon-specific lncRNAs in tomato

Long noncoding RNAs (lncRNAs) regulate gene expression and biological processes. With the development of high-throughput RNA sequencing technology, lncRNAs have been extensively studied in recent years. Nevertheless, the expression and evolution of lncRNAs in plants remain poorly understood. Here, we identified 413 and 709 multi-exon noncoding transcripts from 353 and 595 loci of the cultivar tomato Heinz1706 and its wild relative LA1589, respectively. Systematic comparison of the sequence and expression of lncRNAs showed that they are poorly conserved in Solanaceae, with only < 0.4% lncRNAs present in all sequenced genomes of tomato and potato. Sequence analysis of Lycopersicon-specific lncRNA loci in Solanum lycopersicum and S. pennellii showed that the origins of these molecules are associated with transposable elements (TEs). LncRNA-314, a fruit-specific lncRNA expressed in S. lycopersicum and S. pimpinellifolium, but not in S. pennellii, originated through two evolutionary events: speciation of S. pennellii resulted in insertion of a long terminal repeat (LTR) retrotransposon into chromosome 10 and contributed to most of the transcribed region of lncRNA-314; and a large deletion in Lycopersicon generated the promoter region and part of the transcribed region of lncRNA-314. These results provide novel insights into the evolution of lncRNAs in plants.

A Bipartite Network-based Method for Prediction of Long Non-coding RNA-protein Interactions

As one large class of non-coding RNAs (ncRNAs), long ncRNAs (lncRNAs) have gained considerable attention in recent years. Mutations and dysfunction of lncRNAs have been implicated in human disorders. Many lncRNAs exert their effects through interactions with the corresponding RNA-binding proteins. Several computational approaches have been developed, but only few are able to perform the prediction of these interactions from a network-based point of view. Here, we introduce a computational method named lncRNA–protein bipartite network inference (LPBNI). LPBNI aims to identify potential lncRNA–interacting proteins, by making full use of the known lncRNA–protein interactions. Leave-one-out cross validation (LOOCV) test shows that LPBNI significantly outperforms other network-based methods, including random walk (RWR) and protein-based collaborative filtering (ProCF). Furthermore, a case study was performed to demonstrate the performance of LPBNI using real data in predicting potential lncRNA–interacting proteins.

Predicting Long Noncoding RNA and Protein Interactions Using Heterogeneous Network Model

Recent study shows that long noncoding RNAs (lncRNAs) are participating in diverse biological processes and complex diseases. However, at present the functions of lncRNAs are still rarely known. In this study, we propose a network-based computational method, which is called lncRNA-protein interaction prediction based on Heterogeneous Network Model (LPIHN), to predict the potential lncRNA-protein interactions. First, we construct a heterogeneous network by integrating the lncRNA-lncRNA similarity network, lncRNA-protein interaction network, and protein-protein interaction (PPI) network. Then, a random walk with restart is implemented on the heterogeneous network to infer novel lncRNA-protein interactions. The leave-one-out cross validation test shows that our approach can achieve an AUC value of 96.0%. Some lncRNA-protein interactions predicted by our method have been confirmed in recent research or database, indicating the efficiency of LPIHN to predict novel lncRNA-protein interactions.

Differential lncRNA‑mRNA co‑expression network analysis revealing the potential regulatory roles of lncRNAs in myocardial infarction

Previous studies have reported that long, non-coding RNAs (lncRNAs) are important in cardiovascular disease. However, the lncRNAs involved in myocardial infarction and their detailed mechanism have not been well characterized. In the present study, an affymetrix microarray associated with myocardial infarction was re-annotated, following which a myocardial infarction-related differential lncRNA-mRNA co-expression network (MILMN) was constructed. Subsequently, pathway enrichment analysis was used for all the mRNAs in the MILMN, and an lncRNA-pathway network was constructed. It was found that the mRNAs were predominantly involved in certain cardiovascular disease-associated pathway, for example the dilated cardiomyopathy and mitogen-activated protein kinase signaling pathway. Finally, a total of 39 key lncRNAs were identified, which regulate crucial pathways in myocardial infarction. Through pathway analysis of these 39 key lncRNAs, the novel function of an annotated lncRNAs-H19 was predicted, which may regulate apoptosis signal-regulating kinase, which is a protein that promotes pathological cardiac remodeling following myocardial infarction. The results of the present study not only provide potential non-coding RNA biomarkers, but also provide further insights into understanding the molecular mechanism of lncRNAs.

Exploration of Deregulated Long Non-Coding RNAs in Association with Hepatocarcinogenesis and Survival

Long non-coding RNAs (lncRNAs) are larger than 200 nucleotides in length and pervasively expressed across the genome. An increasing number of studies indicate that lncRNA transcripts play integral regulatory roles in cellular growth, division, differentiation and apoptosis. Deregulated lncRNAs have been observed in a variety of human cancers, including hepatocellular carcinoma (HCC). We determined the expression profiles of 90 lncRNAs for 65 paired HCC tumor and adjacent non-tumor tissues, and 55 lncRNAs were expressed in over 90% of samples. Eight lncRNAs were significantly down-regulated in HCC tumor compared to non-tumor tissues (p < 0.05), but no lncRNA achieved statistical significance after Bonferroni correction for multiple comparisons. Within tumor tissues, carrying more aberrant lncRNAs (6–7) was associated with a borderline significant reduction in survival (HR = 8.5, 95% CI: 1.0–72.5). The predictive accuracy depicted by the AUC was 0.93 for HCC survival when using seven deregulated lncRNAs (likelihood ratio test p = 0.001), which was similar to that combining the seven lncRNAs with tumor size and treatment (AUC = 0.96, sensitivity = 87%, specificity = 87%). These data suggest the potential association of deregulated lncRNAs with hepatocarcinogenesis and HCC survival.

Predicting the functions of long noncoding RNAs using RNA-seq based on Bayesian network

Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, we represent a framework to predict functions of lncRNAs through construction of a regulatory network between lncRNAs and protein-coding genes. Using RNA-seq data, the transcript profiles of lncRNAs and protein-coding genes are constructed. Using the Bayesian network method, a regulatory network, which implies dependency relations between lncRNAs and protein-coding genes, was built. In combining protein interaction network, highly connected coding genes linked by a given lncRNA were subsequently used to predict functions of the lncRNA through functional enrichment. Application of our method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. We found that lncRNAs are involved in diverse biological processes, such as tissue development or embryo development (e.g., nervous system development and mesoderm development). By comparison with functions inferred using the neighboring gene-based method and functions determined using lncRNA knockdown experiments, our method can provide comparable predicted functions of lncRNAs. Overall, our method can be applied to emerging RNA-seq data, which will help researchers identify complex relations between lncRNAs and coding genes and reveal important functions of lncRNAs.

Discovery of Protein-lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

A global view of network of lncRNAs and their binding proteins

Recently, the long non-coding RNAs (lncRNAs) have obtained wide attention because they have broad and crucial functions in regulating complex biological processes. Many lncRNAs functioned by interfacing with corresponding RNA binding proteins and the complexity of lncRNAs' function was attributed to multiple lncRNA-protein interactions. To gain insights into the global relationship between lncRNAs and their binding proteins, here we constructed a lncRNA-protein network (LPN) based on experimentally determined functional interactions between them. This network included 177 lncRNAs, 92 proteins and 683 relationships between them. Cluster analysis of LPN revealed that some proteins (such as AGO and IGFBP families) and lncRNA (such as XIST and MALAT1) were densely connected, suggesting the potential co-regulated mechanism and functional cross-talk of different lncRNAs. We then characterized the lncRNA functions and found that lncRNA binding proteins (LBPs) enriched in many cancer or cancer-related pathways. Finally, we investigated the different topological properties of LBPs in PPIs network. Compared with disease proteins and average ones, LBPs tend to have significantly higher degree, betweenness, and closeness but a relatively lower clustering coefficient, indicating their centrality and essentiality in the context of a biological network.

MicroRNAs in sensorineural diseases of the ear

Non-coding microRNAs (miRNAs) have a fundamental role in gene regulation and expression in almost every multicellular organism. Only discovered in the last decade, miRNAs are already known to play a leading role in many aspects of disease. In the vertebrate inner ear, miRNAs are essential for controlling development and survival of hair cells. Moreover, dysregulation of miRNAs has been implicated in sensorineural hearing impairment, as well as in other ear diseases such as cholesteatomas, vestibular schwannomas, and otitis media. Due to the inaccessibility of the ear in humans, animal models have provided the optimal tools to study miRNA expression and function, in particular mice and zebrafish. A major focus of current research has been to discover the targets of the miRNAs expressed in the inner ear, in order to determine the regulatory pathways of the auditory and vestibular systems. The potential for miRNAs manipulation in development of therapeutic tools for hearing impairment is as yet unexplored, paving the way for future work in the field.

Identification and characterization of long non-coding RNAs related to mouse embryonic brain development from available transcriptomic data

Long non-coding RNAs (lncRNAs) as a key group of non-coding RNAs have gained widely attention. Though lncRNAs have been functionally annotated and systematic explored in higher mammals, few are under systematical identification and annotation. Owing to the expression specificity, known lncRNAs expressed in embryonic brain tissues remain still limited. Considering a large number of lncRNAs are only transcribed in brain tissues, studies of lncRNAs in developmental brain are therefore of special interest. Here, publicly available RNA-sequencing (RNA-seq) data in embryonic brain are integrated to identify thousands of embryonic brain lncRNAs by a customized pipeline. A significant proportion of novel transcripts have not been annotated by available genomic resources. The putative embryonic brain lncRNAs are shorter in length, less spliced and show less conservation than known genes. The expression of putative lncRNAs is in one tenth on average of known coding genes, while comparable with known lncRNAs. From chromatin data, putative embryonic brain lncRNAs are associated with active chromatin marks, comparable with known lncRNAs. Embryonic brain expressed lncRNAs are also indicated to have expression though not evident in adult brain. Gene Ontology analysis of putative embryonic brain lncRNAs suggests that they are associated with brain development. The putative lncRNAs are shown to be related to possible cis-regulatory roles in imprinting even themselves are deemed to be imprinted lncRNAs. Re-analysis of one knockdown data suggests that four regulators are associated with lncRNAs. Taken together, the identification and systematic analysis of putative lncRNAs would provide novel insights into uncharacterized mouse non-coding regions and the relationships with mammalian embryonic brain development.

Long and short non-coding RNAs as regulators of hematopoietic differentiation

Genomic analyses estimated that the proportion of the genome encoding proteins corresponds to approximately 1.5%, while at least 66% are transcribed, suggesting that many non-coding DNA-regions generate non-coding RNAs (ncRNAs). The relevance of these ncRNAs in biological, physiological as well as in pathological processes increased over the last two decades with the understanding of their implication in complex regulatory networks. This review particularly focuses on the involvement of two large families of ncRNAs, namely microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in the regulation of hematopoiesis. To date, miRNAs have been widely studied, leading to a wealth of data about processing, regulation and mechanisms of action and more specifically, their involvement in hematopoietic differentiation. Notably, the interaction of miRNAs with the regulatory network of transcription factors is well documented whereas roles, regulation and mechanisms of lncRNAs remain largely unexplored in hematopoiesis; this review gathers current data about lncRNAs as well as both potential and confirmed roles in normal and pathological hematopoiesis.

Meeting the methodological challenges in molecular mapping of the embryonic epigenome

The past decade of life sciences research has been driven by progress in genomics. Many voices are already proclaiming the post-genomics era, in which phenomena other than sequence polymorphism influence gene expression and also explain complex phenotypes. One of these burgeoning fields is the study of the epigenome. Although the mechanisms by which chromatin structure and reorganization as well as cytosine methylation influence gene expression are not fully understood, they are being invoked to explain the now-accepted long-term impact of the environment on gene expression, which appears to be a factor in the development of numerous diseases. Such studies are particularly relevant in early embryonic development, during which waves of epigenetic reprogramming are known to have profound impacts. Since gametes and zygotes are in the process of resetting the genome in order to create embryonic stem cells that will each differentiate to create one of many specific tissue types, this phase of life is now viewed as a window of susceptibility to epigenetic reprogramming errors. Epigenetics could explain the influence of factors such as the nutritional/metabolic status of the mother or the artificial environment of assisted reproductive technologies. However, the peculiar nature of early embryos in addition to their scarcity poses numerous technological challenges that are slowly being overcome. The principal subject of this article is to review the suitability of various current and emerging technological platforms to study oocytes and early embryonic epigenome with more emphasis on studying DNA methylation. Furthermore, the constraint of samples size, inherent to the study of preimplantation embryo development, was put in perspective with the various molecular platforms described.

Long noncoding RNAs-related diseases, cancers, and drugs

Long noncoding RNA (lncRNA) function is described in terms of related gene expressions, diseases, and cancers as well as their polymorphisms. Potential modulators of lncRNA function, including clinical drugs, natural products, and derivatives, are discussed, and bioinformatic resources are summarized. The improving knowledge of the lncRNA regulatory network has implications not only in gene expression, diseases, and cancers, but also in the development of lncRNA-based pharmacology.

Regulatory Roles for Long ncRNA and mRNA

Recent advances in high-throughput sequencing technology have identified the transcription of a much larger portion of the genome than previously anticipated. Especially in the context of cancer it has become clear that aberrant transcription of both protein-coding and long non-coding RNAs (lncRNAs) are frequent events. The current dogma of RNA function describes mRNA to be responsible for the synthesis of proteins, whereas non-coding RNA can have regulatory or epigenetic functions. However, this distinction between protein coding and regulatory ability of transcripts may not be that strict. Here, we review the increasing body of evidence for the existence of multifunctional RNAs that have both protein-coding and trans-regulatory roles. Moreover, we demonstrate that coding transcripts bind to components of the Polycomb Repressor Complex 2 (PRC2) with similar affinities as non-coding transcripts, revealing potential epigenetic regulation by mRNAs. We hypothesize that studies on the regulatory ability of disease-associated mRNAs will form an important new field of research.

Recent insights and novel bioinformatics tools to understand the role of microRNAs binding to 5' untranslated region

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression through the binding of the 3′ untranslated region (3′UTR) of specific mRNAs. MiRNAs are post-transcriptional regulators and determine the repression of translation processes or the degradation of mRNA targets. Recently, another kind of miRNA-mediated regulation of translation (repression or activation) involving the binding of miRNA to the 5′UTR of target gene has been reported. The possible interactions and the mechanism of action have been reported in many works that we reviewed here. Moreover, we discussed also the available bioinformatics tools for predicting the miRNA binding sites in the 5′UTR and public databases collecting this information.

Long non-coding RNAs and p53 regulation

The advent of novel and high-throughput sequencing (next generation) technologies allowed for the sequencing of the genome at an unprecedented depth. The majority of transcribed RNAs have been classified as non-coding RNAs. Among them, long non-coding RNAs (lncRNAs) are emerging as important regulators in many biological processes. Here, we discuss the role of those lncRNAs which are under the control of p53 or that are able to regulate its activity, due to the central role of p53 pathway in many conditions. We also briefly discussed the emerging need of having novel strategies and computational tools to completely unravel the multifaceted roles of lncRNAs and to pave the way to the development of novel diagnostic and therapeutic applications based on these peculiar molecules.

Computational prediction of polycomb-associated long non-coding RNAs

Among thousands of long non-coding RNAs (lncRNAs) only a small subset is functionally characterized and the functional annotation of lncRNAs on the genomic scale remains inadequate. In this study we computationally characterized two functionally different parts of human lncRNAs transcriptome based on their ability to bind the polycomb repressive complex, PRC2. This classification is enabled by the fact that while all lncRNAs constitute a diverse set of sequences, the classes of PRC2-binding and PRC2 non-binding lncRNAs possess characteristic combinations of sequence-structure patterns and, therefore, can be separated within the feature space. Based on the specific combination of features, we built several machine-learning classifiers and identified the SVM-based classifier as the best performing. We further showed that the SVM-based classifier is able to generalize on the independent data sets. We observed that this classifier, trained on the human lncRNAs, can predict up to 59.4% of PRC2-binding lncRNAs in mice. This suggests that, despite the low degree of sequence conservation, many lncRNAs play functionally conserved biological roles.