Structure Prediction: New Insights into Decrypting Long Noncoding RNAs

Long non-coding RNAs as pathophysiological regulators, therapeutic targets and novel extracellular vesicle biomarkers for the diagnosis of inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic relapsing disease of the gastrointestinal (GI) system that includes two groups, Crohn's disease (CD) and ulcerative colitis (UC). To cope with these two classes of IBD, the investigation of pathogenic mechanisms and the discovery of new diagnostic and therapeutic approaches are crucial. Long non-coding RNAs (lncRNAs) which are non-coding RNAs with a length of longer than 200 nucleotides have indicated significant association with the pathology of IBD and strong potential to be used as accurate biomarkers in diagnosing and predicting responses to the IBD treatment. In the current review, we aim to investigate the role of lncRNAs in the pathology and development of IBD. We first describe recent advances in research on dysregulated lncRNAs in the pathogenesis of IBD from the perspective of epithelial barrier function, intestinal immunity, mitochondrial function, and intestinal autophagy. Then, we highlight the possible translational role of lncRNAs as therapeutic targets, diagnostic biomarkers, and predictors of therapeutic response in colon tissues and plasma samples. Finally, we discuss the potential of extracellular vesicles and their lncRNA cargo in the pathophysiology, diagnosis, and treatment of IBD.

Unraveling the intriguing interplay: Exploring the role of lncRNAs in caspase-independent cell death

Cell death plays a crucial role in various physiological and pathological processes. Until recently, programmed cell death was mainly attributed to caspase-dependent apoptosis. However, emerging evidence suggests that caspase-independent cell death (CICD) mechanisms also contribute significantly to cellular demise. We and others have reported and functionally characterized numerous long noncoding RNAs (lncRNAs) that modulate caspase-dependent apoptotic pathways potentially in a pathway-dependent manner. However, the interplay between lncRNAs and CICD pathways has not been comprehensively documented. One major reason for this is that most CICD pathways have been recently discovered with some being partially characterized at the molecular level. In this review, we discuss the emerging evidence that implicates specific lncRNAs in the regulation and execution of CICD. We summarize the diverse mechanisms through which lncRNAs modulate different forms of CICD, including ferroptosis, necroptosis, cuproptosis, and others. Furthermore, we highlight the intricate regulatory networks involving lncRNAs, protein-coding genes, and signaling pathways that orchestrate CICD in health and disease. Understanding the molecular mechanisms and functional implications of lncRNAs in CICD may unravel novel therapeutic targets and diagnostic tools for various diseases, paving the way for innovative strategies in disease management and personalized medicine. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Long noncoding RNA #61 exerts a broad anti-influenza a virus effect by its long arm rings

Emerging evidence has demonstrated the critical role of long noncoding RNAs (lncRNAs) in regulating gene expression. However, the functional significance and mechanisms underlying influenza A virus (IAV)-host lncRNA interactions are still elusive. Here, we identified a functional lncRNA, LncRNA#61, as a broad anti-IAV factor. LncRNA#61 is highly upregulated by different subtypes of IAV, including human H1N1 virus and avian H5N1 and H7N9 viruses. Furthermore, nuclear-enriched LncRNA#61 can translocate from the nucleus to the cytoplasm soon after IAV infection. Forced LncRNA#61 expression dramatically impedes viral replication of various subtypes of IAV, including human H1N1 virus and avian H3N2/N8, H4N6, H5N1, H6N2/N8, H7N9, H8N4, H10N3, H11N2/N6/N9 viruses. Conversely, abolishing LncRNA#61 expression substantially favored viral replication. More importantly, LncRNA#61 delivered by the lipid nanoparticle (LNP)-encapsulated strategy shows good performance in restraining viral replication in mice. Interestingly, LncRNA#61 is involved in multiple steps of the viral replication cycle, including virus entry, viral RNA synthesis and the virus release period. Mechanistically, the four long ring arms of LncRNA#61 mainly mediate its broad antiviral effect and contribute to its inhibition of viral polymerase activity and nuclear aggregation of key polymerase components. Therefore, we defined LncRNA#61 as a potential broad-spectrum antiviral factor for IAV. Our study further extends our understanding of the stunning and unanticipated biology of lncRNAs as well as their close interaction with IAV, providing valuable clues for developing novel broad anti-IAV therapeutics targeting host lncRNAs.

GM-lncLoc: LncRNAs subcellular localization prediction based on graph neural network with meta-learning

In recent years, a large number of studies have shown that the subcellular localization of long non-coding RNAs (lncRNAs) can bring crucial information to the recognition of lncRNAs function. Therefore, it is of great significance to establish a computational method to accurately predict the subcellular localization of lncRNA. Previous prediction models are based on low-level sequences information and are troubled by the few samples problem. In this study, we propose a new prediction model, GM-lncLoc, which is based on the initial information extracted from the lncRNA sequence, and also combines the graph structure information to extract high level features of lncRNA. In addition, the training mode of meta-learning is introduced to obtain meta-parameters by training a series of tasks. With the meta-parameters, the final parameters of other similar tasks can be learned quickly, so as to solve the problem of few samples in lncRNA subcellular localization. Compared with the previous methods, GM-lncLoc achieved the best results with an accuracy of 93.4 and 94.2% in the benchmark datasets of 5 and 4 subcellular compartments, respectively. Furthermore, the prediction performance of GM-lncLoc was also better on the independent dataset. It shows the effectiveness and great potential of our proposed method for lncRNA subcellular localization prediction. The datasets and source code are freely available at https://github.com/JunzheCai/GM-lncLoc .

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) originates in the squamous cell lining the mucosal surfaces of the head and neck region, including the oral cavity, nasopharynx, tonsils, oropharynx, larynx, and hypopharynx. The heterogeneity, anatomical, and functional characteristics of the patient make the HNSCC a complex and difficult-to-treat disease, leading to a poor survival rate and a decreased quality of life due to the loss of important physiologic functions and aggressive surgical injury. Alteration of driver-oncogenic and tumor-suppressing lncRNAs has recently been recently in HNSCC to obtain possible biomarkers for diagnostic, prognostic, and therapeutic approaches. This review provides current knowledge about the implication of lncRNAs in drug resistance mechanisms in HNSCC. Chemotherapy resistance is a major therapeutic challenge in HNSCC in which lncRNAs are implicated. Lately, it has been shown that lncRNAs involved in autophagy induced by chemotherapy and epithelial–mesenchymal transition (EMT) can act as mechanisms of resistance to anticancer drugs. Conversely, lncRNAs involved in mesenchymal–epithelial transition (MET) are related to chemosensitivity and inhibition of invasiveness of drug-resistant cells. In this regard, long non-coding RNAs (lncRNAs) play a pivotal role in both processes and are important for cancer detection, progression, diagnosis, therapy response, and prognostic values. As the involvement of more lncRNAs is elucidated in chemoresistance mechanisms, an improvement in diagnostic and prognostic tools could promote an advance in targeted and specific therapies in precision oncology.

Plasmodium manipulates the expression of host long non-coding RNA during red blood cell intracellular infection

BACKGROUND

Parasites interact with their host through "direct" and/or "indirect" mechanisms. Plasmodium, for example, either mediates direct physical interactions with host factors or triggers the immune system of the host indirectly, leading to changes in infectious outcomes. Long non-coding RNAs (lncRNAs) participate in regulating biological processes, especially host-pathogen interactions. However, research on the role of host lncRNAs during Plasmodium infection is limited.

METHODS

A RNA sequencing method (RNA-seq) was used to confirm the differential expression profiles of lncRNAs in Plasmodium yeolii 17XL (P.y17XL)-infected BALB/c mice. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to elucidate the potential functions of Plasmodium-induced genes. Subsequently, the effect of specific lncRNAs on the modulation of immune-related signaling pathways in malaria was determined by fluorescence-activated cell sorting, western blot and enzyme-linked immunosorbent assay.

RESULTS

The data showed that in P.y17XL-infected BALB/c mice, Plasmodium upregulated the expression of 132 lncRNAs and downregulated the expression of 159 lncRNAs. Differentially expressed lncRNAs clearly associated with malaria infection were annotated, including four novel dominant lncRNAs: ENMSUSG00000111521.1, XLOC_038009, XLOC_058629 and XLOC_065676. GO and KEGG pathway analyses demonstrated that these four differentially expressed lncRNAs were associated with co-localized/co-expressed protein-coding genes that were totally enriched in malaria and with the transforming growth factor beta (TGF-β) signaling pathway. Using the models of P.y17XL-infected BALB/c mice, data certified that the level of TGF-β production and activation of TGF-β/Smad_2/3 signaling pathway were obviously changed in malaria infection.

CONCLUSIONS

These differentially expressed immune-related genes were deemed to have a role in the process of Plasmodium infection in the host via dendritic/T regulatory cells and the TGF-β/Smad_2/3 signaling pathway. The results of the present study confirmed that Plasmodium infection-induced lncRNA expression is a novel mechanism used by Plasmodium parasites to modify host immune signaling. These results further enhance current understanding of the interaction between Plasmodium and host cells.

Long noncoding RNA Lnc-DIF inhibits bone formation by sequestering miR-489-3p

Osteoporosis has become a high incident bone disease along with the aging of human population. Long noncoding RNAs (LncRNAs) play an important role in osteoporosis incidence. In this study, we screened out an LncRNA negatively correlated with osteoblast differentiation, which was therefore named Lnc-DIF (differentiation inhibiting factor). Functional analysis proved that Lnc-DIF inhibited bone formation. A special structure containing multiple 53 nucleotide repeats was found in the trailing end of Lnc-DIF. Our study suggested that this repeat sequence could sequester multiple miR-489-3p and inhibit bone formation through miR-489-3p/SMAD2 axis. Moreover, siRNA of Lnc-DIF would rescue bone formation in both aging and ovariectomized osteoporosis mice. This study revealed a kind of LncRNA that could function as a sponge and regulate multiple miRNAs. RNA therapy techniques that target these LncRNAs could manipulate its downstream miRNA-target pathway with significantly higher efficiency and specificity. This provided potential therapeutic insight for RNA-based therapy for osteoporosis.

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Identified LncRNA Lnc-DIF that inhibited bone formation

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Lnc-DIF sequestered multiple miR-489-3p by the repeat sequences on its trailing end

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Lnc-DIF repeat sequence inhibited bone formation via miR-489-3p/SMAD2 axis

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Lnc-DIF siRNA showed strong capability on rescuing osteoporosis

Prediction of RNA subcellular localization: Learning from heterogeneous data sources

RNA subcellular localization has recently emerged as a widespread phenomenon, which may apply to the majority of RNAs. The two main sources of data for characterization of RNA localization are sequence features and microscopy images, such as obtained from single-molecule fluorescent in situ hybridization-based techniques. Although such imaging data are ideal for characterization of RNA distribution, these techniques remain costly, time-consuming, and technically challenging. Given these limitations, imaging data exist only for a limited number of RNAs. We argue that the field of RNA localization would greatly benefit from complementary techniques able to characterize location of RNA. Here we discuss the importance of RNA localization and the current methodology in the field, followed by an introduction on prediction of location of molecules. We then suggest a machine learning approach based on the integration between imaging localization data and sequence-based data to assist in characterization of RNA localization on a transcriptome level.

Long noncoding RNA GAS8-AS1: A novel biomarker in human diseases

Long non-coding RNAs (lncRNAs) represent a group of ncRNAs with more than 200 nucleotides. These RNAs can specifically regulate gene expression at both the transcriptional and the post-transcriptional levels, and increasing evidence indicates that they play vital roles in a variety of disease-related cellular processes. The lncRNA GAS8 antisense RNA 1 (GAS8-AS1, also known as C16orf3) is located in the second intron of GAS8 and has been reported to be both abnormally expressed in several diseases and closely correlated with many clinical characteristics. GAS8-AS1 has been shown to affect many biological functions, including cell proliferation, migration, invasiveness, and autophagy using several signaling pathways. In this review, we have summarized current studies on GAS8-AS1 roles in disease and discuss its potential clinical utility. GAS8-AS1 may be a promising biomarker for both diagnoses and prognoses, and a novel target for many disease therapies.

DMS-MaPseq for Genome-Wide or Targeted RNA Structure Probing In Vitro and In Vivo

DMS-MaPseq is a chemical probing method combined with high throughput sequencing used to study RNA structure. Here we present a flexible protocol for adherent and suspension mammalian cells to analyze RNA structure in vitro or in vivo. The protocol provides instruction on either a targeted sequencing of a lncRNA of interest or a transcriptome-wide approach that provides structural data on all expressed RNAs, including lncRNAs. This technique is particularly useful for comparing in vitro and in vivo structure of RNAs, determining how mutations and polymorphisms with phenotypic effects influence RNA structure and analyzing RNA structure across the entire transcriptome.

Long noncoding RNA AK039312 and AK079370 inhibits bone formation via miR-199b-5p

Osteoporosis caused by aging and menopause had become an emerging threat to human health. The reduction of osteoblast differentiation has been considered to be an essential cause of osteoporosis. Osteoblast differentiation could be regulated by LncRNAs, and increasing evidences have proved that LncRNAs may be adopted as potential therapeutic targets for osteoporosis. However, reports on rescue effects of LncRNAs in vivo are relatively limited. In this study, two LncRNAs (AK039312 and AK079370) were screened as osteogenic related LncRNAs. Both AK039312 and AK079370 could inhibit osteoblast differentiation and bone formation through suppressing osteogenic transcription factors. This inhibitory effect was achieved via binding and sequestering miR-199b-5p, and enhanced GSK-3β which further inhibited wnt/β-catenin pathway. Moreover, the siRNAs of AK039312 and AK079370 significantly alleviated postmenopausal osteoporosis, and the combination of si-AK039312 and si-AK079370 was more efficient than applying one si-LncRNA alone. This study has provided new insights for the therapy of osteoporosis.

From structure to function: Route to understanding lncRNA mechanism

RNAs have emerged as a major target for diagnostics and therapeutics approaches. Regulatory nonprotein-coding RNAs (ncRNAs) in particular display remarkable versatility. They can fold into complex structures and interact with proteins, DNA, and other RNAs, thus modulating activity, localization, or interactome of multi-protein complexes. Thus, ncRNAs confer regulatory plasticity and represent a new layer of regulatory control. Interestingly, long noncoding RNAs (lncRNAs) tend to acquire complex secondary and tertiary structures and their function-in many cases-is dependent on structural conservation rather than primary sequence conservation. Whereas for many proteins, structure and its associated function are closely connected, for lncRNAs, the structural domains that determine functionality and its interactome are still not well understood. Numerous approaches for analyzing the structural configuration of lncRNAs have been developed recently. Here, will provide an overview of major experimental approaches used in the field, and discuss the potential benefit of using combinatorial strategies to analyze lncRNA modes of action based on structural information.

Long non-coding RNAs in liver diseases: Focusing on nonalcoholic fatty liver disease, alcohol-related liver disease, and cholestatic liver disease

Long non-coding RNAs (lncRNAs), a class of transcribed RNA molecules with the lengths exceeding 200 nucleotides, are not translated into protein. They can modulate protein-coding genes by controlling transcriptional and posttranscriptional processes. The dysregulation of lncRNAs has been related to various pathological disorders. In this review, we summarized the current knowledge of lncRNAs and their implications in the pathogenesis of three common liver diseases: nonalcoholic fatty liver disease, alcohol-related liver disease, and cholestatic liver disease. Future studies to further define the role of lncRNAs and their mechanisms in various types of liver diseases should be explored. An improved understanding from these studies will provide us a useful perspective leading to mechanism-based intervention by targeting specific lncRNAs for the treatment of liver diseases.

Long Noncoding RNAs Coregulated by Annexin A7 and JNK in Hepatocellular Carcinoma Cells Identified by Whole-Genome Expression Profiling

Knockdown of Annexin A7 (ANXA7) or C-Jun N-terminal kinase (JNK) inhibits the proliferation, migration, invasion, and lymphatic adhesion of hepatocellular carcinoma (HCC) cells, suggesting that ANXA7 and JNK signaling pathways contribute to HCC growth and lymph node metastasis (LNM). While the intervening molecular pathways are largely unknown, emerging evidence suggests that long noncoding RNAs (lncRNAs) participate in ANXA7 and JNK signaling. To identify potential therapeutic targets for HCC, we screened for lncRNAs differentially expressed among Hca-P cells stably expressing shRNA-ANXA7, shRNA-JNK, or control-shRNA. RNA sequencing identified 216 lncRNAs differentially expressed between shRNA-ANXA7 and control-shRNA cells, of which 101 were downregulated and 115 upregulated, as well as 436 lncRNAs differentially expressed between shRNA-JNK and control-shRNA cells, of which 236 were downregulated and 200 upregulated. Fifty-six lncRNAs were differentially expressed under both ANXA7 and JNK knockdown. We selected 4 of these for verification based on putative involvement in cancer regulation according to GO and KEEG analyses of target genes. Knockdown of ANXA7 or JNK suppressed expression of NONMMUT012084.2, NONMMUT024756.2, and ENSMUST00000130486, and enhanced expression of ENSMUST00000197932. These lncRNAs are intriguing candidate targets for mechanistic analysis of HCC progression and therapeutic intervention.

Assembly and Stability of Simian Virus 40 Polymorphs

Understanding viral assembly pathways is of critical importance to biology, medicine, and nanotechology. Here, we study the assembly path of a system with various structures, the simian vacuolating virus 40 (SV40) polymorphs. We simulate the templated assembly process of VP1 pentamers, which are the constituents of SV40, into icosahedal shells made of N = 12 pentamers (T = 1). The simulations include connections formed between pentamers by C-terminal flexible lateral units, termed here "C-terminal ligands", which are shown to control assembly behavior and shell dynamics. The model also incorporates electrostatic attractions between the N-terminal peptide strands (ligands) and the negatively charged cargo, allowing for agreement with experiments of RNA templated assembly at various pH and ionic conditions. During viral assembly, pentamers bound to any template increase its effective size due to the length and flexibility of the C-terminal ligands, which can connect to other VP1 pentamers and recruit them to a partially completed capsid. All closed shells formed other than the T = 1 feature the ability to dynamically rearrange and are thus termed "pseudo-closed". The N = 13 shell can even spontaneously "self-correct" by losing a pentamer and become a T = 1 capsid when the template size fluctuates. Bound pentamers recruiting additional pentamers to dynamically rearranging capsids allow closed shells to continue growing via the pseudo-closed growth mechanism, for which experimental evidence already exists. Overall, we show that the C-terminal ligands control the dynamic assembly paths of SV40 polymorphs.

Analysis of lncRNA-miRNA-mRNA Interactions in Hyper-proliferative Human Pulmonary Arterial Smooth Muscle Cells

We previously reported enhanced proliferation of smooth muscle cells on the combined exposure of HIV proteins and cocaine leading to the development of HIV-pulmonary arterial hypertension. Here, we attempt to comprehensively understand the interactions between long noncoding RNAs (lncRNAs), mRNAs and micro-RNAs (miRNAs) to determine their role in smooth muscle hyperplasia. Differential expression of lncRNAs, mRNAs and miRNAs were obtained by microarray and small-RNA sequencing from HPASMCs treated with and without cocaine and/or HIV-Tat. LncRNA to mRNA associations were conjectured by analyzing their genomic proximity and by interrogating their association to vascular diseases and cancer co-expression patterns reported in the relevant databases. Neuro-active ligand receptor signaling, Ras signaling and PI3-Akt pathway were among the top pathways enriched in either differentially expressed mRNAs or mRNAs associated to lncRNAs. HPASMC with combined exposure to cocaine and Tat (C + T) vs control identified the following top lncRNA-mRNA pairs, ENST00000495536-HOXB13, T216482-CBL, ENST00000602736-GDF7, and, TCONS_00020413-RND1. Many of the down-regulated miRNAs in the HPASMCs treated with C + T were found to be anti-proliferative and targets of up-regulated lncRNAs targeting up-regulated mRNAs, including down-regulation of miR-185, -491 and up-regulation of corresponding ENST00000585387. Specific knock down of the selected lncRNAs highlighted the importance of non-coding RNAs in smooth muscle hyperplasia.

Workflow Development for the Functional Characterization of ncRNAs

During the last decade, ncRNAs have been investigated intensively and revealed their regulatory role in various biological processes. Worldwide research efforts have identified numerous ncRNAs and multiple RNA subtypes, which are attributed to diverse functionalities known to interact with different functional layers, from DNA and RNA to proteins. This makes the prediction of functions for newly identified ncRNAs challenging. Current bioinformatics and systems biology approaches show promising results to facilitate an identification of these diverse ncRNA functionalities. Here, we review (a) current experimental protocols, i.e., for Next Generation Sequencing, for a successful identification of ncRNAs; (b) sequencing data analysis workflows as well as available computational environments; and (c) state-of-the-art approaches to functionally characterize ncRNAs, e.g., by means of transcriptome-wide association studies, molecular network analyses, or artificial intelligence guided prediction. In addition, we present a strategy to cover the identification and functional characterization of unknown transcripts by using connective workflows.

Selection of a DNA Aptamer against Zearalenone and Docking Analysis for Highly Sensitive Rapid Visual Detection with Label-Free Aptasensor

Contamination of feed with zearalenone (ZEN) presents a significant risk to animal health. Here, a visible, rapid, and cost-effective aptamer-based method is described for the detection of ZEN. After 8 rounds of SELEX (systematic evolution of ligands by exponential enrichment) with an affinity-based monitor and counter-screening process, the ssDNA aptamer Z100 was obtained, which had high affinity (dissociation constant = 15.2 ± 3.4 nM) and good specificity. Docking analysis of Z100 indicated that noncovalent bonds (π-π interactions, hydrogen bonds, and hydrophobic interactions) helped ZEN to anchor in the binding sites. Finally, a label-free detection method based on gold nanoparticles and Z100 at 0.25 μM was developed for ZEN determination. Excellent linearity was achieved, and the lowest detection limit was 12.5 nM. This rapid and simple method for ZEN analysis has high sensitivity and can be applied for on-site detection of ZEN in animal feeds.

Prediction of LncRNA Subcellular Localization with Deep Learning from Sequence Features

Long non-coding RNAs are involved in biological processes throughout the cell including the nucleus, chromatin and cytosol. However, most lncRNAs remain unannotated and functional annotation of lncRNAs is difficult due to their low conservation and their tissue and developmentally specific expression. LncRNA subcellular localization is highly informative regarding its biological function, although it is difficult to discover because few prediction methods currently exist. While protein subcellular localization prediction is a well-established research field, lncRNA localization prediction is a novel research problem. We developed DeepLncRNA, a deep learning algorithm which predicts lncRNA subcellular localization directly from lncRNA transcript sequences. We analyzed 93 strand-specific RNA-seq samples of nuclear and cytosolic fractions from multiple cell types to identify differentially localized lncRNAs. We then extracted sequence-based features from the lncRNAs to construct our DeepLncRNA model, which achieved an accuracy of 72.4%, sensitivity of 83%, specificity of 62.4% and area under the receiver operating characteristic curve of 0.787. Our results suggest that primary sequence motifs are a major driving force in the subcellular localization of lncRNAs.

Landscape of SNPs-mediated lncRNA structural variations and their implication in human complex diseases

An increasing number of functional studies shows that long noncoding RNAs (lncRNAs) are involved in many aspects of cellular physiology and fulfills a wide variety of regulatory roles at almost every stage of gene expression. A major feature of lncRNAs is the highly folded modular domains in transcripts. With improved modeling and definition, it is now feasible to explore and gain novel insights into the structural-functional relationship of lncRNAs and their association with complex human diseases. In this study, we utilized an automatic computational pipeline to scan lncRNA architecture at the genome-wide scale and to obtain a landscape of functional domains. An accurate alignment algorithm was performed to identify 40 triple pairs between single-nucleotide polymorphisms (SNPs), lncRNAs and diseases. In order to detect the potential contribution of a lncRNA's modular character, we estimated and evaluated structural rearrangements, which were derived from disease-associated SNPs. In addition, we focused on annotating and comparing the global and local heterogeneity of the wild-type and mutant lncRNAs. Assessing lncRNA architecture has yielded how variations in structured regions impact the molecular mechanisms of lncRNAs and how SNPs disturb binding and recruiting ability. These observations are the first glimpse of the 'lncRNA structurome' and make it possible to robustly explore and assemble intricate space conformation and their stress variation. This result also successfully demonstrates that lncRNA transcripts contain a complex structural landscape and highlights the proposed contribution of lncRNA structure in controlling RNA functions and disease mechanisms.

Epigenomic regulation of heart failure: integrating histone marks, long noncoding RNAs, and chromatin architecture

Epigenetic processes are known to have powerful roles in organ development across biology. It has recently been found that some of the chromatin modulatory machinery essential for proper development plays a previously unappreciated role in the pathogenesis of cardiac disease in adults. Investigations using genetic and pharmacologic gain- and loss-of-function approaches have interrogated the function of distinct epigenetic regulators, while the increased deployment of the suite of next-generation sequencing technologies have fundamentally altered our understanding of the genomic targets of these chromatin modifiers. Here, we review recent developments in basic and translational research that have provided tantalizing clues that may be used to unlock the therapeutic potential of the epigenome in heart failure. Additionally, we provide a hypothesis to explain how signal-induced crosstalk between histone tail modifications and long non-coding RNAs triggers chromatin architectural remodeling and culminates in cardiac hypertrophy and fibrosis.

Long Noncoding RNAs and Cardiac Disease

SIGNIFICANCE

To maintain homeostasis, gene expression has to be tightly regulated by complex and multiple mechanisms occurring at the epigenetic, transcriptional, and post-transcriptional levels. One crucial regulatory component is represented by long noncoding RNAs (lncRNAs), nonprotein-coding RNA species implicated in all of these levels. Thus, lncRNAs have been associated with any given process or pathway of interest in a variety of systems, including the heart. Recent Advances: Mounting evidence implicates lncRNAs in cardiovascular diseases (CVD) and progression and their presence in the blood of heart disease patients indicates that they are attractive potential biomarkers.

CRITICAL ISSUES

Our understanding of the regulation and molecular mechanisms of action of most lncRNAs remains rudimentary. A challenge is represented by their often low evolutionary sequence conservation that limits the use of animal models for preclinical studies. Nevertheless, a growing number of lncRNAs with an impact on heart function is rapidly accumulating. In this study, we will discuss (i) lncRNAs that control heart homeostasis and disease; (ii) concepts, approaches, and methodologies necessary to study lncRNAs in the heart; and (iii) challenges posed and opportunities presented by lncRNAs as potential therapeutic targets and biomarkers.

FUTURE DIRECTIONS

A deeper knowledge of the molecular mechanisms underpinning CVDs is necessary to develop more effective treatments. Further studies are needed to clarify the regulation and function of lncRNAs in the heart before they can be considered as therapeutic targets and disease biomarkers. Antioxid. Redox Signal. 29, 880-901.

lncRNA involvement in hepatocellular carcinoma metastasis and prognosis

Eukaryotic lncRNAs are RNA molecules defined to be greater than 200 bp in length that are not translated to a protein and operate through several mechanisms, including participating in chromatin remodeling and methylation, influencing the integrity and stability of proteins and complexes, or acting as a sponge for miRNA inhibition. A number of recent studies have concentrated on the relationship between long non-coding RNAs (lncRNAs) and cancer. Hepatocellular carcinoma (HCC) is the most prevalent histological type of liver tumors, accounting for about 80 % of the cases worldwide. Lack of proper molecular markers for diagnosis of HCC and treatment evaluation is a significant problem. Dysregulated expression of HCC-related lncRNAs such as MEG-3, MALAT1, HULC, HOTAIR, and H19 have been identified and closely related with tumorigenesis, metastasis, prognosis and diagnosis. In this review, we summarized recent highlighted functions and molecular mechanisms of the most extensively studied lncRNAs in the pathophysiology of hepatocellular carcinoma and their potential for serving as probable therapeutic targets.

Long non-coding RNAs in the failing heart and vasculature

Following completion of the human genome, it became evident that the majority of our DNA is transcribed into non-coding RNAs (ncRNAs) instead of protein-coding messenger RNA. Deciphering the function of these ncRNAs, including both small- and long ncRNAs (lncRNAs), is an emerging field of research. LncRNAs have been associated with many disorders and a number have been identified as key regulators in the development and progression of disease, including cardiovascular disease (CVD). CVD causes millions of deaths worldwide, annually. Risk factors include coronary artery disease, high blood pressure and ageing. In this review, we will focus on the roles of lncRNAs in the cellular and molecular processes that underlie the development of CVD: cardiomyocyte hypertrophy, fibrosis, inflammation, vascular disease and ageing. Finally, we discuss the biomarker and therapeutic potential of lncRNAs.

Epigenetics and bone diseases

Owing to the development of new technologies, the epigenome, a second dimensional method for genome analysis has emerged. Epigenetic mechanisms, including DNA methylation, histone modifications and noncoding RNAs, regulate gene expression without changing the genetic sequence. These epigenetic mechanisms normally modulate gene expression, trans-generational effects and inherited expression states in various biological processes. Abnormal epigenetic patterns typically cause pathological conditions, including cancers, age-related diseases, and specific cartilage and bone diseases. Facing the rapidly developing epigenetic field, we reviewed epigenetic mechanisms and their involvement with the skeletal system and their role in skeletal development, homeostasis and degeneration. Finally, we discuss the prospects for the future of epigenetics.

Long noncoding RNAs and cancer, an overview

Long noncoding RNAs (lncRNAs) are implicated in several biological processes, including but not limited to cardiovascular physiology, reproduction, differentiation, metabolism, DNA repair, and inflammation. Under normal physiological conditions, expression of lncRNAs is tissue-specific and tightly regulated. In contrast, prevalent cancer types exhibit aberrant expression of lncRNAs. In this context, lncRNAs can drive cancer cell characteristics by controlling gene expression programs related to tumor suppressive and oncogenic functions. Hence, they can be excellent biomarkers and targets for therapeutic intervention in cancers. Understanding the molecular mechanisms by which lncRNAs drive cancer progression will improve our understanding of the etiology of cancer and suggest new ways to treat this disease. This review will provide a perspective on the role of lncRNAs in cancer initiation and progression.

Allelic RNA Motifs in Regulating Systemic Trafficking of Potato Spindle Tuber Viroid

Intercellular RNA trafficking has been shown as a widely-existing phenomenon that has significant functions in many aspects of biology. Viroids, circular noncoding RNAs that cause plant diseases, have been a model to dissect the role of RNA structural motifs in regulating intercellular RNA trafficking in plants. Recent studies on potato spindle tuber viroid (PSTVd) showed that the RNA motif loop 19 is important for PSTVd to spread from palisade to spongy mesophyll in infected leaves. Here, we performed saturated mutational analysis to uncover all possible functional variants of loop 19 and exploit this data to pinpoint to a three-dimensional structural model of this motif. Interestingly, we found that two distinct structural motifs can replace loop 19 and retain the systemic trafficking capacity. One of the alternative structures rapidly emerged from the inoculation using a loop 19 abolished mutant that is not capable of systemic trafficking. Our observation indicates the flexibility of multiple structural arrangements interchangeably exerting similar function at a particular RNA locus. Taken together, this study deepens the understanding of RNA structural motifs-regulated viroid RNA trafficking, which has broad implications for studying RNA intercellular trafficking as well.

Cytoplasmic functions of long noncoding RNAs

Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides found throughout the cell that lack protein-coding function. Their functions are closely linked to their interaction with RNA-binding proteins (RBPs) and nucleic acids. Nuclear lncRNAs have been studied extensively, revealing complexes with structural and regulatory roles that enable gene organization and control transcription. Cytoplasmic lncRNAs are less well understood, but accumulating evidence indicates that they also form complexes with diverse structural and regulatory functions. Here, we review our current knowledge of cytoplasmic lncRNAs and the different levels of gene regulation controlled by cytoplasmic lncRNA complexes, including mRNA turnover, translation, protein stability, sponging of cytosolic factors, and modulation of signaling pathways. We conclude by discussing areas of future study needed to elucidate comprehensively the biology of lncRNAs, to further understand the impact of lncRNAs on physiology and design lncRNA-centered therapeutic strategies. This article is categorized under: RNA Export and Localization > RNA Localization Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

Epigenetic regulation of neuroblastoma development

In recent years, technological advances have enabled a detailed landscaping of the epigenome and the mechanisms of epigenetic regulation that drive normal cell function, development and cancer. Rather than merely a structural entity to support genome compaction, we now look at chromatin as a very dynamic and essential constellation that is actively participating in the tight orchestration of transcriptional regulation as well as DNA replication and repair. The unique feature of chromatin flexibility enabling fast switches towards more or less restricted epigenetic cellular states is, not surprisingly, intimately connected to cancer development and treatment resistance, and the central role of epigenetic alterations in cancer is illustrated by the finding that up to 50% of all mutations across cancer entities affect proteins controlling the chromatin status. We summarize recent insights into epigenetic rewiring underlying neuroblastoma (NB) tumor formation ranging from changes in DNA methylation patterns and mutations in epigenetic regulators to global effects on transcriptional regulatory circuits that involve key players in NB oncogenesis. Insights into the disruption of the homeostatic epigenetic balance contributing to developmental arrest of sympathetic progenitor cells and subsequent NB oncogenesis are rapidly growing and will be exploited towards the development of novel therapeutic strategies to increase current survival rates of patients with high-risk NB.

lncRNA in HNSCC: challenges and potential

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cause of cancer mortality in the world. Some progress has been made in the therapy of HNSCC, however treatment remains unsatisfactory. Recent studies have shown that different types of long non-coding RNAs (lncRNAs) are dysregulated in HNSCC and correlate with tumor progression, lymph node metastasis, clinical stage and poor prognosis. lncRNAs are a class of functional RNA molecules that can not be translated into proteins but can modulate the activity of transcription factors or regulate changes in chromatin structure. The lncRNAs might have potential of biomarker in HNSCC diagnosis, prognosis, prediction and targeted treatment. In this review we describe the potential role of lncRNAs as new biomarkers and discuss their features including source of origin, extraction methods, stability, detection methods and data normalization and potential function as biomarkers in HNSCC.

A transfer-RNA-derived small RNA regulates ribosome biogenesis

tRNA-derived small RNAs (tsRNAs; also called tRNA-derived fragments (tRFs)) are an abundant class of small non-coding RNAs whose biological roles are not well defined. We show that inhibition of a specific tsRNA, LeuCAG3′tsRNA, induces apoptosis in rapidly dividing cells in vitro and in a patient-derived orthotopic hepatocellular carcinoma model in mice. This tsRNA binds at least two ribosomal protein mRNAs (for RPS28 and RPS15) to enhance their translation. Reduction of RPS28 mRNA translation blocks pre-18S ribosomal RNA processing, resulting in a decrease in the number of 40S ribosomal subunits. These data establish another post-transcriptional mechanism that can fine-tune gene expression during different physiological states and provide a potential new target for treating cancer.

Elucidating the Role of Host Long Non-Coding RNA during Viral Infection: Challenges and Paths Forward

Research over the past decade has clearly shown that long non-coding RNAs (lncRNAs) are functional. Many lncRNAs can be related to immunity and the host response to viral infection, but their specific functions remain largely elusive. The vast majority of lncRNAs are annotated with extremely limited knowledge and tend to be expressed at low levels, making ad hoc experimentation difficult. Changes to lncRNA expression during infection can be systematically profiled using deep sequencing; however, this often produces an intractable number of candidate lncRNAs, leaving no clear path forward. For these reasons, it is especially important to prioritize lncRNAs into high-confidence “hits” by utilizing multiple methodologies. Large scale perturbation studies may be used to screen lncRNAs involved in phenotypes of interest, such as resistance to viral infection. Single cell transcriptome sequencing quantifies cell-type specific lncRNAs that are less abundant in a mixture. When coupled with iterative experimental validations, new computational strategies for efficiently integrating orthogonal high-throughput data will likely be the driver for elucidating the functional role of lncRNAs during viral infection. This review highlights new high-throughput technologies and discusses the potential for integrative computational analysis to streamline the identification of infection-related lncRNAs and unveil novel targets for antiviral therapeutics.

A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts

Background

In recent years, a rapidly increasing number of RNA transcripts has been generated by thousands of sequencing projects around the world, creating enormous volumes of transcript data to be analyzed. An important problem to be addressed when analyzing this data is distinguishing between long non-coding RNAs (lncRNAs) and protein coding transcripts (PCTs). Thus, we present a Support Vector Machine (SVM) based method to distinguish lncRNAs from PCTs, using features based on frequencies of nucleotide patterns and ORF lengths, in transcripts.

Methods

The proposed method is based on SVM and uses the first ORF relative length and frequencies of nucleotide patterns selected by PCA as features. FASTA files were used as input to calculate all possible features. These features were divided in two sets: (i) 336 frequencies of nucleotide patterns; and (ii) 4 features derived from ORFs. PCA were applied to the first set to identify 6 groups of frequencies that could most contribute to the distinction. Twenty-four experiments using the 6 groups from the first set and the features from the second set where built to create the best model to distinguish lncRNAs from PCTs.

Results

This method was trained and tested with human (Homo sapiens), mouse (Mus musculus) and zebrafish (Danio rerio) data, achieving 98.21%, 98.03% and 96.09%, accuracy, respectively. Our method was compared to other tools available in the literature (CPAT, CPC, iSeeRNA, lncRNApred, lncRScan-SVM and FEELnc), and showed an improvement in accuracy by ≈3.00%. In addition, to validate our model, the mouse data was classified with the human model, and vice-versa, achieving ≈97.80% accuracy in both cases, showing that the model is not overfit. The SVM models were validated with data from rat (Rattus norvegicus), pig (Sus scrofa) and fruit fly (Drosophila melanogaster), and obtained more than 84.00% accuracy in all these organisms. Our results also showed that 81.2% of human pseudogenes and 91.7% of mouse pseudogenes were classified as non-coding. Moreover, our method was capable of re-annotating two uncharacterized sequences of Swiss-Prot database with high probability of being lncRNAs. Finally, in order to use the method to annotate transcripts derived from RNA-seq, previously identified lncRNAs of human, gorilla (Gorilla gorilla) and rhesus macaque (Macaca mulatta) were analyzed, having successfully classified 98.62%, 80.8% and 91.9%, respectively.

Conclusions

The SVM method proposed in this work presents high performance to distinguish lncRNAs from PCTs, as shown in the results. To build the model, besides using features known in the literature regarding ORFs, we used PCA to identify features among nucleotide pattern frequencies that contribute the most in distinguishing lncRNAs from PCTs, in reference data sets. Interestingly, models created with two evolutionary distant species could distinguish lncRNAs of even more distant species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4178-4) contains supplementary material, which is available to authorized users.

Natural antisense transcripts drive a regulatory cascade controlling c-MYC transcription

Cis-natural antisense transcripts (cis-NATs) are long noncoding RNAs transcribed from the opposite strand and overlapping coding and noncoding genes on the sense strand. cis-NATs are widely present in the human genome and can be involved in multiple mechanisms of gene regulation. Here, we describe the presence of cis-NATs in the 3′ distal region of the c-MYC locus and investigate their impact on transcriptional regulation of this key oncogene in human cancers. We found that cis-NATs are produced as consequence of the activation of cryptic transcription initiation sites in the 3′ distal region downstream of the c-MYC 3′UTR. The process is tightly regulated and leads to the formation of two main transcripts, NAT6531 and NAT6558, which differ in their ability to fold into stem-loop secondary structures. NAT6531 acts as a substrate for DICER and as a source of small RNAs capable of modulating c-MYC transcription. This complex system, based on the interplay between cis-NATs and NAT-derived small RNAs, may represent an important layer of epigenetic regulation of the expression of c-MYC and other genes in human cells.

Non-coding RNAs as a new dawn in tumor diagnosis

The current knowledge about non-coding RNAs (ncRNAs) as important regulators of gene expression in both physiological and pathological conditions, has been the main engine for the design of innovative platforms to finalize the pharmacological application of ncRNAs as either therapeutic tools or as molecular biomarkers in cancer. Biochemical alterations of cancer cells are, in fact, largely supported by ncRNA disregulation in the tumor site, which, in turn, reflects the cancer-associated specific modification of circulating ncRNA expression pattern. The aim of this review is to describe the state of the art of pre-clinical and clinical studies that analyze the involvement of miRNAs and lncRNAs in cancer-related processes, such as proliferation, invasion and metastases, giving emphasis to their functional role. A central node of our work has been also the examination of advantages and criticisms correlated with the clinical use of ncRNAs, taking into account the pressing need to refine the profiling methods aimed at identify novel diagnostic and prognostic markers and the request to optimize the delivery of such nucleic acids for a therapeutic use in an imminent future.

JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

Long non-coding RNA TUG1 promotes migration and invasion by acting as a ceRNA of miR-335-5p in osteosarcoma cells

Long non-coding RNA (lncRNA) have been the focus of increasing attention due to the role they play in many diseases, including osteosarcoma. The function of taurine upregulated gene 1 (TUG1) and its mechanism in osteosarcoma remain unclear. In our research, we found that TUG1 was elevated and correlated with a poor prognosis in osteosarcoma patients. In addition, the following functional experiment showed that decreased TUG1 could remarkably inhibit osteosarcoma cell migration and invasion, indicating that TUG1 functioned as an oncogene in osteosarcoma. Moreover, we revealed that TUG1 and Rho-associated coiled-coil-containing protein kinase 1 (ROCK1), a metastasis-related gene targeted by microRNA-335-5p (miR-335-5p), had the same miR-335-5p combining site. The subsequent luciferase assay verified TUG1 was a target of miR-335-5p. Furthermore, the results of a real-time quantitative PCR showed that TUG1 and miR-335-5p could affect each other's expression. respectively. Finally, we affirmed that TUG1 affected ROCK1 expression and ROCK1-mediated migration/invasion by working as a competitive endogenous RNA (ceRNA) via miR-335-5p. In summary, the findings of this study, based on ceRNA theory, combining the research foundation of miR-335-5p and ROCK1, and taking TUG1 as a new study point, provide new insight into molecular-level reversing migration and invasion of osteosarcoma.

PITX2 and PANCR DNA methylation predicts overall survival in patients with head and neck squamous cell carcinoma

BACKGROUND

Squamous cell carcinoma of the head and neck region (HNSCC) is a common malignant disease accompanied by a high risk of local or distant recurrence after curative-intent treatment. Biomarkers that allow for the prediction of disease outcome can guide clinicians with respect to treatment and surveillance strategies. Here, the methylation status of PITX2 and an adjacent lncRNA (PANCR) were evaluated for their ability to predict overall survival in HNSCC patients.

RESULTS

PITX2 hypermethylation was associated with a better overall survival (hazard ratio, HR = 0.51, 95%CI: 0.35-0.74, p<0.001), while PANCR hypermethylation was significantly associated with an increased risk of death (HR = 1.64, 95%CI: 1.12-2.39, p=0.010).

METHODS

Quantitative, methylation-specific real-time PCR assays for PITX2 and PANCR were employed to measure bisulfite-converted DNA from formalin-fixed, paraffin-embedded (FFPE) tissues in a cohort of 399 patients with localized or locally advanced HNSCC who received curative-intent treatment (surgery with optional adjuvant radiochemotherapy or definite radiochemotherapy).

CONCLUSIONS

PITX2 and PANCR methylation status were shown to be independent predictors for overall survival in HNSCC patients. Tissue-based methylation testing could therefore potentially be employed to identify patients with a high risk for death who might benefit from a more radical or alternative treatment.

Computational Approaches for Functional Prediction and Characterisation of Long Noncoding RNAs

Although a considerable portion of eukaryotic genomes is transcribed as long noncoding RNAs (lncRNAs), the vast majority are functionally uncharacterised. The rapidly expanding catalogue of mechanistically investigated lncRNAs has provided evidence for distinct functional subclasses, which are now ripe for exploitation as a general model to predict functions for uncharacterised lncRNAs. By utilising publicly-available genome-wide datasets and computational methods, we present several developed and emerging in silico approaches to characterise and predict the functions of lncRNAs. We propose that the application of these techniques provides valuable functional and mechanistic insight into lncRNAs, and is a crucial step for informing subsequent functional studies.

Understanding the Functions of Long Non-Coding RNAs through Their Higher-Order Structures

Although thousands of long non-coding RNAs (lncRNAs) have been discovered in eukaryotes, very few molecular mechanisms have been characterized due to an insufficient understanding of lncRNA structure. Therefore, investigations of lncRNA structure and subsequent elucidation of the regulatory mechanisms are urgently needed. However, since lncRNA are high molecular weight molecules, which makes their crystallization difficult, obtaining information about their structure is extremely challenging, and the structures of only several lncRNAs have been determined so far. Here, we review the structure-function relationships of the widely studied lncRNAs found in the animal and plant kingdoms, focusing on the principles and applications of both in vitro and in vivo technologies for the study of RNA structures, including dimethyl sulfate-sequencing (DMS-seq), selective 2'-hydroxyl acylation analyzed by primer extension-sequencing (SHAPE-seq), parallel analysis of RNA structure (PARS), and fragmentation sequencing (FragSeq). The aim of this review is to provide a better understanding of lncRNA biological functions by studying them at the structural level.