lncRNA Structure Research Articles

Mitochondrial sequencing identifies long noncoding RNA features that promote binding to PNPase.

Extranuclear localization of long noncoding RNAs (lncRNAs) is poorly understood. Based on machine learning evaluations, we propose a lncRNA-mitochondrial interaction pathway where polynucleotide phosphorylase (PNPase), through domains that provide specificity for primary sequence and secondary structure, binds nuclear-encoded lncRNAs to facilitate mitochondrial import. Using FVB/NJ mouse and human cardiac tissues, RNA from isolated subcellular compartments (cytoplasmic and mitochondrial) and cross-linked immunoprecipitate (CLIP) with PNPase within the mitochondrion were sequenced on the Illumina HiSeq and MiSeq, respectively. lncRNA sequence and structure were evaluated through supervised [classification and regression trees (CART) and support vector machines (SVM)] machine learning algorithms. In HL-1 cells, quantitative PCR of PNPase CLIP knockout mutants (KH and S1) was performed. In vitro fluorescence assays assessed PNPase RNA binding capacity and verified with PNPase CLIP. One hundred twelve (mouse) and 1,548 (human) lncRNAs were identified in the mitochondrion with Malat1 being the most abundant. Most noncoding RNAs binding PNPase were lncRNAs, including Malat1. lncRNA fragments bound to PNPase compared against randomly generated sequences of similar length showed stratification with SVM and CART algorithms. The lncRNAs bound to PNPase were used to create a criterion for binding, with experimental validation revealing increased binding affinity of RNA designed to bind PNPase compared to control RNA. The binding of lncRNAs to PNPase was decreased through the knockout of RNA binding domains KH and S1. In conclusion, sequence and secondary structural features identified by machine learning enhance the likelihood of nuclear-encoded lncRNAs binding to PNPase and undergoing import into the mitochondrion.NEW & NOTEWORTHY Long noncoding RNAs (lncRNAs) are relatively novel RNAs with increasingly prominent roles in regulating genetic expression, mainly in the nucleus but more recently in regions such as the mitochondrion. This study explores how lncRNAs interact with polynucleotide phosphorylase (PNPase), a protein that regulates RNA import into the mitochondrion. Machine learning identified several RNA structural features that improved lncRNA binding to PNPase, which may be useful in targeting RNA therapeutics to the mitochondrion.

Probing RNA structural landscapes across Candida yeast genomes.

Understanding the intricate roles of RNA molecules in virulence and host-pathogen interactions can provide valuable insights into combatting infections and improving human health. Although much progress has been achieved in understanding transcriptional regulation during host-pathogen interactions in diverse species, more is needed to know about the structure of pathogen RNAs. This is particularly true for fungal pathogens, including pathogenic yeasts of the Candida genus, which are the leading cause of hospital-acquired fungal infections. Our work addresses the gap between RNA structure and their biology by employing genome-wide structure probing to comprehensively explore the structural landscape of mRNAs and long non-coding RNAs (lncRNAs) in the four major Candida pathogens. Specifically focusing on mRNA, we observe a robust correlation between sequence conservation and structural characteristics in orthologous transcripts, significantly when sequence identity exceeds 50%, highlighting structural feature conservation among closely related species. We investigate the impact of single nucleotide polymorphisms (SNPs) on mRNA secondary structure. SNPs within 5' untranslated regions (UTRs) tend to occur in less structured positions, suggesting structural constraints influencing transcript regulation. Furthermore, we compare the structural properties of coding regions and UTRs, noting that coding regions are generally more structured than UTRs, consistent with similar trends in other species. Additionally, we provide the first experimental characterization of lncRNA structures in Candida species. Most lncRNAs form independent subdomains, similar to human lncRNAs. Notably, we identify hairpin-like structures in lncRNAs, a feature known to be functionally significant. Comparing hairpin prevalence between lncRNAs and protein-coding genes, we find enrichment in lncRNAs across Candida species, humans, and Arabidopsis thaliana, suggesting a conserved role for these structures. In summary, our study offers valuable insights into the interplay between RNA sequence, structure, and function in Candida pathogens, with implications for gene expression regulation and potential therapeutic strategies against Candida infections.

Deep Conservation and Unexpected Evolutionary History of Neighboring lncRNAs MALAT1 and NEAT1

Long non-coding RNAs (lncRNAs) have begun to receive overdue attention for their regulatory roles in gene expression and other cellular processes. Although most lncRNAs are lowly expressed and tissue-specific, notable exceptions include MALAT1 and its genomic neighbor NEAT1, two highly and ubiquitously expressed oncogenes with roles in transcriptional regulation and RNA splicing. Previous studies have suggested that NEAT1 is found only in mammals, while MALAT1 is present in all gnathostomes (jawed vertebrates) except birds. Here we show that these assertions are incomplete, likely due to the challenges associated with properly identifying these two lncRNAs. Using phylogenetic analysis and structure-aware annotation of publicly available genomic and RNA-seq coverage data, we show that NEAT1 is a common feature of tetrapod genomes except birds and squamates. Conversely, we identify MALAT1 in representative species of all major gnathostome clades, including birds. Our in-depth examination of MALAT1, NEAT1, and their genomic context in a wide range of vertebrate species allows us to reconstruct the series of events that led to the formation of the locus containing these genes in taxa from cartilaginous fish to mammals. This evolutionary history includes the independent loss of NEAT1 in birds and squamates, since NEAT1 is found in the closest living relatives of both clades (crocodilians and tuataras, respectively). These data clarify the origins and relationships of MALAT1 and NEAT1 and highlight an opportunity to study the change and continuity in lncRNA structure and function over deep evolutionary time.

Hidden regulators: the emerging roles of lncRNAs in brain development and disease.

Long non-coding RNAs (lncRNAs) have emerged as critical players in brain development and disease. These non-coding transcripts, which once considered as "transcriptional junk," are now known for their regulatory roles in gene expression. In brain development, lncRNAs participate in many processes, including neurogenesis, neuronal differentiation, and synaptogenesis. They employ their effect through a wide variety of transcriptional and post-transcriptional regulatory mechanisms through interactions with chromatin modifiers, transcription factors, and other regulatory molecules. Dysregulation of lncRNAs has been associated with certain brain diseases, including Alzheimer's disease, Parkinson's disease, cancer, and neurodevelopmental disorders. Altered expression and function of specific lncRNAs have been implicated with disrupted neuronal connectivity, impaired synaptic plasticity, and aberrant gene expression pattern, highlighting the functional importance of this subclass of brain-enriched RNAs. Moreover, lncRNAs have been identified as potential biomarkers and therapeutic targets for neurological diseases. Here, we give a comprehensive review of the existing knowledge of lncRNAs. Our aim is to provide a better understanding of the diversity of lncRNA structure and functions in brain development and disease. This holds promise for unravelling the complexity of neurodevelopmental and neurodegenerative disorders, paving the way for the development of novel biomarkers and therapeutic targets for improved diagnosis and treatment.

Unveiling the Genetic Complexity of Teratozoospermia: Integrated Genomic Analysis Reveals Novel Insights into lncRNAs' Role in Male Infertility.

Male infertility is a global health issue, affecting over 20 million men worldwide. Genetic factors are crucial in various male infertility forms, including teratozoospermia. Nonetheless, the genetic causes of male infertility remain largely unexplored. In this study, we employed whole-genome sequencing and RNA expression analysis to detect differentially expressed (DE) long-noncoding RNAs (lncRNAs) in teratozoospermia, along with mutations that are exclusive to teratozoospermic individuals within these DE lncRNAs regions. Bioinformatic tools were used to assess variants' impact on lncRNA structure, function, and lncRNA-miRNA interactions. Our analysis identified 1166 unique mutations in teratozoospermic men within DE lncRNAs, distinguishing them from normozoospermic men. Among these, 64 variants in 23 lncRNAs showed potential regulatory roles, 7 variants affected 4 lncRNA structures, while 37 variants in 17 lncRNAs caused miRNA target loss or gain. Pathway Enrichment and Gene Ontology analyses of the genes targeted by the affected miRNAs revealed dysregulated pathways in teratozoospermia and a link between male infertility and cancer. This study lists novel variants and lncRNAs associated for the first time with teratozoospermia. These findings pave the way for future studies aiming to enhance diagnosis and therapy in the field of male infertility.

OR2801 Novel Cis-Regulatory Mechanisms Of Lhb Transcription By Non-Coding RNAs And Non-Canonical DNA Structures

Abstract Disclosure: T. Refael: None. H. Gruber: None. G. Golan: None. L. Pnueli: None. P. Melamed: None. Expression of the Lhb gene was shown previously to be directed by synergistic actions of lineage-specific transcription factors at conserved regions of the proximal promoter. However extensive genomic analysis during the last few decades has expanded the repertoire of factors we now know to be involved in transcriptional regulation, revealing roles for distal transcriptional enhancers and long non-coding RNAs (lncRNAs), whose modes of action are only beginning to be elucidated1. Recently it has also become evident that regulatory regions of the genome are enriched with non-canonical DNA structures. These include G-quadruplexes (G4s) which form on guanine-rich stretches of single-stranded DNA and iMotifs (iMs) on the complementary strand, and are reported to bind various proteins which presumably regulate and mediate their actions. We identified in available mice pituitary scATAC-seq data a region of gonadotrope-specific open chromatin upstream of the Lhb gene, and chromatin conformation capture (3C) in murine gonadotrope cell lines indicated the distal sites that are in physical proximity to the Lhb promoter. Further, we show by chromatin immunoprecipitation (ChIP) a peak of H3K4 monomethylation (H3K4me1) ∼3 kbp upstream of the Lhb TSS, and transcription of two bi-directional non-coding enhancer RNAs (eRNAs), both of which are characteristic of transcriptional enhancers. One of the eRNAs was found to direct open chromatin at the Lhb promoter and is required for Lhb transcription, while guide RNA-mediated recruitment of dCas9- KRAB or dCas9-VP64 to this locus altered Lhb mRNA levels accordingly, confirming its functional enhancer activity. However this enhancer activity is not sufficient for optimal Lhb transcription, and we found that splicing in situ of a distinct downstream lncRNA is also required. The DNA at the central non-coding region of the enhancer, and at the promoter of this lncRNA, forms G4 and iM structures, seen by circular dichroism and ChIP. These DNA structures are affected differentially by local conditions including changes in pH or hormonal treatments, and appear to have diverse effects. HMGB2, which is known to bind structured DNA, was found to bind the enhancer iM in cells and in vitro. Further, HMGB2 knockdown reduced the iM signal and Lhb mRNA, eRNA and lncRNA expression levels quite dramatically. We thus present novel elements involved in the regulation of Lhb transcription through various classes of non-coding RNAs and DNA structures, while emphasizing the complexity of transcriptional regulation via context-dependent cis-acting elements.

A lncRNA bra-miR156HG regulates flowering time and leaf morphology as a precursor of miR156 in Brassica campestris and Arabidopsis thaliana

Long non-coding RNAs (lncRNAs) are important regulators in plant growth and development. Here the function of a lncRNA fragment was studied, which was predicted as an endogenous target mimic (eTM) of miR156 in Brassica campesrtis. Unexpectedly, the transformation of this lncRNA into Arabidopsis thaliana neither inhibited the expression of miR156a nor resulted in any phenotypes that differed from the control plants (CK). The full-length sequence of the lncRNA (named bra-miR156HG) was then obtained using RACE and transferred into A. thaliana. The transgenic plants displayed a delay in flowering time, an increasing number of rosette leaves, and a changed morphology of cauline leaves, which was similar to the plants that expressed bra-miR156a. In contrast, the overexpression of bra-miR156HG in B. campestris resulted in an increased tip angle of leaves and changed the length-width ratio of leaves at different nodes, suggesting that bra-miR156HG may be involved in regulating the leaf morphology. Collectively, our study showed that bra-miR156HG functions as a precursor of bra-miR156a involved in regulating plant flowering time and leaf development under different biological backgrounds. The secondary structure of lncRNA is essential not only for the normal roles that it plays but also for expanding the functional diversities.

Interactome of Long Non-Coding RNAs: Transcriptomic Expression Patterns and Shaping Cancer Cell Phenotypes.

RNA biology has gained extensive recognition in the last two decades due to the identification of novel transcriptomic elements and molecular functions. Cancer arises, in part, due to the accumulation of mutations that greatly contribute to genomic instability. However, the identification of differential gene expression patterns of wild-type loci has exceeded the boundaries of mutational study and has significantly contributed to the identification of molecular mechanisms that drive carcinogenic transformation. Non-coding RNA molecules have provided a novel avenue of exploration, providing additional routes for evaluating genomic and epigenomic regulation. Of particular focus, long non-coding RNA molecule expression has been demonstrated to govern and direct cellular activity, thus evidencing a correlation between aberrant long non-coding RNA expression and the pathological transformation of cells. lncRNA classification, structure, function, and therapeutic utilization have expanded cancer studies and molecular targeting, and understanding the lncRNA interactome aids in defining the unique transcriptomic signatures of cancer cell phenotypes.

LncRNA-MALAT1: A Key Participant in the Occurrence and Development of Cancer.

LncRNAs are a group of non-coding RNA transcripts with lengths of over 200 nucleotides and can interact with DNA, RNA, and proteins to regulate gene expression of malignant tumors in human tissues. LncRNAs participate in vital processes, such as chromosomal nuclear transport in the cancerous site of human tissue, activation, and the regulation of proto-oncogenes, the differentiation of immune cells, and the regulation of the cellular immune system. The lncRNA metastasis-associated lung cancer transcript 1 (MALAT1) is reportedly involved in the occurrence and development of many cancers and serves as a biomarker and therapeutic target. These findings highlight its promising role in cancer treatment. In this article, we comprehensively summarized the structure and functions of lncRNA, notably the discoveries of lncRNA-MALAT1 in different cancers, the action mechanisms, and the ongoing research on new drug development. We believe our review would serve as a basis for further research on the pathological mechanism of lncRNA-MALAT1 in cancer and provide evidence and novel insights into its application in clinical diagnoses and treatments.

LncRNASNP v3: an updated database for functional variants in long non-coding RNAs.

Long non-coding RNAs (lncRNAs) act as versatile regulators of many biological processes and play vital roles in various diseases. lncRNASNP is dedicated to providing a comprehensive repository of single nucleotide polymorphisms (SNPs) and somatic mutations in lncRNAs and their impacts on lncRNA structure and function. Since the last release in 2018, there has been a huge increase in the number of variants and lncRNAs. Thus, we updated the lncRNASNP to version 3 by expanding the species to eight eukaryotic species (human, chimpanzee, pig, mouse, rat, chicken, zebrafish, and fruitfly), updating the dataand adding several new features. SNPs in lncRNASNP have increased from 11 181 387 to 67 513 785. The human mutations have increased from 1 174 768 to 2 387 685, including 1 031 639 TCGA mutations and 1 356 046 CosmicNCVs. Compared with the last release, updated and new features in lncRNASNP v3 include (i) SNPs in lncRNAs and their impacts on lncRNAs for eight species, (ii) SNP effects on miRNA-lncRNA interactions for eight species, (iii) lncRNA expression profiles for six species, (iv) disease & GWAS-associated lncRNAs and variants, (v) experimental & predicted lncRNAs and drug target associations and (vi) SNP effects on lncRNA expression (eQTL) across tumor & normal tissues. The lncRNASNP v3 is freely available at http://gong_lab.hzau.edu.cn/lncRNASNP3/.

Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches.

In contrast to messenger RNAs, the function of the wide range of existing long noncoding RNAs (lncRNAs) largely depends on their structure, which determines interactions with partner molecules. Thus, the determination or prediction of the secondary structure of lncRNAs is critical to uncover their function. Classical approaches for predicting RNA secondary structure have been based on dynamic programming and thermodynamic calculations. In the last 4 years, a growing number of machine learning (ML)-based models, including deep learning (DL), have achieved breakthrough performance in structure prediction of biomolecules such as proteins and have outperformed classical methods in short transcripts folding. Nevertheless, the accurate prediction for lncRNA still remains far from being effectively solved. Notably, the myriad of new proposals has not been systematically and experimentally evaluated. In this work, we compare the performance of the classical methods as well as the most recently proposed approaches for secondary structure prediction of RNA sequences using a unified and consistent experimental setup. We use the publicly available structural profiles for 3023 yeast RNA sequences, and a novel benchmark of well-characterized lncRNA structures from different species. Moreover, we propose a novel metric to assess the predictive performance of methods, exclusively based on the chemical probing data commonly used for profiling RNA structures, avoiding any potential bias incorporated by computational predictions when using dot-bracket references. Our results provide a comprehensive comparative assessment of existing methodologies, and a novel and public benchmark resource to aid in the development and comparison of future approaches. Full source code and benchmark datasets are available at: https://github.com/sinc-lab/lncRNA-folding. lbugnon@sinc.unl.edu.ar.

Current Status of Epitranscriptomic Marks Affecting lncRNA Structures and Functions.

Long non-coding RNAs (lncRNAs) belong to a class of non-protein-coding RNAs with their lengths longer than 200 nucleotides. Most of the mammalian genome is transcribed as RNA, yet only a small percent of the transcribed RNA corresponds to exons of protein-coding genes. Thus, the number of lncRNAs is predicted to be several times higher than that of protein-coding genes. Because of sheer number of lncRNAs, it is often difficult to elucidate the functions of all lncRNAs, especially those arising from their relationship to their binding partners, such as DNA, RNA, and proteins. Due to their binding to other macromolecules, it has become evident that the structures of lncRNAs influence their functions. In this regard, the recent development of epitranscriptomics (the field of study to investigate RNA modifications) has become important to further elucidate the structures and functions of lncRNAs. In this review, the current status of lncRNA structures and functions influenced by epitranscriptomic marks is discussed.

Structure–function relationship of long noncoding RNAs: Advances and challenges

AbstractLong noncoding RNAs (lncRNAs) are an emerging and a promising class of RNAs, and the lncRNA field is an intense research area. Once trashed as the junk regions of the genome, lncRNAs have now proved to be one of the crucial elements of a functional genome. These comprise a major chunk of the transcriptome, and similar to proteins, the sequence–structure–function paradigm holds true for lncRNAs as well. While some of the earliest lncRNAs like Xist and H19 have been well‐characterized, many of the emerging lncRNAs remain in oblivion. The low sequence conservation of lncRNAs has prompted researchers to decipher its conserved structure in order to gain an insight into the functional mechanisms. Here, we explore the concept of the sequence–structure–function relationship of lncRNAs, and the biophysical and biochemical laws governing a lncRNA structure which are just beginning to be understood. Proceeding from specific structures, much of the functions of lncRNAs revolve around their regulatory roles, through myriad modes of action. Throughout this review, we discuss the powerful computational as well as some experimental approaches that are applied in a synergistic fashion and highlight promising studies that have proved crucial towards an understanding of lncRNA structure and functional mechanisms. We also discuss at length, the existing challenges and the possible strategies to circumvent it. Given the unknown realm, the patterns and insights generated from these studies will be extremely useful in deciphering the way nature selects and uses a specific lncRNA to regulate a specific gene or gene sets in health and disease.This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Free Energy Methods Structure and Mechanism > Molecular Structures

A genetic variant alters the secondary structure of the lncRNA H19 and is associated with dilated cardiomyopathy

ABSTRACT lncRNAs are at the core of many regulatory processes and have also been recognized to be involved in various complex diseases. They affect gene regulation through direct interactions with RNA, DNA or proteins. Accordingly, lncRNA structure is likely to be essential for their regulatory function. Point mutations, which manifest as SNPs (single nucleotide polymorphisms) in genome screens, can substantially alter their function and, subsequently, the expression of their downstream regulated genes. To test the effect of SNPs on structure, we investigated lncRNAs associated with dilated cardiomyopathy. Among 322 human candidate lncRNAs, we demonstrate first the significant association of an SNP located in lncRNA H19 using data from 1084 diseased and 751 control patients. H19 is generally highly expressed in the heart, with a complex expression pattern during heart development. Next, we used MFE (minimum free energy) folding to demonstrate a significant refolding in the secondary structure of this 861 nt long lncRNA. Since MFE folding may overlook the importance of sub-optimal structures, we showed that this refolding also manifests in the overall Boltzmann structure ensemble. There, the composition of structures is tremendously affected in their thermodynamic probabilities through the genetic variant. Finally, we confirmed these results experimentally, using SHAPE-Seq, corroborating that SNPs affecting such structures may explain hidden genetic variance not accounted for through genome wide association studies. Our results suggest that structural changes in lncRNAs, and lncRNA H19 in particular, affect regulatory processes and represent optimal targets for further in-depth studies probing their molecular interactions.

Structure‐Function Studies of MUNC LncRNA Reveal Domains Required for Its Promyogenic Phenotype

Although thousands of long non-coding RNAs (lncRNAs) have been already discovered, only few are functionally characterized and even fewer provide insights into molecular mechanism based on their structure. Therefore, studies of lncRNA structure and subsequent elucidation of its function and the regulatory mechanisms are urgently needed. MUNC lncRNA is upregulated in murine skeletal muscles and was firstly described as a facilitator of Myod1 function in myogenesis. There are two MUNC isoforms: spliced and genomic, and both have promyogenic abilities. siMUNC reduces myoblast differentiation, and stable overexpression stimulates promyogenic RNAs. MUNC is also one of the conserved lncRNA and its homolog can be found in human muscles. In this study we focus on the relationship between MUNC lncRNA structure and function. We determined the secondary structure of MUNC and found that specific structural domains are critical in the process of skeletal muscle differentiation. Moreover, we characterized structural features facilitate MUNC binding to specific genomic sites and protein interactors. To analyze the functional similarities and differences between the MUNC two isoforms, we performed RNA-seq on myoblasts overexpressing MUNC spliced or genomic in proliferation and differentiation conditions. We show that both MUNC transcripts can regulate different sets of genes that are important for muscle structure development, RNA processing and apoptosis signaling. We obtained the secondary structure using SHAPE-MaP and we found that MUNC spliced and genomic have six common structural domains and eight common proteins protected sites. Knowing that both MUNC isoforms induce the same promyogenic genes, we systematically deleted the most structurally similar regions. We have identified domains which are required for induction of Myod1, Myogenin and Myh3. We have also found out a domain which is necessary for Myod1 stimulation, but not Myogenin, proving again that MUNC can act both in cis and in trans. Using the data about MUNC functional domains, protein binding partners and genomic sites interactions we can now better characterize this lncRNA and describe its mechanism of function.

Establishing RNA-RNA interactions remodels lncRNA structure and promotes PRC2 activity.

Human Polycomb Repressive Complex 2 (PRC2) catalysis of histone H3 lysine 27 methylation at certain loci depends on long noncoding RNAs (lncRNAs). Yet, in apparent contradiction, RNA is a potent catalytic inhibitor of PRC2. Here, we show that intermolecular RNA-RNA interactions between the lncRNA HOTAIR and its targets can relieve RNA inhibition of PRC2. RNA bridging is promoted by heterogeneous nuclear ribonucleoprotein B1, which uses multiple protein domains to bind HOTAIR regions via multivalent protein-RNA interactions. Chemical probing demonstrates that establishing RNA-RNA interactions changes HOTAIR structure. Genome-wide HOTAIR/PRC2 activity occurs at genes whose transcripts can make favorable RNA-RNA interactions with HOTAIR. We demonstrate that RNA-RNA matches of HOTAIR with target gene RNAs can relieve the inhibitory effect of a single lncRNA for PRC2 activity after B1 dissociation. Our work highlights an intrinsic switch that allows PRC2 activity in specific RNA contexts, which could explain how many lncRNAs work with PRC2.

Purification and Structural Characterization of the Long Noncoding RNAs.

Long noncoding RNAs (lncRNAs) are now accepted as key players in diverse cellular functions, yet the structure-function relationships of these novel RNAs remain mostly unknown. Homogenous purification of lncRNAs is a necessary first-step for downstream structural studies. The large size of lncRNAs (often more than 1kb) presents many unique challenges during the purification process. Here, we detail the purification of lncRNAs, including strategies to identify proper folding conditions of the target lncRNA. Next, we discuss two recently developed RNA structure probing techniques, SHAPE-MaP (SHAPE probing followed by mutational profiling) and DMS-MaP (DMS probing followed by mutational profiling). These techniques couple traditional RNA chemical probing methods with next-generation sequencing and allow high-throughput determination of RNA structures. Using the datasets resulting from these orthogonal probing experiments, we lay out the steps to determine and validate the secondary structure of the target lncRNA. Overall, this chapter details an adaptable protocol that can lead to a better understanding of the structure-function relationships of lncRNAs.

Visualization of lncRNA and mRNA Structure Models Within the Integrative Genomics Viewer.

Every class of RNA forms base-paired structures that impact biological functions. Chemical probing of RNA structure, especially with the advent of strategies such as SHAPE-MaP, vastly expands the scale and quantitative accuracy over which RNA structure can be examined. These methods have enabled large-scale structural studies of mRNAs and lncRNAs, but the length and complexity of these RNAs makes interpretation of the data challenging. We have created modules available through the open-source Integrative Genomics Viewer (IGV) for straightforward visualization of RNA structures along with complementary experimental data. Here we present detailed and stepwise strategies for exploring and visualizing complex RNA structures in IGV. Individuals can use these instructions and supplied sample data to become adept at using IGV to visualize RNA structure models in conjunction with useful allied information.

EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments.

Long non-coding RNAs (lncRNAs) play important functional roles in many diverse biological processes. However, not all expressed lncRNAs are functional. Thus, it is necessary to manually collect all experimentally validated functional lncRNAs (EVlncRNA) with their sequences, structures, and functions annotated in a central database. The first release of such a database (EVLncRNAs) was made using the literature prior to 1 May 2016. Since then (till 15 May 2020), 19 245 articles related to lncRNAs have been published. In EVLncRNAs 2.0, these articles were manually examined for a major expansion of the data collected. Specifically, the number of annotated EVlncRNAs, associated diseases, lncRNA-disease associations, and interaction records were increased by 260%, 320%, 484% and 537%, respectively. Moreover, the database has added several new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 drug-resistant, chemoresistant, and stress-resistant lncRNAs. All records have checked against known retraction and fake articles. This release also comes with a highly interactive visual interaction network that facilitates users to track the underlying relations among lncRNAs, miRNAs, proteins, genes and other functional elements. Furthermore, it provides links to four new bioinformatics tools with improved data browsing and searching functionality. EVLncRNAs 2.0 is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs2/.

Mechanisms of Long Non-Coding RNAs in Cancers and Their Dynamic Regulations.

Long non-coding RNA (lncRNA), which is a kind of noncoding RNA, is generally characterized as being more than 200 nucleotide transcripts in length. LncRNAs exhibit many biological activities, including, but not limited to, cancer development. In this review, a search of the PubMed database was performed to identify relevant studies published in English. The term “lncRNA or long non-coding RNA” was combined with a range of search terms related to the core focus of the review: mechanism, structure, regulation, and cancer. The eligibility of the retrieved studies was mainly based on the abstract. The decision as to whether or not the study was included in this review was made after a careful assessment of its content. The reference lists were also checked to identify any other study that could be relevant to this review. We first summarized the molecular mechanisms of lncRNAs in tumorigenesis, including competing endogenous RNA (ceRNA) mechanisms, epigenetic regulation, decoy and scaffold mechanisms, mRNA and protein stability regulation, transcriptional and translational regulation, miRNA processing regulation, and the architectural role of lncRNAs, which will help a broad audience better understand how lncRNAs work in cancer. Second, we introduced recent studies to elucidate the structure of lncRNAs, as there is a link between lncRNA structure and function and visualizing the architectural domains of lncRNAs is vital to understanding their function. Third, we explored emerging evidence for regulators of lncRNA expression, lncRNA turnover, and lncRNA modifications (including 5-methylcytidine, N6-methyladenosine, and adenosine to inosine editing), highlighting the dynamics of lncRNAs. Finally, we used autophagy in cancer as an example to interpret the diverse mechanisms of lncRNAs and introduced clinical trials of lncRNA-based cancer therapies.