The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis

lncRNAs in vascular senescence and microvascular remodeling

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of vascular senescence and microvascular remodeling, processes that significantly contribute to the development of age-related diseases in organs such as the kidneys, heart, and lungs. Through mechanisms like chromatin remodeling, transcriptional regulation, and posttranscriptional modifications, lncRNAs modulate gene expression, thereby influencing cellular processes such as apoptosis, inflammation, fibrosis, and angiogenesis. In chronic kidney disease, cardiovascular disease, and pulmonary disorders, lncRNAs play a central role in promoting vascular dysfunction, endothelial cell aging, and fibrosis. This review focuses on how lncRNAs contribute to endothelial dysfunction, fibrosis, and vascular aging, emphasizing their roles in disease progression within the kidneys, heart, and lungs, where lncRNA-mediated vascular changes play a significant role in disease progression. Understanding the interactions between lncRNAs, vascular senescence, and microvascular remodeling offers promising avenues for developing targeted therapeutic strategies to mitigate the impact of aging on vascular health.

Value of Bioinformatics Models for Predicting Translational Control of Angiogenesis

Angiogenesis, the formation of new blood vessels, is a fundamental biological process with implications for both physiological functions and pathological conditions. While the transcriptional regulation of angiogenesis, mediated by factors such as HIF-1α (hypoxia-inducible factor 1-alpha) and VEGF (vascular endothelial growth factor), is well-characterized, the translational regulation of this process remains underexplored. Bioinformatics has emerged as an indispensable tool for advancing our understanding of translational regulation, offering predictive models that leverage large data sets to guide research and optimize experimental approaches. However, a significant gap persists between bioinformatics experts and other researchers, limiting the accessibility and utility of these tools in the broader scientific community. To address this divide, user-friendly bioinformatics platforms are being developed to democratize access to predictive analytics and empower researchers across disciplines. Translational control, compared with transcriptional control, offers a more energy-efficient mechanism that facilitates rapid cellular responses to environmental changes. Furthermore, transcriptional regulators themselves are often subject to translational control, emphasizing the interconnected nature of these regulatory layers. Investigating translational regulation requires advanced, accessible bioinformatics tools to analyze RNA structures, interacting micro-RNAs, long noncoding RNAs, and RBPs (RNA-binding proteins). Predictive platforms such as RNA structure, human internal ribosome entry site Atlas, and RBPSuite enable the study of RNA motifs and RNA-protein interactions, shedding light on these critical regulatory mechanisms. This review highlights the transformative role of bioinformatics using widely accessible user-friendly tools with a Web-browser interface to elucidate translational regulation in angiogenesis. The bioinformatics tools discussed extend beyond angiogenesis, with applications in diverse fields, including clinical care. By integrating predictive models and experimental insights, researchers can streamline hypothesis generation, reduce experimental costs, and find novel translational regulators. By bridging the bioinformatics knowledge gap, this review aims to empower researchers worldwide to adopt bioinformatics tools in their work, fostering innovation and accelerating scientific discovery.

Long non-coding RNA in the regulation of cell death in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer, accounting for 90% of all cases. Currently, early diagnosis of HCC can be achieved through serum alpha-fetoprotein detection, B-ultrasound, and computed tomography scanning; however, their specificity and sensitivity are suboptimal. Despite significant advancements in HCC biomarker detection, the prognosis for patients with HCC remains unfavorable due to tumor heterogeneity and limited understanding of its pathogenesis. Therefore, it is crucial to explore more sensitive HCC biomarkers for improved diagnosis, monitoring, and management of the disease. Long non-coding RNA (lncRNA) serves as an auxiliary carrier of genetic information and also plays diverse intricate regulatory roles that greatly contribute to genome complexity. Moreover, investigating gene expression regulation networks from the perspective of lncRNA may provide insights into the diagnosis and prognosis of HCC. We searched the PubMed database for literature, comprehensively classified regulated cell death mechanisms and systematically reviewed research progress on lncRNA-mediated cell death pathways in HCC cells. Furthermore, we prospectively summarize its potential implications in diagnosing and treating HCC.

Mechanisms and progress of LncRNAs in prostate cancer development and diagnostic therapy

Prostate cancer (PCa) is a leading cause of cancer-related morbidity and mortality in men worldwide. Despite advancements in diagnosis and treatment, challenges such as late-stage detection, therapeutic resistance, and the complexity of castration-resistant prostate cancer (CRPC) persist. Long non-coding RNAs (LncRNAs) play critical roles in PCa progression through epigenetic regulation, transcriptional and post-transcriptional modulation, and immune response regulation. This review highlights the molecular mechanisms by which LncRNAs influence PCa development, treatment resistance, and immune regulation, emphasizing their potential as biomarkers and therapeutic targets. We also discuss future research directions to advance precision medicine in PCa.

The Relevance of the Accurate Annotation of Micro and Long Non-Coding RNA Interactions for the Development of Therapies

A large fraction of the human genome is transcribed in RNA molecules that do not encode for proteins but that do have a crucial role in regulating almost every level of gene expression and, thus, define the specific phenotype of each cell. These non-coding RNAs include well-characterized microRNAs and thousands of less-defined longer transcripts, named long non-coding RNAs. Both types markedly affect the onset and the progression of numerous pathologies, ranging from cancer to vascular and neuro-degenerative diseases. In recent years, a substantial effort has been made to design drugs targeting ncRNAs, and promising advancements have been produced from micro-RNA mimics and inhibitors. Each ncRNA controls several targets, and the overall effect of its inhibition or overexpression depends on the function of the set of genes it regulates. Therefore, in selecting the most appropriate target, and predicting the final outcome of ncRNA-based therapies, it is crucial to have and utilize detailed and accurate knowledge of their functional interactions. In this review, I recapitulate the principal resources which collect information on microRNA and lncRNA networks, focusing on the non-homogeneity of the data that result from disparate approaches. I highlight the role of RNA identifiers and interaction evidence standardization in helping the user to filter and integrate data derived from different databases in a reliable functional web of regulative relations.

Computational Prediction of Gene Regulation by lncRNAs

High-throughput sequencing technologies and innovative bioinformatics tools discovered that most of the genome is transcribed into RNA. However, only a fraction of the RNAs in cell translates into proteins, while the majority of them are categorized as noncoding RNAs (ncRNAs). The ncRNAs with more than 200 nt without protein-coding ability are termed long noncoding RNAs (lncRNAs). Hundreds of studies established that lncRNAs are a crucial RNA family regulating gene expression. Regulatory RNAs, including lncRNAs, modulate gene expression by interacting with RNA, DNA, and proteins. Several databases and computational tools have been developed to explore the functions of lncRNAs in cellular physiology. This chapter discusses the tools available for lncRNA functional analysis and provides a detailed workflow for the computational analysis of lncRNAs.

Pivotal Role of miRNA-lncRNA Interactions in Human Diseases

New technologies have shown that most of the genome comprises transcripts that cannot code for proteins and are referred to as non-coding RNAs (ncRNAs). Some ncRNAs, like long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), are of substantial interest because of their critical function in controlling genes and numerous biological activities. The expression levels and function of miRNAs and lncRNAs are rigorously monitored throughout developmental processes and the maintenance of physiological homeostasis. Due to their critical roles, any dysregulation or changes in their expression can significantly influence the pathogenesis of various human diseases. The interactions between miRNAs and lncRNAs have been found to influence gene expression in various ways. These interactions significantly influence the understanding of disease etiology, cellular processes, and potential therapeutic targets. Different experimental and in silico methods can be used to investigate miRNA-lncRNA interactions. By aiding the elucidation of miRNA-lncRNA interactions and deepening the understanding of post-transcriptional gene regulation, researchers can open a new window for designing hypotheses, conducting experiments, and discovering methods for diagnosing and treating complex human diseases. This review briefly summarizes miRNA and lncRNA functions, discusses their interaction mechanisms, and examines the experimental and computational methods used to study these interactions. Additionally, we highlight significant studies on lncRNA and miRNA interactions in various diseases from 2000 to 2024, using the academic research databases such as PubMed, Google Scholar, ScienceDirect, and Scopus.

Cellular senescence molecules expression in type 2 diabetes mellitus: CDKN2A, CDKN2B, and lncRNA ANRIL

AIMS

Cellular senescence in type 2 diabetes mellitus (T2DM) has received widespread attention. However, the cellular senescence molecules involved in T2DM are unclear. Furthermore, there are no consistent biomarkers for cellular senescence in T2DM. Therefore, this study aimed to identify cellular senescence molecules in T2DM and investigate their expression in peripheral blood mononuclear cells of individuals with T2DM.

METHODS

Patients with T2DM (n = 40) and healthy controls (n = 40) were enrolled. We used different databases to identify cellular senescence molecules in T2DM and confirmed the obtained genes and lncRNA using real-time PCR.

RESULTS

Bioinformatics analysis indicated that CDKN2A and CDKN2B genes, and long noncoding RNA ANRIL are the most effective cellular senescence molecules in T2DM. Furthermore, CDKN2A and ANRIL expression decreased in individuals with T2DM.

CONCLUSIONS

Cellular senescence may have a protective effect against T2DM. In addition, the cellular senescence molecules CDKN2A and ANRIL may be potential biomarkers of cellular senescence in T2DM.

DinoKnot: Duplex Interaction of Nucleic Acids With PseudoKnots

Interaction of nucleic acid molecules is essential for their functional roles in the cell and their applications in biotechnology. While simple duplex interactions have been studied before, the problem of efficiently predicting the minimum free energy structure of more complex interactions with possibly pseudoknotted structures remains a challenge. In this work, we introduce a novel and efficient algorithm for prediction of Duplex Interaction of Nucleic acids with pseudoKnots, DinoKnot follows the hierarchical folding hypothesis to predict the secondary structure of two interacting nucleic acid strands (both homo- and hetero-dimers). DinoKnot utilizes the structure of molecules before interaction as a guide to find their duplex structure allowing for possible base pair competitions. To showcase DinoKnots's capabilities we evaluated its predicted structures against (1) experimental results for SARS-CoV-2 genome and nine primer-probe sets, (2) a clinically verified example of a mutation affecting detection, and (3) a known nucleic acid interaction involving a pseudoknot. In addition, we compared our results against our closest competition, RNAcofold, further highlighting DinoKnot's strengths. We believe DinoKnot can be utilized for various applications including screening new variants for potential detection issues and supporting existing applications involving DNA/RNA interactions, adding structural considerations to the interaction to elicit functional information.

Carcinogenic roles of MAFG-AS1 in human cancers

The MAF bZIP transcription factor G-antisense RNA 1 (MAFG-AS1) is located on chromosome 17. MAFG-AS1 was upregulated in 15 human cancers. MAFG-AS1 not only suppresses 16 miRNAs but also directly impacts 22 protein-coding genes' expression. Notably, abnormal MAFG-AS1 expression is connected to clinicopathological characteristics and a worse prognosis in a variety of cancers. Moreover, MAFG-AS1 takes its part in the tumorigenesis and progression of various human malignancies by suppressing apoptosis and promoting proliferation, migration, invasion, aerobic glycolysis, ferroptosis, angiogenesis, EMT, and metastasis. Besides, it can predict treatment effectiveness in ER + breast cancer, urothelial bladder carcinoma, and liver cancer by functioning as a trigger of resistance to tamoxifen, sorafenib, and cisplatin. This study systematically presents the functions of MAFG-AS1 in various cancers, as well as the findings of bioinformatics analyses of the MAFG-AS1, which should give clear advice for future research.

The Prognostic Value and Clinical Significance of lncRNA SNHG5 Expression in Patients with Multiple Malignancies: A Bioinformatic and Meta-analysis

BACKGROUND

Long non-coding RNA small nucleolar RNA host gene 5 (lncRNA SNHG5) has been identified as both a promising target for treatment and a predictor of prognosis in diverse types of cancer. The objective of this study was to assess whether lncRNA SNHG5 expression can be utilized as a prognostic biomarker for human cancer.

METHODS

To ensure a thorough search of the literature for relevant English studies published before July 2023, several databases were searched, including PubMed, Web of Science, ProQuest, Cochrane Library, and Google Scholar. The study evaluated the impact of lncRNA SNHG5 on the overall survival (OS) of cancer by calculating the pooled hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (CIs). To further confirm the accuracy of the findings, the study investigated the expression profile and prognostic significance of lncRNA SNHG5 through the use of GenomicScape, OncoLnc, Kaplan-Meier plotter, and GEPIA databases.

RESULTS

In this study, 995 patients were examined across a total of fourteen original studies. The findings indicated that there was a significant relationship between heightened lncRNA SNHG5 expression and reduced OS, as evidenced by both univariate and multivariate analyses (HR = 1.89; 95% CI, 1.44-2.49; p < 0.001; HR = 3.97; 95% CI, 1.80-8.73; p < 0.001, respectively). Pooled OR analysis showed a significant association between over-expression of lncRNA SNHG5 with advanced histological grade (OR = 0.28; 95% CI, 0.11-0.71; p = 0.007), present lymph node metastasis (LNM; OR = 4.28; 95% CI, 2.47-7.43; p < 0.001), and smoking history (OR = 0.27; 95% CI, 0.15-0.49; p < 0.001). Bioinformatic databases confirmed that elevated SNHG5 expression was significantly linked to poor prognosis in cancer patients, including colorectal cancer (CRC), acute myeloid leukemia (AML), and esophageal adenocarcinoma (ESAD), and a longer OS in patients with uterine corpus endometrial carcinoma (UCEC).

CONCLUSION

These results suggest that lncRNA SNHG5 may serve as an adverse prognostic biomarker in several human cancers. Further investigations are needed to better understand the underlying mechanisms that link lncRNA SNHG5 to multiple malignancies.

IncRna: The R Package for Optimizing lncRNA Identification Processes

In silico identification of long noncoding RNAs (lncRNAs) is a multistage process including filtering of transcripts according to their physical characteristics (e.g., length, exon-intron structure) and determination of the coding potential of the sequence. A common issue within this process is the choice of the most suitable method of coding potential analysis for the conducted research. Selection of tools on the sole basis of their single performance may not provide the most effective choice for a specific problem. To overcome these limitations, we developed the R library lncRna, which provides functions to easily carry out the entire lncRNA identification process. For example, the package prepares the data files for coding potential analysis to perform error analysis. Moreover, the package gives the opportunity to analyze the effectiveness of various combinations of the lncRNA prediction methods to select the optimal configuration of the entire process.

Evaluation of the Expression of miRNAs, LncRNAs, and their Target Gene, Caspase 3 in Glioblastoma Multiform: A Case-Control Study

Glioblastoma multiform (GBM) is an invasive cancer that causes high mortality in patients. Disruption of the apoptosis process is one of the main pathogenesis of the disease. Recently, LncRNAs and miRNAs have been shown to play an important role in the process of apoptosis. To follow the aim of study, 100 patients participated in the two groups of 50 individuals, including 50 GBM patients and 50 healthy individuals as the control group. Mononuclear cells were isolated from peripheral blood samples and RNA extraction was done. The expression changes of miR-17-5p, miR-20-5p, LINC01605, FAS-AS1, and Caspase 3 were examined using RT-PCR in both groups. Expression of LINC01605, miR-20-5p, and miR-17-5p increased in patients, while Caspase 3 and FAS-AS1 decreased; the difference was statistically significant between the two groups. In addition, it was found that these factors have the appropriate sensitivity and specificity as diagnostic markers. Finally, It is suggested to use the LINC01605, FAS-AS1, miR-20-5p, miR-17-5p, and Caspase 3 as apoptosis predictors in the GM patients.

Analysis of lncRNAs in Lupinus mutabilis (Tarwi) and Their Potential Role in Drought Response

Lupinus mutabilis is a legume with high agronomic potential and available transcriptomic data for which lncRNAs have not been studied. Therefore, our objective was to identify, characterize, and validate the drought-responsive lncRNAs in L. mutabilis. To achieve this, we used a multilevel approach based on lncRNA prediction, annotation, subcellular location, thermodynamic characterization, structural conservation, and validation. Thus, 590 lncRNAs were identified by at least two algorithms of lncRNA identification. Annotation with the PLncDB database showed 571 lncRNAs unique to tarwi and 19 lncRNAs with homology in 28 botanical families including Solanaceae (19), Fabaceae (17), Brassicaceae (17), Rutaceae (17), Rosaceae (16), and Malvaceae (16), among others. In total, 12 lncRNAs had homology in more than 40 species. A total of 67% of lncRNAs were located in the cytoplasm and 33% in exosomes. Thermodynamic characterization of S03 showed a stable secondary structure with -105.67 kcal/mol. This structure included three regions, with a multibranch loop containing a hairpin with a SECIS-like element. Evaluation of the structural conservation by CROSSalign revealed partial similarities between L. mutabilis (S03) and S. lycopersicum (Solyc04r022210.1). RT-PCR validation demonstrated that S03 was upregulated in a drought-tolerant accession of L. mutabilis. Finally, these results highlighted the importance of lncRNAs in tarwi improvement under drought conditions.

Decoding the regulatory roles of non-coding RNAs in cellular metabolism and disease

Non-coding RNAs, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), are being studied extensively in a variety of fields. Their roles in metabolism have received increasing attention in recent years but are not yet clear. The regulation of glucose, fatty acid, and amino acid metabolism is an imperative physiological process that occurs in living organisms and takes part in cancer and cardiovascular diseases. Here, we summarize the important roles played by non-coding RNAs in glucose metabolism, fatty acid metabolism, and amino acid metabolism, as well as the mechanisms involved. We also summarize the therapeutic advances for non-coding RNAs in diseases such as obesity, cardiovascular disease, and some metabolic diseases. Overall, non-coding RNAs are indispensable factors in metabolism and have a significant role in the three major metabolisms, which may be exploited as therapeutic targets in the future.

RNA-Chrom: a manually curated analytical database of RNA-chromatin interactome

Every year there is more and more evidence that non-coding RNAs play an important role in biological processes affecting various levels of organization of living systems: from the cellular (regulation of gene expression, remodeling and maintenance of chromatin structure, co-transcriptional suppression of transposons, splicing, post-transcriptional RNA modifications, etc.) to cell populations and even organismal ones (development, aging, cancer, cardiovascular and many other diseases). The development and creation of mutually complementary databases that will aggregate, unify and structure different types of data can help to reach the system level of studying non-coding RNAs. Here we present the RNA-Chrom manually curated analytical database, which contains the coordinates of billions of contacts of thousands of human and mouse RNAs with chromatin. Through the user-friendly web interface (https://rnachrom2.bioinf.fbb.msu.ru/), two approaches to the analysis of the RNA-chromatin interactome were implemented. Firstly, to find out whether the RNA of interest to a user contacts with chromatin, and if so, with which genes or DNA loci? Secondly, to find out which RNAs are in contact with the DNA locus of interest to a user (and probably participate in its regulation), and if there are such, what is the nature of their interaction? For a more detailed study of contact maps and their comparison with other data, the web interface allows a user to view them in the UCSC Genome Browser. Database URL https://genome.ucsc.edu/.

Mechanisms of circRNA/lncRNA-miRNA interactions and applications in disease and drug research

In recent years, breakthroughs in bioinformatics have been made with the discovery of many functionally significant non-coding RNAs (ncRNAs). The discovery of these ncRNAs has further demonstrated the multi-level characteristics of intracellular gene expression regulation, which plays an important role in assisting diagnosis, guiding clinical drug use and determining prognosis in the treatment process of various diseases. microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) are the three major types of ncRNAs that interact with each other. Studies have shown that lncRNAs and circRNAs can sponge miRNAs, thereby influencing normal physiological processes and regulating mRNA expression and, thus, the physiological state of cells. This paper summarizes the mechanism of action and research progress of the three ncRNA and seven types of modalities. This summary is intended to provide new ideas for diagnosing and treating diseases and researching and developing new drugs.

Discovery of Transacting Long Noncoding RNAs That Regulate Smooth Muscle Cell Phenotype

BACKGROUND

Smooth muscle cells (SMC), the major cell type in atherosclerotic plaques, are vital in coronary artery diseases (CADs). SMC phenotypic transition, which leads to the formation of various cell types in atherosclerotic plaques, is regulated by a network of genetic and epigenetic mechanisms and governs the risk of disease. The involvement of long noncoding RNAs (lncRNAs) has been increasingly identified in cardiovascular disease. However, SMC lncRNAs have not been comprehensively characterized, and their regulatory role in SMC state transition remains unknown.

METHODS

A discovery pipeline was constructed and applied to deeply strand-specific RNA sequencing from perturbed human coronary artery SMC with different disease-related stimuli, to allow for the detection of novel lncRNAs. The functional relevance of a select few novel lncRNAs were verified in vitro.

RESULTS

We identified 4579 known and 13 655 de novo lncRNAs in human coronary artery SMC. Consistent with previous long noncoding RNA studies, these lncRNAs overall have fewer exons, are shorter in length than protein-coding genes (pcGenes), and have relatively low expression level. Genomic location of these long noncoding RNA is disproportionately enriched near CAD-related TFs (transcription factors), genetic loci, and gene regulators of SMC identity, suggesting the importance of their function in disease. Two de novo lncRNAs, ZIPPOR (ZEB-interacting suppressor) and TNS1-AS2 (TNS1-antisense 2), were identified by our screen. Combining transcriptional data and in silico modeling along with in vitro validation, we identified CAD gene ZEB2 as a target through which these lncRNAs exert their function in SMC phenotypic transition.

CONCLUSIONS

Expression of a large and diverse set of lncRNAs in human coronary artery SMC are highly dynamic in response to CAD-related stimuli. The dynamic changes in expression of these lncRNAs correspond to alterations in transcriptional programs that are relevant to CAD, suggesting a critical role for lncRNAs in SMC phenotypic transition and human atherosclerotic disease.

Long Non-Coding RNAs (lncRNAs) as Regulators of the PI3K/AKT/mTOR Pathway in Gastric Carcinoma

Gastric cancer (GC) represents ~10% of the global cancer-related deaths, increasingly affecting the younger population in active stages of life. The high mortality of GC is due to late diagnosis, the presence of metastasis and drug resistance development. Additionally, current clinical markers do not guide the patient management adequately, thereby new and more reliable biomarkers and therapeutic targets are still needed for this disease. RNA-seq technology has allowed the discovery of new types of RNA transcripts including long non-coding RNAs (lncRNAs), which are able to regulate the gene/protein expression of many signaling pathways (e.g., the PI3K/AKT/mTOR pathway) in cancer cells by diverse molecular mechanisms. In addition, these lncRNAs might also be proposed as promising diagnostic or prognostic biomarkers or as potential therapeutic targets in GC. This review describes important topics about some lncRNAs that have been described as regulators of the PI3K/AKT/mTOR signaling pathway, and hence, their potential oncogenic role in the development of this malignancy.

Comparative transcriptomic analysis of long noncoding RNAs in Leishmania-infected human macrophages

It is well established that infection with Leishmania alters the host cell's transcriptome. Since mammalian cells have multiple mechanisms to control gene expression, different molecules, such as noncoding RNAs, can be involved in this process. MicroRNAs have been extensively studied upon Leishmania infection, but whether long noncoding RNAs (lncRNAs) are also altered in macrophages is still unexplored. We performed RNA-seq from THP-1-derived macrophages infected with Leishmania amazonensis (La), L. braziliensis (Lb), and L. infantum (Li), investigating a previously unappreciated fraction of macrophage transcriptome. We found that more than 24% of the total annotated transcripts and 30% of differentially expressed (DE) RNAs in Leishmania-infected macrophage correspond to lncRNAs. LncRNAs and protein coding RNAs with altered expression are similar among macrophages infected with the Leishmania species. Still, some species-specific alterations could occur due to distinct pathophysiology in which Li infection led to a more significant number of exclusively DE RNAs. The most represented classes among DE lncRNAs were intergenic and antisense lncRNAs. We also found enrichment for immune response-related pathways in the DE protein coding RNAs, as well as putative targets of the lncRNAs. We performed a coexpression analysis to explore potential cis regulation of coding and antisense noncoding transcripts. We identified that antisense lncRNAs are similarly regulated as its neighbor protein coding genes, such as the BAALC/BAALC-AS1, BAALC/BAALC-AS2, HIF1A/HIF1A-AS1, HIF1A/HIF1A-AS3 and IRF1/IRF1-AS1 pairs, which can occur as a species-specific modulation. These findings are a novelty in the field because, to date, no study has focused on analyzing lncRNAs in Leishmania-infected macrophage. Our results suggest that lncRNAs may account for a novel mechanism by which Leishmania can control macrophage function. Further research must validate putative lncRNA targets and provide additional prospects in lncRNA function during Leishmania infection.

An overview of long noncoding RNAs: Biology, functions, therapeutics, analysis methods, and bioinformatics tools

Long noncoding RNAs (lncRNAs) are a diverse class of RNAs whose functions are widespread in all branches of life and have been the focus of attention in the last decade. While a huge number of lncRNAs have been identified, there is still much work to be done and plenty to be learned. In the current review, we begin with the biogenesis and function of lncRNAs as they are involved in the different cellular processes from regulating the architecture of chromosomes to controlling translation and post-translation modifications. Questions on how overexpression, mutations, or deficiency of lncRNAs can affect the cellular status and result in the pathogenesis of various human diseases are responded to. Besides, we allocate an overview of several studies, concerning the application of lncRNAs either as diagnostic and prognostic biomarkers or novel therapeutics. We also introduce the currently available techniques to explore details of lncRNAs such as their function, cellular localization, and structure. In the last section, as exponentially growing data in this area need to be gathered and organized in comprehensive databases, we have a particular focus on presenting general and specialized databases. Taken together, with this review, we aim to provide the latest information on different aspects of lncRNAs to highlight their importance in physiopathologic states and take a step towards helping future studies.

Identification of Differentially Expressed Intronic Transcripts in Osteosarcoma

Over the past decade; the discovery and characterization of long noncoding RNAs (lncRNAs) have revealed that they play a major role in the development of various diseases; including cancer. Intronic transcripts are one of the most fascinating lncRNAs that are located within intron regions of protein-coding genes, which have the advantage of encoding micropeptides. There have been several studies looking at intronic transcript expression profiles in cancer; but almost none in osteosarcoma. To overcome this problem; we have investigated differentially expressed intronic transcripts between osteosarcoma and normal bone tissues. The results highlighted that NRG1-IT1; FGF14-IT1; and HAO2-IT1 were downregulated; whereas ER3-IT1; SND1-IT1; ANKRD44-IT1; AGAP1-IT1; DIP2A-IT1; LMO7DN-IT1; SLIT2-IT1; RNF216-IT1; and TCF7L1-IT1 were upregulated in osteosarcoma tissues compared to normal bone tissues. Furthermore, we identified if the transcripts encode micropeptides and the transcripts' locations in a cell.

Metformin Treatment Modulates Long Non-Coding RNA Isoforms Expression in Human Cells

Long noncoding RNAs (lncRNAs) undergo splicing and have multiple transcribed isoforms. Nevertheless, for lncRNAs, as well as for mRNA, measurements of expression are routinely performed only at the gene level. Metformin is the first-line oral therapy for type 2 diabetes mellitus and other metabolic diseases. However, its mechanism of action remains not thoroughly explained. Transcriptomic analyses using metformin in different cell types reveal that only protein-coding genes are considered. We aimed to characterize lncRNA isoforms that were differentially affected by metformin treatment on multiple human cell types (three cancer, two non-cancer) and to provide insights into the lncRNA regulation by this drug. We selected six series to perform a differential expression (DE) isoform analysis. We also inferred the biological roles for lncRNA DE isoforms using in silico tools. We found the same isoform of an lncRNA (AC016831.6-205) highly expressed in all six metformin series, which has a second exon putatively coding for a peptide with relevance to the drug action. Moreover, the other two lncRNA isoforms (ZBED5-AS1-207 and AC125807.2-201) may also behave as cis-regulatory elements to the expression of transcripts in their vicinity. Our results strongly reinforce the importance of considering DE isoforms of lncRNA for understanding metformin mechanisms at the molecular level.

ncRNAs and polyphenols: new therapeutic strategies for hypertension

Polyphenols have gained significant attention in protecting several chronic diseases, such as cardiovascular diseases (CVDs). Accumulating evidence indicates that polyphenols have potential protective roles for various CVDs. Hypertension (HTN) is among the hazardous CVDs accounting for nearly 8.5 million deaths worldwide. HTN is a complex and multifactorial disease and a combination of genetic susceptibility and environmental factors play major roles in its development. However, the underlying regulatory mechanisms are still elusive. Polyphenols have shown to cause favourable and beneficial effects in the management of HTN. Noncoding RNAs (ncRNAs) as influential mediators in modulating the biological properties of polyphenols, have shown significant footprints in CVDs. ncRNAs control basic functions in virtually all cell types relevant to the cardiovascular system and, thus, a direct link with blood pressure (BP) regulation is highly probable. Recent evidence suggests that a number of ncRNAs, including main small ncRNAs, microRNAs (miRNAs) and long ncRNAs (lncRNAs), play crucial roles with respect to the antihypertensive effects of polyphenols. Indeed, targeting lncRNAs by polyphenols will be a novel and promising strategy in the management of HTN. Herein, we reviewed the effects of polyphenols in HTN. Additionally, we emphasized on the potential effects of polyphenols on regulations of main ncRNAs, which imply the role of polyphenols in regulating ncRNAs in order to exert protective effects and thus proposing them as new targets for HTN treatment.Abbreviations : CVD: cardiovascular disease; BP: blood pressure; HTN: hypertension, lncRNAs: long noncoding RNAs; p38-MAPK: p38-mitogenactivated protein kinase; OPCs: oligomeric procyanidins; GTP: guanosine triphosphate; ROS: reactive oxygen species; cGMP: cyclic guanosine monophosphate; SGC: soluble guanylate cyclase; PI3K: phosphatidylinositol 3-kinase; cGMP: Cyclic GMP; eNOS: endothelial NO synthase; ERK ½: extracellular signal-regulated kinase ½; L-Arg: L-Arginine; MAPK: mitogen-activated protein kinases; NO: Nitric oxide; P: Phosphorus; PDK1: Phosphoinositide-dependent kinase 1; PI3-K: Phosphatidylinositol 3-kinase; PIP2: Phosphatidylinositol diphosphate; ncRNAs: non-protein-coding RNA; miRNAs: microRNAs; OPCs: oligomeric procyanidins; RES: resveratrol; GE: grape extract; T2DM: type 2 diabetes mellitus; IL: interleukin; TNF-α: tumour necrosis factor-alpha; NF-κB: nuclear factor NF-kappa-B; ALP: alkaline phosphatase; PARP1: poly [ADP-ribose] polymerase 1; HIF1a: Hypoxia-inducible-factor 1A; NFATc2: nuclear factor of activated T cells 2; PAD: peripheral artery disease; SHR: spontaneously hypertensive rat; RAAS: renin-angiotensin-aldosterone system; AT₁R: angiotensin type-1 receptor; Nox: NADPH oxidase; HO-1: haem oxygenase-1; JAK/STAT: Janus kinase/signal transducers/activators of the transcription; PNS: panax notoginseng saponin; snoRNA: small nucleolar RNA; hnRNA: heterogeneous nuclear RNA; VSMCs: vascular smooth muscle cells; irf7: interferon regulatory factor 7; limo2: LIM only domain 2; GWAS: genome-wide association study; GAS5: Growth arrest-specific 5; Asb3, Ankyrin repeat and SPCS box containing 3; Chac2: cation transport regulator homolog 2; Pex11b: peroxisomal membrane 11B; Sp5: Sp5 transcription factor; EGCG: epigallocatechin gallate; ApoE: Apo lipoprotein E; ERK-MAP kinase: extracellular signal-regulated kinases-mitogen-activated protein kinase; PAH: pulmonary artery hypertension; PAP: pulmonary arterial pressure; HIF1a: hypoxia-inducible-factor 1A; NFATc2: nuclear factor of activated T cells 2; HMEC-1: Human microvascular endothelial cells; stat2: signal transducers and activators of transcription 2; JNK: c-Jun N-terminal kinase; iNOS: inducible NO synthase. SNP: single nucleotide polymorphism; CAD: coronary artery disease.

Insight Into the Long Noncoding RNA and mRNA Coexpression Profile in the Human Blood Transcriptome Upon Leishmania infantum Infection

Visceral leishmaniasis (VL) is a vector-borne infectious disease that can be potentially fatal if left untreated. In Brazil, it is caused by Leishmania infantum parasites. Blood transcriptomics allows us to assess the molecular mechanisms involved in the immunopathological processes of several clinical conditions, namely, parasitic diseases. Here, we performed mRNA sequencing of peripheral blood from patients with visceral leishmaniasis during the active phase of the disease and six months after successful treatment, when the patients were considered clinically cured. To strengthen the study, the RNA-seq data analysis included two other non-diseased groups composed of healthy uninfected volunteers and asymptomatic individuals. We identified thousands of differentially expressed genes between VL patients and non-diseased groups. Overall, pathway analysis corroborated the importance of signaling involving interferons, chemokines, Toll-like receptors and the neutrophil response. Cellular deconvolution of gene expression profiles was able to discriminate cellular subtypes, highlighting the contribution of plasma cells and NK cells in the course of the disease. Beyond the biological processes involved in the immunopathology of VL revealed by the expression of protein coding genes (PCGs), we observed a significant participation of long noncoding RNAs (lncRNAs) in our blood transcriptome dataset. Genome-wide analysis of lncRNAs expression in VL has never been performed. lncRNAs have been considered key regulators of disease progression, mainly in cancers; however, their pattern regulation may also help to understand the complexity and heterogeneity of host immune responses elicited by L. infantum infections in humans. Among our findings, we identified lncRNAs such as IL21-AS1, MIR4435-2HG and LINC01501 and coexpressed lncRNA/mRNA pairs such as CA3-AS1/CA1, GASAL1/IFNG and LINC01127/IL1R1-IL1R2. Thus, for the first time, we present an integrated analysis of PCGs and lncRNAs by exploring the lncRNA–mRNA coexpression profile of VL to provide insights into the regulatory gene network involved in the development of this inflammatory and infectious disease.

Identification of human gene research articles with wrongly identified nucleotide sequences

Nucleotide sequence reagents underpin molecular techniques that have been applied across hundreds of thousands of publications. We have previously reported wrongly identified nucleotide sequence reagents in human research publications and described a semi-automated screening tool Seek & Blastn to fact-check their claimed status. We applied Seek & Blastn to screen >11,700 publications across five literature corpora, including all original publications in Gene from 2007 to 2018 and all original open-access publications in Oncology Reports from 2014 to 2018. After manually checking Seek & Blastn outputs for >3,400 human research articles, we identified 712 articles across 78 journals that described at least one wrongly identified nucleotide sequence. Verifying the claimed identities of >13,700 sequences highlighted 1,535 wrongly identified sequences, most of which were claimed targeting reagents for the analysis of 365 human protein-coding genes and 120 non-coding RNAs. The 712 problematic articles have received >17,000 citations, including citations by human clinical trials. Given our estimate that approximately one-quarter of problematic articles may misinform the future development of human therapies, urgent measures are required to address unreliable gene research articles.

FibroDB: Expression Analysis of Protein-Coding and Long Non-Coding RNA Genes in Fibrosis

Most long non-coding RNAs (lncRNAs) are expressed at lower levels than protein-coding genes and their expression is often restricted to specific cell types, certain time points during development, and various stress and disease conditions, respectively. To revisit this long-held concept, we focused on fibroblasts, a common cell type in various organs and tissues. Using fibroblasts and changes in their expression profiles during fibrosis as a model system, we show that the overall expression level of lncRNA genes is significantly lower than that of protein-coding genes. Furthermore, we identified lncRNA genes whose expression is upregulated during fibrosis. Using dermal fibroblasts as a model, we performed loss-of-function experiments and show that the knockdown of the lncRNAs LINC00622 and LINC01711 result in gene expression changes associated with cellular and inflammatory responses, respectively. Since there are no lncRNA databases focused on fibroblasts and fibrosis, we built a web application, FibroDB, to further promote functional and mechanistic studies of fibrotic lncRNAs.

Long RNA-Mediated Chromatin Regulation in Fission Yeast and Mammals

As part of a complex network of genome control, long regulatory RNAs exert significant influences on chromatin dynamics. Understanding how this occurs could illuminate new avenues for disease treatment and lead to new hypotheses that would advance gene regulatory research. Recent studies using the model fission yeast Schizosaccharomyces pombe (S. pombe) and powerful parallel sequencing technologies have provided many insights in this area. This review will give an overview of key findings in S. pombe that relate long RNAs to multiple levels of chromatin regulation: histone modifications, gene neighborhood regulation in cis and higher-order chromosomal ordering. Moreover, we discuss parallels recently found in mammals to help bridge the knowledge gap between the study systems.

Advances in the identification of long non-coding RNA binding proteins

Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nt without evident protein coding function. They play important regulatory roles in many biological processes, e.g., gene regulation, chromatin remodeling, and cell fate determination during development. Dysregulation of lncRNAs has been observed in various diseases including cancer. Interacting with proteins is a crucial way for lncRNAs to play their biological roles. Therefore, the characterization of lncRNA binding proteins is important to understand their functions and to delineate the underlying molecular mechanism. Large-scale studies based on mass spectrometry have characterized over a thousand new RNA binding proteins without known RNA-binding domains, thus revealing the complexity and diversity of RNA-protein interactions. In addition, several methods have been developed to identify the binding proteins for particular RNAs of interest. Here we review the progress of the RNA-centric methods for the identification of RNA-protein interactions, focusing on the studies involving lncRNAs, and discuss their strengths and limitations.

Long non-coding RNAs and their potential impact on diagnosis, prognosis, and therapy in prostate cancer: racial, ethnic, and geographical considerations

INTRODUCTION

Advances in high-throughput sequencing have greatly advanced our understanding of long non-coding RNAs (lncRNAs) in a relatively short period of time. This has expanded our knowledge of cancer, particularly how lncRNAs drive many important cancer phenotypes via their regulation of gene expression.

AREAS COVERED

Men of African descent are disproportionately affected by PC in terms of incidence, morbidity, and mortality. LncRNAs could serve as biomarkers to differentiate low-risk from high-risk diseases. Additionally, they may represent therapeutic targets for advanced and castrate-resistant cancer. We review current research surrounding lncRNAs and their association with PC. We discuss how lncRNAs can provide new insights and diagnostic biomarkers for African American men. Finally, we review advances in computational approaches that predict the regulatory effects of lncRNAs in cancer.

EXPERT OPINION

PC diagnostic biomarkers that offer high specificity and sensitivity are urgently needed. PC specific lncRNAs are compelling as diagnostic biomarkers owing to their high tissue and tumor specificity and presence in bodily fluids. Recent studies indicate that PCA3 clinical utility might be restricted to men of European descent. Further work is required to develop lncRNA biomarkers tailored for men of African descent.

Long non-coding RNAs: novel regulators of cellular physiology and function

Long non-coding RNAs were once considered as “junk” RNA produced by aberrant DNA transcription. They are now understood to play central roles in diverse cellular processes from proliferation and migration to differentiation, senescence and DNA damage control. LncRNAs are classed as transcripts longer than 200 nucleotides that do not encode a peptide. They are relevant to many physiological and pathophysiological processes through their control of fundamental molecular functions. This review summarises the recent progress in lncRNA research and highlights the far-reaching physiological relevance of lncRNAs. The main areas of lncRNA research encompassing their characterisation, classification and mechanisms of action will be discussed. In particular, the regulation of gene expression and chromatin landscape through lncRNA control of proteins, DNA and other RNAs will be introduced. This will be exemplified with a selected number of lncRNAs that have been described in numerous physiological contexts and that should be largely representative of the tens-of-thousands of mammalian lncRNAs. To some extent, these lncRNAs have inspired the current thinking on the central dogmas of epigenetics, RNA and DNA mechanisms.

Fragmentation of Apolipoprotein E4 is Required for Differential Expression of Inflammation and Activation Related Genes in Microglia Cells

The apolipoprotein E4 (APOE4) allele represents the single greatest risk factor for late-onset Alzheimer's disease (AD) and accumulating evidence suggests that fragmentation with a toxic-gain of function may be a key molecular step associated with this risk. Recently, we demonstrated strong immunoreactivity of a 151 amino-terminal fragment of apoE4 (E4-fragment) within the nucleus of microglia in the human AD brain. In vitro, this fragment led to toxicity and activation of inflammatory processes in BV2 microglia cells. Additionally, a transcriptome analysis following exogenous treatment of BV2 microglia cells with this E4 fragment led to a > 2-fold up regulation of 1,608 genes, with many genes playing a role in inflammation and microglia activation. To extend these findings, we here report a similar transcriptome analysis in BV2 microglia cells following treatment with full-length ApoE4 (FL-ApoE4). The results indicated that full-length ApoE4 had a very small effect on gene expression compared to the fragment. Only 48 differentially expressed genes (DEGs) were identified (p < 0.05, and greater than 2-fold change). A gene ontology analysis of these DEGs indicated that they are not involved in inflammatory and activation processes, in contrast to the genes up regulated by the E4-fragment. In addition, genes that showed a negative fold-change upon FL-E4 treatment typically showed a strong positive fold-change upon treatment with the fragment (Pearson's r = -0.7). Taken together, these results support the hypothesis that a key step in the conversion of microglia to an activated phenotype is proteolytic cleavage of FL-ApoE4. Therefore, the neutralization of this amino-terminal fragment of ApoE4, specifically, may serve as an important therapeutic strategy in the treatment of AD.

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.

(In)Distinctive Role of Long Non-Coding RNAs in Common and Rare Ovarian Cancers

Rare ovarian cancers (ROCs) are OCs with an annual incidence of fewer than 6 cases per 100,000 women. They affect women of all ages, but due to their low incidence and the potential clinical inexperience in management, there can be a delay in diagnosis, leading to a poor prognosis. The underlying causes for these tumors are varied, but generally, the tumors arise due to alterations in gene/protein expression in cellular processes that regulate normal proliferation and its checkpoints. Dysregulation of the cellular processes that lead to cancer includes gene mutations, epimutations, non-coding RNA (ncRNA) regulation, posttranscriptional and posttranslational modifications. Long non-coding RNA (lncRNA) are defined as transcribed RNA molecules, more than 200 nucleotides in length which are not translated into proteins. They regulate gene expression through several mechanisms and therefore add another level of complexity to the regulatory mechanisms affecting tumor development. Since few studies have been performed on ROCs, in this review we summarize the mechanisms of action of lncRNA in OC, with an emphasis on ROCs.

Single-Cell RNA-Seq Reveals Heterogeneous lncRNA Expression in Xenografted Triple-Negative Breast Cancer Cells

Breast cancer is the most commonly diagnosed cancer in the world, with triple-negative breast cancer (TNBC) making up 12% of these diagnoses. TNBC tumours are highly heterogeneous in both inter-tumour and intra-tumour gene expression profiles, where they form subclonal populations of varying levels of aggressiveness. These aspects make it difficult to study and treat TNBC, requiring further research into tumour heterogeneity as well as potential therapeutic targets and biomarkers. Recently, it was discovered that the majority of the transcribed genome comprises non-coding RNAs, in particular long non-coding RNAs (lncRNAs). LncRNAs are transcripts of >200 nucleotides in length that do not encode a protein. They have been characterised as regulatory molecules and their expression can be associated with a malignant phenotype. We set out to explore TNBC tumour heterogeneity in vivo at a single cell level to investigate whether lncRNA expression varies across different cells within the tumour, even if cells are coming from the same cell line, and whether lncRNA expression is sufficient to define cellular subpopulations. We applied single-cell expression profiling due to its ability to capture expression signals of lncRNAs expressed in small subpopulations of cells. Overall, we observed most lncRNAs to be expressed at low, but detectable levels in TNBC xenografts, with a median of 25 lncRNAs detected per cell. LncRNA expression alone was insufficient to define a subpopulation of cells, and lncRNAs showed highly heterogeneous expression patterns, including ubiquitous expression, subpopulation-specific expression, and a hybrid pattern of lncRNAs expressed in several, but not all subpopulations. These findings reinforce that transcriptionally defined tumour cell subpopulations can be identified in cell-line derived xenografts, and uses single-cell RNA-seq (scRNA-seq) to detect and characterise lncRNA expression across these subpopulations in xenografted tumours. Future studies will aim to investigate the spatial distribution of lncRNAs within xenografts and patient tissues, and study the potential of subclone-specific lncRNAs as new therapeutic targets and/or biomarkers.

Epigenetic Regulation of the Vascular Endothelium by Angiogenic LncRNAs

The functional properties of the vascular endothelium are diverse and heterogeneous between vascular beds. This is especially evident when new blood vessels develop from a pre-existing closed cardiovascular system, a process termed angiogenesis. Endothelial cells are key drivers of angiogenesis as they undergo a highly choreographed cascade of events that has both exogenous (e.g., hypoxia and VEGF) and endogenous regulatory inputs. Not surprisingly, angiogenesis is critical in health and disease. Diverse therapeutics target proteins involved in coordinating angiogenesis with varying degrees of efficacy. It is of great interest that recent work on non-coding RNAs, especially long non-coding RNAs (lncRNAs), indicates that they are also important regulators of the gene expression paradigms that underpin this cellular cascade. The protean effects of lncRNAs are dependent, in part, on their subcellular localization. For instance, lncRNAs enriched in the nucleus can act as epigenetic modifiers of gene expression in the vascular endothelium. Of great interest to genetic disease, they are undergoing rapid evolution and show extensive inter- and intra-species heterogeneity. In this review, we describe endothelial-enriched lncRNAs that have robust effects in angiogenesis.

Decoding LncRNAs

Non-coding RNAs (ncRNAs) have been considered as unimportant additions to the transcriptome. Yet, in light of numerous studies, it has become clear that ncRNAs play important roles in development, health and disease. Long-ignored, long non-coding RNAs (lncRNAs), ncRNAs made of more than 200 nucleotides have gained attention due to their involvement as drivers or suppressors of a myriad of tumours. The detailed understanding of some of their functions, structures and interactomes has been the result of interdisciplinary efforts, as in many cases, new methods need to be created or adapted to characterise these molecules. Unlike most reviews on lncRNAs, we summarize the achievements on lncRNA studies by taking into consideration the approaches for identification of lncRNA functions, interactomes, and structural arrangements. We also provide information about the recent data on the involvement of lncRNAs in diseases and present applications of these molecules, especially in medicine.

Web tools to perform long non-coding RNAs analysis in oncology research

Accumulated evidence suggests that the widely expressed long-non-coding RNAs (lncRNAs) are involved in biogenesis. Some aberrant lncRNAs are closely related to pathological changes, for instance, in cancer. Both in tumorigenesis and cancer progression, depending on the interplay with cellular molecules, lncRNAs can modulate transcriptional interference, chromatin remodeling, post-translational regulation and protein modification, and further interfere with signaling pathways. Aiming to the diagnosis/ prognosis markers or potential therapeutical targets, it is important to figure out the specific mechanism and the tissue-specific expressing patterns of lncRNAs. Generally, the bioinformatics analysis is the first step. More and more in silico databases are increasing. But the existing integrative online platforms’ functions are not only having their unique features but also share some common features, which may lead to a waste of time for researchers. Here, we reviewed these web tools according to the functions. For each database, we clarified the data source, analysis method and the evidence that the analysis result is derived from. This review also illustrated examples in practical use for a specific lncRNA by these web tools. It will provide convenience for researchers to quickly choose the appropriate bioinformatics web tools in oncology studies.