The State of Long Non-Coding RNA Biology. Noncoding RNA. 2018;4:17. [PMID: 30103474 PMCID: PMC6162524 DOI: 10.3390/ncrna4030017]

Fundamental Neurochemistry Review: At the intersection between the brain and the immune system: Non-coding RNAs spanning learning, memory and adaptive immunity

Non-coding RNAs (ncRNAs) are highly plastic RNA molecules that can sequester cellular proteins and other RNAs, serve as transporters of cellular cargo and provide spatiotemporal feedback to the genome. Mounting evidence indicates that ncRNAs are central to biology, and are critical for neuronal development, metabolism and intra- and intercellular communication in the brain. Their plasticity arises from state-dependent dynamic structure states that can be influenced by cell type and subcellular environment, which can subsequently enable the same ncRNA with discrete functions in different contexts. Here, we highlight different classes of brain-enriched ncRNAs, including microRNA, long non-coding RNA and other enigmatic ncRNAs, that are functionally important for both learning and memory and adaptive immunity, and describe how they may promote cross-talk between these two evolutionarily ancient biological systems.

DNAJB1-PRKACA fusion protein-regulated LINC00473 promotes tumor growth and alters mitochondrial fitness in fibrolamellar carcinoma

Fibrolamellar carcinoma (FLC) is a rare liver cancer that disproportionately affects adolescents and young adults. Currently, no standard of care is available and there remains a dire need for new therapeutics. Most patients harbor the fusion oncogene DNAJB1-PRKACA (DP fusion), but clinical inhibitors are not yet developed and it is critical to identify downstream mediators of FLC pathogenesis. Here, we identify long noncoding RNA LINC00473 among the most highly upregulated genes in FLC tumors and determine that it is strongly suppressed by RNAi-mediated inhibition of the DP fusion in FLC tumor epithelial cells. We show by loss- and gain-of-function studies that LINC00473 suppresses apoptosis, increases the expression of FLC marker genes, and promotes FLC growth in cell-based and in vivo disease models. Mechanistically, LINC00473 plays an important role in promoting glycolysis and altering mitochondrial activity. Specifically, LINC00473 knockdown leads to increased spare respiratory capacity, which indicates mitochondrial fitness. Overall, we propose that LINC00473 could be a viable target for this devastating disease.

Role of long non-coding RNAs in the pathophysiology of Alzheimer's disease and other dementias

Dementia is the term used to describe a group of cognitive disorders characterized by a decline in memory, thinking, and reasoning abilities that interfere with daily life activities. Examples of dementia include Alzheimer's Disease (AD), Frontotemporal dementia (FTD), Amyotrophic lateral sclerosis (ALS), Vascular dementia (VaD) and Progressive supranuclear palsy (PSP). AD is the most common form of dementia. The hallmark pathology of AD includes formation of β-amyloid (Aβ) oligomers and tau hyperphosphorylation in the brain, which induces neuroinflammation, oxidative stress, synaptic dysfunction, and neuronal apoptosis. Emerging studies have associated long non-coding RNAs (lncRNAs) with the pathogenesis and progression of the neurodegenerative diseases. LncRNAs are defined as RNAs longer than 200 nucleotides that lack the ability to encode functional proteins. LncRNAs play crucial roles in numerous biological functions for their ability to interact with different molecules, such as proteins and microRNAs, and subsequently regulate the expression of their target genes at transcriptional and post-transcriptional levels. In this narrative review, we report the function and mechanisms of action of lncRNAs found to be deregulated in different types of dementia, with the focus on AD. Finally, we discuss the emerging role of lncRNAs as biomarkers of dementias.

Targeting long non-coding RNA MALAT1 reverses cancerous phenotypes of breast cancer cells through microRNA-561-3p/TOP2A axis

Non-coding RNAs, including Inc-RNA and miRNA, have been reported to regulate gene expression and are associated with cancer progression. MicroRNA-561-3p (miR-561-3p), as a tumor suppressor, has been reported to play a role in preventing cancer cell progression, and MALAT1 (Lnc-RNA) have also been demonstrated to promote malignancy in various cancers, such as breast cancer (BC). In this study, we aimed to determine the correlation between miR-561-3p and MALAT1 and their roles in breast cancer progression. The expression of MALAT1, mir-561-3p, and topoisomerase alpha 2 (TOP2A) as a target of miR-561-3p was determined in BC clinical samples and cell lines via qRT-PCR. The binding site between MALAT1, miR-561-3p, and TOP2A was investigated by performing the dual luciferase reporter assay. MALAT1 was knocked down by siRNA, and cell proliferation, apoptotic assays, and cell cycle arrest were evaluated. MALAT1 and TOP2A were significantly upregulated, while mir-561-3p expression was downregulated in BC samples and cell lines. MALAT1 knockdown significantly increased miR-561-3p expression, which was meaningfully inverted by co-transfection with the miR 561-3p inhibitor. Furthermore, the knockdown of MALAT1 by siRNA inhibited proliferation, induced apoptosis, and arrested the cell cycle at the G1 phase in BC cells. Notably, the mechanistic investigation revealed that MALAT1 predominantly acted as a competing endogenous RNA in BC by regulating the miR-561-3p/TOP2A axis. Based on our results, MALAT1 upregulation in BC may function as a tumor promoter in BC via directly sponging miRNA 561-3p, and MALAT1 knockdown serves a vital antitumor role in BC cell progression through the miR-561-3p/TOP2A axis.

The Mission of Long Non-Coding RNAs in Human Adult Renal Stem/Progenitor Cells and Renal Diseases

Long non-coding RNAs (lncRNAs) are a large, heterogeneous class of transcripts and key regulators of gene expression at both the transcriptional and post-transcriptional levels in different cellular contexts and biological processes. Understanding the potential mechanisms of action of lncRNAs and their role in disease onset and development may open up new possibilities for therapeutic approaches in the future. LncRNAs also play an important role in renal pathogenesis. However, little is known about lncRNAs that are expressed in the healthy kidney and that are involved in renal cell homeostasis and development, and even less is known about lncRNAs involved in human adult renal stem/progenitor cells (ARPC) homeostasis. Here we give a thorough overview of the biogenesis, degradation, and functions of lncRNAs and highlight our current understanding of their functional roles in kidney diseases. We also discuss how lncRNAs regulate stem cell biology, focusing finally on their role in human adult renal stem/progenitor cells, in which the lncRNA HOTAIR prevents them from becoming senescent and supports these cells to secrete high quantities of α-Klotho, an anti-aging protein capable of influencing the surrounding tissues and therefore modulating the renal aging.

The MYC-regulated lncRNA LNROP (ENSG00000254887) enables MYC-driven cell proliferation by controlling the expression of OCT2

MYC controls most of the non-coding genome. Several long noncoding transcripts were originally identified in the human B cell line P496-3 and then shown to be required for MYC-driven proliferation of Burkitt lymphoma-derived RAMOS cells. In this study, we used RAMOS cells exclusively as a representative of the human B cell lineage. One of the MYC-controlled lncRNAs required for RAMOS cell proliferation is ENSG00000254887 which we will term LNROP (long non-coding regulator of POU2F2). In the genome, LNROP is located in close proximity of POU2F2, the gene encoding OCT2. OCT2 is a transcription factor with important roles in sustaining the proliferation of human B cells. Here we show that LNROP is a nuclear RNA and a direct target of MYC. Downregulation of LNROP attenuates the expression of OCT2. This effect of LNROP on the expression of OCT2 is unidirectional as downregulation of OCT2 does not alter the expression of LNROP. Our data suggest that LNROP is a cis-acting regulator of OCT2. To illustrate the downstream reach of LNROP, we chose a prominent target of OCT2, the tyrosine phosphatase SHP-1. Downregulation of OCT2 elevates the expression of SHP-1. Our data suggest the following path of interactions: LNROP enables the proliferation of B cells by positively and unidirectionally regulating the growth-stimulatory transcription factor OCT2. In actively proliferating B cells, OCT2 attenuates the expression and anti-proliferative activity of SHP-1.

Pseudoknots in RNA Structure Prediction

RNA molecules play active roles in the cell and are important for numerous applications in biotechnology and medicine. The function of an RNA molecule stems from its structure. RNA structure determination is time consuming, challenging, and expensive using experimental methods. Thus, much research has been directed at RNA structure prediction through computational means. Many of these methods focus primarily on the secondary structure of the molecule, ignoring the possibility of pseudoknotted structures. However, pseudoknots are known to play functional roles in many RNA molecules or in their method of interaction with other molecules. Improving the accuracy and efficiency of computational methods that predict pseudoknots is an ongoing challenge for single RNA molecules, RNA-RNA interactions, and RNA-protein interactions. To improve the accuracy of prediction, many methods focus on specific applications while restricting the length and the class of the pseudoknotted structures they can identify. In recent years, computational methods for structure prediction have begun to catch up with the impressive developments seen in biotechnology. Here, we provide a non-comprehensive overview of available pseudoknot prediction methods and their best-use cases. © 2023 Wiley Periodicals LLC.

Inefficient splicing of long non-coding RNAs is associated with higher transcript complexity in human and mouse

Recent reports show that long non-coding RNAs (lncRNAs) have inefficient splicing and fewer alternative splice variants than mRNAs. Here, we have explored the efficiency of lncRNAs and mRNAs in producing various splice variants, given the number of exons in humans and mice. Intriguingly, lncRNAs produce more splice variants per exon, referred to as Transcript Complexity, than mRNAs. Most lncRNA splice variants are the product of the alternative last exon and exon skipping. LncRNAs and mRNAs with higher transcript complexity have shorter intron lengths. Longer exon length and GC/AG at 5'/3' splice sites are associated with higher transcript complexity in lncRNAs. Lastly, our results indicate that inefficient splicing of lncRNAs may facilitate multiple introns splicing and, thus, more spliced products per exon.

A common transcriptional mechanism involving R-loop and RNA abasic site regulates an enhancer RNA of APOE

RNA is modified by hundreds of chemical reactions and folds into innumerable shapes. However, the regulatory role of RNA sequence and structure and how dysregulation leads to diseases remain largely unknown. Here, we uncovered a mechanism where RNA abasic sites in R-loops regulate transcription by pausing RNA polymerase II. We found an enhancer RNA, AANCR, that regulates the transcription and expression of apolipoprotein E (APOE). In some human cells such as fibroblasts, AANCR is folded into an R-loop and modified by N-glycosidic cleavage; in this form, AANCR is a partially transcribed nonfunctional enhancer and APOE is not expressed. In contrast, in other cell types including hepatocytes and under stress, AANCR does not form a stable R-loop as its sequence is not modified, so it is transcribed into a full-length enhancer that promotes APOE expression. DNA sequence variants in AANCR are associated significantly with APOE expression and Alzheimer's Disease, thus AANCR is a modifier of Alzheimer's Disease. Besides AANCR, thousands of noncoding RNAs are regulated by abasic sites in R-loops. Together our data reveal the essentiality of the folding and modification of RNA in cellular regulation and demonstrate that dysregulation underlies common complex diseases such as Alzheimer's disease.

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.

SILCS-RNA: Toward a Structure-Based Drug Design Approach for Targeting RNAs with Small Molecules

RNA molecules can act as potential drug targets in different diseases, as their dysregulated expression or misfolding can alter various cellular processes. Noncoding RNAs account for ∼70% of the human genome, and these molecules can have complex tertiary structures that present a great opportunity for targeting by small molecules. In the present study, the site identification by ligand competitive saturation (SILCS) computational approach is extended to target RNA, termed SILCS-RNA. Extensions to the method include an enhanced oscillating excess chemical potential protocol for the grand canonical Monte Carlo calculations and individual simulations of the neutral and charged solutes from which the SILCS functional group affinity maps (FragMaps) are calculated for subsequent binding site identification and docking calculations. The method is developed and evaluated against seven RNA targets and their reported small molecule ligands. SILCS-RNA provides a detailed characterization of the functional group affinity pattern in the small molecule binding sites, recapitulating the types of functional groups present in the ligands. The developed method is also shown to be useful for identification of new potential binding sites and identifying ligand moieties that contribute to binding, granular information that can facilitate ligand design. However, limitations in the method are evident including the ability to map the regions of binding sites occupied by ligand phosphate moieties and to fully account for the wide range of conformational heterogeneity in RNA associated with binding of different small molecules, emphasizing inherent challenges associated with applying computer-aided drug design methods to RNA. While limitations are present, the current study indicates how the SILCS-RNA approach may enhance drug discovery efforts targeting RNAs with small molecules.

Identification of cuproptosis-associated IncRNAs signature and establishment of a novel nomogram for prognosis of stomach adenocarcinoma

Purpose: Stomach adenocarcinoma (STAD) is one of the common cancers globally. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in STAD is unknown.

Methods: STAD patient data from TCGA were used to identify prognostic lncRNAs by Cox regression and LASSO. A nomogram was constructed to predict patient survival. The biological profiles were evaluated through GO and KEGG.

Results: We identified 298 cuproptosis-related lncRNAs and 13 survival-related lncRNAs. Patients could be categorized into either high risk group or low risk group with 9-lncRNA risk model with significantly different survival time (p < 0.001). ROC curve and nomogram confirmed the 9-lncRNA risk mode had good prediction capability. Patients in the lower risk score had high gene mutation burden. We also found that patients in the two groups might respond differently to immune checkpoint inhibitors and some anti-tumor compounds.

Conclusion: The nomogram with 9-lncRNA may help guide treatment of STAD. Future clinical studies are necessary to verify the nomogram.

Graph Convolutional Auto-Encoders for Predicting Novel lncRNA-Disease Associations

LncRNAs are intermediate molecules that participate in the most diverse biological processes in humans, such as gene expression control and X-chromosome inactivation. Numerous researches have associated lncRNAs with a wide range of diseases, such as breast cancer, leukemia, and many other conditions. In this work, we propose a graph-based method named PANDA. This method treats the prediction of new associations between lncRNAs and diseases as a link prediction problem in a graph. We start by building a heterogeneous graph that contains the known associations between lncRNAs and diseases and additional information such as gene expression levels and symptoms of diseases. We then use a Graph Auto-encoder to learn the representation of the nodes' features and edges, finally applying a Neural Network to predict potentially interesting novel edges. The experimental results indicate that PANDA achieved a 0.976 AUC-ROC, surpassing state-of-the-art methods for the same problem, showing that PANDA could be a promising approach to generate embeddings to predict potentially novel lncRNA-disease associations.

A Novel Necroptosis-Associated IncRNAs Signature for Prognosis of Head and Neck Squamous Cell Carcinoma

Purpose: The prognosis of head and neck squamous cell carcinoma (HNSCC) is poor. Necroptosis is a novel programmed form of necrotic cell death. The prognostic value of necroptosis-associated lncRNAs expression in HNSCC has not been explored. Methods: We downloaded mRNA expression data of HNSCC patients from TCGA databases. Prognostic lncRNAs were identified by univariate Cox regression. LASSO was used to establish a model with necroptosis-related lncRNAs. Kaplan-Meier analysis and ROC were applied to verify the model. Finally, functional studies including gene set enrichment analyses, immune microenvironment analysis, and anti-tumor compound IC50 prediction were performed. Results: We identified 1,117 necroptosis-related lncRNAs. The Cox regression showed 55 lncRNAs were associated with patient survival (p < 0.05). The risk model of 24- lncRNAs signature categorized patients into high and low risk groups. The patients in the low-risk group survived longer than the high-risk group (p < 0.001). Validation assays including ROC curve, nomogram and correction curves confirmed the prediction capability of the 24-lncRNA risk mode. Functional studies showed the two patient groups had distinct immunity conditions and IC50. Conclusion: The 24-lncRNA model has potential to guide treatment of HNSCC. Future clinical studies are needed to verify the model.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

Long Noncoding RNA TUG1 Aggravates Cerebral Ischemia/Reperfusion Injury by Acting as a ceRNA for miR-3072-3p to Target St8sia2

Long noncoding RNA taurine-upregulated gene 1 (TUG1) is considered to be involved in postischemic cerebral inflammation, whereas polysialic acid (polySia, PSA), the product of St8sia2, constitutes polysialylated neural adhesion cell molecule (PSA-NCAM) in both mice and humans and that cerebral PSA-NCAM level is elevated in neuronal progenitor cells in response to transient focal ischemia. Herein, we aim to identify novel miRNAs that bridge the functions of St8sia2 and TUG1 in ischemia-associated injuries. In both in vivo (C57BL/6J mouse ischemia/reperfusion, I/R model) and in vitro (mouse neuroblastoma N2A cell oxygen glucose deprivation/reoxygenation, OGD model) settings, we observed upregulated TUG1 and St8sia2 after the induction of ischemic injury, accompanied by reduced miR-3072-3p expression. We performed siRNA-induced TUG1 knockdown combined with the induction of ischemic injury; the results showed that inhibiting TUG1 expression led to the reduced infarct area and improved neurological deficit. Through bioinformatics analysis, miR-3072-3p was found to target both St8sia2 and TUG1, which was subsequently verified by the luciferase reporter system and RNA binding protein immunoprecipitation assay. Also, the addition of miR-3072-3p mimic/inhibitor resulted in reduced/elevated St8sia2 expression at the protein level. Further studies revealed that in both in vivo and in vitro settings, TUG1 bound competitively to miR-3072-3p to regulate St8sia2 expression and promote apoptosis. In summary, targeting the TUG1/miR-3072-3p/St8sia2 regulatory cascade, a novel cascade we identified in cerebral ischemia injury, may render feasible therapeutic possibilities for overcoming cerebral ischemic insults.

Whole-genome-scale identification of novel non-protein-coding RNAs controlling cell proliferation and survival through a functional forward genetics strategy

Identification of cell fate-controlling lncRNAs is essential to our understanding of molecular cell biology. Here we present a human genome-scale forward-genetics approach for the identification of lncRNAs based on gene function. This approach can identify genes that play a causal role, and immediately distinguish them from those that are differentially expressed but do not affect cell function. Our genome-scale library plus next-generation-sequencing and bioinformatic approach, radically upscales the breadth and rate of functional ncRNA discovery. Human gDNA was digested to produce a lentiviral expression library containing inserts in both sense and anti-sense orientation. The library was used to transduce human Jurkat T-leukaemic cells. Cell populations were selected using continuous culture ± anti-FAS IgM, and sequencing used to identify sequences controlling cell proliferation. This strategy resulted in the identification of thousands of new sequences based solely on their function including many ncRNAs previously identified as being able to modulate cell survival or to act as key cancer regulators such as AC084816.1*, AC097103.2, AC087473.1, CASC15*, DLEU1*, ENTPD1-AS1*, HULC*, MIRLET7BHG*, PCAT-1, SChLAP1, and TP53TG1. Independent validation confirmed 4 out of 5 sequences that were identified by this strategy, conferred a striking resistance to anti-FAS IgM-induced apoptosis.

β-Asarone Protects PC12 Cells Against Hypoxia-Induced Injury Via Negatively Regulating RPPH1/MiR-542-3p/DEDD2 Axis

Hypoxic injury to the brain is very intricate under the control of biochemical reactions induced by various factors and mechanisms. Long non-coding RNAs (lncRNAs) have already been revealed to affect pathological processes in the nervous system of different degrees. This research aimed to investigate the mechanisms implicated in hypoxic brain injury. β-Asarone mitigated the decrease of cell viability, superoxide dismutase activity, and mitochondrial membrane potential, as well as the increase of cell apoptosis, lactate dehydrogenase release, malondialdehyde content, and reactive oxidative species production by cobalt chloride. LncRNA ribonuclease P RNA component H1 (RPPH1) was discovered to be highly expressed in hypoxia-induced PC12 cells, and β-Asarone addition led to a decline in RPPH1 expression. RPPH1 overexpression reversed the effect of β-Asarone on hypoxia-induced injury in PC12 cells. Furthermore, we proved that RPPH1 could sponge miR-542-3p. Subsequently, death effector domain containing 2 (DEDD2) was proven as the downstream gene of RPPH1/miR-542-3p axis. Eventually, the whole regulation mechanism of RPPH1/miR-542-3p/DEDD2 axis was testified through rescue assays. The impacts of β-Asarone on hypoxia-induced PC12 cells could be countervailed by RPPH1 augment, which was also discovered to be neutralized in response to miR-542-3p overexpression or DEDD2 depletion. These findings offered a novel perspective for understanding neuroprotection.

Characterization of protein isoform diversity in human umbilical vein endothelial cells via long-read proteogenomics

Endothelial cells (ECs) comprise the lumenal lining of all blood vessels and are critical for the functioning of the cardiovascular system. Their phenotypes can be modulated by alternative splicing of RNA to produce distinct protein isoforms. To characterize the RNA and protein isoform landscape within ECs, we applied a long read proteogenomics approach to analyse human umbilical vein endothelial cells (HUVECs). Transcripts delineated from PacBio sequencing serve as the basis for a sample-specific protein database used for downstream mass-spectrometry (MS) analysis to infer protein isoform expression. We detected 53,863 transcript isoforms from 10,426 genes, with 22,195 of those transcripts being novel. Furthermore, the predominant isoform in HUVECs does not correspond with the accepted "reference isoform" 25% of the time, with vascular pathway-related genes among this group. We found 2,597 protein isoforms supported through unique peptides, with an additional 2,280 isoforms nominated upon incorporation of long-read transcript evidence. We characterized a novel alternative acceptor for endothelial-related gene CDH5, suggesting potential changes in its associated signalling pathways. Finally, we identified novel protein isoforms arising from a diversity of RNA splicing mechanisms supported by uniquely mapped novel peptides. Our results represent a high-resolution atlas of known and novel isoforms of potential relevance to endothelial phenotypes and function.[Figure: see text].

An RNA-Based Theory of Natural Universal Computation

Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal computation, i.e., Turing-equivalent in scope. Generic finite-dimensional dynamical systems (which encompass most models of neural networks, intracellular signaling cascades, and gene regulatory networks) fall short of universal computation, but are assumed to be capable of explaining cognition and development. I present a class of models that bridge two concepts from distant fields: combinatory logic (or, equivalently, lambda calculus) and RNA molecular biology. A set of basic RNA editing rules can make it possible to compute any computable function with identical algorithmic complexity to that of Turing machines. The models do not assume extraordinarily complex molecular machinery or any processes that radically differ from what we already know to occur in cells. Distinct independent enzymes can mediate each of the rules and RNA molecules solve the problem of parenthesis matching through their secondary structure. In the most plausible of these models all of the editing rules can be implemented with merely cleavage and ligation operations at fixed positions relative to predefined motifs. This demonstrates that universal computation is well within the reach of molecular biology. It is therefore reasonable to assume that life has evolved - or possibly began with - a universal computer that yet remains to be discovered. The variety of seemingly unrelated computational problems across many scales can potentially be solved using the same RNA-based computation system. Experimental validation of this theory may immensely impact our understanding of memory, cognition, development, disease, evolution, and the early stages of life.

Natural SINEUP RNAs in Autism Spectrum Disorders: RAB11B-AS1 Dysregulation in a Neuronal CHD8 Suppression Model Leads to RAB11B Protein Increase

CHD8 represents one of the highest confidence genetic risk factors implied in Autism Spectrum Disorders, with most mutations leading to CHD8 haploinsufficiency and the insurgence of specific phenotypes, such as macrocephaly, facial dysmorphisms, intellectual disability, and gastrointestinal complaints. While extensive studies have been conducted on the possible consequences of CHD8 suppression and protein coding RNAs dysregulation during neuronal development, the effects of transcriptional changes of long non-coding RNAs (lncRNAs) remain unclear. In this study, we focused on a peculiar class of natural antisense lncRNAs, SINEUPs, that enhance translation of a target mRNA through the activity of two RNA domains, an embedded transposable element sequence and an antisense region. By looking at dysregulated transcripts following CHD8 knock down (KD), we first identified RAB11B-AS1 as a potential SINEUP RNA for its domain configuration. Then we demonstrated that such lncRNA is able to increase endogenous RAB11B protein amounts without affecting its transcriptional levels. RAB11B has a pivotal role in vesicular trafficking, and mutations on this gene correlate with intellectual disability and microcephaly. Thus, our study discloses an additional layer of molecular regulation which is altered by CHD8 suppression. This represents the first experimental confirmation that naturally occurring SINEUP could be involved in ASD pathogenesis and underscores the importance of dysregulation of functional lncRNAs in neurodevelopment.

SINEUPs: a novel toolbox for RNA therapeutics

RNA molecules have emerged as a new class of promising therapeutics to expand the range of druggable targets in the genome. In addition to ‘canonical’ protein-coding mRNAs, the emerging richness of sense and antisense long non-coding RNAs (lncRNAs) provides a new reservoir of molecular tools for RNA-based drugs. LncRNAs are composed of modular structural domains with specific activities involving the recruitment of protein cofactors or directly interacting with nucleic acids. A single therapeutic RNA transcript can then be assembled combining domains with defined secondary structures and functions, and antisense sequences specific for the RNA/DNA target of interest.

As the first representative molecules of this new pharmacology, we have identified SINEUPs, a new functional class of natural antisense lncRNAs that increase the translation of partially overlapping mRNAs. Their activity is based on the combination of two domains: an embedded mouse inverted SINEB2 element that enhances mRNA translation (effector domain) and an overlapping antisense region that provides specificity for the target sense transcript (binding domain). By genetic engineering, synthetic SINEUPs can potentially target any mRNA of interest increasing translation and therefore the endogenous level of the encoded protein.

In this review, we describe the state-of-the-art knowledge of SINEUPs and discuss recent publications showing their potential application in diseases where a physiological increase of endogenous protein expression can be therapeutic.

LINC00152 expression in normal and Chronic Lymphocytic Leukemia B cells

Long non‐coding RNAs are emerging as essential regulators of gene expression, but their role in normal and neoplastic B cells is still largely uncharacterized. Here, we report on the expression pattern of the LINC00152 in normal B cells and Chronic Lymphocytic Leukemia B cell clones. Higher LINC00152 levels were consistently observed in memory B cell populations when compared to naïve B cells in the normal tissues analyzed [peripheral blood (PB), tonsils, and spleen]. In addition, independent stimulation via Immunoglobulins (IG), CD40, or Toll‐like Receptor 9 (TLR9) upregulated LINC00152 in PB B cells. The expression of LINC00152 in a cohort of 107 early stage Binet A CLL patients was highly variable and did not correlate with known prognostic markers or clinical evolution. TLR9 stimulation, but not CD40 or IG challenge, was able to upregulate LINC00152 expression in CLL cells. In addition, LINC00152 silencing in CLL cell lines expressing LINC00152 failed to induce significant cell survival or apoptosis changes. These data suggest that, in normal B cells, the expression of LINC00152 is regulated by immunomodulatory signals, which are only partially effective in CLL cells. However, LINC00152 does not appear to contribute to CLL cell expansion and/or survival in a cohort of newly diagnosed CLL patients.

Development and Validation of an Autophagy-Related LncRNA Prognostic Signature in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the greatest public challenges because of delayed diagnosis and poor prognosis. In this study, we established an autophagy-associated long non-coding (Lnc)RNA prognostic signature to assess the prognosis of HNSCC patients. The LncRNA expression profiles and clinical information of 499 HNSCC samples were available in The Cancer Genome Atlas. Autophagic LncRNAs were analyzed using Pearson correlation. A co-expression network showed the interactions between autophagic genes and LncRNAs. An autophagic LncRNAs prognostic signature, consisting of MYOSLID, AL139287.1, AC068580.1, AL022328.2, AC104083.1, AL160006.1, AC116914.2, LINC00958, and AL450992.2, was developed through uni- and multivariate Cox regressions. High- and low-risk groups were classified based on the median risk scores. The high-risk group had significantly worse overall survival according to Kaplan–Meier curve analysis. Multivariate Cox regression demonstrated that risk scores were a significant independent prognostic factor (hazard ratio = 1.739, 95% confidence interval: 1.460–2.072), with an area under the curve of 0.735. Principal component analysis distinguished two categories based on the nine-LncRNA prognostic signature. In conclusion, this novel autophagic LncRNA signature is an independent prognostic factor and may suggest novel therapeutic targets for HNSCC.

Evolutionary dynamics of circular RNAs in primates

Many primate genes produce circular RNAs (circRNAs). However, the extent of circRNA conservation between closely related species remains unclear. By comparing tissue-specific transcriptomes across over 70 million years of primate evolution, we identify that within 3 million years circRNA expression profiles diverged such that they are more related to species identity than organ type. However, our analysis also revealed a subset of circRNAs with conserved neural expression across tens of millions of years of evolution. By comparing to species-specific circRNAs, we identified that the downstream intron of the conserved circRNAs display a dramatic lengthening during evolution due to the insertion of novel retrotransposons. Our work provides comparative analyses of the mechanisms promoting circRNAs to generate increased transcriptomic complexity in primates.

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and discrimination of each neurodegenerative disorder a priority. Several investigations have revealed the importance of microRNAs and long non-coding RNAs in neurodevelopment, brain function, maturation, and neuronal activity, as well as its dysregulation involved in many types of neurological diseases. Therefore, the expression pattern of these molecules in the different NDs have gained significant attention to improve the diagnostic and treatment at earlier stages. In this sense, we gather the different microRNAs and long non-coding RNAs that have been reported as dysregulated in each disorder. Since there are a vast number of non-coding RNAs altered in NDs, some sort of synthesis, filtering and organization method should be applied to extract the most relevant information. Hence, machine learning is considered as an important tool for this purpose since it can classify expression profiles of non-coding RNAs between healthy and sick people. Therefore, we deepen in this branch of computer science, its different methods, and its meaningful application in the diagnosis of NDs from the dysregulated non-coding RNAs. In addition, we demonstrate the relevance of machine learning in NDs from the description of different investigations that showed an accuracy between 85% to 95% in the detection of the disease with this tool. All of these denote that artificial intelligence could be an excellent alternative to help the clinical diagnosis and facilitate the identification diseases in early stages based on non-coding RNAs.

Non-Coding RNAs in Kidney Diseases: The Long and Short of Them

Recent progress in genomic research has highlighted the genome to be much more transcribed than expected. The formerly so-called junk DNA encodes a miscellaneous group of largely unknown RNA transcripts, which contain the long non-coding RNAs (lncRNAs) family. lncRNAs are instrumental in gene regulation. Moreover, understanding their biological roles in the physiopathology of many diseases, including renal, is a new challenge. lncRNAs regulate the effects of microRNAs (miRNA) on mRNA expression. Understanding the complex crosstalk between lncRNA–miRNA–mRNA is one of the main challenges of modern molecular biology. This review aims to summarize the role of lncRNA on kidney diseases, the molecular mechanisms involved, and their function as emerging prognostic biomarkers for both acute and chronic kidney diseases. Finally, we will also outline new therapeutic opportunities to diminish renal injury by targeting lncRNA with antisense oligonucleotides.

Covid-19 and the need for more history and philosophy of RNA

RNA is central to the COVID-19 pandemic-it shapes how the SARS Coronavirus 2 (SARS-CoV-2) behaves, and how researchers investigate and fight it. However, RNA has received relatively little attention in the history and philosophy of the life sciences. By analysing RNA biology in more detail, philosophers and historians of science could gain new and powerful tools to assess the current pandemic, and the biological sciences more generally.

Small Activating RNAs: Towards the Development of New Therapeutic Agents and Clinical Treatments

Small double-strand RNA (dsRNA) molecules can activate endogenous genes via an RNA-based promoter targeting mechanism. RNA activation (RNAa) is an evolutionarily conserved mechanism present in diverse eukaryotic organisms ranging from nematodes to humans. Small activating RNAs (saRNAs) involved in RNAa have been successfully used to activate gene expression in cultured cells, and thereby this emergent technique might allow us to develop various biotechnological applications, without the need to synthesize hazardous construct systems harboring exogenous DNA sequences. Accordingly, this thematic issue aims to provide insights into how RNAa cellular machinery can be harnessed to activate gene expression leading to a more effective clinical treatment of various diseases.

Long Non-Coding RNA FENDRR: Gene Structure, Expression, and Biological Relevance

The FOXF1 Adjacent Noncoding Developmental Regulatory RNA (Fendrr) plays an important role in the control of gene expression in mammals. It is transcribed in the opposite direction to the neighboring Foxf1 gene with which it shares a region containing promoters. In humans, FENDRR is located on chromosome 16q24.1, and is positively regulated both by the FOXF1 distant lung-specific cis-acting enhancer and by trans-acting FOXF1. Fendrr has been shown to function as a competing endogenous RNA, sponging microRNAs and protein factors that control stability of mRNAs, and as an epigenetic modifier of chromatin structure around gene promoters and other regulatory sites, targeting them with histone methyltrasferase complexes. In mice, Fendrr is essential for development of the heart, lungs, and gastrointestinal system; its homozygous loss causes embryonic or perinatal lethality. Importantly, deregulation of FENDRR expression has been causatively linked also to tumorigenesis, resistance to chemotherapy, fibrosis, and inflammatory diseases. Here, we review the current knowledge on the FENDRR structure, expression, and involvement in development and tissue maintenance.

LINC00483 Has a Potential Tumor-Suppressor Role in Colorectal Cancer Through Multiple Molecular Axes

Long non-coding RNAs (lncRNAs) are the most heterogeneous class of non-protein-coding RNAs involved in a broad spectrum of molecular mechanisms controlling genome function, including the generation of complex networks of RNA-RNA competitive interactions. Accordingly, their dysregulation contributes to the onset of many tumors, including colorectal cancer (CRC). Through a combination of in silico approaches (statistical screening of expression datasets) and in vitro analyses (enforced expression, artificial inhibition, or activation of pathways), we identified LINC00483 as a potential tumor suppressor lncRNA in CRC. LINC00483 was downregulated in CRC biopsies and metastases and its decreased levels were associated with severe clinical features. Inhibition of the MAPK pathway and cell cycle arrest by starvation induced an upregulation of LINC00483, while the epithelial to mesenchymal transition activation by TGFβ-1 and IL-6 caused its down-modulation. Moreover, enforced expression of LINC00483 provoked a slowing down of cell migration rate without affecting cell proliferation. Since LINC00483 was predominantly cytoplasmic, we hypothesized a “miRNA sponge” role for it. Accordingly, we computationally reconstructed the LINC00483/miRNA/mRNA axes and evaluated the expression of mRNAs in different experimental conditions inducing LINC00483 alteration. By this approach, we identified a set of mRNAs sharing the miRNA response elements with LINC00483 and modulated in accordance with it. Moreover, we found that LINC00483 is potentially under negative control of transcription factor HNF4α. In conclusion, we propose that LINC00483 is a tumor suppressor in CRC that, through an RNA-RNA network, may control cell migration and participate in proliferation signaling.

LncRNAs and Available Databases

Long noncoding RNAs (lncRNAs) are involved in many regulatory mechanisms in practically every step of the RNA cycle, from transcription to RNA stability and translation. They are a highly heterogeneous class of molecules in terms of site of production, interaction networks, and functions. More and more databases are available on the web with the aim to make public information about lncRNA accessible to the scientific community. Here we review the most interesting resources with the purpose to organize a compendium of useful tools to interrogate before studying a lncRNA of interest.

Microarray Analysis of Whole-Transcriptome RNAs Including Non-Coding RNAs

Non-coding RNAs participate in most cellular processes and play a causative role in several diseases. In addition to their relevance as targets or tools for therapy, ncRNAs have been extensively detected in body fluids supporting their role as easily accessible and minimally invasive biomarkers. However, the precise measurement of circulating ncRNAs remains challenging due to their low abundance and the heterogeneity of the ncRNA population (size, polyadenylation status, circular forms). Microarrays constitute a very powerful method to analyze the expression level and the splicing pattern of circulating ncRNAs since they preserve sample integrity (no need to remove globin or rRNA) and allow precise quantification of low-abundance transcripts (no limitation by read depth). This chapter describes the protocols used in our lab to extract and purify total RNAs from PAXgene RNA Blood Tubes and to perform RNA labeling and hybridization on the Clariom™ D microarrays from Affymetrix.

Non-coding RNAs and Ischemic Cardiovascular Diseases

The Ischemic Heart Disease (IHD) is considered a clinical condition characterized by myocardial ischemia causing an imbalance between myocardial blood supply and demand, leading to morbidity and mortality across the worldwide. Prompt diagnostic and prognostic represents key factors for the treatment and reduction of the mortality rate. Therefore, one of the newest frontiers in cardiovascular research is related to non-coding RNAs (ncRNAs), which prompted a huge interest in exploring ncRNAs candidates for utilization as potential therapeutic targets for diagnostic and prognostic and/or biomarkers in IHD. However, there are undoubtedly many more functional ncRNAs yet to be discovered and characterized. Here we will discuss our current knowledge and we will provide insight on the roles and effects elicited by some ncRNAs related to IHD.

Long Noncoding RNAs CARMN, LUCAT1, SMILR, and MALAT1 in Thoracic Aortic Aneurysm: Validation of Biomarkers in Clinical Samples

Materials and Methods

Relative expression of lncRNAs CARMN, LUCAT1, SMILR, and MALAT1 was tested in clinical aortic tissue and blood plasma samples from TAA and non-TAA patients using the qRT-PCR method. The Mann–Whitney U test was used to compare ΔCt values between the study groups. ROC curve analysis was performed to evaluate the diagnostic value of plasma lncRNAs.

Results

We found significantly reduced CARMN (p = 0.033) and LUCAT1 (p = 0.009) expression in aortic tissue samples from TAA patients. Relative expression of MALAT1 (p = 0.117) and SMILR (p = 0.610) did not differ in aortic tissue between the TAA and non-TAA groups. Expression of both LUCAT1 and SMILR was significantly decreased in TAA patients' blood plasma compared to controls (p = 0.018 and p = 0.032, respectively). However, only LUCAT1 showed the ability to discriminate aneurysmal disease in patients' blood plasma (AUC = 0.654, 95%CI = 0.534‐0.775, p = 0.018).

Conclusions

We have shown that the expression of lncRNAs CARMN and LUCAT1 is reduced in dilated aortic tissue and that the LUCAT1 and SMILR expression is lower in the blood plasma of TAA patients. Decreased LUCAT1 expression in TAA patients' blood plasma may have diagnostic potential in discriminating patients with TAA.

Role of Long Non-coding RNAs in Reprogramming to Induced Pluripotency

The generation of induced pluripotent stem cells through somatic cell reprogramming requires a global reorganization of cellular functions. This reorganization occurs in a multi-phased manner and involves a gradual revision of both the epigenome and transcriptome. Recent studies have shown that the large-scale transcriptional changes observed during reprogramming also apply to long non-coding RNAs (lncRNAs), a type of traditionally neglected RNA species that are increasingly viewed as critical regulators of cellular function. Deeper understanding of lncRNAs in reprogramming may not only help to improve this process but also have implications for studying cell plasticity in other contexts, such as development, aging, and cancer. In this review, we summarize the current progress made in profiling and analyzing the role of lncRNAs in various phases of somatic cell reprogramming, with emphasis on the re-establishment of the pluripotency gene network and X chromosome reactivation.

GC-AG Introns Features in Long Non-coding and Protein-Coding Genes Suggest Their Role in Gene Expression Regulation

Long non-coding RNAs (lncRNAs) are recognized as an important class of regulatory molecules involved in a variety of biological functions. However, the regulatory mechanisms of long non-coding genes expression are still poorly understood. The characterization of the genomic features of lncRNAs is crucial to get insight into their function. In this study, we exploited recent annotations by GENCODE to characterize the genomic and splicing features of long non-coding genes in comparison with protein-coding ones, both in human and mouse. Our analysis highlighted differences between the two classes of genes in terms of their gene architecture. Significant differences in the splice sites usage were observed between long non-coding and protein-coding genes (PCG). While the frequency of non-canonical GC-AG splice junctions represents about 0.8% of total splice sites in PCGs, we identified a significant enrichment of the GC-AG splice sites in long non-coding genes, both in human (3.0%) and mouse (1.9%). In addition, we found a positional bias of GC-AG splice sites being enriched in the first intron in both classes of genes. Moreover, a significant shorter length and weaker donor and acceptor sites were found comparing GC-AG introns to GT-AG introns. Genes containing at least one GC-AG intron were found conserved in many species, more prone to alternative splicing and a functional analysis pointed toward their enrichment in specific biological processes such as DNA repair. Our study shows for the first time that GC-AG introns are mainly associated with lncRNAs and are preferentially located in the first intron. Additionally, we discovered their regulatory potential indicating the existence of a new mechanism of non-coding and PCGs expression regulation.

LNCipedia 5: towards a reference set of human long non-coding RNAs

While long non-coding RNA (lncRNA) research in the past has primarily focused on the discovery of novel genes, today it has shifted towards functional annotation of this large class of genes. With thousands of lncRNA studies published every year, the current challenge lies in keeping track of which lncRNAs are functionally described. This is further complicated by the fact that lncRNA nomenclature is not straightforward and lncRNA annotation is scattered across different resources with their own quality metrics and definition of a lncRNA. To overcome this issue, large scale curation and annotation is needed. Here, we present the fifth release of the human lncRNA database LNCipedia (https://lncipedia.org). The most notable improvements include manual literature curation of 2482 lncRNA articles and the use of official gene symbols when available. In addition, an improved filtering pipeline results in a higher quality reference lncRNA gene set.

Differential long non-coding RNA expression profiles in the peripheral blood and CD4+ T cells of patients with active rheumatoid arthritis

The human transcriptome is primarily composed of long non-coding RNAs (lncRNAs), which are key regulatory molecules of multiple biological processes. In the present study, the expression profiles of lncRNAs in the peripheral blood and CD4⁺ T cells of patients with active rheumatoid arthritis (RA) were determined. Based on the expression profiles, 493 lncRNAs and 374 mRNAs were identified to be differentially expressed in the peripheral blood of active RA patients and healthy donors. Further verification of lncRNAs was performed using reverse transcription-quantitative (RT-q) PCR analysis of peripheral blood from 5 healthy donors and 5 patients with active RA and 14 additional differentially expressed genes were identified. CD4⁺ T cells in peripheral blood from 12 patients with active RA and 8 healthy donors were isolated using magnetic beads and qPCR was used to assess differentially expressed lncRNAs. The results suggested that 7 lncRNAs were upregulated and 2 were downregulated. The results indicated that these 9 lncRNAs may be involved in the pathogenesis of RA. An increased ratio of Th17: T-regulatory (Treg) cells was also observed. It may be hypothesized that LncRNAs serve important roles in the differentiation of CD4⁺ T cells. Receiver operating characteristic curve analysis suggested that these 9 lncRNAs are of potential clinical diagnostic value for RA. Pearson correlation analysis indicated that the correlation coefficient between Ensembl transcript (ENST)00000569543 and complement C4 was 0.623 (P<0.05), and that between ENST00000420096 and anti-cyclic citrullinated peptide antibody or disease activity evaluation score, the correlation coefficient was 0.662 and 0.605, respectively (P<0.05 for each). In conclusion, the results of the present study suggest a possible role of lncRNAs in the differentiation of CD4⁺ T cells and the pathogenesis of RA, as well as the potential value as diagnostic biomarkers for active RA.

LINC00511 promotes gastric cancer cell growth by acting as a ceRNA

BACKGROUND

Gastric cancer (GC) is one of the most aggressive malignancies, with a high incidence and poor prognosis worldwide. Recently, accumulating evidence has illustrated that long noncoding RNAs (lncRNAs) play pivotal roles in many cancers. It has been reported that LINC00511 contributes to tumorigenesis in various diseases. However, the role of LINC00511 in GC cell growth remains mostly unknown.

AIM

To determine whether the lncRNA LINC00511 exerted its carcinogenic function in GC via the miR-124-3p/PDK4 axis.

METHODS

Cell culture and transfection, RNA extraction and quantitative real-time PCR, CCK-8 assay, Colony formation assay, Luciferase reporter assay, RIP assay, RNA pull-down assay, and Western blot analysis were used to show expression and mechanisms of LINC00511 in GC progression and apoptosis. Rescue assays were performed to verify the relationships among LINC00511, miR-124-3p and PDK4 further.

RESULTS

The expression of LINC00511 was remarkably upregulated in GC cells compared to that in corresponding normal cell lines. Compared to the controls, cell proliferation was inhibited, and cell apoptosis was increased upon LINC00511 knockdown, demonstrating that LINC00511 influenced GC cell growth. An exploration of the molecular mechanism revealed that LINC00511 functioned as a molecular sponge of miR-124-3p and that PDK4 was a downstream target of miR-124-3p in GC. Rescue assays showed that the overexpression of PDK4 could partly restore the inhibitory function of si-LINC00511 in GC.

CONCLUSION

These data demonstrate that LINC00511 promotes gastric cancer cell growth by acting as a ceRNA to regulate the miR-124-3p/PDK4 axis, which may be a promising therapeutic target for GC.

The Development of RNA-KISS, a Mammalian Three-Hybrid Method to Detect RNA-Protein Interactions in Living Mammalian Cells

RNA-protein interactions are essential for the regulation of mRNA and noncoding RNA functions and are implicated in many diseases, such as cancer and neurodegenerative disorders. A method that can detect RNA-protein interactions in living mammalian cells on a proteome-wide scale will be an important asset to identify and study these interactions. Here we show that a combination of the mammalian two-hybrid protein-protein detection method KISS (kinase substrate sensor) and the yeast RNA three-hybrid method, utilizing the specific interaction between the MS2 RNA and MS2 coat protein, is capable of detecting RNA-protein interactions in living mammalian cells. For conceptional proof we used the subgenomic flavivirus RNA (sfRNA) of the dengue virus (DENV), a highly structured noncoding RNA derived from the DENV genome known to target host cell proteins involved in innate immunity and antiviral defense, as bait. Using RNA-KISS, we could confirm the previously established interaction between the RNA-binding domain of DDX6 and the DENV sfRNA. Finally, we performed a human proteome-wide screen for DENV sfRNA-binding host factors, identifying several known flavivirus host factors such as DDX6 and PACT, further validating the RNA-KISS method as a robust and high-throughput cell-based RNA-protein interaction screening tool.

[Do circular RNAs play tricks on us?]

RNA has not said its last word with the rise of a new RNA family, circular RNAs (circRNAs). Discovered 25 years ago, circRNAs were initially considered as splicing byproducts. Today it appears that 14% of human genes produce circRNAs, whereas more than 100 000 different circRNAs are expressed. They are produced from coding genes through an alternative splicing mechanism called backsplicing, where an acceptor site is linked with a donor site located downstream. Nuclear circRNAs regulate transcription and splicing of their linear isoform. Cytoplasmic circRNAs, which are predominant, either sequester miRNAs or RNA binding proteins, or are translated via internal initiation mechanisms. CircRNAs may constitute a powerful biotechnogical tool for protein synthesis, as their translation is stable over time. In addition, exogenous circRNAs generate less immune response than their linear counterparts. We will also discuss in this review their biotechnological potential and their roles in pathological processes.

Deciphering miRNAs' Action through miRNA Editing

MicroRNAs (miRNAs) are small non-coding RNAs with the capability of modulating gene expression at the post-transcriptional level either by inhibiting messenger RNA (mRNA) translation or by promoting mRNA degradation. The outcome of a myriad of physiological processes and pathologies, including cancer, cardiovascular and metabolic diseases, relies highly on miRNAs. However, deciphering the precise roles of specific miRNAs in these pathophysiological contexts is challenging due to the high levels of complexity of their actions. Indeed, regulation of mRNA expression by miRNAs is frequently cell/organ specific; highly dependent on the stress and metabolic status of the organism; and often poorly correlated with miRNA expression levels. Such biological features of miRNAs suggest that various regulatory mechanisms control not only their expression, but also their activity and/or bioavailability. Several mechanisms have been described to modulate miRNA action, including genetic polymorphisms, methylation of miRNA promoters, asymmetric miRNA strand selection, interactions with RNA-binding proteins (RBPs) or other coding/non-coding RNAs. Moreover, nucleotide modifications (A-to-I or C-to-U) within the miRNA sequences at different stages of their maturation are also critical for their functionality. This regulatory mechanism called "RNA editing" involves specific enzymes of the adenosine/cytidine deaminase family, which trigger single nucleotide changes in primary miRNAs. These nucleotide modifications greatly influence a miRNA's stability, maturation and activity by changing its specificity towards target mRNAs. Understanding how editing events impact miRNA's ability to regulate stress responses in cells and organs, or the development of specific pathologies, e.g., metabolic diseases or cancer, should not only deepen our knowledge of molecular mechanisms underlying complex diseases, but can also facilitate the design of new therapeutic approaches based on miRNA targeting. Herein, we will discuss the current knowledge on miRNA editing and how this mechanism regulates miRNA biogenesis and activity.

Invited Review: Long non-coding RNAs: important regulators in the development, function and disorders of the central nervous system

Genome-wide transcriptional studies have demonstrated that tens of thousands of long non-coding RNAs (lncRNA) genes are expressed in the central nervous system (CNS) and that they exhibit tissue- and cell-type specificity. Their regulated and dynamic expression and their co-expression with protein-coding gene neighbours have led to the study of the functions of lncRNAs in CNS development and disorders. In this review, we describe the general characteristics, localization and classification of lncRNAs. We also elucidate the examples of the molecular mechanisms of nuclear and cytoplasmic lncRNA actions in the CNS and discuss common experimental approaches used to identify and unveil the functions of lncRNAs. Additionally, we provide examples of lncRNA studies of cell differentiation and CNS disorders including CNS injuries and neurodegenerative diseases. Finally, we review novel lncRNA-based therapies. Overall, this review highlights the important biological roles of lncRNAs in CNS functions and disorders.

Long Noncoding RNA HCP5, a Hybrid HLA Class I Endogenous Retroviral Gene: Structure, Expression, and Disease Associations

The HCP5 RNA gene (NCBI ID: 10866) is located centromeric of the HLA-B gene and between the MICA and MICB genes within the major histocompatibility complex (MHC) class I region. It is a human species-specific gene that codes for a long noncoding RNA (lncRNA), composed mostly of an ancient ancestral endogenous antisense 3′ long terminal repeat (LTR, and part of the internal pol antisense sequence of endogenous retrovirus (ERV) type 16 linked to a human leukocyte antigen (HLA) class I promoter and leader sequence at the 5′-end. Since its discovery in 1993, many disease association and gene expression studies have shown that HCP5 is a regulatory lncRNA involved in adaptive and innate immune responses and associated with the promotion of some autoimmune diseases and cancers. The gene sequence acts as a genomic anchor point for binding transcription factors, enhancers, and chromatin remodeling enzymes in the regulation of transcription and chromatin folding. The HCP5 antisense retroviral transcript also interacts with regulatory microRNA and immune and cellular checkpoints in cancers suggesting its potential as a drug target for novel antitumor therapeutics.

LncRNA PAPAS promotes oral squamous cell carcinoma by upregulating transforming growth factor-β1

PAPAS is a recently identified long noncoding RNA (lncRNA) with inhibitory effects on ribosomal RNA synthesis. We studied the role of PAPAS in oral squamous cell carcinoma (OSCC). In the present study we showed that plasma PAPAS and transforming growth factor β1 (TGF-β1) were both upregulated in patients with OSCC, and were positively correlated only in patients with OSCC. Plasma levels of PAPAS were not significantly affected by AJCC stages and upregulation of PAPAS distinguished stage I OSCC patients from healthy controls. High plasma levels of PAPAS were followed by low overall survival rate. PAPAS overexpression led to upregulation of TGF-β1 in OSCC cells, while TGF-β1 treatment failed to significantly affect PAPAS. PAPAS overexpression and exogenous TGF-β1 treatment led to promoted invasion and migration of OSCC cells. In addition, TGF-β inhibitor attenuated the effects of PAPAS overexpression. Therefore, lncRNA PAPAS may promote OSCC by upregulating TGF-β1.

Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy

The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic predictors of CP in newborns and to investigate disease pathogenesis. Methylation analysis of newborn blood DNA using an Illumina HumanMethylation450K array was performed in 23 CP cases and 21 unaffected controls. There were 230 significantly differentially-methylated CpG loci in 258 genes. Each locus had at least 2.0-fold change in methylation in CP versus controls with a FDR p-value ≤ 0.05. Methylation level for each CpG locus had an area under the receiver operating curve (AUC) ≥ 0.75 for CP detection. Using Artificial Intelligence (AI) platforms/Machine Learning (ML) analysis, CpG methylation levels in a combination of 230 significantly differentially-methylated CpG loci in 258 genes had a 95% sensitivity and 94.4% specificity for newborn prediction of CP. Using pathway analysis, multiple canonical pathways plausibly linked to neuronal function were over-represented. Altered biological processes and functions included: neuromotor damage, malformation of major brain structures, brain growth, neuroprotection, neuronal development and de-differentiation, and cranial sensory neuron development. In conclusion, blood leucocyte epigenetic changes analyzed using AI/ML techniques appeared to accurately predict CP and provided plausible mechanistic information on CP pathogenesis.