lncRNAdb v2.0: expanding the reference database for functional long noncoding RNAs

LncRNAs, nuclear architecture and the immune response

Long noncoding RNAs (LncRNAs) are key regulators of gene expression and can mediate their effects in both the nucleus and cytoplasm. Some of the best-characterized lncRNAs are localized within the nucleus, where they modulate the nuclear architecture and influence gene expression. In this review, we discuss the role of lncRNAs in nuclear architecture in the context of their gene regulatory functions in innate immunity. Here, we discuss various approaches to functionally characterize nuclear-localized lncRNAs and the challenges faced in the field.

Human lncRNAs harbor conserved modules embedded in different sequence contexts

We analyzed the structure of human long non-coding RNA (lncRNAs) genes to investigate whether the non-coding transcriptome is organized in modular domains, as is the case for protein-coding genes. To this aim, we compared all known human lncRNA exons and identified 340 pairs of exons with high sequence and/or secondary structure similarity but embedded in a dissimilar sequence context. We grouped these pairs in 106 clusters based on their reciprocal similarities. These shared modules are highly conserved between humans and the four great ape species, display evidence of purifying selection and likely arose as a result of recent segmental duplications. Our analysis contributes to the understanding of the mechanisms driving the evolution of the non-coding genome and suggests additional strategies towards deciphering the functional complexity of this class of molecules.

Role of long noncoding RNAs in the regulation of alternative splicing in glioblastoma

Glioblastoma multiforme (GBM) is a highly severe primary brain tumor. Despite extensive research, effective treatments remain elusive. Long noncoding RNAs (lncRNAs) play a significant role in both cancer and normal biology. They influence alternative splicing (AS), which is crucial in cancer. Advances in lncRNA-specific microarrays and next-generation sequencing have enhanced understanding of AS. Abnormal AS contributes to cancer invasion, metastasis, apoptosis, therapeutic resistance, and tumor development, including glioma. lncRNA-mediated AS affects several cellular signaling pathways, promoting or suppressing cancer malignancy. This review discusses the lncRNAs regulating AS in glioblastoma and their mechanisms.

Hierarchical lncRNA regulatory network in early-onset severe preeclampsia

BACKGROUND

Recent studies have shown that several long non-coding RNAs (lncRNAs) in the placenta are associated with preeclampsia (PE). However, the extent to which lncRNAs may contribute to the pathological progression of PE is unclear.

RESULTS

Here, we report a hierarchical regulatory network involved in early-onset severe PE (EOSPE). We have carried out transcriptome sequencing on the placentae from patients and normal subjects to identify the differentially expressed genes (DEGs), including some lncRNAs (DElncRNAs). We then constructed a high-quality hierarchical regulatory network of lncRNAs, transcription factors (TFs), and target DEGs, containing 1851 lncRNA-TF interactions and 6901 TF-promoter interactions. The lncRNA-to-target regulatory interactions were further validated by the triplex structures between the DElncRNAs and the promoters of the target DEGs. The DElncRNAs in the regulatory network were clustered into 3 clusters, one containing DElncRNAs correlated with the blood pressure, including FLNB-AS1 with targeting 27.89% (869/3116) DEGs in EOSPE. We further demonstrated that FLNB-AS1 could bind the transcription factor JUNB to regulate a series members of the HIF-1 signaling pathway in trophoblast cells.

CONCLUSIONS

Our results suggest that the differential expression of lncRNAs may perturb the lncRNA-TF-DEG hierarchical regulatory network, leading to the dysregulation of many genes involved in EOSPE. Our study provides a new strategy and a valuable resource for studying the mechanism underlying gene dysregulation in EOSPE patients.

Long non-coding RNAs; potential contributors in cancer chemoresistance through modulating diverse molecular mechanisms and signaling pathways

One of the mainstays of cancer treatment is chemotherapy. Drug resistance, however, continues to be the primary factor behind clinical treatment failure. Gene expression is regulated by long non-coding RNAs (lncRNAs) in several ways, including chromatin remodeling, translation, epigenetic, and transcriptional levels. Cancer hallmarks such as DNA damage, metastasis, immunological evasion, cell stemness, drug resistance, metabolic reprogramming, and angiogenesis are all influenced by LncRNAs. Numerous studies have been conducted on LncRNA-driven mechanisms of resistance to different antineoplastic drugs. Diverse medication kinds elicit diverse resistance mechanisms, and each mechanism may have multiple contributing factors. As a result, several lncRNAs have been identified as new biomarkers and therapeutic targets for identifying and managing cancers. This compels us to thoroughly outline the crucial roles that lncRNAs play in drug resistance. In this regard, this article provides an in-depth analysis of the recently discovered functions of lncRNAs in the pathogenesis and chemoresistance of cancer. As a result, the current research might offer a substantial foundation for future drug resistance-conquering strategies that target lncRNAs in cancer therapies.

Identification of a circulating long non-coding RNA signature panel in plasma as a novel biomarker for the detection of acute/early-stage HIV-1 infection

BACKGROUND

Individuals with acute / early HIV-1 infection are often unaware that they are infected with HIV-1 and may be involved in high-risk behavior leading to transmission of HIV-1. Identifying individuals with acute / early HIV-1 infection is critical to prevent further HIV-1 transmission, as diagnosis can lead to several effective HIV-1 prevention strategies. Identification of disease-stage specific non-viral host biomarkers would be useful as surrogate markers to accurately identify new HIV-1 infections. The goal of this study was to identify a panel of host derived plasma long non-coding RNAs (lncRNAs) that could serve as prognostic and predictive biomarkers to detect early/acute HIV-1 infection.

METHODS

A total of 84 lncRNAs were analyzed in sixteen plasma samples from HIV-1 infected individuals and four healthy controls using the lncRNA PCR-array. Twenty-one lncRNAs were selected and validated in 80 plasma samples from HIV-1 infected individuals [HIV-1 infected patients in the eclipse stage (n = 20), acute stage (n = 20), post-seroconversion p31 negative stage (n = 20), and post-seroconversion p31 positive stage (n = 20) of infection] and 20 healthy controls. The validation study results were used to develop a plasma lncRNA panel that was evaluated in the panel test phase to detect early/acute HIV-1 infection in 52 independent samples.

RESULTS

We identified a lncRNA panel (Pmodel-I) containing eight lncRNAs (DISC2, H19, IPW, KRASP1, NEAT1, PRINS, WT1-AS and ZFAS1) that could distinguish HIV-1 infection from healthy controls with high AUC 0·990 (95% CI 0.972-1.000), sensitivity (98.75%), and specificity (95%). We also found that Pmodel-II and Pmodel-III demonstrates 100% sensitivity and specificity (AUC 1·00; 95%CI:1·00-1·00) and could distinguish eclipse stage and acute stage of HIV-1 infection from healthy controls respectively. Antiretroviral treatment (ART) cumulatively restored the levels of lncRNAs to healthy controls levels.

CONCLUSION

lncRNA expression changes significantly in response to HIV-1 infection. Our findings also highlight the potential of using circulating lncRNAs to detect both the eclipse and acute stages of HIV-1 infection, which may help to shorten the window period and facilitate early detection and treatment initiation. Initiating ART treatment at this stage would significantly reduce HIV-1 transmission. The differentially expressed lncRNAs identified in this study could serve as potential prognostic and diagnostic biomarkers of HIV-1 infection, as well as new therapeutic targets.

Update on functional analysis of long non-coding RNAs in common crops

With the rapid advances in next-generation sequencing technology, numerous non-protein-coding transcripts have been identified, including long noncoding RNAs (lncRNAs), which are functional RNAs comprising more than 200 nucleotides. Although lncRNA-mediated regulatory processes have been extensively investigated in animals, there has been considerably less research on plant lncRNAs. Nevertheless, multiple studies on major crops showed lncRNAs are involved in crucial processes, including growth and development, reproduction, and stress responses. This review summarizes the progress in the research on lncRNA roles in several major crops, presents key strategies for exploring lncRNAs in crops, and discusses current challenges and future prospects. The insights provided in this review will enhance our comprehension of lncRNA functions in crops, with potential implications for improving crop genetics and breeding.

Long non-coding RNAs in cardiac hypertrophy and heart failure: functions, mechanisms and clinical prospects

The surge in reports describing non-coding RNAs (ncRNAs) has focused attention on their possible biological roles and effects on development and disease. ncRNAs have been touted as previously uncharacterized regulators of gene expression and cellular processes, possibly working to fine-tune these functions. The sheer number of ncRNAs identified has outpaced the capacity to characterize each molecule thoroughly and to reliably establish its clinical relevance; it has, nonetheless, created excitement about their potential as molecular targets for novel therapeutic approaches to treat human disease. In this Review, we focus on one category of ncRNAs - long non-coding RNAs - and their expression, functions and molecular mechanisms in cardiac hypertrophy and heart failure. We further discuss the prospects for this specific class of ncRNAs as novel targets for the diagnosis and treatment of these conditions.

RNA Therapeutics for the Cardiovascular System

RNA therapeutics hold significant promise in the treatment of cardiovascular diseases. RNAs are biologically diverse and functionally specific and can be used for gain- or loss-of-function purposes. The effectiveness of mRNA-based vaccines in the recent COVID-19 pandemic has undoubtedly proven the benefits of an RNA-based approach. RNA-based therapies are becoming more common as a treatment modality for cardiovascular disease. This is most evident in hypertension where several small interfering RNA-based drugs have proven to be effective in managing high blood pressure in several clinical trials. As befits a rapidly burgeoning field, there is significant interest in other classes of RNA. Revascularization of the infarcted heart through an mRNA drug is under clinical investigation. mRNA technology may provide the platform for the expression of paracrine factors for myocardial protection and regeneration. Emergent technologies on the basis of microRNAs and gene editing are tackling complex diseases in a novel fashion. RNA-based gene editing offers hope of permanent cures for monogenic cardiovascular diseases, and long-term control of complex diseases such as essential hypertension, as well. Likewise, microRNAs are proving effective in regenerating cardiac muscle. The aim of this review is to provide an overview of the current landscape of RNA-based therapies for the treatment of cardiovascular disease. The review describes the large number of RNA molecules that exist with a discussion of the clinical development of each RNA type. In addition, the review also presents a number of avenues for future development.

The pivotal role of long non-coding RNAs as potential biomarkers and modulators of chemoresistance in ovarian cancer (OC)

Ovarian cancer (OC) is a fatal gynecological disease that is often diagnosed at later stages due to its asymptomatic nature and the absence of efficient early-stage biomarkers. Previous studies have identified genes with abnormal expression in OC that couldn't be explained by methylation or mutation, indicating alternative mechanisms of gene regulation. Recent advances in human transcriptome studies have led to research on non-coding RNAs (ncRNAs) as regulators of cancer gene expression. Long non-coding RNAs (lncRNAs), a class of ncRNAs with a length greater than 200 nucleotides, have been identified as crucial regulators of physiological processes and human diseases, including cancer. Dysregulated lncRNA expression has also been found to play a crucial role in ovarian carcinogenesis, indicating their potential as novel and non-invasive biomarkers for improving OC management. However, despite the discovery of several thousand lncRNAs, only one has been approved for clinical use as a biomarker in cancer, highlighting the importance of further research in this field. In addition to their potential as biomarkers, lncRNAs have been implicated in modulating chemoresistance, a major problem in OC. Several studies have identified altered lncRNA expression upon drug treatment, further emphasizing their potential to modulate chemoresistance. In this review, we highlight the characteristics of lncRNAs, their function, and their potential to serve as tumor markers in OC. We also discuss a few databases providing detailed information on lncRNAs in various cancer types. Despite the promising potential of lncRNAs, further research is necessary to fully understand their role in cancer and develop effective strategies to combat this devastating disease.

Computational prediction and experimental validation identify functionally conserved lncRNAs from zebrafish to human

Functional studies of long noncoding RNAs (lncRNAs) have been hindered by the lack of methods to assess their evolution. Here we present lncRNA Homology Explorer (lncHOME), a computational pipeline that identifies a unique class of long noncoding RNAs (lncRNAs) with conserved genomic locations and patterns of RNA-binding protein (RBP) binding sites (coPARSE-lncRNAs). Remarkably, several hundred human coPARSE-lncRNAs can be evolutionarily traced to zebrafish. Using CRISPR-Cas12a knockout and rescue assays, we found that knocking out many human coPARSE-lncRNAs led to cell proliferation defects, which were subsequently rescued by predicted zebrafish homologs. Knocking down coPARSE-lncRNAs in zebrafish embryos caused severe developmental delays that were rescued by human homologs. Furthermore, we verified that human, mouse and zebrafish coPARSE-lncRNA homologs tend to bind similar RBPs with their conserved functions relying on specific RBP-binding sites. Overall, our study demonstrates a comprehensive approach for studying the functional conservation of lncRNAs and implicates numerous lncRNAs in regulating vertebrate physiology.

Long noncoding RNA study: Genome-wide approaches

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.

Exploring the landscape of tools and resources for the analysis of long non-coding RNAs

In recent years, research on long non-coding RNAs (lncRNAs) has gained considerable attention due to the increasing number of newly identified transcripts. Several characteristics make their functional evaluation challenging, which called for the urgent need to combine molecular biology with other disciplines, including bioinformatics. Indeed, the recent development of computational pipelines and resources has greatly facilitated both the discovery and the mechanisms of action of lncRNAs. In this review, we present a curated collection of the most recent computational resources, which have been categorized into distinct groups: databases and annotation, identification and classification, interaction prediction, and structure prediction. As the repertoire of lncRNAs and their analysis tools continues to expand over the years, standardizing the computational pipelines and improving the existing annotation of lncRNAs will be crucial to facilitate functional genomics studies.

An RNA-informed dosage sensitivity map reflects the intrinsic functional nature of genes

Understanding dosage sensitivity or why Mendelian diseases have dominant vs. recessive modes of inheritance is crucial for uncovering the etiology of human disease. Previous knowledge of dosage sensitivity is mainly based on observations of rare loss-of-function mutations or copy number changes, which are underpowered due to ultra rareness of such variants. Thus, the functional underpinnings of dosage constraint remain elusive. In this study, we aim to systematically quantify dosage perturbations from cis-regulatory variants in the general population to yield a tissue-specific dosage constraint map of genes and further explore their underlying functional logic. We reveal an inherent divergence of dosage constraints in genes by functional categories with signaling genes (transcription factors, protein kinases, ion channels, and cellular machinery) being dosage sensitive, while effector genes (transporters, metabolic enzymes, cytokines, and receptors) are generally dosage resilient. Instead of being a metric of functional dispensability, we show that dosage constraint reflects underlying homeostatic constraints arising from negative feedback. Finally, we employ machine learning to integrate DNA and RNA metrics to generate a comprehensive, tissue-specific map of dosage sensitivity (MoDs) for autosomal genes.

VirhostlncR: A comprehensive database to explore lncRNAs and their targets in viral infections

Long non-coding-RNAs (lncRNAs) are an expanding set of cis-/trans-regulatory RNA genes that outnumber the protein-coding genes. Although being increasingly discovered, the functional role of the majority of lncRNAs in diverse biological conditions is undefined. Increasing evidence supports the critical role of lncRNAs in the emergence, regulation, and progression of various viral infections including influenza, hepatitis, coronavirus, and human immunodeficiency virus. Hence, the identification of signature lncRNAs would facilitate focused analysis of their functional roles accounting for their targets and regulatory mechanisms associated with infections. Towards this, we compiled 2803 lncRNAs identified to be modulated by 33 viral strains in various mammalian cell types and are provided through the resource named VirhostlncR (http://ciods.in/VirhostlncR/). The information on each of the viral strains, their multiplicity of infection, duration of infection, host cell name and cell types, fold change of lncRNA expression, and their specific identification methods are integrated into VirhostlncR. Based on the current datasets, we report 150 lncRNAs including differentiation antagonizing non-protein coding RNA (DANCR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), maternally expressed gene 3 (MEG3), nuclear paraspeckle assembly transcript 1 (NEAT1), and plasmacytoma variant translocation 1 (PVT1) to be perturbed by two or more viruses. Analysis of viral protein interactions with human transcription factors (TFs) or TF-containing protein complexes identified that distinct viruses can transcriptionally regulate many of these lncRNAs through multiple protein complexes. Together, we believe that the current dataset will enable priority selection of lncRNAs for identification of their targets and serve as an effective platform for the analysis of noncoding RNA-mediated regulations in viral infections.

Unlocking the potential of non-coding RNAs in cancer research and therapy

Non-coding RNAs (ncRNAs) have emerged as key regulators of gene expression, with growing evidence implicating their involvement in cancer development and progression. The potential of ncRNAs as diagnostic and prognostic biomarkers for cancer is promising, with emphasis on their use in liquid biopsy and tissue-based diagnostics. In a nutshell, the review comprehensively summarizes the diverse classes of ncRNAs implicated in cancer, including microRNAs, long non-coding RNAs, and circular RNAs, and their functions and mechanisms of action. Furthermore, we describe the potential therapeutic applications of ncRNAs, including anti-miRNA oligonucleotides, siRNAs, and other RNA-based therapeutics in cancer treatment. However, significant challenges remain in developing effective ncRNA-based diagnostics and therapeutics, including the lack of specificity, limited understanding of mechanisms, and delivery challenges. This review also covers the current state-of-the-art non-coding RNA research technologies and bioinformatic analysis tools. Lastly, we outline future research directions in non-coding RNA research in cancer, including developing novel biomarkers, therapeutic targets, and modalities. In summary, this review provides a comprehensive understanding of non-coding RNAs in cancer and their potential clinical applications, highlighting both the opportunities and challenges in this rapidly evolving field.

A review from biological mapping to computation-based subcellular localization

Subcellular localization is crucial to the study of virus and diseases. Specifically, research on protein subcellular localization can help identify clues between virus and host cells that can aid in the design of targeted drugs. Research on RNA subcellular localization is significant for human diseases (such as Alzheimer's disease, colon cancer, etc.). To date, only reviews addressing subcellular localization of proteins have been published, which are outdated for reference, and reviews of RNA subcellular localization are not comprehensive. Therefore, we collated (the most up-to-date) literature on protein and RNA subcellular localization to help researchers understand changes in the field of protein and RNA subcellular localization. Extensive and complete methods for constructing subcellular localization models have also been summarized, which can help readers understand the changes in application of biotechnology and computer science in subcellular localization research and explore how to use biological data to construct improved subcellular localization models. This paper is the first review to cover both protein subcellular localization and RNA subcellular localization. We urge researchers from biology and computational biology to jointly pay attention to transformation patterns, interrelationships, differences, and causality of protein subcellular localization and RNA subcellular localization.

Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment

According to the World Health Organization, every year, an estimated 400,000+ new cancer cases affect children under the age of 20 worldwide. Unlike adult cancers, pediatric cancers develop very early in life due to alterations in signaling pathways that regulate embryonic development, and environmental factors do not contribute much to cancer development. The highly organized complex microenvironment controlled by synchronized gene expression patterns plays an essential role in the embryonic stages of development. Dysregulated development can lead to tumor initiation and growth. The low mutational burden in pediatric tumors suggests the predominant role of epigenetic changes in driving the cancer phenotype. However, one more upstream layer of regulation driven by ncRNAs regulates gene expression and signaling pathways involved in the development. Deregulation of ncRNAs can alter the epigenetic machinery of a cell, affecting the transcription and translation profiles of gene regulatory networks required for cellular proliferation and differentiation during embryonic development. Therefore, it is essential to understand the role of ncRNAs in pediatric tumor development to accelerate translational research to discover new treatments for childhood cancers. This review focuses on the role of ncRNA in regulating the epigenetics of pediatric tumors and their tumor microenvironment, the impact of their deregulation on driving pediatric tumor progress, and their potential as effective therapeutic targets.

Molecular hallmarks of long non-coding RNAs in aging and its significant effect on aging-associated diseases

Aging is linked to the deterioration of many physical and cognitive abilities and is the leading risk factor for Alzheimer's disease. The growing aging population is a significant healthcare problem globally that researchers must investigate to better understand the underlying aging processes. Advances in microarrays and sequencing techniques have resulted in deeper analyses of diverse essential genomes (e.g., mouse, human, and rat) and their corresponding cell types, their organ-specific transcriptomes, and the tissue involved in aging. Traditional gene controllers such as DNA- and RNA-binding proteins significantly influence such programs, causing the need to sort out long non-coding RNAs, a new class of powerful gene regulatory elements. However, their functional significance in the aging process and senescence has yet to be investigated and identified. Several recent researchers have associated the initiation and development of senescence and aging in mammals with several well-reported and novel long non-coding RNAs. In this review article, we identified and analyzed the evolving functions of long non-coding RNAs in cellular processes, including cellular senescence, aging, and age-related pathogenesis, which are the major hallmarks of long non-coding RNAs in aging.

Long non-coding RNAs as critical regulators and novel targets in cervical cancer: current status and future perspectives

Cervical cancer is among the leading causes of cancer-associated mortality in women. In spite of vaccine availability, improved screening procedures, and chemoradiation therapy, cervical cancer remains the most commonly diagnosed cancer in 23 countries and the leading cause of cancer deaths in 36 countries. There is, therefore, a need to come up with novel diagnostic and therapeutic targets. Long non-coding RNAs (lncRNAs) play a remarkable role in genome regulation and contribute significantly to several developmental and disease pathways. The deregulation of lncRNAs is often observed in cancer patients, where they are shown to affect multiple cellular processes, including cell cycle, apoptosis, angiogenesis, and invasion. Many lncRNAs are found to be involved in the pathogenesis as well as progression of cervical cancer and have shown potency to track metastatic events. This review provides an overview of lncRNA mediated regulation of cervical carcinogenesis and highlights their potential as diagnostic and prognostic biomarkers as well as therapeutic targets for cervical cancer. In addition, it also discusses the challenges associated with the clinical implication of lncRNAs in cervical cancer.

Research progress on the roles of lncRNAs in plant development and stress responses

Long non-coding RNAs (lncRNAs) are RNAs of more than 200 nucleotides in length that are not (or very rarely) translated into proteins. In eukaryotes, lncRNAs regulate gene expression at the transcriptional, post-transcriptional, and epigenetic levels. lncRNAs are categorized according to their genomic position and molecular mechanism. This review summarized the characteristics and mechanisms of plant lncRNAs involved in vegetative growth, reproduction, and stress responses. Our discussion and model provide a theoretical basis for further studies of lncRNAs in plant breeding.

ncR2Met (lncR2metasta v2.0): An updated database for experimentally supported ncRNAs during cancer metastatic events

Non-coding RNAs (ncRNAs) are widely involved in cancer metastatic events (CMEs, e.g., cancer cell invasion, intravasation, extravasation, proliferation), which collaboratively accelerate tumor spread and cause high patient mortality. In early 2020, we developed a manually curated database named 'lncR2metasta' to provide a comprehensive repository for long ncRNA (lncRNA) regulation during CMEs. We updated this database by supplementing other two important ncRNA types, microRNAs (miRNAs) and circular RNAs (circRNAs), for their involvement during CMEs after a thorough manual curation from published studies. ncR2metasta documents 1565 lncRNA-associated, 882 miRNA-associated, and 628 circRNA-associated entries for ncRNA-CME associations during 50 CMEs across 63 human cancer subtypes. ncR2Met has a concise web interface for researchers to easily browse, search and download as well as to submit novel ncRNA-CME associations. We anticipated that it could be a valuable resource, which will significantly improve our understanding of ncRNA functions in metastasis. It is freely available at http://ncr2met.wchoda.com.

Mechanisms of Long Non-Coding RNA in Breast Cancer

The landscape of pervasive transcription in eukaryotic genomes has made space for the identification of thousands of transcripts that are difficult to frame in a specific functional category. A new class has been broadly named as long non-coding RNAs (lncRNAs) and shortly defined as transcripts that are longer than 200 nucleotides with no or limited coding potential. So far, about 19,000 lncRNAs genes have been annotated in the human genome (Gencode 41), nearly matching the number of protein-coding genes. A key scientific priority is the functional characterization of lncRNAs, a major challenge in molecular biology that has encouraged many high-throughput efforts. LncRNA studies have been stimulated by the enormous clinical potential that these molecules promise and have been based on the characterization of their expression and functional mechanisms. In this review, we illustrate some of these mechanisms as they have been pictured in the context of breast cancer.

Advances in Plant Epigenome Editing Research and Its Application in Plants

Plant epistatic regulation is the DNA methylation, non-coding RNA regulation, and histone modification of gene sequences without altering the genome sequence, thus regulating gene expression patterns and the growth process of plants to produce heritable changes. Epistatic regulation in plants can regulate plant responses to different environmental stresses, regulate fruit growth and development, etc. Genome editing can effectively improve plant genetic efficiency by targeting the design and efficient editing of genome-specific loci with specific nucleases, such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALEN), and clustered regularly interspaced short palindromic repeats/CRISPR-associated 9 (CRISPR/Cas9). As research progresses, the CRISPR/Cas9 system has been widely used in crop breeding, gene expression, and epistatic modification due to its high editing efficiency and rapid translation of results. In this review, we summarize the recent progress of CRISPR/Cas9 in epigenome editing and look forward to the future development direction of this system in plant epigenetic modification to provide a reference for the application of CRISPR/Cas9 in genome editing.

Plasma and urinary extracellular vesicles as a source of RNA biomarkers for prostate cancer in liquid biopsies

Introduction: Extracellular vesicles (EVs) have emerged as a very attractive source of cancer- derived RNA biomarkers for the early detection, prognosis and monitoring of various cancers, including prostate cancer (PC). However, biofluids contain a mixture of EVs released from a variety of tissues and the fraction of total EVs that are derived from PC tissue is not known. Moreover, the optimal biofluid-plasma or urine-that is more suitable for the detection of EV- enclosed RNA biomarkers is not yet clear. Methodology: In the current study, we performed RNA sequencing analysis of plasma and urinary EVs collected before and after radical prostatectomy, and matched tumor and normal prostate tissues of 10 patients with prostate cancer. Results and Discussion: The most abundant RNA biotypes in EVs were miRNA, piRNA, tRNA, lncRNA, rRNA and mRNA. To identify putative cancer-derived RNA biomarkers, we searched for RNAs that were overexpressed in tumor as compared to normal tissues, present in the pre-operation EVs and decreased in the post-operation EVs in each RNA biotype. The levels of 63 mRNAs, 3 lncRNAs, 2 miRNAs and 1 piRNA were significantly increased in the tumors and decreased in the post-operation urinary EVs, thus suggesting that these RNAs mainly originate from PC tissue. No such RNA biomarkers were identified in plasma EVs. This suggests that the fraction of PC-derived EVs in urine is larger than in plasma and allows the detection and tracking of PC-derived RNAs.

Recent advances in predicting lncRNA-disease associations based on computational methods

Mutations in and dysregulation of long non-coding RNAs (lncRNAs) are closely associated with the development of various human complex diseases, but only a few lncRNAs have been experimentally confirmed to be associated with human diseases. Predicting new potential lncRNA-disease associations (LDAs) will help us to understand the pathogenesis of human diseases and to detect disease markers, as well as in disease diagnosis, prevention and treatment. Computational methods can effectively narrow down the screening scope of biological experiments, thereby reducing the duration and cost of such experiments. In this review, we outline recent advances in computational methods for predicting LDAs, focusing on LDA databases, lncRNA/disease similarity calculations, and advanced computational models. In addition, we analyze the limitations of various computational models and discuss future challenges and directions for development.

lncRNA LINC00960 promotes apoptosis by sponging ubiquitin ligase Nrdp1-targeting miR-183-5p

<p indent="0mm">The ubiquitin ligase Nrdp1/RNF41 promotes the ubiquitin-dependent degradation of multiple important substrates, including BRUCE/BIRC6, a giant ubiquitin-conjugating enzyme inhibiting both apoptosis and autophagy. miR-183-5p is associated with various malignancies potentially by targeting dozens of genes. Here, we show that the lncRNA LINC00960 binds to the Nrdp1-targeting miR-183-5p and promotes apoptosis. Compared to other known miR-183-5p targets, Nrdp1 mRNA is among the few with top scores to complement miR-183-5p. miR-183-5p binds to the <sc>3'UTR</sc> of Nrdp1 mRNA and downregulates Nrdp1 at both the mRNA and protein levels. The miR-183-5p mimics inhibit DNA damage-induced apoptosis probably by upregulating BRUCE level, whereas the miR-183-5p inhibitor suppresses the effects of miR-183-5p. LINC00960 is the noncoding RNA with the highest score to complement miR-183-5p. LINC00960 overexpression reduces, but its knockdown increases, the level of miR-183-5p, whereas LINC00960 overexpression increases, but its knockdown decreases, the level of Nrdp1 and apoptosis. Importantly, the expression of LINC00960, which is associated with multiple types of tumors, positively correlates with that of Nrdp1 in several tumors but inversely correlates with that of miR-183-5p in multiple human tumor cell lines, as analysed by quantitative PCR. Thus, miR-183-5p downregulates Nrdp1 expression and inhibits apoptosis, whereas LINC00960 upregulates Nrdp1 and promotes apoptosis by inhibiting miR-183-5p. These results may provide new ideas for the prevention, diagnosis and treatment of apoptosis-related diseases, such as tumors and neurodegenerative diseases. </p>.

Functional Relevance of the Long Intergenic Non-Coding RNA Regulator of Reprogramming (Linc-ROR) in Cancer Proliferation, Metastasis, and Drug Resistance

Cancer is responsible for more than 10 million deaths every year. Metastasis and drug resistance lead to a poor survival rate and are a major therapeutic challenge. Substantial evidence demonstrates that an increasing number of long non-coding RNAs are dysregulated in cancer, including the long intergenic non-coding RNA, regulator of reprogramming (linc-ROR), which mostly exerts its role as an onco-lncRNA acting as a competing endogenous RNA that sequesters micro RNAs. Although the properties of linc-ROR in relation to some cancers have been reviewed in the past, active research appends evidence constantly to a better comprehension of the role of linc-ROR in different stages of cancer. Moreover, the molecular details and some recent papers have been omitted or partially reported, thus the importance of this review aimed to contribute to the up-to-date understanding of linc-ROR and its implication in cancer tumorigenesis, progression, metastasis, and chemoresistance. As the involvement of linc-ROR in cancer is elucidated, an improvement in diagnostic and prognostic tools could promote and advance in targeted and specific therapies in precision oncology.

T-REX17 is a transiently expressed non-coding RNA essential for human endoderm formation

Long non-coding RNAs (lncRNAs) have emerged as fundamental regulators in various biological processes, including embryonic development and cellular differentiation. Despite much progress over the past decade, the genome-wide annotation of lncRNAs remains incomplete and many known non-coding loci are still poorly characterized. Here, we report the discovery of a previously unannotated lncRNA that is transcribed 230 kb upstream of the SOX17 gene and located within the same topologically associating domain. We termed it T-REX17 (Transcript Regulating Endoderm and activated by soX17) and show that it is induced following SOX17 activation but its expression is more tightly restricted to early definitive endoderm. Loss of T-REX17 affects crucial functions independent of SOX17 and leads to an aberrant endodermal transcriptome, signaling pathway deregulation and epithelial to mesenchymal transition defects. Consequently, cells lacking the lncRNA cannot further differentiate into more mature endodermal cell types. Taken together, our study identified and characterized T-REX17 as a transiently expressed and essential non-coding regulator in early human endoderm differentiation.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

Role of long non coding RNA in plants under abiotic and biotic stresses

Evolutionary processes have evolved plants to cope with several different natural stresses. Basic physiological activities of crop plants are significantly harmed by these stresses, reducing productivity and eventually leading to death. The recent advancements in high-throughput sequencing of transcriptome and expression profiling with NGS techniques lead to the innovation of various RNAs which do not code for proteins, more specifically long non-coding RNAs (lncRNAs), undergirding regulate growth, development, and the plant defence mechanism transcriptionally under stress situations. LncRNAs are a diverse set of RNAs that play key roles in various biological processes at the level of transcription, post-transcription, and epigenetics. These are thought to serve crucial functions in plant immunity and response to changes in the environment. In plants, however, just a few lncRNAs have been functionally identified. In this review, we will address recent advancements in comprehending lncRNA regulatory functions, focusing on the expanding involvement of lncRNAs in modulating environmental stress responsiveness in plants.

The Idiopathic Pulmonary Fibrosis-Associated Single Nucleotide Polymorphism RS35705950 Is Transcribed in a MUC5B Promoter Associated Long Non-Coding RNA (AC061979.1)

LncRNAs are involved in regulatory processes in the human genome, including gene expression. The rs35705950 SNP, previously associated with IPF, overlaps with the recently annotated lncRNA AC061979.1, a 1712 nucleotide transcript located within the MUC5B promoter at chromosome 11p15.5. To document the expression pattern of the transcript, we processed 3.9 TBases of publicly available RNA-SEQ data across 27 independent studies involving lung airway epithelial cells. Epithelial lung cells showed expression of this putative pancRNA. The findings were independently validated in cell lines and primary cells. The rs35705950 is found within a conserved region (from fish to primates) within the expressed sequence indicating functional importance. These results implicate the rs35705950-containing AC061979.1 pancRNA as a novel component of the MUC5B expression control minicircuitry.

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.

A large-scale benchmark study of tools for the classification of protein-coding and non-coding RNAs

Identification of protein-coding and non-coding transcripts is paramount for understanding their biological roles. Computational approaches have been addressing this task for over a decade; however, generalized and high-performance models are still unreliable. This benchmark study assessed the performance of 24 tools producing >55 models on the datasets covering a wide range of species. We have collected 135 small and large transcriptomic datasets from existing studies for comparison and identified the potential bottlenecks hampering the performance of current tools. The key insights of this study include lack of standardized training sets, reliance on homogeneous training data, gradual changes in annotated data, lack of augmentation with homology searches, the presence of false positives and negatives in datasets and the lower performance of end-to-end deep learning models. We also derived a new dataset, RNAChallenge, from the benchmark considering hard instances that may include potential false alarms. The best and least well performing models under- and overfit the dataset, respectively, thereby serving a dual purpose. For computational approaches, it will be valuable to develop accurate and unbiased models. The identification of false alarms will be of interest for genome annotators, and experimental study of hard RNAs will help to untangle the complexity of the RNA world.

FDRdb: a manually curated database of fibrotic disease–associated RNAome and high-throughput datasets

Fibrosis is a common and serious disease that exists as a complicated impairment in many organs and triggers a complex cascade of responses. The deregulation of Ribonucleic Acids (RNAs) plays important roles in a variety of organ fibrosis cases. However, for fibrotic diseases, there is still a lack of an integrated platform with up-to-date information on RNA deregulation and high-throughput data. The Fibrotic Disease–associated RNAome database (FDRdb) (http://www.medsysbio.org/FDRdb) is a manually curated database of fibrotic disease–associated RNAome information and high-throughput datasets. This initial release (i) contains 1947 associations between 912 RNAs and 92 fibrotic diseases in eight species; (ii) collects information on 764 datasets of fibrotic diseases; (iii) provides a user-friendly web interface that allows users to browse, search and download the RNAome information on fibrotic diseases and high-throughput datasets and (iv) provides tools to analyze the expression profiles of fibrotic diseases, including differential expression analysis and pathway enrichment. The FDRdb is a valuable resource for researchers to explore the mechanisms of RNA dysregulation in organ fibrosis.

Database URL: http://www.medsysbio.org/FDRdb

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

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

EpiFactors 2022: expansion and enhancement of a curated database of human epigenetic factors and complexes

We present an update of EpiFactors, a manually curated database providing information about epigenetic regulators, their complexes, targets, and products which is openly accessible at http://epifactors.autosome.org. An updated version of the EpiFactors contains information on 902 proteins, including 101 histones and protamines, and, as a main update, a newly curated collection of 124 lncRNAs involved in epigenetic regulation. The amount of publications concerning the role of lncRNA in epigenetics is rapidly growing. Yet, the resource that compiles, integrates, organizes, and presents curated information on lncRNAs in epigenetics is missing. EpiFactors fills this gap and provides data on epigenetic regulators in an accessible and user-friendly form. For 820 of the genes in EpiFactors, we include expression estimates across multiple cell types assessed by CAGE-Seq in the FANTOM5 project. In addition, the updated EpiFactors contains information on 73 protein complexes involved in epigenetic regulation. Our resource is practical for a wide range of users, including biologists, bioinformaticians and molecular/systems biologists.

Structure-based screening for functional non-coding RNAs in fission yeast identifies a factor repressing untimely initiation of sexual differentiation

Non-coding RNAs (ncRNAs) ubiquitously exist in normal and cancer cells. Despite their prevalent distribution, the functions of most long ncRNAs remain uncharacterized. The fission yeast Schizosaccharomyces pombe expresses >1800 ncRNAs annotated to date, but most unconventional ncRNAs (excluding tRNA, rRNA, snRNA and snoRNA) remain uncharacterized. To discover the functional ncRNAs, here we performed a combinatory screening of computational and biological tests. First, all S. pombe ncRNAs were screened in silico for those showing conservation in sequence as well as in secondary structure with ncRNAs in closely related species. Almost a half of the 151 selected conserved ncRNA genes were uncharacterized. Twelve ncRNA genes that did not overlap with protein-coding sequences were next chosen for biological screening that examines defects in growth or sexual differentiation, as well as sensitivities to drugs and stresses. Finally, we highlighted an ncRNA transcribed from SPNCRNA.1669, which inhibited untimely initiation of sexual differentiation. A domain that was predicted as conserved secondary structure by the computational operations was essential for the ncRNA to function. Thus, this study demonstrates that in silico selection focusing on conservation of the secondary structure over species is a powerful method to pinpoint novel functional ncRNAs.

Deep whole genome sequencing identifies recurrent genomic alterations in commonly used breast cancer cell lines and patient-derived xenograft models

Background

Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDXs) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions.

Results

Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60 × coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1, previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers.

Conclusions

Our WGS data provides a comprehensive genome sequencing resource of these models.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01540-0.

LncPheDB: a genome-wide lncRNAs regulated phenotypes database in plants

LncPheDB (https://www.lncphedb.com/) is a systematic resource of genome-wide long non-coding RNAs (lncRNAs)-phenotypes associations for multiple species. It was established to display the genome-wide lncRNA annotations, target genes prediction, variant-trait associations, gene-phenotype correlations, lncRNA-phenotype correlations, and the similar non-coding regions of the queried sequence in multiple species. LncPheDB sorted out a total of 203,391 lncRNA sequences, 2000 phenotypes, and 120,271 variants of nine species (Zea mays L., Gossypium barbadense L., Triticum aestivum L., Lycopersicon esculentum Mille, Oryza sativa L., Hordeum vulgare L., Sorghum bicolor L., Glycine max L., and Cucumis sativus L.). By exploring the relationship between lncRNAs and the genomic position of variants in genome-wide association analysis, a total of 68,862 lncRNAs were found to be related to the diversity of agronomic traits. More importantly, to facilitate the study of the functions of lncRNAs, we analyzed the possible target genes of lncRNAs, constructed a blast tool for performing similar fragmentation studies in all species, linked the pages of phenotypic studies related to lncRNAs that possess similar fragments and constructed their regulatory networks. In addition, LncPheDB also provides a user-friendly interface, a genome visualization platform, and multi-level and multi-modal convenient data search engine. We believe that LncPheDB plays a crucial role in mining lncRNA-related plant data.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-022-00084-3.

The Long Read Transcriptome of Rice (Oryza sativa ssp. japonica var. Nipponbare) Reveals Novel Transcripts

BACKGROUND

High-throughput next-generation sequencing technologies offer a powerful approach to characterizing the transcriptomes of plants. Long read sequencing has been shown to support the discovery of novel isoforms of transcripts. This approach enables the generation of full-length sequences revealing splice variants that may be important in regulating gene action. Investigation of the diversity of transcripts in the rice transcriptome including splice variants was conducted using PacBio long-read sequence data to improve the annotation of the rice genome.

RESULTS

A cDNA library was prepared from RNA extracted from leaves, roots, seeds, inflorescences, and panicles of O. sativa ssp. japonica var Nipponbare and sequenced on a PacBio Sequel platform. This produced 346,190 non-redundant full-length non-chimeric reads (FLNC) resulting in 33,504 high-quality transcripts. Half of the transcripts were multi-exonic and entirely matched with the reference transcripts. However, 14,874 novel isoforms were also identified resulting predominantly from intron retention and at least one novel splice site. Intron retention was the prevalent alternative splicing event and exon skipping was the least observed. Of 73,659 splice junctions, 12,755 (17%) represented novel splice junctions with canonical and non-canonical intron boundaries. The complexity of the transcriptome was examined in detail for 19 starch synthesis-related genes, defining 276 spliced isoforms of which 94 splice variants were novel.

CONCLUSION

The data reveal the great complexity of the rice transcriptome. The novel transcripts provide new insights that may be a key input in future research to improve the annotation of the rice genome.

Utilization and Potential of RNA-Based Therapies in Cardiovascular Disease

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RNA-based therapeutics have the potential to reach previously “undruggable” pathways in cardiovascular disease

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RNA-based therapeutics constitute a vast array of technologies, including unique forms, chemistries, and modalities of delivery

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Rapid development of RNA-based vaccines was made possible by decades of foundational work

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Specificity and efficacy of targeting and determination of mechanism(s) of action remain a distinct challenge

Cardiovascular disease (CVD) remains the largest cause of mortality worldwide. The development of new effective therapeutics is a major unmet need. The current review focuses broadly on the concept of nucleic acid (NA)–based therapies, considering the use of various forms of NAs, including mRNAs, miRNAs, siRNA, and guide RNAs, the latter specifically for the purpose of CRISPR-Cas directed gene editing. We describe the current state-of-the-art of RNA target discovery and development, the status of RNA therapeutics in the context of CVD, and some of the challenges and hurdles to be overcome.

dbEssLnc: A manually curated database of human and mouse essential lncRNA genes

Long non-coding RNAs (lncRNAs) play important roles in many biological processes. Knocking out or knocking down some lncRNAs will lead to lethality or infertility. These lncRNAs are called essential lncRNAs. Knowledges of essential lncRNAs are important in establishing minimal genomes of living cells, developing drug therapies and early diagnostic approaches for complex diseases. However, existing databases focus on collecting essential coding genes. Essential non-coding gene records are rare in existing databases. A comprehensive collection of essential non-coding genes, particularly essential lncRNA genes, is demanded. We manually curated 207 essential lncRNAs from literatures for establishing a database on essential lncRNAs, which is named as dbEssLnc (Database of essential lncRNAs). The dbEssLnc database has a web-based user-friendly interface for the users to browse, to search, to visualize and to blast search records in the database. The dbEssLnc database is freely accessible at https://esslnc.pufengdu.org. All data and source codes for mirroring the dbEssLnc database have been deposited in GitHub (https://github.com/yyZhang14/dbEssLnc).

Revealing the novel complexity of plant long non-coding RNA by strand-specific and whole transcriptome sequencing for evolutionarily representative plant species

Background

Previous studies on plant long noncoding RNAs (lncRNAs) lacked consistency and suffered from many factors like heterogeneous data sources and experimental protocols, different plant tissues, inconsistent bioinformatics pipelines, etc. For example, the sequencing of RNAs with poly(A) tails excluded a large portion of lncRNAs without poly(A), and use of regular RNA-sequencing technique did not distinguish transcripts’ direction for lncRNAs. The current study was designed to systematically discover and analyze lncRNAs across eight evolutionarily representative plant species, using strand-specific (directional) and whole transcriptome sequencing (RiboMinus) technique.

Results

A total of 39,945 lncRNAs (25,350 lincRNAs and 14,595 lncNATs) were identified, which showed molecular features of lncRNAs that are consistent across divergent plant species but different from those of mRNA. Further, transposable elements (TEs) were found to play key roles in the origination of lncRNA, as significantly large number of lncRNAs were found to contain TEs in gene body and promoter region, and transcription of many lncRNAs was driven by TE promoters. The lncRNA sequences were divergent even in closely related species, and most plant lncRNAs were genus/species-specific, amid rapid turnover in evolution. Evaluated with PhastCons scores, plant lncRNAs showed similar conservation level to that of intergenic sequences, suggesting that most lincRNAs were young and with short evolutionary age. INDUCED BY PHOSPHATE STARVATION (IPS) was found so far to be the only plant lncRNA group with conserved motifs, which may play important roles in the adaptation of terrestrial life during migration from aquatic to terrestrial. Most highly and specially expressed lncRNAs formed co-expression network with coding genes, and their functions were believed to be closely related to their co-expression genes.

Conclusion

The study revealed novel features and complexity of lncRNAs in plants through systematic analysis, providing important insights into the origination and evolution of plant lncRNAs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08602-9.

Long Non-Coding RNAs in Cardiac Hypertrophy

Heart disease represents one of the main challenges in modern medicine with insufficient treatment options. Whole genome sequencing allowed for the discovery of several classes of non-coding RNA (ncRNA) and widened our understanding of disease regulatory circuits. The intrinsic ability of long ncRNAs (lncRNAs) and circular RNAs (circRNAs) to regulate gene expression by a plethora of mechanisms make them candidates for conceptually new treatment options. However, important questions remain to be addressed before we can fully exploit the therapeutic potential of these molecules. Increasing our knowledge of their mechanisms of action and refining the approaches for modulating lncRNAs expression are just a few of the challenges we face. The accurate identification of novel lncRNAs is hampered by their relatively poor cross-species sequence conservation and their low and context-dependent expression pattern. Nevertheless, progress has been made in their annotation in recent years, while a few experimental studies have confirmed the value of lncRNAs as new mechanisms in the development of cardiac hypertrophy and other cardiovascular diseases. Here, we explore cardiac lncRNA biology and the evidence that this class of molecules has therapeutic benefit to treat cardiac hypertrophy.

DeepMNE: Deep Multi-network Embedding for lncRNA-Disease Association prediction

Long non-coding RNA (lncRNA) participates in various biological processes, hence its mutations and disorders play an important role in the pathogenesis of multiple human diseases. Identifying disease-related lncRNAs is crucial for the diagnosis, prevention, and treatment of diseases. Although a large number of computational approaches have been developed, effectively integrating multi-omics data and accurately predicting potential lncRNA-disease associations remains a challenge, especially regarding new lncRNAs and new diseases. In this work, we propose a new method with deep multi-network embedding, called DeepMNE, to discover potential lncRNA disease associations, especially for novel diseases and lncRNAs. DeepMNE extracts multi-omics data to describe diseases and lncRNAs, and proposes a network fusion method based on deep learning to integrate multi-source information. Moreover, DeepMNE complements the sparse association network and uses kernel neighborhood similarity to construct disease similarity and lncRNA similarity networks. Furthermore, A graph embedding method is adopted to predict potential associations. Experimental results demonstrate that compared to other state-of-the-art methods, DeepMNE has a higher predictive performance on new associations, new lncRNAs and new diseases. Besides, DeepMNE also elicits a considerable predictive performance on perturbed datasets. Additionally, the results of two different types of case studies indicate that DeepMNE can be used as an effective tool for disease-related lncRNA prediction. The code of DeepMNE is freely available at https://github.com/Mayingjun20179/ DeepMNE.

Exploring clinical implications and role of non-coding RNAs in lung carcinogenesis

Lung cancer is the utmost familiar category of cancer with greatest fatality rate worldwide and several regulatory mechanisms exercise cellular control on critical oncogenic trails implicated in lung associated carcinogenesis. The non-coding RNAs (ncRNAs) are shown to play a variety of regulatory roles, including stimulating cell proliferation, inhibiting programmed cell death, enhancing cancer cell metastatic ability and acquiring resistance to drugs. Furthermore, ncRNAs exhibit tissue-specific expression as well as great stability in bodily fluids. As a consequence, they are strong contenders for cancer based theragnostics. microRNA (miRNA) alters gene expression primarily by either degrading or interfering with the translation of targeted mRNA and long non-coding RNAs (lncRNAs) can influence gene expression by targeting transcriptional activators or repressors, RNA polymers and even DNA-duplex. lncRNAs are typically found to be dysregulated in lung cancer and hence targeting ncRNAs could be a viable strategy for developing potential therapies as well as for overcoming chemoresistance in lung cancer. The purpose of this review is to elucidate the role of ncRNAs, revisiting the recent studies in lung cancer.

Bioinformatics Analysis of Long Non-coding RNA and Related Diseases: An Overview

Long non-coding RNAs (lncRNAs) are usually located in the nucleus and cytoplasm of cells. The transcripts of lncRNAs are >200 nucleotides in length and do not encode proteins. Compared with small RNAs, lncRNAs have longer sequences, more complex spatial structures, and more diverse and complex mechanisms involved in the regulation of gene expression. LncRNAs are widely involved in the biological processes of cells, and in the occurrence and development of many human diseases. Many studies have shown that lncRNAs can induce the occurrence of diseases, and some lncRNAs undergo specific changes in tumor cells. Research into the roles of lncRNAs has covered the diagnosis of, for example, cardiovascular, cerebrovascular, and central nervous system diseases. The bioinformatics of lncRNAs has gradually become a research hotspot and has led to the discovery of a large number of lncRNAs and associated biological functions, and lncRNA databases and recognition models have been developed. In this review, the research progress of lncRNAs is discussed, and lncRNA-related databases and the mechanisms and modes of action of lncRNAs are described. In addition, disease-related lncRNA methods and the relationships between lncRNAs and human lung adenocarcinoma, rectal cancer, colon cancer, heart disease, and diabetes are discussed. Finally, the significance and existing problems of lncRNA research are considered.