Functional annotation of human long noncoding RNAs via molecular phenotyping

Big data and deep learning for RNA biology

The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively.

Long Non-Coding RNAs in Sjögren's Disease

Sjögren's disease (SjD) is a heterogeneous autoimmune disease characterized by severe dryness of mucosal surfaces, particularly the mouth and eyes; fatigue; and chronic pain. Chronic inflammation of the salivary and lacrimal glands, auto-antibody formation, and extra-glandular manifestations occur in subsets of patients with SjD. An aberrant expression of long, non-coding RNAs (lncRNAs) has been described in many autoimmune diseases, including SjD. Here, we review the current literature on lncRNAs in SjD and their role in regulating X chromosome inactivation, immune modulatory functions, and their potential as biomarkers.

Annotation of nuclear lncRNAs based on chromatin interactions

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

Functional identification of cis-regulatory long noncoding RNAs at controlled false discovery rates

A key attribute of some long noncoding RNAs (lncRNAs) is their ability to regulate expression of neighbouring genes in cis. However, such 'cis-lncRNAs' are presently defined using ad hoc criteria that, we show, are prone to false-positive predictions. The resulting lack of cis-lncRNA catalogues hinders our understanding of their extent, characteristics and mechanisms. Here, we introduce TransCistor, a framework for defining and identifying cis-lncRNAs based on enrichment of targets amongst proximal genes. TransCistor's simple and conservative statistical models are compatible with functionally defined target gene maps generated by existing and future technologies. Using transcriptome-wide perturbation experiments for 268 human and 134 mouse lncRNAs, we provide the first large-scale survey of cis-lncRNAs. Known cis-lncRNAs are correctly identified, including XIST, LINC00240 and UMLILO, and predictions are consistent across analysis methods, perturbation types and independent experiments. We detect cis-activity in a minority of lncRNAs, primarily involving activators over repressors. Cis-lncRNAs are detected by both RNA interference and antisense oligonucleotide perturbations. Mechanistically, cis-lncRNA transcripts are observed to physically associate with their target genes and are weakly enriched with enhancer elements. In summary, TransCistor establishes a quantitative foundation for cis-lncRNAs, opening a path to elucidating their molecular mechanisms and biological significance.

Machine learning-based morphological quantification of replicative senescence in human fibroblasts

Although aging has been investigated extensively at the organismal and cellular level, the morphological changes that individual cells undergo along their replicative lifespan have not been precisely quantified. Here, we present the results of a readily accessible machine learning-based pipeline that uses standard fluorescence microscope and open access software to quantify the minute morphological changes that human fibroblasts undergo during their replicative lifespan in culture. Applying this pipeline in a widely used fibroblast cell line (IMR-90), we find that advanced replicative age robustly increases (+28-79%) cell surface area, perimeter, number and total length of pseudopodia, and nuclear surface area, while decreasing cell circularity, with phenotypic changes largely occurring as replicative senescence is reached. These senescence-related morphological changes are recapitulated, albeit to a variable extent, in primary dermal fibroblasts derived from human donors of different ancestry, age, and sex groups. By performing integrative analysis of single-cell morphology, our pipeline further classifies senescent-like cells and quantifies how their numbers increase with replicative senescence in IMR-90 cells and in dermal fibroblasts across all tested donors. These findings provide quantitative insights into replicative senescence, while demonstrating applicability of a readily accessible computational pipeline for high-throughput cell phenotyping in aging research.

Are non-protein coding RNAs junk or treasure?: An attempt to explain and reconcile opposing viewpoints of whether the human genome is mostly transcribed into non-functional or functional RNAs

The human genome project's lasting legacies are the emerging insights into human physiology and disease, and the ascendance of biology as the dominant science of the 21st century. Sequencing revealed that >90% of the human genome is not coding for proteins, as originally thought, but rather is overwhelmingly transcribed into non-protein coding, or non-coding, RNAs (ncRNAs). This discovery initially led to the hypothesis that most genomic DNA is "junk", a term still championed by some geneticists and evolutionary biologists. In contrast, molecular biologists and biochemists studying the vast number of transcripts produced from most of this genome "junk" often surmise that these ncRNAs have biological significance. What gives? This essay contrasts the two opposing, extant viewpoints, aiming to explain their bases, which arise from distinct reference frames of the underlying scientific disciplines. Finally, it aims to reconcile these divergent mindsets in hopes of stimulating synergy between scientific fields.

Tracing vitamins on the long non-coding lane of the transcriptome: vitamin regulation of LncRNAs

A major revelation of genome-scale biological studies in the post-genomic era has been that two-thirds of human genes do not encode proteins. The majority of non-coding RNA transcripts in humans are long non-coding RNA (lncRNA) molecules, non-protein-coding regulatory transcripts with sizes greater than 500 nucleotides. LncRNAs are involved in nearly every aspect of cellular physiology, playing fundamental regulatory roles both in normal cells and in disease. As result, they are functionally linked to multiple human diseases, from cancer to autoimmune, inflammatory, and neurological disorders. Numerous human conditions and diseases stem from gene-environment interactions; in this regard, a wealth of reports demonstrate that the intake of specific and essential nutrients, including vitamins, shapes our transcriptome, with corresponding impacts on health. Vitamins command a vast array of biological activities, acting as coenzymes, antioxidants, hormones, and regulating cellular proliferation and coagulation. Emerging evidence suggests that vitamins and lncRNAs are interconnected through several regulatory axes. This type of interaction is expected, since lncRNA has been implicated in sensing the environment in eukaryotes, conceptually similar to riboswitches and other RNAs that act as molecular sensors in prokaryotes. In this review, we summarize the peer-reviewed literature to date that has reported specific functional linkages between vitamins and lncRNAs, with an emphasis on mammalian models and humans, while providing a brief overview of the source, metabolism, and function of the vitamins most frequently investigated within the context of lncRNA molecular mechanisms, and discussing the published research findings that document specific connections between vitamins and lncRNAs.

LncRNA LUESCC promotes esophageal squamous cell carcinoma by targeting the miR-6785-5p/NRSN2 axis

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent gastrointestinal malignancies with high mortality worldwide. Emerging evidence indicates that long noncoding RNAs (lncRNAs) are involved in human cancers, including ESCC. However, the detailed mechanisms of lncRNAs in the regulation of ESCC progression remain incompletely understood. LUESCC was upregulated in ESCC tissues compared with adjacent normal tissues, which was associated with gender, deep invasion, lymph node metastasis, and poor prognosis of ESCC patients. LUESCC was mainly localized in the cytoplasm of ESCC cells. Knockdown of LUESCC inhibited cell proliferation, colony formation, migration, and invasion in vitro and suppressed tumor growth in vivo. Mechanistic investigation indicated that LUESCC functions as a ceRNA by sponging miR-6785-5p to enhance NRSN2 expression, which is critical for the malignant behaviors of ESCC. Furthermore, ASO targeting LUESCC substantially suppressed ESCC both in vitro and in vivo. Collectively, these data demonstrate that LUESCC may exerts its oncogenic role by sponging miR-6785-5p to promote NRSN2 expression in ESCC, providing a potential diagnostic marker and therapeutic target for ESCC patients.

Targeting and engineering long non-coding RNAs for cancer therapy

RNA therapeutics (RNATx) aim to treat diseases, including cancer, by targeting or employing RNA molecules for therapeutic purposes. Amongst the most promising targets are long non-coding RNAs (lncRNAs), which regulate oncogenic molecular networks in a cell type-restricted manner. lncRNAs are distinct from protein-coding genes in important ways that increase their therapeutic potential yet also present hurdles to conventional clinical development. Advances in genome editing, oligonucleotide chemistry, multi-omics and RNA engineering are paving the way for efficient and cost-effective lncRNA-focused drug discovery pipelines. In this Review, we present the emerging field of lncRNA therapeutics for oncology, with emphasis on the unique strengths and challenges of lncRNAs within the broader RNATx framework. We outline the necessary steps for lncRNA therapeutics to deliver effective, durable, tolerable and personalized treatments for cancer.

Integration of transcription regulation and functional genomic data reveals lncRNA SNHG6's role in hematopoietic differentiation and leukemia

BACKGROUND

Long non-coding RNAs (lncRNAs) are pivotal players in cellular processes, and their unique cell-type specific expression patterns render them attractive biomarkers and therapeutic targets. Yet, the functional roles of most lncRNAs remain enigmatic. To address the need to identify new druggable lncRNAs, we developed a comprehensive approach integrating transcription factor binding data with other genetic features to generate a machine learning model, which we have called INFLAMeR (Identifying Novel Functional LncRNAs with Advanced Machine Learning Resources).

METHODS

INFLAMeR was trained on high-throughput CRISPR interference (CRISPRi) screens across seven cell lines, and the algorithm was based on 71 genetic features. To validate the predictions, we selected candidate lncRNAs in the human K562 leukemia cell line and determined the impact of their knockdown (KD) on cell proliferation and chemotherapeutic drug response. We further performed transcriptomic analysis for candidate genes. Based on these findings, we assessed the lncRNA small nucleolar RNA host gene 6 (SNHG6) for its role in myeloid differentiation. Finally, we established a mouse K562 leukemia xenograft model to determine whether SNHG6 KD attenuates tumor growth in vivo.

RESULTS

The INFLAMeR model successfully reconstituted CRISPRi screening data and predicted functional lncRNAs that were previously overlooked. Intensive cell-based and transcriptomic validation of nearly fifty genes in K562 revealed cell type-specific functionality for 85% of the predicted lncRNAs. In this respect, our cell-based and transcriptomic analyses predicted a role for SNHG6 in hematopoiesis and leukemia. Consistent with its predicted role in hematopoietic differentiation, SNHG6 transcription is regulated by hematopoiesis-associated transcription factors. SNHG6 KD reduced the proliferation of leukemia cells and sensitized them to differentiation. Treatment of K562 leukemic cells with hemin and PMA, respectively, demonstrated that SNHG6 inhibits red blood cell differentiation but strongly promotes megakaryocyte differentiation. Using a xenograft mouse model, we demonstrate that SNHG6 KD attenuated tumor growth in vivo.

CONCLUSIONS

Our approach not only improved the identification and characterization of functional lncRNAs through genomic approaches in a cell type-specific manner, but also identified new lncRNAs with roles in hematopoiesis and leukemia. Such approaches can be readily applied to identify novel targets for precision medicine.

Conceptual breakthroughs of the long noncoding RNA functional system and its endogenous regulatory role in the cancerous regime

Long noncoding RNAs (lncRNAs) derived from noncoding regions in the human genome were once regarded as junks with no biological significance, but recent studies have shown that these molecules are highly functional, prompting an explosion of studies on their biology. However, these recent efforts have only begun to recognize the biological significance of a small fraction (< 1%) of the lncRNAs. The basic concept of these lncRNA functions remains controversial. This controversy arises primarily from conventional biased observations based on limited datasets. Fortunately, emerging big data provides a promising path to circumvent conventional bias to understand an unbiased big picture of lncRNA biology and advance the fundamental principles of lncRNA biology. This review focuses on big data studies that break through the critical concepts of the lncRNA functional system and its endogenous regulatory roles in all cancers. lncRNAs have unique functional systems distinct from proteins, such as transcriptional initiation and regulation, and they abundantly interact with mitochondria and consume less energy. lncRNAs, rather than proteins as traditionally thought, function as the most critical endogenous regulators of all cancers. lncRNAs regulate the cancer regulatory regime by governing the endogenous regulatory network of all cancers. This is accomplished by dominating the regulatory network module and serving as a key hub and top inducer. These critical conceptual breakthroughs lay a blueprint for a comprehensive functional picture of the human genome. They also lay a blueprint for combating human diseases that are regulated by lncRNAs.

An emerging link between lncRNAs and cancer sex dimorphism

The prevalence and progression of cancer differ in males and females, and thus, sexual dimorphism in tumor development directly impacts clinical research and medicine. Long non-coding RNAs (lncRNAs) are increasingly recognized as important players in gene expression and various cellular processes, including cancer development and progression. In recent years, lncRNAs have been implicated in the differences observed in cancer incidence, progression, and treatment responses between men and women. Here, we present a brief overview of the current knowledge regarding the role of lncRNAs in cancer sex dimorphism, focusing on how they affect epigenetic processes in male and female mammalian cells. We discuss the potential mechanisms by which lncRNAs may contribute to sex differences in cancer, including transcriptional control of sex chromosomes, hormonal signaling pathways, and immune responses. We also propose strategies for studying lncRNA functions in cancer sex dimorphism. Furthermore, we emphasize the importance of considering sex as a biological variable in cancer research and the need to investigate the role lncRNAs play in mediating these sex differences. In summary, we highlight the emerging link between lncRNAs and cancer sex dimorphism and their potential as therapeutic targets.

Using long-read CAGE sequencing to profile cryptic-promoter-derived transcripts and their contribution to the immunopeptidome

Recent studies have shown that the noncoding genome can produce unannotated proteins as antigens that induce immune response. One major source of this activity is the aberrant epigenetic reactivation of transposable elements (TEs). In tumors, TEs often provide cryptic or alternate promoters, which can generate transcripts that encode tumor-specific unannotated proteins. Thus, TE-derived transcripts (TE transcripts) have the potential to produce tumor-specific, but recurrent, antigens shared among many tumors. Identification of TE-derived tumor antigens holds the promise to improve cancer immunotherapy approaches; however, current genomics and computational tools are not optimized for their detection. Here we combined CAGE technology with full-length long-read transcriptome sequencing (long-read CAGE, or LRCAGE) and developed a suite of computational tools to significantly improve immunopeptidome detection by incorporating TE and other tumor transcripts into the proteome database. By applying our methods to human lung cancer cell line H1299 data, we show that long-read technology significantly improves mapping of promoters with low mappability scores and that LRCAGE guarantees accurate construction of uncharacterized 5' transcript structure. Augmenting a reference proteome database with newly characterized transcripts enabled us to detect noncanonical antigens from HLA-pulldown LC-MS/MS data. Lastly, we show that epigenetic treatment increased the number of noncanonical antigens, particularly those encoded by TE transcripts, which might expand the pool of targetable antigens for cancers with low mutational burden.

Evidence for widespread existence of functional novel and non-canonical human transcripts

BACKGROUND

Fraction of functional sequence in the human genome remains a key unresolved question in Biology and the subject of vigorous debate. While a plethora of studies have connected a significant fraction of human DNA to various biochemical processes, the classical definition of function requires evidence of effects on cellular or organismal fitness that such studies do not provide. Although multiple high-throughput reverse genetics screens have been developed to address this issue, they are limited to annotated genomic elements and suffer from non-specific effects, arguing for a strong need to develop additional functional genomics approaches.

RESULTS

In this work, we established a high-throughput lentivirus-based insertional mutagenesis strategy as a forward genetics screen tool in aneuploid cells. Application of this approach to human cell lines in multiple phenotypic screens suggested the presence of many yet uncharacterized functional elements in the human genome, represented at least in part by novel exons of known and novel genes. The novel transcripts containing these exons can be massively, up to thousands-fold, induced by specific stresses, and at least some can represent bi-cistronic protein-coding mRNAs.

CONCLUSIONS

Altogether, these results argue that many unannotated and non-canonical human transcripts, including those that appear as aberrant splice products, have biological relevance under specific biological conditions.

The status of the human gene catalogue

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

ZENBU-Reports: a graphical web-portal builder for interactive visualization and dissemination of genome-scale data

In the genomic era, data dissemination and visualization is an integral part of scientific publications and research projects involving international consortia producing massive genome-wide data sets, intra-organizational collaborations, or individual labs. However, creating custom supporting websites is oftentimes impractical due to the required programming effort, web server infrastructure, and data storage facilities, as well as the long-term maintenance burden. ZENBU-Reports (https://fantom.gsc.riken.jp/zenbu/reports) is a web application to create interactive scientific web portals by using graphical interfaces while providing storage and secured collaborative sharing for data uploaded by users. ZENBU-Reports provides the scientific visualization elements commonly used in supplementary websites, publications and presentations, presenting a complete solution for the interactive display and dissemination of data and analysis results during the full lifespan of a scientific project both during the active research phase and after publication of the results.

Involvement of lncRNAs in cancer cells migration, invasion and metastasis: cytoskeleton and ECM crosstalk

Cancer is the main cause of death worldwide and metastasis is a major cause of poor prognosis and cancer-associated mortality. Metastatic conversion of cancer cells is a multiplex process, including EMT through cytoskeleton remodeling and interaction with TME. Tens of thousands of putative lncRNAs have been identified, but the biological functions of most are still to be identified. However, lncRNAs have already emerged as key regulators of gene expression at transcriptional and post-transcriptional level to control gene expression in a spatio-temporal fashion. LncRNA-dependent mechanisms can control cell fates during development and their perturbed expression is associated with the onset and progression of many diseases including cancer. LncRNAs have been involved in each step of cancer cells metastasis through different modes of action. The investigation of lncRNAs different roles in cancer metastasis could possibly lead to the identification of new biomarkers and innovative cancer therapeutic options.

Long non-coding RNAs: definitions, functions, challenges and recommendations

Genes specifying long non-coding RNAs (lncRNAs) occupy a large fraction of the genomes of complex organisms. The term 'lncRNAs' encompasses RNA polymerase I (Pol I), Pol II and Pol III transcribed RNAs, and RNAs from processed introns. The various functions of lncRNAs and their many isoforms and interleaved relationships with other genes make lncRNA classification and annotation difficult. Most lncRNAs evolve more rapidly than protein-coding sequences, are cell type specific and regulate many aspects of cell differentiation and development and other physiological processes. Many lncRNAs associate with chromatin-modifying complexes, are transcribed from enhancers and nucleate phase separation of nuclear condensates and domains, indicating an intimate link between lncRNA expression and the spatial control of gene expression during development. lncRNAs also have important roles in the cytoplasm and beyond, including in the regulation of translation, metabolism and signalling. lncRNAs often have a modular structure and are rich in repeats, which are increasingly being shown to be relevant to their function. In this Consensus Statement, we address the definition and nomenclature of lncRNAs and their conservation, expression, phenotypic visibility, structure and functions. We also discuss research challenges and provide recommendations to advance the understanding of the roles of lncRNAs in development, cell biology and disease.

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research.

An open access, machine learning pipeline for high-throughput quantification of cell morphology

Cell morphology is influenced by many factors and can be used as a phenotypic marker. Here we describe a machine-learning-based protocol for high-throughput morphological measurement of human fibroblasts using a standard fluorescence microscope and the pre-existing, open access software ilastik for cell body identification, ImageJ/Fiji for image overlay, and CellProfiler for morphological quantification. Because this protocol overlays nuclei with their cell bodies and relies on coloration differences, it can be broadly applied to other cell types beyond fibroblasts. For details on the use and execution of this protocol, please also refer to Leung et al. (2022).1.

lncHUB2: aggregated and inferred knowledge about human and mouse lncRNAs

Long non-coding ribonucleic acids (lncRNAs) account for the largest group of non-coding RNAs. However, knowledge about their function and regulation is limited. lncHUB2 is a web server database that provides known and inferred knowledge about the function of 18 705 human and 11 274 mouse lncRNAs. lncHUB2 produces reports that contain the secondary structure fold of the lncRNA, related publications, the most correlated coding genes, the most correlated lncRNAs, a network that visualizes the most correlated genes, predicted mouse phenotypes, predicted membership in biological processes and pathways, predicted upstream transcription factor regulators, and predicted disease associations. In addition, the reports include subcellular localization information; expression across tissues, cell types, and cell lines, and predicted small molecules and CRISPR knockout (CRISPR-KO) genes prioritized based on their likelihood to up- or downregulate the expression of the lncRNA. Overall, lncHUB2 is a database with rich information about human and mouse lncRNAs and as such it can facilitate hypothesis generation for many future studies. The lncHUB2 database is available at https://maayanlab.cloud/lncHUB2. Database URL: https://maayanlab.cloud/lncHUB2.

RNA out of the mist

RNA has long been regarded primarily as the intermediate between genes and proteins. It was a surprise then to discover that eukaryotic genes are mosaics of mRNA sequences interrupted by large tracts of transcribed but untranslated sequences, and that multicellular organisms also express many long 'intergenic' and antisense noncoding RNAs (lncRNAs). The identification of small RNAs that regulate mRNA translation and half-life did not disturb the prevailing view that animals and plant genomes are full of evolutionary debris and that their development is mainly supervised by transcription factors. Gathering evidence to the contrary involved addressing the low conservation, expression, and genetic visibility of lncRNAs, demonstrating their cell-specific roles in cell and developmental biology, and their association with chromatin-modifying complexes and phase-separated domains. The emerging picture is that most lncRNAs are the products of genetic loci termed 'enhancers', which marshal generic effector proteins to their sites of action to control cell fate decisions during development.

Bioinformatics analysis of markers based on m6 A related to prognosis combined with immune invasion of renal clear cell carcinoma

The incidence rate of renal cell carcinoma (RCC) is about 3% of all adult cancers. Of these, the Kidney clear cell renal cell carcinoma (KIRC) is the most common type, accounting for about 70%-75% of RCC. KIRC is difficult to be detected in time clinically. KIRC still has no effective treatment at this stage. We combined high-throughput bioinformatics analysis to obtained the structural sequence transcriptome data, relevant clinical information, and m⁶ A gene map of KIRC patients from genomics TCGA database. Pearson's correlation analysis was used to explore m⁶ A related gene long noncoding RNAs (lncRNAs), and then univariate Cox regression analysis was performed to screen the prognostic role of KIRC patients. Lasso-Cox regression was performed to establish the lncRNAs risk model associated with m⁶ A.LINC02154 and AC016773.2, Z98200.2, AL161782.1, EMX2OS, AC021483.2, CD27-AS1, AC006213.3 were iidentif. Compared with the low-risk group, the overall survival of patients in the high-risk group was significantly worse. Analyzing whether there are differences in immune cells between high-risk and low-risk subgroups. There were CD4 memory resting, Monocytes, Macrophages M1, Dendritic cells activated, Mast cells resting, which had higher infiltrations in the low-risk group. We performed Go enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set enrichment analysis enrichment analysis. Overall, our results suggest that the component of m6A-related lncRNAs in the prognostic signal may be a key mediator in the immune microenvironment of KIRC, which represents a promising therapeutic effect.

Antisense-oligonucleotide-mediated perturbation of long non-coding RNA reveals functional features in stem cells and across cell types

Within the scope of the FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem cells (iPSCs) and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition. From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell-type enrichment analysis identifies lncRNAs associated with pluripotency, while the knockdown of LINC02595, CATG00000090305.1, and RP11-148B6.2 modulates colony formation of iPSCs. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit a consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights that molecular phenotyping is more comprehensive in revealing affected pathways.

Scalable Functional Assays for the Interpretation of Human Genetic Variation

Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

Epigenetic Mechanisms Underlying Melanoma Resistance to Immune and Targeted Therapies

Melanoma is an aggressive skin cancer reliant on early detection for high likelihood of successful treatment. Solar UV exposure transforms melanocytes into highly mutated tumor cells that metastasize to the liver, lungs, and brain. Even upon resection of the primary tumor, almost thirty percent of patients succumb to melanoma within twenty years. Identification of key melanoma genetic drivers led to the development of pharmacological BRAF^V600E and MEK inhibitors, significantly improving metastatic patient outcomes over traditional cytotoxic chemotherapy or pioneering IFN-α and IL-2 immune therapies. Checkpoint blockade inhibitors releasing the immunosuppressive effects of CTLA-4 or PD-1 proved to be even more effective and are the standard first-line treatment. Despite these major improvements, durable responses to immunotherapy and targeted therapy have been hindered by intrinsic or acquired resistance. In addition to gained or selected genetic alterations, cellular plasticity conferred by epigenetic reprogramming is emerging as a driver of therapy resistance. Epigenetic regulation of chromatin accessibility drives gene expression and establishes distinct transcriptional cell states. Here we review how aberrant chromatin, transcriptional, and epigenetic regulation contribute to therapy resistance and discuss how targeting these programs sensitizes melanoma cells to immune and targeted therapies.

Transcriptomic meta-analysis reveals unannotated long non-coding RNAs related to the immune response in sheep

Long non-coding RNAs (lncRNAs) are involved in several biological processes, including the immune system response to pathogens and vaccines. The annotation and functional characterization of lncRNAs is more advanced in humans than in livestock species. Here, we take advantage of the increasing number of high-throughput functional experiments deposited in public databases in order to uniformly analyse, profile unannotated lncRNAs and integrate 422 ovine RNA-seq samples from the ovine immune system. We identified 12302 unannotated lncRNA genes with support from independent CAGE-seq and histone modification ChIP-seq assays. Unannotated lncRNAs showed low expression levels and sequence conservation across other mammal species. There were differences in expression levels depending on the genomic location-based lncRNA classification. Differential expression analyses between unstimulated and samples stimulated with pathogen infection or vaccination resulted in hundreds of lncRNAs with changed expression. Gene co-expression analyses revealed immune gene-enriched clusters associated with immune system activation and related to interferon signalling, antiviral response or endoplasmic reticulum stress. Besides, differential co-expression networks were constructed in order to find condition-specific relationships between coding genes and lncRNAs. Overall, using a diverse set of immune system samples and bioinformatic approaches we identify several ovine lncRNAs associated with the response to an external stimulus. These findings help in the improvement of the ovine lncRNA catalogue and provide sheep-specific evidence for the implication in the general immune response for several lncRNAs.

The non-coding genome in early human development - Recent advancements

Not that long ago, the human genome was discovered to be mainly non-coding, that is comprised of DNA sequences that do not code for proteins. The initial paradigm that non-coding is also non-functional was soon overturned and today the work to uncover the functions of non-coding DNA and RNA in human early embryogenesis has commenced. Early human development is characterized by large-scale changes in genomic activity and the transcriptome that are partly driven by the coordinated activation and repression of repetitive DNA elements scattered across the genome. Here we provide examples of recent novel discoveries of non-coding DNA and RNA interactions and mechanisms that ensure accurate non-coding activity during human maternal-to-zygotic transition and lineage segregation. These include studies on small and long non-coding RNAs, transposable element regulation, and RNA tailing in human oocytes and early embryos. High-throughput approaches to dissect the non-coding regulatory networks governing early human development are a foundation for functional studies of specific genomic elements and molecules that has only begun and will provide a wider understanding of early human embryogenesis and causes of infertility.

Exploratory meta-analysis of hypoxic transcriptomes using a precise transcript reference sequence set

Gene expression studies are intrinsically biased, with many studies influenced by concomitant information such as gene-disease associations. This limitation can be overcome using a data-driven analysis approach without relying on ancillary information. The FANTOM CAGE-Associated Transcriptome project provides a comprehensive meta-assembly of the human transcriptome using coding and noncoding genes. Hypoxia strongly influences gene expression; in addition, noncoding RNA (ncRNA) metabolism is down-regulated in response to hypoxic stimuli. We evaluated the differential response of various transcripts to hypoxia by determining their hypoxia responsiveness scores. Enrichment analysis revealed that several genes associated with ncRNA metabolism, particularly those involved in ribosomal RNA processing, were down-regulated in response to hypoxia. Previously published information from the FANTOM CAGE-Associated Transcriptome project was suitable for meta-analysis of the transcriptome sequencing data from both coding and ncRNAs and to evaluate the hypoxia responsiveness of target transcripts and relationship between sense-antisense transcripts from the same locus. Our results may facilitate functional annotation of various transcripts including ncRNAs, allowing for both sense and antisense and coding and noncoding evaluations.

The HASTER lncRNA promoter is a cis-acting transcriptional stabilizer of HNF1A

The biological purpose of long non-coding RNAs (lncRNAs) is poorly understood. Haploinsufficient mutations in HNF1A homeobox A (HNF1A), encoding a homeodomain transcription factor, cause diabetes mellitus. Here, we examine HASTER, the promoter of an lncRNA antisense to HNF1A. Using mouse and human models, we show that HASTER maintains cell-specific physiological HNF1A concentrations through positive and negative feedback loops. Pancreatic β cells from Haster mutant mice consequently showed variegated HNF1A silencing or overexpression, resulting in hyperglycaemia. HASTER-dependent negative feedback was essential to prevent HNF1A binding to inappropriate genomic regions. We demonstrate that the HASTER promoter DNA, rather than the lncRNA, modulates HNF1A promoter-enhancer interactions in cis and thereby regulates HNF1A transcription. Our studies expose a cis-regulatory element that is unlike classic enhancers or silencers, it stabilizes the transcription of its target gene and ensures the fidelity of a cell-specific transcription factor program. They also show that disruption of a mammalian lncRNA promoter can cause diabetes mellitus.

Host-Directed Targeting of LincRNA-MIR99AHG Suppresses Intracellular Growth of Mycobacterium tuberculosis

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) kills 1.6 million people worldwide every year, and there is an urgent need for targeting host-pathogen interactions as a strategy to reduce mycobacterial resistance to current antimicrobials. Noncoding RNAs are emerging as important regulators of numerous biological processes and avenues for exploitation in host-directed therapeutics. Although long noncoding RNAs (lncRNAs) are abundantly expressed in immune cells, their functional role in gene regulation and bacterial infections remains understudied. In this study, we identify an immunoregulatory long intergenic noncoding RNA, lincRNA-MIR99AHG, which is upregulated in mouse and human macrophages upon IL-4/IL-13 stimulation and downregulated after clinical Mtb HN878 strain infection and in peripheral blood mononuclear cells from active TB patients. To evaluate the functional role of lincRNA-MIR99AHG, we used antisense locked nucleic acid (LNA) GapmeR-mediated antisense oligonucleotide (ASO) lncRNA knockdown experiments. Knockdown of lincRNA-MIR99AHG with ASOs significantly reduced intracellular Mtb growth in mouse and human macrophages and reduced pro-inflammatory cytokine production. In addition, in vivo treatment of mice with MIR99AHG ASOs reduced the mycobacterial burden in the lung and spleen. Furthermore, in macrophages, lincRNA-MIR99AHG is translocated to the nucleus and interacts with high affinity to hnRNPA2/B1 following IL-4/IL-13 stimulation and Mtb HN878 infection. Together, these findings identify lincRNA-MIR99AHG as a positive regulator of inflammation and macrophage polarization to promote Mtb growth and a possible target for adjunctive host-directed therapy against TB.

CCIVR facilitates comprehensive identification of cis-natural antisense transcripts with their structural characteristics and expression profiles

Cis-natural antisense transcripts (cis-NATs) are transcribed from the same genomic locus as their partner gene but from the opposite DNA strand and overlap with the partner gene transcript. Here, we developed a simple and convenient program termed CCIVR (comprehensive cis-NATs identifier via RNA-seq data) that comprehensively identifies all kinds of cis-NATs based on genome annotation with expression data obtained from RNA-seq. Using CCIVR with genome databases, we demonstrated total cis-NAT pairs from 11 model organisms. CCIVR analysis with RNA-seq data from parthenogenetic and androgenetic embryonic stem cells identified well-known imprinted cis-NAT pair, KCNQ1/KCNQ1OT1, ensuring the availability of CCIVR. Finally, CCIVR identified cis-NAT pairs that demonstrate inversely correlated expression upon TGFβ stimulation including cis-NATs that functionally repress their partner genes by introducing epigenetic alteration in the promoters of partner genes. Thus, CCIVR facilitates the investigation of structural characteristics and functions of cis-NATs in numerous processes in various species.

Chronic stress-driven glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts

Chronic environmental stress can profoundly impact cell and body function. Although the underlying mechanisms are poorly understood, epigenetics has emerged as a key link between environment and health. The genomic effects of stress are thought to be mediated by the action of glucocorticoid stress hormones, primarily cortisol in humans, which act via the glucocorticoid receptor (GR). To dissect how chronic stress-driven GR activation influences epigenetic and cell states, human fibroblasts underwent prolonged exposure to physiological stress levels of cortisol and/or a selective GR antagonist. Cortisol was found to drive robust changes in cell proliferation, migration, and morphology, which were abrogated by concomitant GR blockade. The GR-driven cell phenotypes were accompanied by widespread, yet genomic context-dependent, changes in DNA methylation and mRNA expression, including gene loci with known roles in cell proliferation and migration. These findings provide insights into how chronic stress-driven functional epigenomic patterns become established to shape key cell phenotypes.

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Physiological stress levels of cortisol drive robust changes in key cell phenotypes

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Stress-driven changes in cell phenotypes are abrogated by concomitant GR blockade

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GR activation induces functional and phenotypically relevant epigenomic changes

Deep sequencing of short capped RNAs reveals novel families of noncoding RNAs

In eukaryotes, capped RNAs include long transcripts such as messenger RNAs and long noncoding RNAs, as well as shorter transcripts such as spliceosomal RNAs, small nucleolar RNAs, and enhancer RNAs. Long capped transcripts can be profiled using cap analysis gene expression (CAGE) sequencing and other methods. Here, we describe a sequencing library preparation protocol for short capped RNAs, apply it to a differentiation time course of the human cell line THP-1, and systematically compare the landscape of short capped RNAs to that of long capped RNAs. Transcription initiation peaks associated with genes in the sense direction have a strong preference to produce either long or short capped RNAs, with one out of six peaks detected in the short capped RNA libraries only. Gene-associated short capped RNAs have highly specific 3' ends, typically overlapping splice sites. Enhancers also preferentially generate either short or long capped RNAs, with 10% of enhancers observed in the short capped RNA libraries only. Enhancers producing either short or long capped RNAs show enrichment for GWAS-associated disease SNPs. We conclude that deep sequencing of short capped RNAs reveals new families of noncoding RNAs and elucidates the diversity of transcripts generated at known and novel promoters and enhancers.

Lnc-EST12, which is negatively regulated by mycobacterial EST12, suppresses antimycobacterial innate immunity through its interaction with FUBP3

Long noncoding RNAs (lncRNAs) have been implicated in the pathogenesis of intracellular pathogens. However, the role and mechanism of the important lncRNAs in Mycobacterium tuberculosis (M.tb) infection remain largely unexplored. Recently, we found that a secreted M.tb Rv1579c (an early secreted target with a molecular weight of 12 kDa, named EST12) protein activates NLRP3-gasdermin D (GSDMD)-mediated pyroptosis and plays a pivotal role in M.tb-induced immunity. In the present study, M.tb and the EST12 protein negatively regulated the expression of a key lncRNA (named lnc-EST12) in mouse macrophages by activating the JAK2-STAT5a signaling pathway. Lnc-EST12, with a size of 1583 bp, is mainly expressed in immune-related organs (liver, lung and spleen). Lnc-EST12 not only reduces the expression of the proinflammatory cytokines IL-1β, IL-6, and CCL5/8 but also suppresses the NLRP3 inflammasome and GSDMD pyroptosis-IL-1β immune pathway through its interaction with the transcription factor far upstream element-binding protein 3 (FUBP3). The KH3 and KH4 domains of FUBP3 are the critical sites for binding to lnc-EST12. Deficiency of mouse lnc-EST12 or FUBP3 in macrophages increased M.tb clearance and inflammation in mouse macrophages or mice. In conclusion, we report a new immunoregulatory mechanism in which mouse lnc-EST12 negatively regulates anti-M.tb innate immunity through FUBP3.

Construction and validation of a cuproptosis-related lncRNA signature as a novel and robust prognostic model for colon adenocarcinoma

Background

Cuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. Long non-coding RNAs (lncRNAs) are reported to be associated with tumor progression and prognosis in colon adenocarcinoma (COAD). However, the role and prognostic value of cuproptosis-related lncRNAs in COAD remains unknown. This study is devoted to constructing and validating a cuproptosis-related lncRNA signature that can predict COAD patient outcomes using bioinformatics methods.

Methods

The COAD mRNA and lncRNA expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and 2,567 cuproptosis-related lncRNAs were obtained. A 10 cuproptosis-related-lncRNA prognostic signature was then constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression model and patients were divided into high- and low-risk groups. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve, and a nomogram were employed to evaluate the predictive power of the signature. The immune characteristics and drug sensitivity were also investigated based on the signature. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to verify the risk model. In vitro experiments were conducted to validate the expression of the ten lncRNAs during cuproptosis.

Results

The high-risk group was associated with shorter overall survival (OS) time in COAD patients (p&lt;0.001). Multivariate Cox regression indicated that a high-risk score was an independent risk factor for poor prognosis (p&lt;0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 3 years: 0.879). Gene Ontology (GO) enrichment analysis revealed that the signature was highly correlated with the immune response in biological processes. The immune function, the score of the immune cells, and the expression of immune checkpoints were significantly different between the two risk groups. Three drugs, LAQ824, FH535, YM155, were found to be more sensitive in the high-risk group. Finally, the expression levels of the ten lncRNAs comprising the signature were tested by qRT-PCR.

Conclusion

A ten-cuproptosis-related lncRNA signature was constructed that provided promising insights into personalized prognosis and drug selection among COAD patients.

Identification of Ferroptosis-Associated Long Noncoding RNA Prognostic Model and Tumor Immune Microenvironment in Thyroid Cancer

Background

Thyroid cancer (TC) is a rapidly increasing incidence of endocrine malignancies, occupying 3% of new cancer incidence, of which 10% has a heterogeneous prognosis. Ferroptosis is a form of cell death distinct from apoptosis, which involves antitumor drug-related research. Long noncoding RNAs (lncRNAs) could affect cancer prognosis by regulating the ferroptosis; thus, ferroptosis-associated lncRNAs are emerging as prospective biomarkers for cancer therapy and prognosis. However, the prognostic factors of ferroptosis-associated lncRNAs in this solid tumor and their mechanisms remain unknown.

Methods

The TC lncRNA data were extracted from RNA sequencing files of The Cancer Genome Atlas (TCGA). Then, we performed a two-cluster analysis and grouped 502 patients with TC in a 7 : 3 ratio. Both the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis were conducted to create and validate the ferroptosis-associated lncRNA prognostic model (Ferr-LPM). Based on the median Ferr-LPM-based risk score (LPM_score) of the training cohort, we categorized patients into high and low LPM_score groups, which were then subjected to prognostic correlation and difference analysis. We also created a nomogram and assessed its predictive ability. Furthermore, immune-related mechanisms were investigated by analyzing the tumor immune microenvironment (TIME) and applying algorithms such as CIBERSROT.

Results

We built a highly accurate nomogram to promote the clinical applicability of Ferr-LPM. The area under the receiver operating characteristic curve (AUC-ROC) reached above 0.9. Survival analysis suggested that when the Ferr-LPM score was higher, the overall survival (OS) of patients within this group was shorter. Meanwhile, we found a strong association between Ferr-LPM and TIME. Interestingly, the LPM_score was inversely proportional to the tumor purity but positively related to immune checkpoint blockade (ICB) response.

Conclusion

We constructed a novel ferroptosis-associated lncRNA nomogram that could highly predict the prognosis of TC patients. Ferroptosis-associated lncRNAs might possess potential functions in regulating TIME, and lncRNAs provide TC patients with new prognostic biomarkers and therapeutic targets.

EWAS of post-COVID-19 patients shows methylation differences in the immune-response associated gene, IFI44L, three months after COVID-19 infection

Although substantial progress has been made in managing COVID-19, it is still difficult to predict a patient’s prognosis. We explored the epigenetic signatures of COVID-19 in peripheral blood using data from an ongoing prospective observational study of COVID-19 called the Norwegian Corona Cohort Study. A series of EWASs were performed to compare the DNA methylation profiles between COVID-19 cases and controls three months post-infection. We also investigated differences associated with severity and long-COVID. Three CpGs—cg22399236, cg03607951, and cg09829636—were significantly hypomethylated (FDR < 0.05) in COVID-19 positive individuals. cg03607951 is located in IFI44L which is involved in innate response to viral infection and several systemic autoimmune diseases. cg09829636 is located in ANKRD9, a gene implicated in a wide variety of cellular processes, including the degradation of IMPDH2. The link between ANKRD9 and IMPDH2 is striking given that IMPDHs are considered therapeutic targets for COVID-19. Furthermore, gene ontology analyses revealed pathways involved in response to viruses. The lack of significant differences associated with severity and long-COVID may be real or reflect limitations in sample size. Our findings support the involvement of interferon responsive genes in the pathophysiology of COVID-19 and indicate a possible link to systemic autoimmune diseases.

Oxidative Stress-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Responses in Patients With LUAD

Lung adenocarcinoma is increasingly harmful to society and individuals as cancer with an inferior prognosis and insensitive to chemotherapy. Previous studies have demonstrated that oxidative stress and lncRNAs play a vital role in many biological processes. Therefore, we explored the role of lncRNAs associated with oxidative stress in the prognosis and survival of LUAD patients. We examined the expression profiles of lncRNAs and oxidative stress genes in this study. A prognosis prediction model and a nomogram were built based on oxidative stress-related lncRNAs. Functional and drug sensitivity analyses were also performed depending on oxidative stress-related lncRNA signature. Moreover, we investigated the relationship between immune response and immunotherapy. The results showed that a risk scoring model based on 16 critical oxidative stress lncRNAs was able to distinguish the clinical status of LUAD and better predict the prognosis and survival. Additionally, the model demonstrated a close correlation with the tumor immune system, and these key lncRNAs also revealed the relationship between LUAD and chemotherapeutic drug sensitivity. Our work aims to provide new perspectives and new ideas for the treatment and management of LUAD.

Designing libraries for pooled CRISPR functional screens of long noncoding RNAs

Human and other genomes encode tens of thousands of long noncoding RNAs (lncRNAs), the vast majority of which remain uncharacterised. High-throughput functional screening methods, notably those based on pooled CRISPR-Cas perturbations, promise to unlock the biological significance and biomedical potential of lncRNAs. Such screens are based on libraries of single guide RNAs (sgRNAs) whose design is critical for success. Few off-the-shelf libraries are presently available, and lncRNAs tend to have cell-type-specific expression profiles, meaning that library design remains in the hands of researchers. Here we introduce the topic of pooled CRISPR screens for lncRNAs and guide readers through the three key steps of library design: accurate annotation of transcript structures, curation of optimal candidate sets, and design of sgRNAs. This review is a starting point and reference for researchers seeking to design custom CRISPR screening libraries for lncRNAs.

New Insights into the Roles of lncRNAs as Modulators of Cytoskeleton Architecture and Their Implications in Cellular Homeostasis and in Tumorigenesis

The importance of the cytoskeleton not only in cell architecture but also as a pivotal element in the transduction of signals that mediate multiple biological processes has recently been highlighted. Broadly, the cytoskeleton consists of three types of structural proteins: (1) actin filaments, involved in establishing and maintaining cell shape and movement; (2) microtubules, necessary to support the different organelles and distribution of chromosomes during cell cycle; and (3) intermediate filaments, which have a mainly structural function showing specificity for the cell type where they are expressed. Interaction between these protein structures is essential for the cytoskeletal mesh to be functional. Furthermore, the cytoskeleton is subject to intense spatio-temporal regulation mediated by the assembly and disassembly of its components. Loss of cytoskeleton homeostasis and integrity of cell focal adhesion are hallmarks of several cancer types. Recently, many reports have pointed out that lncRNAs could be critical mediators in cellular homeostasis controlling dynamic structure and stability of the network formed by cytoskeletal structures, specifically in different types of carcinomas. In this review, we summarize current information available about the roles of lncRNAs as modulators of actin dependent cytoskeleton and their impact on cancer pathogenesis. Finally, we explore other examples of cytoskeletal lncRNAs currently unrelated to tumorigenesis, to illustrate knowledge about them.

A Novel Ferroptosis-Related lncRNAs Signature Predicts Clinical Prognosis and Is Associated With Immune Landscape in Pancreatic Cancer

Pancreatic cancer is one of the most lethal malignancies and currently therapies are severely lacking. In this study, we aimed to establish a novel ferroptosis-related lncRNAs signature to predict the prognosis of patients with pancreatic cancer and evaluate the predictive abilities of candidate lncRNAs. According to The Cancer Genome Atlas (TCGA) database, a total of 182 patients with pancreatic cancer were included in our study. Ferroptosis-related lncRNAs were screened by Pearson correlation analysis with 60 reported ferroptosis-related genes. Through univariate, least absolute shrinkage and selection operator (LASSO) regression and multivariate regression analyses, a novel signature based on five ferroptosis-related lncRNAs(ZNF236-DT, CASC8, PAN3-AS1, SH3PXD2A-AS1, LINP1) was constructed. Risk-related differentially expressed genes (DEGs) were subjected to enrichment analyses for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The results revealed that immune cell infiltration, immune-related functions and checkpoints were factors to affect prognoisis of pancreatic cancer. In summary, we identified the prognostic ferroptosis-related lncRNAs(ZNF236-DT, CASC8, PAN3-AS1, SH3PXD2A-AS1, LINP1) in pancreatic cancer and these lncRNAs may serve as therapeutic targets for pancreatic cancer.

Long non-coding RNA LINC00680 functions as a ceRNA to promote esophageal squamous cell carcinoma progression through the miR-423-5p/PAK6 axis

Background

Esophageal squamous cell carcinoma (ESCC) is a common invasive malignancy worldwide with poor clinical outcomes. Increasing amount of long non-coding RNAs (lncRNAs) have been reported to be involved in cancer development. However, lncRNAs that are functional in ESCC and the underlying molecular mechanisms remain largely unknown.

Methods

Transcriptomic analysis was performed to identify dysregulated lncRNAs in ESCC tissue samples. The high expression of LINC00680 in ESCC was validated by RT-qPCR, and the oncogenic functions of LINC00680 was investigated by cell proliferation, colony formation, migration and invasion assays in ESCC cells in vitro and xenografts derived from ESCC cells in mice. RNA-seq, competitive endogenous RNA (ceRNA) network analysis, and luciferase reporter assays were carried out to identify LINC00680 target genes and the microRNAs (miRNAs) bound to LINC00680. Antisense oligonucleotides (ASOs) were used for in vivo treatment.

Results

Transcriptome profiling revealed that a large number of lncRNAs was dysregulated in ESCC tissues. Notably, LINC00680 was highly expressed, and upregulation of LINC00680 was associated with large tumor size, advanced tumor stage, and poor prognosis. Functionally, knockdown of LINC00680 restrained ESCC cell proliferation, colony formation, migration, and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, LINC00680 was found to act as a ceRNA by sponging miR-423-5p to regulate PAK6 (p21-activated kinase 6) expression in ESCC cells. The cell viability and motility inhibition induced by LINC00680 knockdown was significantly reversed upon PAK6 restoration and miR-423-5p inhibition. Furthermore, ASO targeting LINC00680 substantially suppressed ESCC both in vitro and in vivo.

Conclusions

An oncogenic lncRNA, LINC00680, was identified in ESCC, which functions as a ceRNA by sponging miR-423-5p to promote PAK6 expression and ESCC. LINC00680/miR-423-5p/PAK6 axis may serve as promising diagnostic and prognostic biomarkers and therapeutic targets for ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-022-01539-3.

HiMoRNA: A Comprehensive Database of Human lncRNAs Involved in Genome-Wide Epigenetic Regulation

Long non-coding RNAs (lncRNAs) play an important role in genome regulation. Specifically, many lncRNAs interact with chromatin, recruit epigenetic complexes and in this way affect large-scale gene expression programs. However, the experimental data about lncRNA-chromatin interactions is still limited. The majority of experimental protocols do not provide any insight into the mechanics of lncRNA-based genome-wide epigenetic regulation. Here we present the HiMoRNA (Histone-Modifying RNA) database, a resource containing correlated lncRNA–epigenetic changes in specific genomic locations genome-wide. HiMoRNA integrates a large amount of multi-omics data to characterize the effects of lncRNA on epigenetic modifications and gene expression. The current release of HiMoRNA includes more than five million associations in humans for ten histone modifications in multiple genomic loci and 4145 lncRNAs. HiMoRNA provides a user-friendly interface to facilitate browsing, searching and retrieving of lncRNAs associated with epigenetic profiles of various chromatin loci. Analysis of the HiMoRNA data suggests that several lncRNA including JPX might be involved not only in regulation of XIST locus but also in direct establishment or maintenance of X-chromosome inactivation. We believe that HiMoRNA is a convenient and valuable resource that can provide valuable biological insights and greatly facilitate functional annotation of lncRNAs.

Molecular Mechanisms of lncRNAs in the Dependent Regulation of Cancer and Their Potential Therapeutic Use

Deep whole genome and transcriptome sequencing have highlighted the importance of an emerging class of non-coding RNA longer than 200 nucleotides (i.e., long non-coding RNAs (lncRNAs)) that are involved in multiple cellular processes such as cell differentiation, embryonic development, and tissue homeostasis. Cancer is a prime example derived from a loss of homeostasis, primarily caused by genetic alterations both in the genomic and epigenetic landscape, which results in deregulation of the gene networks. Deregulation of the expression of many lncRNAs in samples, tissues or patients has been pointed out as a molecular regulator in carcinogenesis, with them acting as oncogenes or tumor suppressor genes. Herein, we summarize the distinct molecular regulatory mechanisms described in literature in which lncRNAs modulate carcinogenesis, emphasizing epigenetic and genetic alterations in particular. Furthermore, we also reviewed the current strategies used to block lncRNA oncogenic functions and their usefulness as potential therapeutic targets in several carcinomas.

Illuminating lncRNA Function Through Target Prediction

Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion's share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions-that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead-as was the case for better-studied ncRNAs in the past-researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.

The Complexity of the Mammalian Transcriptome

Draft genome assemblies for multiple mammalian species combined with new technologies to map transcripts from diverse RNA samples to these genomes developed in the early 2000s revealed that the mammalian transcriptome was vastly larger and more complex than previously anticipated. Efforts to comprehensively catalog the identity and features of transcripts present in a variety of species, tissues and cell lines revealed that a large fraction of the mammalian genome is transcribed in at least some settings. A large number of these transcripts encode long non-coding RNAs (lncRNAs). Many lncRNAs overlap or are anti-sense to protein coding genes and others overlap small RNAs. However, a large number are independent of any previously known mRNA or small RNA. While the functions of a majority of these lncRNAs are unknown, many appear to play roles in gene regulation. Many lncRNAs have species-specific and cell type specific expression patterns and their evolutionary origins are varied. While technological challenges have hindered getting a full picture of the diversity and transcript structure of all of the transcripts arising from lncRNA loci, new technologies including single molecule nanopore sequencing and single cell RNA sequencing promise to generate a comprehensive picture of the mammalian transcriptome.

Intron-encoded cistronic transcripts for minimally invasive monitoring of coding and non-coding RNAs

Despite their fundamental role in assessing (patho)physiological cell states, conventional gene reporters can follow gene expression but leave scars on the proteins or substantially alter the mature messenger RNA. Multi-time-point measurements of non-coding RNAs are currently impossible without modifying their nucleotide sequence, which can alter their native function, half-life and localization. Thus, we developed the intron-encoded scarless programmable extranuclear cistronic transcript (INSPECT) as a minimally invasive transcriptional reporter embedded within an intron of a gene of interest. Post-transcriptional excision of INSPECT results in the mature endogenous RNA without sequence alterations and an additional engineered transcript that leaves the nucleus by hijacking the nuclear export machinery for subsequent translation into a reporter or effector protein. We showcase its use in monitoring interleukin-2 (IL2) after T cell activation and tracking the transcriptional dynamics of the long non-coding RNA (lncRNA) NEAT1 during CRISPR interference-mediated perturbation. INSPECT is a method for monitoring gene transcription without altering the mature lncRNA or messenger RNA of the target of interest.

Integration of high-resolution promoter profiling assays reveals novel, cell type-specific transcription start sites across 115 human cell and tissue types

Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type–specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks are primarily proximal to GENCODE-annotated TSSs and are concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3′ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations are supported by epigenomic and other transcriptomic data sets. To show the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association study (GWAS) catalog and identified new candidate GWAS genes. Overall, our work shows the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.