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At least 19 recordsLinked to original sources
PubMed2025

The small nucleolar RNA NON-CODING RNA 1 negatively regulates drought tolerance in Arabidopsis thaliana.

Small nucleolar RNAs (snoRNAs) function in ribosome biogenesis, and many ribosome biogenesis-related genes were downregulated by osmotic stress, implying a negative role of snoRNAs in drought tolerance. A snoRNA, namely, the NON-CODING RNA 1 (NCR1) was studied for its roles in drought tolerance in Arabidopsis. In comparison with wild-type (WT) plants, the loss-of-function ncr1 mutant plants showed enhanced drought tolerance, which was restored in the NCR1-complemented plants, whereas the NCR1-overexpressing plants revealed a drought-sensitive phenotype. Physiological analyses revealed that the ncr1 plants had a higher leaf surface temperature, lower water loss rates, and improved cell membrane integrity compared with WT. Comparative leaf transcriptomics and proteomics suggested that wax biosynthesis, anthocyanin metabolism, and leaf senescence processes are regulated by NCR1 under both normal and water-deficit conditions. Under drought, an increase in wax and anthocyanin accumulations and a delay in leaf senescence in ncr1 plants, when compared with WT, supported the transcriptome and proteomics data. Additionally, the ncr1 plants exhibited higher abscisic acid (ABA) sensitivity and longer root hairs than WT. Collectively, our results suggest that NCR1 negatively regulates drought tolerance through modification of wax biosynthesis, anthocyanin accumulation, leaf senescence, cell membrane integrity, ABA responses, and root hair development.

Arabidopsis↗
PubMed2025

LncRAnalyzer: a robust workflow for long non-coding RNA discovery using RNA-Seq.

Long non-coding RNA (lncRNA) is a major transcript category that lacks protein-coding capabilities, with relatively low abundance and complex expression patterns. Distinguishing lncRNAs from protein-coding genes is a complex process involving multiple filtering steps. We developed an automated pipeline named LncRAnalyzer featuring retrained models for 60 species. This workflow aims to reduce the likelihood of obtaining protein-coding or partial protein-coding transcripts during lncRNA identification by utilizing eight distinct approaches. We conducted a 10-fold cross-validation of the sorghum models and training sets with their standard ones and other approaches using real-life RNA-Seq datasets and known lncRNA and CDS sequences of sorghum. The results showed that the sorghum models and training sets were outperformed. The pipeline output comprises upset plots illustrating the number of lncRNA/NPCTs identified by the approaches, commonly identified lncRNA and their classes, NPCTs, and expression count tables. A feature-level comparison and benchmarking analysis of LncRAnalyzer with four existing pipelines, namely, LncPipe, LncEvo, lncRNA-Annotation, and Plant-LncPipe, demonstrated that LncRAnalyzer is more comprehensive, easier to implement, and accurate in lncRNA predictions. This workflow also ascertains lncRNA origins from various Transposable Elements (TEs) in plants using TE annotations from APTEdb [http://apte.cp.utfpr.edu.br/]. LncRAnalyzer is publicly available on GitLab [https://gitlab.com/nikhilshinde0909/LncRAnalyzer.git] for academic users.

RNA, Long Noncoding↗
PubMed2026

HyLnc: a hybrid deep learning and feature-based approach for long non-coding RNA prediction.

Long non-coding RNAs (lncRNAs) play important roles in gene regulation, development and disease, yet accurate identification of lncRNAs from transcriptomic data remains a major computational challenge. Existing methods often rely either on handcrafted sequence features or deep learning approaches, each with their inherent limitations in capturing the full complexity of RNA sequences. In this study, we proposed HyLnc, a computational framework that integrates transformer-based contextual embeddings with biologically meaningful sequence features for improved lncRNA prediction. A custom BERT-based model was first pre-trained on a large corpus of metazoan RNA sequences using a masked language modelling strategy to learn contextual nucleotide dependencies. The model was subsequently fine-tuned on curated datasets of lncRNAs and protein-coding transcripts and 256-dimensional deep sequence embeddings were extracted. Parallelly, 348 handcrafted features, including ORF characteristics, untranslated region (UTR) properties, nucleotide composition and Fickett scores, were computed. A multi-stage feature selection strategy was applied to identify the most informative features, resulting in optimized hybrid feature sets. Multiple machine learning classifiers were evaluated, with the RF model achieving the best performance. The proposed framework attained an accuracy of 91.30%, F1-score of 91.23% and MCC of 82.60 on an independent validation dataset, outperforming several existing lncRNA prediction tools. Thus, HyLnc demonstrates that integrating deep contextual representations with biologically interpretable features enhances lncRNA prediction. This approach provides a robust and scalable solution for large-scale transcriptome annotation and can be extended to other sequence-based prediction.

RNA, Long Noncoding↗
PubMed2026

Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review.

Non-coding RNAs (ncRNAs), once considered genomic dark matter, are now established as key regulators of gene expression with widespread roles in cellular homeostasis and disease. In cancer, ncRNA expression is frequently and systematically dysregulated, and many of these molecules circulate in stable, protected form within biofluids, offering a compelling basis for non-invasive or minimally invasive diagnostic strategies. However, their clinical translation remains substantially hindered to date due to biological complexity, technical noise, and high dimensionality inherent to ncRNA expression datasets. In this context, machine learning (ML) has emerged as a powerful analytical tool to address these challenges, enabling the identification of subtle, reproducible ncRNA signatures predictive of diverse malignancies. This review critically evaluates ML-driven frameworks for cancer diagnosis and prognosis across four ncRNA subclasses, namely miRNAs, lncRNAs, circRNAs, and piRNAs, while also acknowledging the biophysical and thermodynamic models that reinforce ncRNA bioinformatics. Despite substantial methodological progress in ML-based cancer diagnosis and prognosis, key challenges persist, including tumor biological heterogeneity, limited multicenter validation, and the lack of widely adopted standardized protocols for preprocessing, normalization, and reporting workflows. Furthermore, many current ML models lack interpretability in biological or clinical context, constraining their translational utility. By synthesizing recent advances and identifying unresolved barriers, this review charts a roadmap for developing a robust, clinically actionable ncRNA biomarker platform for cancer detection. With global cancer incidence projected to exceed 35 million annual cases by 2050, validated ncRNA-ML-driven frameworks hold potential to revolutionize early-stage detection and personalized therapeutic strategies, thereby reducing the escalating socio-economic burden of cancer worldwide.

Humans↗
PubMed2026

Non-coding RNA 7SK drives tumor resistance by coupling local oncogenic activation with global transcriptional repression.

The conserved non-coding RNA 7SK is a well-established global transcriptional repressor, yet its context-specific functions in cancer and therapy resistance remain paradoxical. Here, we resolve this paradox by uncovering a dual-axis mechanism through which 7SK drives colorectal cancer (CRC) resistance. By integrating single-cell multi-omics with functional assays, we demonstrate that 7SK not only selectively activates the JUN transcriptional network to fuel tumor proliferation but also reduces global transcriptional entropy to stabilize an immunosuppressive microenvironment and promote immune escape. This "local activation-global suppression" paradigm is conserved across multiple cancer types, positioning 7SK as a potential pan-cancer therapeutic target. Our findings reveal 7SK as a dynamic modulator that balances oncogene-specific transcription with global transcriptional suppression across cancers, providing a new framework for understanding and targeting ncRNA-mediated resistance.

Humans↗
PubMed2024

Ageing-associated long non-coding RNA extends lifespan and reduces translation in non-dividing cells.

Genomes produce widespread long non-coding RNAs (lncRNAs) of largely unknown functions. We characterize aal1 (ageing-associated lncRNA), which is induced in quiescent fission yeast cells. Deletion of aal1 shortens the chronological lifespan of non-dividing cells, while ectopic overexpression prolongs their lifespan, indicating that aal1 acts in trans. Overexpression of aal1 represses ribosomal-protein gene expression and inhibits cell growth, and aal1 genetically interacts with coding genes functioning in protein translation. The aal1 lncRNA localizes to the cytoplasm and associates with ribosomes. Notably, aal1 overexpression decreases the cellular ribosome content and inhibits protein translation. The aal1 lncRNA binds to the rpl1901 mRNA, encoding a ribosomal protein. The rpl1901 levels are reduced ~2-fold by aal1, which is sufficient to extend lifespan. Remarkably, the expression of the aal1 lncRNA in Drosophila boosts fly lifespan. We propose that aal1 reduces the ribosome content by decreasing Rpl1901 levels, thus attenuating the translational capacity and promoting longevity. Although aal1 is not conserved, its effect in flies suggests that animals feature related mechanisms that modulate ageing, based on the conserved translational machinery.

RNA, Long Noncoding↗
PubMed2026

A human-specific non-coding RNA for EFHC1, an epilepsy-associated gene, regulates neural stem cell proliferation for cortical development.

Epilepsy is a prevalent brain disorder in humans but rarely occurs naturally in other species, highlighting the potential for human-specific mechanisms in its pathogenesis, and thus, current animal models fail to recapitulate human symptoms. Comparing RNA sequencing (RNA-seq) datasets from human and mouse neural stem cells (NSCs), we identified EFHC1, a juvenile myoclonic epilepsy gene, as exhibiting a human-biased expression. EFHC1 knockdown reduced human NSC proliferation, while its overexpression in mouse embryonic brains increased cortical NSC number. Mechanistically, EFHC1 prevented endoplasmic reticulum stress, thereby reducing inflammatory activation of p38 MAPK and promoting continuous proliferation of human NSCs. We also identified pancEFHC1, a bidirectional promoter-associated non-coding RNA (pancRNA), located at the human EFHC1 promoter. Knockdown of pancEFHC1 in human NSCs increased DNA methylation to reduce EFHC1 expression, with the resulting phenotype rescued by EFHC1 overexpression. We propose that the evolutionary acquisition of pancEFHC1 has introduced a complex regulatory mechanism for EFHC1 expression that allows distinguishing it in humans.

Humans↗
PubMed2026

A Comparative Analysis of the Methylation Status of Non-Coding RNA Promoters in Fibroid and Matched Myometrium.

Uterine fibroids exhibit dysregulated expression of non-coding RNAs (ncRNAs), although the underlying mechanisms remain incompletely understood. We investigated promoter DNA methylation and its relationship with ncRNA expression in fibroids. Genomic DNA from eight paired fibroid and matched myometrial tissues was analyzed using MeDIP-chip to identify differentially methylated ncRNA promoters. Selected candidates were validated by methylation-specific PCR (MSP) in 16 paired samples, and transcript expression was assessed by qRT-PCR in 68-94 paired specimens. MeDIP-chip identified 538 lncRNAs and 61 miRNAs with differential promoter methylation, including 300 hypermethylated and 238 hypomethylated lncRNAs and 47 hypermethylated and 14 hypomethylated miRNAs. Promoter methylation was not significantly correlated with transcript expression (r = -0.1224). MSP confirmed hypermethylation of LINC-PINT and MIR9-3 and hypomethylation of WT1-AS and TTLL10-AS1. Correspondingly, LINC-PINT and MIR9-3 expression was decreased, whereas WT1-AS and TTLL10-AS1 expression was increased in fibroids. However, LINC-PINT and TTLL10-AS1 methylation did not fully correspond with MeDIP-chip findings. These results reveal widespread ncRNA promoter methylation alterations in uterine fibroids but demonstrate that genome-wide methylation does not consistently predict transcript expression, highlighting the complexity of ncRNA epigenetic regulation and the importance of locus-specific validation.

Humans↗
PubMed2025

Short-term diet intervention comprising of olive oil, vitamin D, and omega-3 fatty acids alters the small non-coding RNA (sncRNA) landscape of human sperm.

Offspring health outcomes are often linked with epigenetic alterations triggered by maternal nutrition and intrauterine environment. Strong experimental data also link paternal preconception nutrition with pathophysiology in the offspring, but the mechanism(s) routing effects of paternal exposures remain elusive. Animal experimental models have highlighted small non-coding RNAs (sncRNAs) as potential regulators of paternal effects. Here, we characterised the baseline sncRNA landscape of human sperm and the effect of a 6-week dietary intervention on their expression profile. This study involves sncRNAseq profiling, that was performed on a subset (n = 17) of the participants enrolled in the PREPARE trial: 9 from the control group and 8 from the intervention group. 5'tRFs, miRNAs and piRNAs were the most abundant sncRNA subtypes identified; their expression was associated with age, BMI, and sperm quality. Nutritional intervention with olive oil, vitamin D and omega-3 fatty acids altered expression of 3 tRFs, 15 miRNAs and 112 piRNAs, targeting genes involved in fatty acid metabolism and transposable elements in the sperm genome. PREPARE Trial registration number: ISRCTN50956936, Trial registration date: 10/02/2014.

Humans↗
PubMed2025

Long non-coding RNA NEAT1 promotes colorectal cancer progression via interacting with SIRT1.

Nuclear-enriched abundant transcript 1 (NEAT1), a long noncoding RNA, is found to be significantly dysregulated in different types of cancer, including colorectal cancer (CRC). Nevertheless, there is still much to learn about the precise functions and processes of NEAT1 in the progression of CRC. Using The Cancer Genome Atlas (TCGA) database and 50 CRC specimens from the First Affiliated Hospital of Dali University, we assessed the expression of NEAT1 to determine its clinical impact. Through gene set enrichment analysis (GSEA), Cancer Single-cell State Atlas (CancerSEA), and immune infiltration studies, we elucidated key functions of NEAT1. We utilized Cell Counting Kit-8 (CCK8), wound healing, and Transwell assays to investigate the role of NEAT1 in the progression of CRC. Through the use of GSEA and immunohistochemistry, additional investigations were conducted to unveil the downstream targets of NEAT1 and gain insights into their regulatory dynamics. Our in vitro studies confirmed the regulatory role of NEAT1 in CRC. Findings indicate that increased NEAT1 expression correlates with adverse outcomes in colorectal tissues. In the CRC model, reduced levels of NEAT1 lead to reduced cell proliferation, invasion, and migration. Additionally, NEAT1 influenced immune cell infiltration in CRC and functioned as an oncogene by upregulating Sirtuin 1 (SIRT1) expression. This study demonstrates that NEAT1 promotes CRC progression and metastasis through a SIRT1-mediated mechanism, suggesting its potential as a prognostic biomarker and therapeutic target for CRC.

RNA, Long Noncoding↗
PubMed2018

Long non-coding RNA metallothionein 1 pseudogene 3 promotes p2y12 expression by sponging miR-126 to activate platelet in diabetic animal model.

Platelet hyperaggregation and hypercoagulation are associated with increase of thrombogenic risk, especially in patients with type 2 diabetes (T2D). High activity of P2Y12 receptor is found in T2D patients, exposing such patients to a prothrombotic condition. P2Y12 is a promising target for antiplatelet, but due to P2Y12 receptor constitutive activation, the clinical practical phenomena such as "clopidogrel resistance" are commonly occurring. In this study, we investigate the role of lncRNA on platelet activation. By lncRNA array, we screened thousands of differentially expressed lncRNA in megakaryocytes from T2D patients and confirmed that lncRNA metallothionein 1 pseudogene 3 (MT1P3) was significantly upregulated in megakaryocytes from T2D patients than in healthy controls. And we further investigate the biofunction of MT1P3 on platelet activation and the regulatory mechanism on p2y12. MT1P3 was positively correlated with p2y12 mRNA levels and promoted p2y12 expression by sponging miR-126. Knockdown of MT1P3 by siRNA reduced p2y12 expression, inhibiting platelet activation and aggregation in diabetes animal model. In conclusion, our findings identify MT1P3 as a key regulator in platelet activation by increasing p2y12 expression through sponging miR-126 under T2D condition. These findings may provide a new insight for managing platelet hyperactivity-related diseases.

Animals↗
PubMed2026

Nuclear body assembly by a viral repeat RNA promotes Kaposi's sarcoma-associated herpesvirus gene expression.

Kaposin is the most abundantly expressed viral RNA in tumors caused by the oncogenic virus Kaposi's sarcoma-associated herpesvirus (KSHV); however, its role in viral replication is not understood. Here, we show that kaposin, previously viewed as a protein-coding transcript, exists primarily as a nuclear viral long non-coding RNA (lncRNA) that rebuilds cellular nuclear speckles (NSs) adjacent to the viral genome to enhance viral gene expression. Kaposin is both necessary and sufficient to drive substantial NS remodeling, and this effect depends on repetitive elements within the RNA. Absence of kaposin-mediated NS remodeling, depletion of the essential NS protein, serine/arginine repetitive matrix 2 (SRRM2), or steric blocking of the kaposin repetitive elements impair viral gene expression. This work defines kaposin as a viral architectural RNA that drives nuclear speckle seeding beside the viral genome and reframes our understanding of lncRNA function and the spatial organization of transcription in the infected cell nucleus.

Kaposi's sarcoma-associated herpesvirus↗
PubMed2025

TripLexicon: prediction and analysis of gene regulatory RNA-DNA interactions.

MOTIVATION: Non-coding RNA (ncRNA) plays a crucial role in gene regulation, including by forming sequence-specific RNA-DNA interactions at gene regulatory elements. One form of interaction takes place via the formation of RNA:DNA:DNA triple helices (triplexes). Accurate computational prediction of triplex formation from nucleotide sequences is an important tool in ncRNA research but remains somewhat inaccessible and complex. To address this, we created TripLexicon, a web-based interface for accessing and analyzing predicted gene regulatory RNA-DNA interactions in human and mouse. RESULTS: Predicted interactions can be accessed from RNA-, DNA-, and region-centric perspectives. For each RNA transcript, visualizations at genome and nucleotide resolution are available, providing insight into target genes and regions, as well as putative functional domains of the transcript. Predicted target genes can immediately be subjected to ontology and pathway enrichment analysis, providing rapid insight into potential functions mediated by the RNA-DNA interactions of the queried transcript. DNA and region queries are designed to identify potentially important ncRNA interactors at sites of interest. AVAILABILITY AND IMPLEMENTATION: TripLexicon is accessible at https://triplexicon.uni-frankfurt.de. This website is free and open to all users and there is no login requirement. All data and code is uploaded to Zenodo: https://zenodo.org/records/17143608 and the code for the webserver is available on Github: https://github.com/SchulzLab/TripLexicon.

Software↗
PubMed2026

Differentiation-independent activation of HPV genome replication by the lncRNA DINO.

Human papillomaviruses (HPVs) rely on multiple host cell factors to replicate the viral genome, yet the contribution of host long non-coding RNAs (lncRNAs) to viral genome maintenance and amplification in the productive life cycle remains poorly understood. In this study, we show that the lncRNA damage-induced long non-coding RNA (DINO) is a driver of HPV DNA replication. DINO levels increase during keratinocyte differentiation, and ectopic expression of DINO promotes both HPV genome replication and the formation of replication foci, and this is independent of keratinocyte differentiation signals. Ectopic DINO expression increases select early viral transcript levels, including E1^E4, E1, and E2. Notably, DINO's subcellular localization is also context-dependent: during DNA damage, DINO is predominantly cytoplasmic, but during keratinocyte differentiation, nuclear retention is observed. This differential localization suggests that DINO has distinct functional roles in keratinocyte differentiation and HPV biology. Our findings highlight DINO as a lncRNA that promotes HPV genome replication and suggest that lncRNAs may play underappreciated roles in host-virus interactions. This work provides a foundation for further exploration of lncRNAs as potential therapeutic targets in HPV-associated diseases.IMPORTANCEHuman papillomaviruses (HPVs) are the causative agents of many anogenital tract and oral cancers, yet the host factors that trigger and support viral genome replication during the productive life cycle are incompletely understood. This study identifies the long non-coding RNA DINO as a host regulator that promotes HPV DNA replication, replication focus formation, and early viral gene expression independently of keratinocyte differentiation. We further show that DINO exhibits context-dependent subcellular localization, suggesting distinct functional roles in cellular stress responses and HPV biology. These findings reveal an underappreciated role for host lncRNAs in virus-host interactions and provide new insight into cellular pathways that support HPV genome replication.

Virus Replication↗
PubMed2026

Insights into the regulation of the HOTAIR proximal promoter.

HOTAIR (HOX transcript antisense RNA) is a HOXC-cluster long intervening non-coding RNA (lincRNA) whose cancer relevance is tightly coupled to how its transcription is wired into hormone, hypoxia, inflammatory, and developmental signaling. HOTAIR is known to associate with cancer cell proliferation, motility, tumor invasion, and metastasis. The present mini-review focuses on the regulatory architecture and mechanistic complexity of HOTAIR transcriptional regulation, with emphasis on three organizing principles. First, we consider the impact of promoter choice between a canonical proximal promoter (P1), which supports the 2.2-2.4 kb transcript, and an alternative upstream promoter/TSS (P2), which contributes to context-dependent transcription initiation. Second, we examine the long-distance enhancer-promoter communication between HOTAIR distal enhancer and P1/P2. Third, we summarize the recent epigenetic and epi-transcriptomic mechanisms involved in HOTAIR transcript initiation and elongation. A combination of these events determines isoform-specific transcription to govern cell-type-, context-, and cancer specific modulation of HOTAIR expression that promotes tumor formation and cancer progression. Finally, the review proposes how large-scale RNA datasets, long-read sequencing, and isoform-specific studies can refine our understanding of this versatile lincRNA's regulation.

Humans↗
PubMed2026

The HOXA gene cluster: a critical regulator in bone-related disorders.

BACKGROUND: Skeletal homeostasis relies on the dynamic balance between bone formation and bone resorption. The disruption of this balance acts as the central pathological mechanism of multiple metabolic bone diseases including osteoporosis, and is closely correlated with the progression of various other bone-related disorders. As pivotal transcription factors regulating embryonic development and cell fate, the homeobox A (HOXA) gene family plays an essential role in skeletal physiological and pathological processes. METHODS: This review systematically summarizes recent research advances of the HOXA gene family in bone-related diseases, concludes the evolutionarily conserved regulatory patterns of HOXA members, and clarifies the molecular mechanisms by which HOXA genes mediate bone metabolic disorders and the occurrence as well as development of bone diseases. RESULTS: Accumulating evidence demonstrates that HOXA family members present complex functions and strong heterogeneity in bone-related diseases. They participate in the pathogenesis of bone diseases via three evolutionarily conserved regulatory manners: determining regional patterning, modulating signaling pathways, and integrating epigenetic and non-coding RNA (ncRNA) regulatory networks. CONCLUSION: Further exploring the underlying mechanisms of the HOXA family in bone-related diseases provides novel insights into the pathogenesis of bone disorders. Meanwhile, it also supplies solid theoretical basis and potential therapeutic targets for the development of novel HOXA-targeted therapeutic strategies against bone diseases.

Humans↗
PubMed2025

Genetic and chromatin regulation of Pvt1 monoallelic expression.

While most genes are equivalently expressed on both alleles, genes with random monoallelic expression (RME) stably maintain expression from only one allele, but the mechanisms and consequences of RME remain unclear. We performed allele-specific RNA sequencing (RNA-seq) on ∼100 F1 hybrid neural progenitor cell (NPC) clonal lines to reveal the extent of autosomal RME (aRME). Of the 287 aRME genes, Pvt1, an oncogenic long non-coding RNA, is an aRME with a genetic bias. In the absence of genetic differences, Pvt1 undergoes balanced aRME. Pvt1 monoallelic expression is maintained by allele-specific active and repressive histone modifications, opposed to DNA methylation. Additionally, we provide a two-step mechanism for the initiation of aRME and demonstrate that Pvt1 monoallelic expression results in a growth phenotype due to the interplay with Myc. These findings provide insight into how genetic differences can skew a stochastic process, resulting in monoallelic expression with a phenotypic consequence in early development.

Chromatin↗