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PubMed2026

Non-coding RNAs in cancer: multi-omics insights, liquid biopsy advances, drug resistance mechanisms, and the road to clinical translation.

For most of the twentieth century, the transcriptional output of the human genome was thought to be biologically inert-a characterization that has been proven wrong in almost every important respect. Non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), small nucleolar RNAs (snoRNAs) and PIWI-interacting RNAs (piRNAs) are now thought of as vital regulators of gene expression in all the stages of cancer pathogenesis, including the initial epigenetic changes, metastatic spread and the development of therapeutic resistance. This review highlights four areas where the clinical potential of ncRNAs is most promising: reconstruction of ncRNA regulatory networks by multi-omics integration; circulating ncRNAs as minimally invasive cancer biomarkers; causal roles of ncRNAs in drug resistance through epithelial-mesenchymal plasticity, metabolic reprogramming, and stromal communication; and translation of ncRNA targeting strategies to clinical trials. We will need to invest equally in mechanistic rigor and translational infrastructure to move forward.

antisense oligonucleotides↗

PubMed2026

Long non-coding RNAs link DNA methylation to immune regulatory networks in bovine subclinical mastitis.

Long non-coding RNAs (lncRNAs) are emerging as important regulators of inflammatory and immune signaling, yet their contribution to bovine subclinical mastitis remains poorly defined. Here, we characterized the lncRNA expression landscape associated with disease in milk somatic cells of healthy and subclinical mastitic Vrindavani cattle. We identified 11,403 high-confidence lncRNAs, of which 104 were differentially expressed in subclinical mastitis (adjusted P < 0.05; |log2FC| ≥ 1), with the vast majority upregulated in mastitic samples. Predicted cis- and trans-associated target analyses identified 637 non-redundant genes, and KEGG analysis identified 8 significantly enriched cis-associated pathways and 152 significantly enriched trans-associated pathways (adjusted P < 0.05), predominantly enriched for immune and inflammation-related pathways. These findings prioritized a subset of mastitis-associated lncRNAs for subsequent methylation and interaction-network analyses. A subset of these lncRNAs further overlapped differentially methylated regions (DMRs), suggesting a potential association between lncRNA expression changes and DNA methylation alterations. Integration of lncRNA-miRNA and miRNA-mRNA interactions identified lncRNA-miRNA-mRNA interaction networks involving DMR-associated lncRNAs. Among the prioritized candidates, MSTRG.28878.1 showed overlap with a hypomethylated promoter-associated DMR, increased expression, and multiple connections within the predicted interaction network. Together, these findings identify candidate lncRNAs, methylation-associated loci, and predicted molecular interactions associated with bovine subclinical mastitis and provide a resource for future functional investigation of candidate non-coding RNA-associated mechanisms in disease.

Animals↗

PubMed2026

Targeting ncRNA control networks with engineered exosomes to overcome therapy resistance in thyroid cancer.

Papillary thyroid cancer (PTC) is the most prevalent endocrine malignancy, accounting for over 90% of thyroid cancers. While differentiated thyroid cancers (DTCs) typically have favorable outcomes, a significant subset progresses to radioactive iodine-refractory (RAIR) disease, characterized by impaired iodine uptake and a 10-year survival rate below 10%. Genetic alterations and dysregulated signaling pathways underlie this transition. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs), play critical regulatory roles in tumor biology and may be transported via exosomes, facilitating intercellular communication and contributing to RAIR-PTC. This systematic review, conducted according to PRISMA 2020 guidelines, evaluated the role of exosomal ncRNAs in RAIR-PTC. A comprehensive search of PubMed, PubMed Central, and Google Scholar identified studies published within the past 15 years in English. Following stringent quality appraisal, studies with a non-bias score above 40% were included. Of 961 identified publications, 96 high-quality studies met inclusion criteria. Evidence indicates that therapy resistance in RAIR-PTC is driven by convergent ncRNA regulatory networks that suppress sodium-iodide symporter (NIS) expression and activate oncogenic pathways, most notably MAPK, PI3K/AKT/mTOR, and Wnt/β-catenin signaling. Multiple ncRNAs converge on key regulatory nodes, forming redundant circuits that sustain dedifferentiation, metabolic adaptation, and impaired iodide transport. Several consistently dysregulated ncRNAs directly or indirectly regulate NIS expression and trafficking, highlighting actionable targets. Exosomes emerge as biologically compatible, programmable delivery vehicles capable of transporting therapeutic ncRNA payloads independent of endogenous packaging mechanisms. These findings support a precision therapeutic paradigm in which engineered exosomes reprogram ncRNA networks to restore iodine-handling pathways and overcome therapy resistance in RAIR-PTC.

Humans↗

PubMed2026

Adaptation to Plant Defence in an Agricultural Insect Pest: Integrating Genome Scans and Gene Expression in the Soybean Aphid Reveals Multi-Genic Pathways.

In agroecosystems, intense selection pressures cause species to adapt and spread, often leading to the evolution and persistence of pests. Understanding how pests rapidly adapt can help develop sustainable strategies for their management and improve agroecosystem health. Pest adaptation involves stable variations in DNA sequence, as well as dynamic shifts in gene expression, often mediated by non-coding regulatory elements. We examined adaptation to plant defences in the soybean aphid, Aphis glycines, in which virulent aphids have overcome plant defences and avirulent aphids have not. Previous data with laboratory colonies suggested that virulent aphids have higher overall gene expression, including transposable elements, some of which influence gene regulation. However, we lack information on how genetic variation in natural populations impacts adaptation and potentially gene regulation. We integrated population genome scans of field-collected, soybean aphid populations with gene expression profiles of virulent and avirulent laboratory colonies to uncover connections between genetic differentiation and gene regulation for virulence. Genome scan methods found 2144 single nucleotide polymorphisms (SNPs) with significant genetic differentiation (i.e., outliers) in field-collected populations. These SNPs were near 1004 genes, representing 5.16% of the effective number of genes. Based on previous RNA-Seq data with laboratory colonies, we found 3160 genes and 147 long non-coding RNAs (lncRNAs) with differential expression among virulent and avirulent biotypes. By integrating both data sets, we identified 16 genes and 5 long non-coding RNAs with differential expression and that were associated with an outlier SNP (within 10 kbp). We validated SNPs with additional field collected aphids and found an aphid clone with stronger virulence than our laboratory virulent colony, surviving on 2 different aphid-resistant soybean varieties. This new virulent clone had fixed allele differences at 9 SNPs compared to our avirulent and other virulent colony. Field collected soybean aphids matching the phenotype of this new virulent clone had significant genetic differentiation with 3 outlier SNPs near genes related to zinc transport and lachesin compared to field collected avirulent aphids. Our entire data reinforced the importance of a potential multi-genetic response to overcome plant defence and generates new insights into complex genetic and regulatory mechanisms involved in insect-plant interactions.

Animals↗

PubMed2026

Whole-transcriptome RNA sequencing and ceRNA network analyses provide novel insights into the antibacterial immune response of Hippocampus abdominalis against Vibrio harveyi.

Long non-coding RNAs (lncRNAs) stand as newly-arisen molecular types that exert regulatory effects, able to operate as competitive endogenous RNAs (ceRNAs) to engage microRNAs (miRNAs) in interaction, resulting in the recovery of target mRNA expression and activity. Increasing evidences indicate that the ceRNA network affects various biological processes in mammals, including development, cellular differentiation, metabolism, immune response, and disease pathogenesis. In teleost fish, the lncRNA-miRNA-mRNA regulatory networks have been reported occasionally. However, up to now, the roles of lncRNAs in the big-belly seahorse (Hippocampus abdominalis) remains unclear. In this study, we reported for the first time, via whole-transcriptome RNA sequencing, the lncRNA mediated ceRNA regulatory network in Vibrio harveyi-infected H. abdominalis. A total of 4197 differentially expressed mRNAs (DE-mRNAs), 1317 DE-lncRNAs, and 183 DE-miRNAs were identified. Furthermore, the crosstalk between miRNAs and lncRNAs as well as between miRNAs and mRNAs was inferred based on the negative correlations between miRNAs and their target lncRNAs/mRNAs. A core immune associated lncRNA-miRNA-mRNA putative regulatory network was thus constructed, comprising 211 lncRNA-miRNA and 224 mRNA-miRNA pairs. In conclusion, our findings provide an integrative overview of the ceRNA regulatory networks on the underlying immune responses to V. harveyi infection in the big-belly seahorse, and offer a solid theoretical foundation for the comparative immunological research of teleost fish.

Animals↗

PubMed2026

New insights on Plasmodium gene expression from direct RNA sequencing.

Oxford Nanopore Technology (ONT) direct RNA sequencing enables the sequencing of native RNA molecules without cDNA conversion. The long-read approach captures full-length reads spanning entire genes and has transformed the study of gene expression in Plasmodium parasites by enabling analysis of untranslated regions, isoforms, and alternative splicing. In addition, ONT provides unique insights into non-coding RNAs, RNA modifications, and polyadenylated tail dynamics, which are expanding our understanding of post-transcriptional regulation in Plasmodium, including processes beyond translational repression in gametocytes and sporozoites. Here, we discuss the past and future applications of direct RNA sequencing in Plasmodium research and highlight its advantages, limitations, and future prospects.

Oxford Nanopore Technology↗

PubMed2026

Circular RNAs in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, with most cases lacking a clear genetic basis. Emerging evidence highlights the involvement of non-coding RNAs, particularly circular RNAs (circRNAs), in disease onset and progression. Here, we investigated circRNAs implicated in ALS and related motor neuron diseases (MNDs). Here, we provide a general overview of circular RNA metabolism and cellular functions. We then present our systematic literature review that identified ALS-associated circRNAs, followed by in silico analyses of 15 circular RNA candidates that were selected based on the most compelling data regarding ALS. Our results revealed that several circular RNAs regulate ALS-related genes, such as unfolded protein response, oxidative stress, cell cycle regulation, and apoptosis. Protein-RNA interaction analysis further showed that ALS-related circRNAs can sponge 20 RNA-binding proteins. Additionally, molecular docking analysis demonstrated that ALS-associated FUS variants significantly alter its binding affinity to circular RNAs. RNA-seq data from ALS patients confirmed significant alterations in the expression of host genes of ALS-related circRNAs and hub proteins in ALS-affected CNS tissues. Collectively, our findings identify circRNAs as potential key contributors to ALS pathogenesis.

Amyotrophic Lateral Sclerosis↗

PubMed2026

EGFR-co-amplified lncRNA ELDR drives glioblastoma tumorigenicity by enhancing BMI1 activity.

BACKGROUND: In glioblastoma (GBM), epidermal growth factor receptor (EGFR) amplification, one of the most prevalent genetic alterations, often occurs on extrachromosomal DNAs (ecDNAs) that contain amplified oncogenes and regulatory elements, driving tumor progression. Despite the central oncogenic role of EGFR amplification, therapeutic strategies targeting EGFR have demonstrated limited clinical efficacy, suggesting that additional mechanisms may underlie EGFR-driven GBM malignancy and treatment resistance. Long non-coding RNAs (lncRNAs) are critical regulators in cancer; however, the roles of EGFR-associated lncRNAs-particularly those localized on ecDNA-in GBM tumorigenicity and therapeutic resistance remain poorly understood. METHODS: Transcriptomic and genomic analyses were performed to identify lncRNAs co-amplified with EGFR. Biochemical and molecular biological studies were carried out to reveal the mechanisms. In vivo xenograft models were used to evaluate the tumorigenicity and the therapeutic efficacy of combination treatment strategies. RESULTS: The lncRNA EGFR long non-coding downstream RNA (ELDR) was co-amplified with EGFR on ecDNA and chromosomes and was associated with poor prognosis in glioma. ELDR promoted GBM tumorigenicity through a BMI1-dependent epigenetic mechanism operating in parallel with canonical EGFR signaling. Mechanistically, ELDR interacted with purine-rich element-binding protein A (PURA), disrupted the inhibitory PURA-BMI1 interaction, and thereby enhanced the activity of BMI1, a core component of Polycomb repressive complex 1 (PRC1). Therapeutically, combining a BMI1 inhibitor or ELDR-targeting antisense oligonucleotides (ASOs) with an EGFR inhibitor erlotinib significantly enhanced antitumor efficacy in preclinical models of  EGFR  -amplified GBM with high ELDR expression. CONCLUSION: EGFR co-amplified ELDR promotes GBM tumorigenicity by enhancing BMI1 activity. Targeting the ELDR-BMI1 axis in combination with EGFR inhibition represents a promising therapeutic strategy for a subset of  EGFR  -amplified GBMs with high ELDR expression.

EGFR↗

PubMed2026

Identifying Co-Expressed lncRNAs Correlated With Traits of Interest in an Animal Model for Metabolic Diseases in Humans.

Nutrigenomics investigates how nutrients modulate gene expression. Among them, fatty acids (FA) play important roles in regulating gene transcription, while long non-coding RNAs (lncRNAs) may be associated with gene regulation and metabolic diseases. This study aimed to analyze the hepatic transcriptome of pigs, a species frequently used as a model for nutrigenomic studies, to identify novel lncRNAs and their potential target genes in response to diets containing different sources of FA. Seventy-two pigs were fed four diets supplemented with 1.5% soybean oil (control), 3% canola oil, 3% fish oil, and 3% soybean oil. RNA sequencing of liver samples was performed to identify novel lncRNAs. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify modules associated with phenotypic traits related to lipid metabolism and inflammation. Functional enrichment analyses were then conducted to annotate genes within these modules using Gene Ontology (GO) terms and to assess overlap with Quantitative Trait Loci (QTL). The results revealed 106 novel lncRNAs potentially regulating genes associated with lipid metabolism and immune responses in pigs fed diets with different FA sources. These findings enhance understanding of the regulatory role of lncRNAs in pigs and reinforce their relevance as models for human metabolic diseases.

Animals↗

PubMed2026

Context-dependent effects of MIR100HG on tumorigenic phenotypes and p38/MAPK-AKT signaling in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide and is characterized by a hypoxic tumor microenvironment that promotes tumor progression, cellular adaptation, and therapeutic resistance. Increasing evidence indicates that long non-coding RNAs (lncRNAs) play critical roles in regulating tumor-associated signaling networks; however, the contribution of MIR100HG to hepatocellular carcinoma progression, particularly under hypoxic conditions, remains insufficiently understood. In this study, we investigated the expression pattern and functional significance of MIR100HG in hepatocellular carcinoma using epithelial-like Hep3B and mesenchymal-like SNU-398 cells, together with non-tumor hepatocytes (Clone-9). Gain- and loss-of-function approaches were employed to evaluate the impact of MIR100HG on tumor-associated cellular phenotypes under both normoxic and hypoxic conditions. Functional assays demonstrated that MIR100HG overexpression significantly enhanced cell proliferation, clonogenic potential, migration, and invasion, whereas MIR100HG silencing markedly suppressed these tumorigenic properties and increased apoptotic cell death. Mechanistic analyses revealed that MIR100HG promotes oncogenic signaling through the p38/MAPK and AKT pathways under normoxic conditions, whereas MIR100HG depletion reduced the phosphorylation of these key signaling proteins. Notably, additional pathway analyses under hypoxia-mimicking conditions revealed a distinct signaling response, in which the MIR100HG-associated activation of p38/MAPK and AKT observed under normoxia was not maintained. Moreover, the expression patterns of AKT-associated regulatory genes, including GAS6 and PTEN, were reversed under hypoxia-mimicking conditions. These findings suggest that the effects of MIR100HG on oncogenic signaling are highly dependent on the cellular oxygenation context and that hypoxia reshapes the downstream signaling consequences of MIR100HG expression in HCC cells. Collectively, our findings identify MIR100HG as a hypoxia-associated oncogenic regulator that enhances tumorigenic phenotypes and promotes survival signaling in hepatocellular carcinoma. These results highlight MIR100HG as a potential biomarker and therapeutic target in liver cancer and provide new insights into the molecular mechanisms underlying hypoxia-driven tumor progression.

Humans↗

PubMed2026

Transcriptomic changes in the gut mucosa of fasting northern elephant seal pups reveal immune modulation during early microbiome establishment.

Fasting is an integral component of the life-history of many species. Following abrupt weaning, northern elephant seal pups (Mirounga angustirostris) undergo an extended post-weaning fast of approximately 60 days. During this period, enteric bacterial diversity increases, suggesting that host immune regulation may facilitate the establishment of microbial communities. However, the molecular processes occurring within the intestinal mucosa during this transition remain poorly understood. To investigate these mechanisms, we characterized transcriptional changes in the enteric mucosa of male and female northern elephant seal pups sampled at weaning and after one month of fasting. Total RNA isolated from rectal swabs was sequenced and aligned to the Mirounga angustirostris reference genome. Differential gene expression and gene set enrichment analyses were used to identify genes and pathways associated with fasting and sex-specific responses. Fasting was accompanied primarily by transcriptional downregulation, including genes involved in antimicrobial defense, inflammation, protein turnover, and epithelial remodeling. In contrast, several genes associated with B-cell activity and immune recognition were upregulated. Gene Set Enrichment Analysis revealed coordinated activation of immune-regulatory pathways indicating dynamic modulation of intestinal immunity rather than generalized immune suppression. Pronounced sex-specific differences were also observed. Male pups exhibited transcriptional patterns consistent with enhanced immune tolerance, whereas females showed broader immune-pathway activation, including enrichment of pro-inflammatory and stress-response pathways. Several non-coding RNAs also displayed sex-specific changes in expression. Together, these findings suggest that fasting induces transcriptional remodeling of the gut and may contribute to immune regulation during a critical period of microbiome establishment in northern elephant seal pups.

Animals↗

PubMed2026

Comparative transcriptome analysis reveals ncRNA-mediated regulatory networks associated with muscle crispiness in grass carp.

Non-coding RNAs (ncRNAs) have been demonstrated to be involved in muscle development and to function as key regulators. However, the molecular mechanism underlying muscle crispiness in grass carp (GC) remains poorly understood, and whether these ncRNAs are involved in its regulation is still unknown. In the current investigation, differentially expressed (DE) RNAs (including lncRNAs, circRNAs, miRNAs, and mRNAs) were identified; concomitantly, target genes prediction was conducted, and functional and signaling pathway enrichment analyses were performed. Pathways related to muscle crispiness were identified, and the competitive endogenous RNA (ceRNA) (lncRNA/circRNA-miRNA-mRNA) regulatory network was further constructed. The results showed that a total of 126 DE-lncRNAs, 17 DE-circRNAs, 329 DE-miRNAs, and 442 DE-mRNAs were identified in muscle tissues of both the GC and crisp grass carp (CGC). GO and KEGG enrichment analyses revealed that target genes of DE-ncRNAs were significantly enriched in signaling pathways, including structural constituents of muscle, apoptosis, oxidative phosphorylation, and regulation of actin cytoskeleton, suggesting that these pathways may be involved in muscle texture remodeling. Subsequently, DE-RNAs enriched in related pathways were identified, and a core ceRNA regulation network comprising 3 lncRNAs, 4 circRNAs, 3 miRNAs, and 17 mRNAs was constructed. Additionally, 10 DE-RNAs from randomly selected groups were validated by qRT-PCR. Our findings not only provide scientific evidence elucidating the molecular mechanisms underlying muscle crispiness in GC but also establish a foundation for studying changes in muscle textural qualities across other fish species.

Animals↗

PubMed2026

The identification of growth-promoting lncRNAs in oral cavity squamous cell carcinoma.

Oral Cavity Squamous Cell Carcinoma (OCSCC) is an aggressive tumor that develops within the mouth of patients. Tumor-suppressor gene loss and genomic arrangements fuel tumorigenesis and transcriptional reprogramming. Understanding how these alterations contribute to OCSCC growth and cell survival may identify new therapeutic vulnerabilities or biomarkers. We profiled the role of long non-coding RNAs (lncRNAs) in the growth of three OCSCC cell lines using a CRISPRi-screen and identified 19 lncRNAs that contribute to OCSCC proliferation. By comparing these lncRNAs to other screens, we find that these lncRNAs are uniquely required in OCSCC and not other malignancies. We show that these lncRNAs are abundantly expressed in OCSCC cells and tumors. Independent testing of candidate lncRNAs confirms their role in supporting OCSCC growth. Our results show that a novel subset of lncRNAs are required for the growth of OCSCC cancer cells and that these lncRNAs are cell lineage specific.

CRISPRi↗

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

Digital Kennison: A bioinformatics pipeline for rapid mapping of sequences to the Drosophila melanogaster Y chromosome.

The Drosophila melanogaster Y chromosome is currently known to contain 13 single-copy protein-coding genes, six of which are essential for male fertility, as well as several non-coding genes and abundant repetitive DNA. Localization of Y-linked sequences has traditionally relied on labor-intensive crosses using Kennison's translocation strains, which map Y-linked loci by generating flies deficient for each of the six Y-chromosome fertility regions (ks-1, ks-2, kl-1, kl-2, kl-3, and kl-5). Here we present Digital Kennison, a computational pipeline that recasts this classical mapping strategy as a sequence-based analysis. The pipeline queries eight genomic databases derived from Kennison's strains using BLAST and read coverage, assigning sequences to fertility regions or the centromeric region with a calibrated confidence score. We benchmarked the method on 60 Y-linked sequences spanning all seven regions, including single-copy protein-coding genes, Mst77Y family members, non-coding RNAs, and the centromere. Digital Kennison achieved 97% precision while resolving challenging cases, including boundary-spanning genes (PRY and Ppr-Y), fragmented Mst77Y copies, and FDY, which has a closely related autosomal paralog. Beyond validating known localizations, the pipeline localized the unmapped gene CG41561 to the kl-1region and reassigned the transcript CR40629-RC from the kl-2 region to kl-5. It also localized 7 of 16 recently transferred Y-linked sequences, including 4 with high confidence. Applied to 904 R6 scaffolds, Digital Kennison assigned 75% to fertility regions, including five currently annotated as autosomal-pericentromeric. Digital Kennison reduces sequence localization from weeks of genetic crosses to minutes of computation while preserving the power of classical translocation mapping.

Drosophila melanogaster↗

PubMed2026

Deletion of the MALAT1 RNA 3' end promotes transcript decay and inhibits proliferation in gastric and breast cancer cells.

The long non-coding RNA MALAT1 is a conserved oncogenic driver whose function relies on a 3' triple-helix motif. While its biochemistry is well-characterized in vitro, the endogenous requirement for this motif in regulating the stability of the transcript and other genes residing in its locus remains unclear. In this study, we employed a dual-sgRNA CRISPR-Cas9 approach to systematically excise triple-helix-forming sequences from the native MALAT1 locus in gastric (AGS) and breast (MCF7) cancer cells. Our findings demonstrate that the 3' end strongly contributes to MALAT1 stability. Perturbations ranging from genomic deletions to a single-base changes trigger transcript collapse and rapid exonucleolytic decay, while the biogenesis of the small RNA mascRNA (a byproduct of MALAT1, also involved in cancer) remains decoupled and unaffected. In cellulo, DMS probing reveals that edited transcripts retain structural complexity in the 3' region. Phenotypically, structural disruption of the 3' end significantly impairs proliferation of both cancer cellular models. These results identify the 3' triple-helix as a determinant of MALAT1 stability and provide endogenous validation for its role in the analyzed AGS and MCF7 cells.

Cancer↗

PubMed2026

The dark genome in cardiovascular medicine.

Only ∼1%-2% of the human genome directly codes for proteins. The remainder consists of non-coding DNA, often referred to as the 'dark genome'. This includes regulatory elements, transposable and repetitive sequences, structural genomic features, pseudogenes, intronic and intergenic regions, and non-coding RNA (ncRNA) genes. These components are increasingly recognized as major regulators of gene expression, cell identity, and disease susceptibility. Currently, dark genome elements, particularly ncRNAs are increasingly recognized as important regulators of cardiovascular health and disease. Advances in genome analysis technologies have greatly improved our understanding of these non-coding regions and revealed clearer connections between the dark genome and cardiovascular traits. This review highlights major parts of the dark genome involved in cardiovascular disease, with emphasis on those for which mechanistic understanding and translational relevance are beginning to emerge. As mechanistic insight into individual and collective components of the dark genome advances, it increasingly enables the development of new opportunities for targeted therapeutics for cardiovascular prevention and disease management.

Humans↗

PubMed2026

A modular class-aware workflow for small RNA sequencing analysis using mouse sperm as a case study.

BACKGROUND: Small RNA sequencing analysis is challenging because RNA classes differ in biogenesis, sequence redundancy, genomic organization, and annotation reliability. Integrated workflows accommodating these constraints remain limited, particularly for fragment-level and cluster-level analysis. METHODS: We present a reproducible, containerized, class-aware workflow for small RNA sequencing analysis, using mouse sperm as a case study. The workflow combines standardized preprocessing with complementary annotation and quantification strategies for microRNAs (miRNAs), transfer RNA-derived small RNAs (tsRNAs), ribosomal RNA-derived small RNAs (rsRNAs), and PIWI-interacting RNA (piRNA)-enriched genomic clusters. Using sperm small RNA data from offspring of lipopolysaccharide (LPS)-exposed male mice, we compared integrated-reference mapping, multi-class annotation, fragment-level tsRNA profiling, and genome-based piRNA cluster analysis, with custom modules for locus-aware harmonization and condition-specific cluster analysis. RESULTS: Integrated-reference mapping aligned 88.17% of reads and retained 690 features after filtering. It identified 11 differentially expressed miRNAs between LPS and controls, while other classes showed limited signal. Fragment-level profiling improved tsRNA resolution. piRNA cluster analysis identified 958 control and 940 LPS clusters, with 18 control-specific and no LPS-specific clusters. CONCLUSION: This workflow supports transparent, reproducible, class-aware interpretation of small RNA sequencing data while emphasizing cautious interpretation of piRNA-enriched signals from total small RNA sequencing.

Small non-coding RNA analysis↗