Non-Coding RNA最新文献

Paratuberculosis or Johne's disease (JD), a chronic granulomatous gastroenteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP), causes huge economic losses and reduces animal welfare in dairy cattle herds worldwide. At present, molecular mechanisms and biological functions involved in immune responses to MAP infection of dairy cattle are not clearly understood. Our purpose was to integrate transcriptomic profiles and competing endogenous RNA (ceRNA) network analyses to identify key messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of peripheral blood mononuclear cells (PBMCs) for MAP infection in dairy cattle. In total, 28 lncRNAs, 42 miRNAs, and 370 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In this regard, we identified 21 hub genes (CCL20, CCL5, CD40, CSF2, CXCL8, EIF2AK2, FOS, IL10, IL17A, IL1A, IL1B, IRF1, MX2, NFKB1, NFKBIA, PTGS2, SOCS3, TLR4, TNF, TNFAIP3, and VCAM1) involved in MAP infection. Furthermore, eight candidate subnets with eight lncRNAs, 29 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 510, 22, and 11 significantly enriched GO terms related to MAP infection in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways related to MAP infection that were enriched included the immune system process, defense response, response to cytokine, leukocyte migration, regulation of T cell activation, defense response to bacterium, NOD-like receptor, B cell receptor, TNF, NF-kappa B, IL-17, and T cell receptor signaling pathways. Contributions of transcriptome profiles from MAP-positive and MAP-negative sample groups plus a ceRNA regulatory network underlying phenotypic differences in the intensity of pathogenicity of JD provided novel insights into molecular mechanisms associated with immune system responses to MAP infection in dairy cattle.

Noncoding RNAs (ncRNAs), which include small nuclear RNAs (snRNAs), small nucleolar RNAs (snoRNAs), microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), are RNA molecules that arise from genomic regions without protein-coding potential and display a variety of mechanisms and functions by regulating gene expression at the transcriptional, RNA processing, and translational levels and participating in virtually all cellular processes [...].

Telomerase is an enzyme involved in the maintenance of telomeres. Telomere shortening due to the end-replication problem is a threat to the genome integrity of all eukaryotes. Telomerase inside cells depends on a myriad of protein-protein and RNA-protein interactions to properly assemble and regulate the function of the telomerase holoenzyme. These interactions are well studied in model eukaryotes, like humans, yeast, and the ciliated protozoan known as Tetrahymena thermophila. Emerging evidence also suggests that deep-branching eukaryotes, such as the parasitic protist Trypanosoma brucei require conserved and novel RNA-binding proteins for the assembly and function of their telomerase. In this review, we will discuss telomerase regulatory pathways in the context of telomerase-interacting proteins, with special attention paid to RNA-binding proteins. We will discuss these interactors on an evolutionary scale, from parasitic protists to humans, to provide a broader perspective on the extensive role that protein-protein and RNA-protein interactions play in regulating telomerase activity in eukaryotes.

Hypertension is a chronic, multifactorial disease, leading to high cardiovascular morbidity and mortality globally. Despite the advantages of pharmaceutical treatments, natural products have gained scientific interest due to their emerging phytotherapeutic properties. Chios mastic is a natural Greek product, consisting of bioactive compounds which modify microRNAs' (small, expression-regulating molecules) expression. In this study, we investigated the antihypertensive properties of Chios mastic through the assessment of miR-21 levels. Herein, plasma samples of 57 individuals with hypertension, recruited for the purposes of the HYPER-MASTIC study, were analyzed. This was a clinical trial with Chios mastic supplements in which the patients were divided into groups receiving high and low mastic doses and placebo supplements, respectively. miR-21 was significantly upregulated in patients compared to normotensive individuals. Mean changes in miR-21 levels were statistically significant, after adjusting for sex and age, between the placebo and low-dose group and between the low- and high-dose group. Post-intervention miR-21 levels were positively associated with night-time systolic blood pressure, pulse pressure, and central systolic mean arterial pressure and negatively associated with night-time pulse wave velocity in the low-dose group. Our findings suggest a potential implication of miR-21 in the association of Chios mastic with night-time blood pressure measurements.

The long non-coding RNA (lncRNA) hepatocyte nuclear factor-1 alpha (HNF1A) antisense RNA 1 (HNF1A-AS1) is an important lncRNA for liver growth, development, cell differentiation, and drug metabolism. Like many lncRNAs, HNF1A-AS1 has multiple annotated alternative transcripts in the human genome. Several fundamental biological questions are still not solved: (1) How many transcripts really exist in biological samples, such as liver samples and liver cell lines? (2) What are the expression patterns of different alternative HNF1A-AS1 transcripts at different conditions, including during cell growth and development, after exposure to xenobiotics (such as drugs), and in disease conditions, such as metabolic dysfunction-associated steatotic liver disease (MASLD), alcohol-associated liver disease (ALD) cirrhosis, and obesity? (3) Does the siRNA used in previous studies knock down one or multiple transcripts? (4) Do different transcripts have the same or different functions for gene regulation? The presented data confirm the existence of several annotated HNF1A-AS1 transcripts in liver samples and cell lines, but also identify some new transcripts, which are not annotated in the Ensembl genome database. Expression patterns of the identified HNF1A-AS1 transcripts are highly correlated with the cell differentiation of matured hepatocyte-like cells from human embryonic stem cells (hESC), growth and differentiation of HepaRG cells, in response to rifampicin induction, and in various liver disease conditions. The expression levels of the HNF1A-AS1 transcripts are also highly correlated to the expression of cytochrome P450 enzymes, such as CYP3A4, during HepaRG growth, differentiation, and in response to rifampicin induction.

Temporal lobe epilepsy (TLE) represents the most common form of refractory focal epilepsy. The identification of innovative clinical biomarkers capable of categorizing patients with TLE, allowing for improved treatment and outcomes, still represents an unmet need. Circulating microRNAs (c-miRNAs) are short non-coding RNAs detectable in body fluids, which play crucial roles in the regulation of gene expression. Their characteristics, including extracellular stability, detectability through non-invasive methods, and responsiveness to pathological changes and/or therapeutic interventions, make them promising candidate biomarkers in various disease settings. Recent research has investigated c-miRNAs in various bodily fluids, including serum, plasma, and cerebrospinal fluid, of TLE patients. Despite some discrepancies in methodologies, cohort composition, and normalization strategies, a common dysregulated signature of c-miRNAs has emerged across different studies, providing the basis for using c-miRNAs as novel biomarkers for TLE patient management.

MicroRNAs (miRs) have been implicated in numerous diseases, presenting an attractive target for the development of novel therapeutics. The various regulatory roles of miRs in cellular processes underscore the need for precise strategies. Recent advances in RNA research offer hope by enabling the identification of small molecules capable of selectively targeting specific disease-associated miRs. This understanding paves the way for developing small molecules that can modulate the activity of disease-associated miRs. Herein, we discuss the progress made in the field of drug discovery processes, transforming the landscape of miR-targeted therapeutics by small molecules. By leveraging various approaches, researchers can systematically identify compounds to modulate miR function, providing a more potent intervention either by inhibiting or degrading miRs. The implementation of these multidisciplinary approaches bears the potential to revolutionize treatments for diverse diseases, signifying a significant stride towards the targeting of miRs by precision medicine.

Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.

Non-coding RNAs (ncRNAs) are RNA molecules that do not code for protein but play key roles in regulating cellular processes. NcRNAs globally affect gene expression in diverse physiological and pathological contexts. Functionally important ncRNAs act in chromatin modifications, in mRNA stabilization and translation, and in regulation of various signaling pathways. Non-alcoholic fatty liver disease (NAFLD) is a set of conditions caused by the accumulation of triacylglycerol in the liver. Studies of ncRNA in NAFLD are limited but have demonstrated that ncRNAs play a critical role in the pathogenesis of NAFLD. In this review, we summarize NAFLD's pathogenesis and clinical features, discuss current treatment options, and review the involvement of ncRNAs as regulatory molecules in NAFLD and its progression to non-alcoholic steatohepatitis (NASH). In addition, we highlight signaling pathways dysregulated in NAFLD and review their crosstalk with ncRNAs. Having a thorough understanding of the disease process's molecular mechanisms will facilitate development of highly effective diagnostic and therapeutic treatments. Such insights can also inform preventive strategies to minimize the disease's future development.

Biological research has demonstrated the significance of identifying miRNA-disease associations in the context of disease prevention, diagnosis, and treatment. However, the utilization of experimental approaches involving biological subjects to infer these associations is both costly and inefficient. Consequently, there is a pressing need to devise novel approaches that offer enhanced accuracy and effectiveness. Presently, the predominant methods employed for predicting disease associations rely on Graph Convolutional Network (GCN) techniques. However, the Graph Convolutional Network algorithm, which is locally aggregated, solely incorporates information from the immediate neighboring nodes of a given node at each layer. Consequently, GCN cannot simultaneously aggregate information from multiple nodes. This constraint significantly impacts the predictive efficacy of the model. To tackle this problem, we propose a novel approach, based on HyperGCN and Sørensen-Dice loss (HGSMDA), for predicting associations between miRNAs and diseases. In the initial phase, we developed multiple networks to represent the similarity between miRNAs and diseases and employed GCNs to extract information from diverse perspectives. Subsequently, we draw into HyperGCN to construct a miRNA-disease heteromorphic hypergraph using hypernodes and train GCN on the graph to aggregate information. Finally, we utilized the Sørensen-Dice loss function to evaluate the degree of similarity between the predicted outcomes and the ground truth values, thereby enabling the prediction of associations between miRNAs and diseases. In order to assess the soundness of our methodology, an extensive series of experiments was conducted employing the Human MicroRNA Disease Database (HMDD v3.2) as the dataset. The experimental outcomes unequivocally indicate that HGSMDA exhibits remarkable efficacy when compared to alternative methodologies. Furthermore, the predictive capacity of HGSMDA was corroborated through a case study focused on colon cancer. These findings strongly imply that HGSMDA represents a dependable and valid framework, thereby offering a novel avenue for investigating the intricate association between miRNAs and diseases.