Vault RNAs (vtRNAs) are a novel group of non-coding RNAs that are involved in various signaling mechanisms. vtRNAs are joined by three proteins major vault protein (MVP), vault poly (ADP-ribose) polymerase (VPARP), and telomerase-associated protein 1 (TEP1) to form the vault complex. In humans, only four vtRNA including vtRNA 1-1, vtRNA 1-2, vtRNA 1-3, vtRNA 2-1) have been discovered. In nerve cells, vtRNA is involved in synapse formation through MAPK signaling. vtRNA travels to the distal area of neurites as a key unit in the vault complex. Moreover, tRNA is detached from the vault complex in the neurite via a mitotic kinase Aurora-A-reliant MVP phosphorylation. Several molecules contribute to the formation of vtRNAs. For instance, SRSF2 and NSUN2 and their attachment to vtRNA1-1 determines the production of small-vtRNAs. Through the same factors, vtRNAs could play a role in neurodevelopmental deficits. Addition the role of vtRNA expression and vault proteins has been recently studied in neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) as well as brain cancers. While the mechanisms of vtRNA involvement in neurological disorders is not well-demonstrated, we believe this could be related to the impact of vtRNA regulation in autophagy, immunoregulation, RNA stability, cellular stress, apoptosis, and regulation of other epigenetic pathways. The present review captures the state-of-the-art regarding the role of vtRNAs in neurodevelopment, normal nervous system function, and neurological disorders.

The sources and degradation profiles of dissolved environmental RNAs from fish in water remain unknown. In this study, laboratory experiments and mathematical modelling were conducted to investigate the permeability of RNA extracted from zebrafish cells through filters, the release of dissolved environmental RNAs from live and dying zebrafish cells, and the degradation of RNA extracted from zebrafish cells in a non-sterile aqueous environment. This research aimed to provide biological and ecological insights into fish RNAs dissolved in water. The results showed that most of the RNA extracted from zebrafish cells was detected in the filtrates after passage through 0.45 µm filters. Over the course of the 6-day experiment, dynamic levels of the RNAs in the liquid environment containing live or dying zebrafish cells were determined. The release and degradation rates of dissolved environmental RNA from zebrafish cells were calculated using mathematical modelling. RNA extracted from zebrafish cells degraded in non-sterile water in the tubes, and after 2 months, more than 15% of the RNAs in the water remained detectable. The half-life of the RNA in the tubes was approximately 20 ~ 43 days. The modelling results suggest that the levels of the dissolved environmental fish RNAs in natural waters or aquariums could be so low that it would be difficult to detect them using current techniques. The results obtained in this study will help develop new methods for measuring the dynamics of dissolved environmental fish RNAs in water and determining their significance.

Human metapneumovirus (hMPV) is a significant global pathogen that causes acute respiratory tract infections, especially in infants, young children, the elderly, and immunocompromised individuals. Despite its increasing prevalence, there are currently no vaccines or effective treatments available for hMPV. The pathogenesis of hMPV infection is a complex process involving a multitude of host factors and viral receptors. These interactions determine the virus ability to enter host cells, replicate, and evade the immune response. This review is the first to provide a comprehensive overview of the current understanding of host-virus interactions in hMPV pathogenesis. By elucidating these mechanisms, we can identify potential targets for antiviral drugs and improve the management of hMPV infections.

The diversity of molecular entities emerging from a single gene are recognized. Several studies have thus established the cellular role(s) of transcript variants and protein isoforms. A step ahead in challenging the central dogma towards expanding molecular diversity is the identification of fusion genes, chimeric transcripts and chimeric proteins that harbor sequences from more than one gene. The mechanisms for generation of chimeras largely follow similar patterns across all levels of gene regulation but also have interdependence and mutual exclusivity. Whole genome and RNA-seq technologies supported by development of computational algorithms and programs for processing datasets have increasingly enabled the identification of fusion genes and chimeric transcripts, while the discovery of chimeric proteins is as yet more subtle. Earlier thought to be associated with cellular transformation, the contribution of chimeric molecules to normal physiology is also realized and found to influence the expression of their parental genes and regulate cellular pathways. This review offers a collective and comprehensive overview of cellular chimeric entities encompassing the mechanisms involved in their generation, insights on their evolution, functions in gene regulation and their current and novel clinical applications.

Salinity plays a vital role in fish aquaculture, profoundly influencing the growth and development of fish. Scales, as the protective outer layer of fish, function as a critical defense against external factors. In this study, we employed transcriptome sequencing to analyze the ceRNA expression profiles to reveal the effect of salinity acclimation on transcriptional expression changes in the scales of cobia (Rachycentron canadum). The results revealed that after being exposed to a salinity level of 15 ‰ for just one day (1D), a total of 407 mRNAs/genes were significantly regulated; 66 miRNAs were respectively significantly regulated; and 109 target genes of the differentially expressed miRNAs were significantly regulated; a total of 185 differently expressed lncRNAs and 292 differently expressed target genes (DetGenes) of differently expressed lncRNAs were also identified. After 7 days (7D), a total of 2195 mRNAs/genes were found to be significantly regulated and 82 miRNAs were significantly regulated; among the target genes of the differentially expressed miRNAs, 245 were regulated. Moreover, 438 differently expressed lncRNAs and 681 DetGenes of these lncRNAs were identified. Subsequent analysis through GO, KEGG pathway, in 1D vs. CG (control group), DeGenes, which first respond to changes in salinity, are mainly involved in negative regulation of macrophage differentiation, negative regulation of granulocyte differentiation and negative regulation of phagocytosis, and are mainly related to biological processes related to the immune function of fish. After a 7-day process, DeGenes were enriched in the collagen fibril organization, regulation of nodal signaling pathway and cell recognition biology processes. These biological processes are not only related to the immune function of fish, but more importantly, to the physiological structure of fish. By analyzing the co down-regulated miRNAs of 1D vs. CG, as well as 7D vs. CG, the functions of these miRNAs are mainly related to bone differentiation and development. In addition，ceRNA network uncovered that the effect of salinity is temporal. The first competing lncRNAs mainly regulated genes related to physiological processes and biological development, while target genes related to immunity and body defense were less competitive. On the contrary, after a period of salinity treatment, the types of competing lncRNAs involved changed.

Vascular dementia (VaD) is a progressive neurodegenerative disease characterized by cognitive decline and memory deficits. Despite its significant prevalence and impact, the pathophysiology of VaD remains poorly understood, and current treatments are limited to symptom management. Emerging evidence highlights the importance of lifestyle-associated risk factors in VaD, emphasizing the role of gene-environment interactions, particularly in the realm of epigenetics. While preclinical studies using animal models have provided valuable insights into epigenetic mechanisms, the translatability of these findings to human clinical settings remains limited, and research into VaD-specific epigenetics is still in its infancy. This review aims to elucidate the intricate interplay between epigenetics and VaD, shedding light on potential therapeutic interventions rooted in epigenetic mechanisms. By synthesizing insights from existing literature, we also discuss the challenges and opportunities in translating preclinical findings into clinically viable treatments, underscoring the need for further research to bridge the gap between animal models and human applications.

Cancer is the world's leading cause of death impacting millions of lives globally. The increasing research over the past several decades has focused on the development of new anticancer drugs, but still cancer continues to be a global health challenge. Thus, several new alternative therapeutic strategies have been tried for the drug design and discovery. Purine and pyrimidine heterocyclic compounds have received attention recently due to their potential in targeting various cancers. It is evident from the recently published data over the last decade that incorporation of the purine and pyrimidine rings in the synthesized derivatives resulted in the development of potent anticancer molecules. This review presents synthetic strategies encompassing several examples of recently developed purine and pyrimidine-containing compounds as anticancer agents. In addition, their structure-activity relationships are represented in the schemes indicating the fragment or groups that are essential for the enhanced anticancer activities. Purine and pyrimidines combined with other heterocyclic compounds have resulted in many novel anticancer molecules that address the challenges of drug resistance. The purine and pyrimidine derivatives showed significantly enhanced anticancer activities against targeted receptor proteins with numerous compounds with an IC50 value in the nanomolar range. The review will support medicinal chemists and contribute in progression and development of synthesis of more potent chemotherapeutic drug candidates to mitigate the burden of this dreadful disease.

RNA plays a crucial role not only in information transfer as messenger RNA during gene expression but also in various biological functions as non-coding RNAs. Understanding mechanical mechanisms of function needs tertiary structure information; however, experimental determination of three-dimensional RNA structures is costly and time-consuming, leading to a substantial gap between RNA sequence and structural data. To address this challenge, we developed NuFold, a novel computational approach that leverages state-of-the-art deep learning architecture to accurately predict RNA tertiary structures. NuFold is a deep neural network trained end-to-end for the output structure from the input sequence. NuFold incorporates a nucleobase center representation, which enables flexible conformation of ribose rings. Benchmark study showed that NuFold clearly outperformed energy-based methods and demonstrated comparable results with existing state-of-the-art deep-learning-based methods. NuFold exhibited a particular advantage in building correct local geometries of RNA. Analyses of individual components in the NuFold pipeline indicated that the performance improved by utilizing metagenome sequences for multiple sequence alignment and increasing the number of recycling. NuFold is also capable of predicting multimer complex structures of RNA by linking the input sequences.

This study conducts an in-depth review of the correlation between testis tissue changes and circulating microRNAs (miRNA) in diabetes-induced male reproductive complications, drawing upon both animal and clinical studies. The original articles published in English that specifically investigate miRNAs linked to male infertility in humans or animals with either type I or ΙΙ diabetes mellitus were included. The relevant articles were gathered from the PubMed, Google Scholar, Cochrane Library, and ScienceDirect databases. The quality of study was assessed utilizing the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies. We collected an overall number of 1989 citations relating to our research subject. Following the elimination of articles based on the criteria, a total of 20 papers were included in the study. Aberrant expression profiles of 25 miRNAs were identified in diabetes associated with male reproductive issues, with 15 miRNAs exhibiting increased expression and 10 miRNAs showing decreased expression. Among the chosen publications, eighteen were identified as low-risk and two were classed as moderate quality. The dysregulated miRNAs were linked to testicular injury, disrupted steroid production, decreased sperm development and quality, and erectile dysfunction. The results demonstrate that the miRNA-mRNA network is linked to the pathological progression of diabetic testicular damage or erectile dysfunction. From a therapeutic perspective, the identification of circulating miRNAs could be beneficial in the timely identification and prevention of diabetes problems, such as diabetes-induced male infertility. Among all signaling pathways influenced by modified miRNAs, the Bax-caspase-3, MAPK, PI3K-Akt, and eNOS-cGMP-PKC were the main deregulated pathways.

RNAs are often studied in nonnative sequence contexts to facilitate structural studies. However, seemingly innocuous changes to an RNA sequence may perturb the native structure and generate inaccurate or ambiguous structural models. To facilitate the investigation of native RNA secondary structure by selective 2' hydroxyl acylation analyzed by primer extension (SHAPE), we engineered an approach that couples minimal enzymatic steps to RNA chemical probing and mutational profiling (MaP) reverse transcription (RT) methods-a process we call template switching and mutational profiling (Switch-MaP). In Switch-MaP, RT templates and additional library sequences are added postprobing through ligation and template switching, capturing reactivities for every nucleotide. For a candidate SAM-I riboswitch, we compared RNA structure models generated by the Switch-MaP approach to those of traditional primer-based MaP, including RNAs with or without appended structure cassettes. Primer-based MaP masked reactivity data in the 5' and 3' ends of the RNA, producing ambiguous ensembles inconsistent with the conserved SAM-I riboswitch secondary structure. Structure cassettes enabled unambiguous modeling of an aptamer-only construct but introduced nonnative interactions in the full-length riboswitch. In contrast, Switch-MaP provided reactivity data for all nucleotides in each RNA and enabled unambiguous modeling of secondary structure, consistent with the conserved SAM-I fold. Switch-MaP is a straightforward alternative approach to primer-based and cassette-based chemical probing methods that precludes primer masking and the formation of alternative secondary structures due to nonnative sequence elements.

There is accumulating evidence indicating a close crosstalk between key molecular events regulating cell growth and proliferation, which could profoundly impact carcinogenesis and its progression. Here we focus on reviewing observations highlighting the interplay between epigenetic modifications, irreversible cell cycle arrest or senescence, and cellular redox metabolism. Epigenetic alterations, such as DNA methylation and histone modifications, dynamically influence tumour transcriptome, thereby impacting tumour phenotype, survival, growth and spread. Interestingly, the acquisition of senescent phenotype can be triggered by epigenetic changes, acting as a double-edged sword via its ability to suppress tumorigenesis or by facilitating an inflammatory milieu conducive for cancer progression. Concurrently, an aberrant redox metabolism, which is a function of the balance between reactive oxygen species (ROS) generation and intracellular anti-oxidant defences, influences signalling cascades and genomic stability in cancer cells by serving as a critical link between epigenetics and senescence. Recognizing this intricate interconnection offers a nuanced perspective for therapeutic intervention by simultaneously targeting specific epigenetic modifications, modulating senescence dynamics, and restoring redox homeostasis.

Around the world, oral cancer (OC) is a major public health problem, resulting in a significant number of deaths each year. Early detection and treatment are crucial for improving patient outcomes. Recent progress in DNA sequencing and transcriptome profiling has revealed extensive non-coding RNAs (ncRNAs) transcription, underscoring their regulatory importance. NcRNAs influence genomic transcription and translation and molecular signaling pathways, making them valuable for various clinical applications. Combining spatial transcriptomics (ST) and spatial metabolomics (SM) with single-cell RNA sequencing provides deeper insights into tumor microenvironments, enhancing diagnostic and therapeutic precision for OC. Additionally, the exploration of salivary biomarkers offers a non-invasive diagnostic avenue. This article explores the potential of ncRNAs as diagnostic and therapeutic tools for OC.

RNA structure is essential for the function of many non-coding RNAs. Using multiple homologous sequences, which share structure and function, secondary structure can be predicted with much higher accuracy than with a single sequence. It can be difficult, however, to establish a set of homologous sequences when their structure is not yet known. We developed a method to identify sequences in a set of putative homologs that are in fact non-homologs.

Previously, we developed TurboFold to estimate conserved structure using multiple, unaligned RNA homologs. Here, we report that the positive predictive value of TurboFold is significantly reduced by the presence of contamination by non-homologous sequences, although the reduction is less than 1%. We developed a method called DecoyFinder, which applies machine learning trained with features determined by TurboFold, to detect sequences that are not homologous with the other sequences in the set. This method can identify approximately 45% of non-homologous sequences, at a rate of 5% misidentification of true homologous sequences.

DecoyFinder and TurboFold are incorporated in RNAstructure, which is provided for free and open source under the GPL V2 license. It can be downloaded at http://rna.urmc.rochester.edu/RNAstructure.html.

Despite the numerous sequencing methods available, the diversity in RNA size and chemical modification makes it difficult to capture all RNAs in a cell. We developed a method that combines quasi-random priming with template switching to construct sequencing libraries from RNA molecules of any length and with any type of 3' modifications, allowing for the sequencing of virtually all RNA species. Our ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to identify and quantify all classes of coding and non-coding RNAs. With LIDAR, we comprehensively characterized the transcriptomes of mouse embryonic stem cells, neural progenitor cells, mouse tissues, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared with traditional ligation-dependent sequencing methods and uncovered tDRs with blocked 3' ends that had previously escaped detection. Therefore, LIDAR can capture all RNAs in a sample and uncover RNA species with potential regulatory functions.

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are two typical types of non-coding RNAs that interact and play important regulatory roles in many animal organisms. Exploring the unknown interactions between lncRNAs and miRNAs contributes to a better understanding of their functional involvement. Currently, studying the interactions between lncRNAs and miRNAs heavily relies on laborious biological experiments. Therefore, it is necessary to design a computational method for predicting lncRNA-miRNA interactions. In this work, we propose a method called MPGK-LMI, which utilizes a graph attention network (GAT) to predict lncRNA-miRNA interactions in animals. First, we construct a meta-path similarity matrix based on known lncRNA-miRNA interaction information. Then, we use GAT to aggregate the constructed meta-path similarity matrix and the computed Gaussian kernel similarity matrix to update the feature matrix with neighbourhood information. Finally, a scoring module is used for prediction. By comparing with three state-of-the-art algorithms, MPGK-LMI achieves the best results in terms of performance, with AUC value of 0.9077, AUPR of 0.9327, ACC of 0.9080, F1-score of 0.9143 and precision of 0.8739. These results validate the effectiveness and reliability of MPGK-LMI. Additionally, we conduct detailed case studies to demonstrate the effectiveness and feasibility of our approach in practical applications. Through these empirical results, we gain deeper insights into the functional roles and mechanisms of lncRNA-miRNA interactions, providing significant breakthroughs and advancements in this field of research. In summary, our method not only outperforms others in terms of performance but also establishes its practicality and reliability in biological research through real-case analysis, offering strong support and guidance for future studies and applications.

Bacteria of the genus Pseudomonas are ubiquitous on Earth due to their great metabolic versatility and adaptation to fluctuating environments and different hosts. Some groups are important animal/human and plant pathogens, whereas others are studied for their biotechnological applications, including bioremediation, biological control of phytopathogens and plant growth promotion. Notably, their adaptability is mediated by various signal transduction systems, with the post-transcriptional Gac-Rsm cascade playing a key role. This pervasive Pseudomonas pathway controls major transitions at the population level, such as motile/sessile lifestyle, primary/secondary metabolism or replicative/infective behaviour. A hallmark of the Gac-Rsm cascade is the participation of small, regulatory, non-coding RNAs of the Rsm clan. These RNAs are synthetised in response to cell-density-dependent autoinducer signals channelled through the GacS/GacA two-component system, and they counteract, by molecular mimicry, the translational control that RNA-binding proteins of the RsmA family exert over hundreds of mRNAs. Rsm RNAs have been investigated in a few Pseudomonas model species, evidencing the presence of a variable number and families of genes depending on the taxonomic clade. However, the global picture of the distribution of these riboregulators at the genus level was unknown until now. We have undertaken a comprehensive survey and annotation of the vast array of gene sequences encoding members of the Rsm RNA clan in 245 complete genomes that cover 28 phylogenomic clades across the entire genus. The properties of the different families of rsm genes, their phylogenetic radiation, as well as the features of their promoters and adjacent regions, are discussed. The novel insights presented in our manuscript will significantly boost research on the biology of these prevalent RNAs in understudied species of the genus Pseudomonas and closely related genera.

The role of microRNAs (miRNAs) in the pathogenesis of rare genetic disorders has been gradually discovered. MiRNAs, a class of small non-coding RNAs, regulate gene expression by silencing target messenger RNAs (mRNAs). Their biogenesis involves transcription into primary miRNA (pri-miRNA), processing by the DROSHA-DGCR8 (DiGeorge syndrome critical region 8) complex, exportation to the cytoplasm, and further processing by DICER to generate mature miRNAs. These mature miRNAs are incorporated into the RNA-induced silencing complex (RISC), where they modulate gene expression.

The dysregulation of miRNAs is implicated in various Mendelian disorders and familial diseases, including DICER1 syndrome, neurodevelopmental disorders (NDDs), and conditions linked to mutations in miRNA-binding sites. We summarized a few mechanisms how miRNA processing and regulation abnormalities lead to rare genetic disorders. Examples of such genetic diseases include hearing loss associated with MIR96 mutations, eye disorders linked to MIR184 mutations, and skeletal dysplasia involving MIR140 mutations.

Understanding these molecular mechanisms is crucial, as miRNA dysregulation is a key factor in the pathogenesis of these conditions, offering significant potential for the diagnosis and potential therapeutic intervention.

RNA structural motifs are the recurrent segments in RNA three-dimensional structures that play a crucial role in the functional diversity of RNAs. Understanding the similarities and variations within these recurrent motif groups is essential for gaining insights into RNA structure and function. While recurrent structural motifs are generally assumed to be composed of the same isosteric base interactions, this consistent pattern is not observed across all examples of these motifs. Existing methods for analyzing and comparing RNA structural motifs may overlook variations in base interactions and associated nucleotides. RNAMotifProfile is a novel profile-to-profile alignment algorithm that generates a comprehensive profile from a group of structural motifs, incorporating all base interactions and associated nucleotides at each position. By structurally aligning input motif instances using a guide-tree-based approach, RNAMotifProfile captures the similarities and variations within recurrent motif groups. Additionally, RNAMotifProfile can function as a motif search tool, enabling the identification of instances of a specific motif family by searching with the corresponding profile. The ability to generate accurate and comprehensive profiles for RNA structural motif families, and to search for these motifs, facilitates a deeper understanding of RNA structure-function relationships and potential applications in RNA engineering and therapeutic design.

Predicting the consensus structure of a set of aligned RNA homologs is a convenient method to find conserved structures in an RNA genome, which has many applications including viral diagnostics and therapeutics. However, the most commonly used tool for this task, RNAalifold, is prohibitively slow for long sequences, due to a cubic scaling with the sequence length, taking over a day on 400 SARS-CoV-2 and SARS-related genomes (∼30,000nt). We present LinearAlifold, a much faster alternative that scales linearly with both the sequence length and the number of sequences, based on our work LinearFold that folds a single RNA in linear time. Our work is orders of magnitude faster than RNAalifold (0.7 h on the above 400 genomes, or ∼36× speedup) and achieves higher accuracies when compared to a database of known structures. More interestingly, LinearAlifold's prediction on SARS-CoV-2 correlates well with experimentally determined structures, substantially outperforming RNAalifold. Finally, LinearAlifold supports two energy models (Vienna and BL*) and four modes: minimum free energy (MFE), maximum expected accuracy (MEA), ThreshKnot, and stochastic sampling, each of which takes under an hour for hundreds of SARS-CoV variants. Our resource is at: https://github.com/LinearFold/LinearAlifold (code) and http://linearfold.org/linear-alifold (server).

In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer's disease.

RNA pseudoknots are RNA molecules with specialized three-dimensional structures that play important roles in various biological processes. To understand the functions and mechanisms of pseudoknots, it is essential to elucidate their structures and folding pathways. The most fundamental step in RNA folding is the opening and closing of a base pair. The effect of flexible loops on the base pair in pseudoknots remains unclear. In this work, we use molecular dynamics simulations and Markov state model to study the configurations, thermodynamic and kinetic of single base pair in pseudoknots. We find that the presence of the loop leads to a trap state. In addition, the rate-limiting step for the formation of base pair is the disruption of the trap state, rather than the open state to the closed state, which is quite different from the previous studies on non-pseudoknot RNA. For the thermodynamic parameters in pseudoknots, we find that the entropy difference upon opening the base pair between this simulation and the nearest-neighbor model results from the different entropy of different lengths of loop in solution. The thermodynamic parameters of the stack in pseudoknot are close to the nearest-neighbor parameters. The bases on the loop have different distribution patterns in different states, and the slow transition states of the loop are determined by the orientation of the bases.

Small non-coding RNAs (sncRNAs) derived from tRNAs are known as tRNA-derived small RNAs (tsRNAs). These tsRNAs are further categorized into tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs), which play significant roles in the various molecular mechanisms underlying certain human diseases. However, the generation of tsRNAs and their potential roles during Dengue virus (DENV) infection is not yet known. Here, we performed small RNA sequencing to identify the generation and alterations in tsRNAs expression profiles of DENV-infected Huh7 cells. Upon DENV infection, tRNA fragmentation was found to be increased. We identified a significant number of differentially expressed tsRNAs during DENV infection. Interestingly, the 3'tRF population showed upregulation, while the i-tRF population exhibited downregulation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to analyze the impact of differentially expressed tsRNAs on DENV pathogenesis. Our results suggest that differentially expressed tsRNAs are involved in transcriptional regulation via RNA polymerase II promoter and metabolic pathways. Overall, our study contributes significantly to our understanding of the roles played by tsRNAs in the complex dynamics of DENV infection.

Spermatogenesis produces male gametes from spermatogonial stem cells (SSC), beginning at puberty. Modern-day laboratory techniques allow for the long-term culture of SSC and in vitro spermatogenesis. The specific biochemical processes that occur during spermatogenesis remain poorly understood. One particular element of spermatogenesis that has yet to be characterized is the role of microRNAs (miRNA), short, non-transcribed RNAs that act as post-translational regulators of gene activity. In this study, we seek to describe the presence of miRNA in a two-dimensional (2D) SSC culture and a 3D human testis organoid (HTO) system. Testicular cells were isolated from the frozen tissue of three brain-dead subjects, propagated in cultures for four to five weeks, and used to form 3D HTOs. Following organoid formation, differentiation of testicular cells was induced. RNA was isolated from the whole testis tissue (WT) showing in vivo conditions, HTO Day Zero (2D SSC culture), Day 2 HTOs, and Day 23 differentiated HTOs, then analyzed for changes in miRNA expression using the Nanostring nCounter miRNA panel. One hundred ninety-five miRNAs met the criteria for expression in WT, 186 in 2D culture, 190 in Day 2 HTOs, and 187 in differentiated HTOs. One hundred thirty-three miRNAs were common across all conditions, and 41, 17, 6, and 11 miRNAs were unique for WT, 2D culture, Day 2 HTOs, and differentiated HTOs, respectively. Twenty-two miRNAs were similar between WT and differentiated HTOS. We evaluated the miRNA expression profiles of progressively complex stages of testicular cell culture, culminating in a 3D organoid model capable of meiotic differentiation, and compared these to WT. We identified a great variance between the native tissue and the culture system; however, some miRNAs are preserved. These data may provide avenues for deeper understanding of spermatogenesis and the ability to improve this process in the laboratory. Research on miRNA continues to be an essential avenue for understanding human spermatogenesis.

piwiRNA is a kind of non-coding RNA (ncRNA) that cannot be translated into proteins. It helps in understanding the study of gametes generation and regulation of gene expression over both transcriptional and post-transcriptional levels. piwiRNA has the function of instructing deadenylation, animal fertility, silencing transposons, fighting viruses, and regulating endogenous genes. Due to the great significance of piwiRNA, prediction of piwiRNA is essential for crucial cellular functions. Several predictors were established for prediction of piwiRNA. However, improving the prediction of piwiRNA is highly desirable. In the current study, we developed a more promising predictor named, BLP-piwiRNA. The features are explored by reverse complement k-mer, gapped-k-mer composition, and k-mer composition. The feature set of all descriptors is fused and the best features are selected by cascade and relief feature selection strategies. The best feature sets are provided to random forest (RF), deep neural network (DNN), and support vector machine (SVM). The models validation are examined by 10-fold test. DNN with optimal features of Cascade feature selection approach secured the highest prediction results. The results illustrate that BLP-piwiRNA effectively outperforms the existing studies. The proposed approach would be beneficial for both research community and drug development industry. BLP-piwiRNA would serve as novel biomarkers and therapeutic targets for tumor diagnostics and treatment.Communicated by Ramaswamy H. Sarma.

For many clinically prevalent severe injuries, the inherent regenerative capacity of skeletal muscle remains inadequate. Skeletal muscle tissue engineering (SMTE) seeks to meet this clinical demand. With continuous progress in biomedicine and related technologies including micro/nanotechnology and 3D printing, numerous studies have uncovered various intrinsic mechanisms regulating skeletal muscle regeneration and developed tailored biomaterial systems based on these understandings. Here, the skeletal muscle structure and regeneration process are discussed and the diverse biomaterial systems derived from various technologies are explored in detail. Biomaterials serve not merely as local niches for cell growth, but also as scaffolds endowed with structural or physicochemical properties that provide tissue regenerative cues such as topographical, electrical, and mechanical signals. They can also act as delivery systems for stem cells and bioactive molecules that have been shown as key participants in endogenous repair cascades. To achieve bench-to-bedside translation, the typical effect enabled by biomaterial systems and the potential underlying molecular mechanisms are also summarized. Insights into the roles of biomaterials in SMTE from cellular and molecular perspectives are provided. Finally, perspectives on the advancement of SMTE are provided, for which gene therapy, exosomes, and hybrid biomaterials may hold promise to make important contributions.

DNA droplets, artificial liquid-like condensates of well-engineered DNA sequences, allow the critical aspects of phase-separated biological condensates to be harnessed programmably, such as molecular sensing and phase-state regulation. In contrast, their RNA-based counterparts remain less explored despite more diverse molecular structures and functions ranging from DNA-like to protein-like features. Here, we design and demonstrate computational RNA droplets capable of two-input AND logic operations. We use a multibranched RNA nanostructure as a building block comprising multiple single-stranded RNAs. Its branches engaged in RNA-specific kissing-loop (KL) interaction enables the self-assembly into a network-like microstructure. Upon two inputs of target miRNAs, the nanostructure is programmed to break up into lower-valency structures that are interconnected in a chain-like manner. We optimize KL sequences adapted from viral sequences by numerically and experimentally studying the base-wise adjustability of the interaction strength. Only upon receiving cognate microRNAs, RNA droplets selectively show a drastic phase-state change from liquid to dispersed states due to dismantling of the network-like microstructure. This demonstration strongly suggests that the multistranded motif design offers a flexible means to bottom-up programming of condensate phase behavior. Unlike submicroscopic RNA-based logic operators, the macroscopic phase change provides a naked-eye-distinguishable readout of molecular sensing. Our computational RNA droplets can be applied to in situ programmable assembly of computational biomolecular devices and artificial cells from transcriptionally derived RNA within biological/artificial cells.

Long noncoding RNAs (lncRNAs) play important roles in various biological processes. However, the regulatory roles of lncRNAs underlying fruit development have not been extensively studied. The pumpkin (Cucurbita spp.) is a preferred model for understanding the molecular mechanisms regulating fruit development because of its variable shape and size and large inferior ovary. Here, we performed strand-specific transcriptome sequencing on pumpkin (Cucurbita maxima "Rimu") fruits at 6 developmental stages and identified 5,425 reliably expressed lncRNAs. Among the 332 lncRNAs that were differentially expressed during fruit development, the lncRNA MSTRG.44863.1 was identified as a negative regulator of pumpkin fruit development. MSTRG.44863.1 showed a relatively high expression level and an obvious period-specific expression pattern. Transient overexpression and silencing of MSTRG.44863.1 significantly increased and decreased the content of 1-aminocyclopropane carboxylic acid (a precursor of ethylene) and ethylene production, respectively. RNA pull-down and microscale thermophoresis assays further revealed that MSTRG.44863.1 can interact with S-adenosyl-L-methionine synthetase (SAMS), an enzyme in the ethylene synthesis pathway. Considering that ethylene negatively regulates fruit development, these results indicate that MSTRG.44863.1 plays an important role in the regulation of pumpkin fruit development, possibly through interacting with SAMS and affecting ethylene synthesis. Overall, our findings provide a rich resource for further study of fruit-related lncRNAs while offering insights into the regulation of fruit development in plants.

Non-coding RNAs (ncRNAs) are recognized as pivotal players in the regulation of essential physiological processes such as nutrient homeostasis, development, and stress responses in plants. Common methods for predicting ncRNAs are susceptible to significant effects of experimental conditions and computational methods, resulting in the need for significant investment of time and resources. Therefore, we constructed an ncRNA predictor(MFPINC), to predict potential ncRNA in plants which is based on the PINC tool proposed by our previous studies. Specifically, sequence features were carefully refined using variance thresholding and F-test methods, while deep features were extracted and feature fusion were performed by applying the GRU model. The comprehensive evaluation of multiple standard datasets shows that MFPINC not only achieves more comprehensive and accurate identification of gene sequences, but also significantly improves the expressive and generalization performance of the model, and MFPINC significantly outperforms the existing competing methods in ncRNA identification. In addition, it is worth mentioning that our tool can also be found on Github ( https://github.com/Zhenj-Nie/MFPINC ) the data and source code can also be downloaded for free.

Centromeres are the chromosomal domains, where the kinetochore protein complex is formed, mediating proper segregation of chromosomes during cell division. Although the function of centromeres has remained conserved during evolution, centromeric DNA is highly variable, even in closely related species. In addition, the composition of the kinetochore complexes varies among organisms. Therefore, it is assumed that the centromeric position is determined epigenetically, and the centromeric histone H3 (CENH3) serves as an epigenetic marker. The loading of CENH3 onto centromeres depends on centromere-licensing factors, chaperones, and transcription of centromeric repeats. Several proteins that regulate CENH3 loading and kinetochore assembly interact with the centromeric transcripts and DNA in a sequence-independent manner. However, the functional aspects of these interactions are not fully understood. This review discusses the variability of centromeric sequences in different organisms and the regulation of their transcription through the RNA Pol II and RNAi machinery. The data suggest that the interaction of proteins involved in CENH3 loading and kinetochore assembly with centromeric DNA and transcripts plays a role in centromere, and possibly neocentromere, formation in a sequence-independent manner.

Protein-encoding genes only constitute less than 2% of total human genomic sequences, and 98% of genetic information was previously referred to as "junk DNA". Meanwhile, non-coding RNAs (ncRNAs) consist of approximately 60% of the transcriptional output of human cells. Thousands of ncRNAs have been identified in recent decades, and their essential roles in the regulation of gene expression in diverse cellular pathways associated with fundamental cell processes, including proliferation, differentiation, apoptosis, and metabolism, have been extensively investigated. Furthermore, the gene regulation networks they form modulate gene expression in normal development and under pathological conditions. In this review, we integrate current information about the classification, biogenesis, and function of ncRNAs and how these ncRNAs support skeletal development through their regulation of critical genes and signaling pathways in vivo. We also summarize the updated knowledge of ncRNAs involved in common skeletal diseases and disorders, including but not limited to osteoporosis, osteoarthritis, rheumatoid arthritis, scoliosis, and intervertebral disc degeneration, by highlighting their roles established from in vivo, in vitro, and ex vivo studies.

Cancer is a comprehensive classification encompassing more than 100 forms of malignancies that manifest in diverse tissues within the human body. Recent studies have provided evidence that aberrant epigenetic modifications are pivotal indicators of cancer. Epigenetics encapsulates DNA methyltransferases as a crucial class of modifiers. DNMTs, including DNMT3A, assume central roles in DNA methylation processes that orchestrate normal biological functions, such as gene transcription, predominantly in mammals. Typically, deviations in DNMT3A function engender distortions in factors that drive tumor growth and progression, thereby exacerbating the malignant phenotype of tumors. Consequently, such abnormalities pose significant challenges in cancer therapy because they impede treatment efficacy. Non-coding RNAs (ncRNAs) represent a group of RNA molecules that cannot encode functional proteins. Recent investigation attests to the crucial significance of regulatory ncRNAs in epigenetic regulation. Notably, recent reports have illuminated the complex interplay between ncRNA expression and epigenetic regulatory machinery, including DNMT3A, particularly in cancer. Recent findings have demonstrated that miRNAs, namely miR-770-5p, miR-101, and miR-145 exhibit the capability to target DNMT3A directly, and their aberration is implicated in diverse cellular abnormalities that predispose to cancer development. This review aims to articulate the interplay between DNMT3A and the ncRNAs, focusing on its impact on the development and progression of cancer, cancer therapy resistance, cancer stem cells, and prognosis. Importantly, the emergence of such reports that suggest a connection between DNMT3A and ncRNAs in several cancers indicates that this connecting axis offers a valuable target with significant therapeutic potential that might be exploited for cancer management.

Exosomes are extracellular vesicles that can contain DNA, RNA, proteins, and metabolites. They are secreted by cells and play a regulatory role in various biological responses by mediating cell-to-cell communication. Moreover, exosomes are of interest in developing therapies for retinal vascular disorders because they can deliver various substances to cellular targets. According to recent research, exosomes can be used as a strategy for managing retinal vascular diseases, and they are being investigated for therapeutic purposes in eye conditions, including glaucoma, dry eye syndrome, retinal ischemia, diabetic retinopathy, and age-related macular degeneration. However, the role of exosomal noncoding RNA in retinal vascular diseases is not fully understood. Here, we reviewed the latest research on the biological role of exosomal noncoding RNA in treating retinal vascular diseases. Research has shown that noncoding RNAs, including microRNAs, circular RNAs, and long noncoding RNAs play a significant role in the regulation of retinal vascular diseases. Furthermore, through exosome engineering, the expression of relevant noncoding RNAs in exosomes can be controlled to regulate retinal vascular diseases. Therefore, this review suggests that exosomal noncoding RNA could be considered as a biomarker for diagnosis and as a therapeutic target for treating retinal vascular disease.

The physicochemical characteristics of RNA admit non-coding RNAs to perform a different range of biological acts through various mechanisms and are involved in regulating a diversity of fundamental processes. Notably, some reports of pathological conditions have proved abnormal expression of many non-coding RNAs guides the ailment. Vault RNAs are a class of non-coding RNAs containing stem regions or loops with well-conserved sequence patterns that play a fundamental role in the function of vault particles through RNA-ligand, RNA-RNA, or RNA-protein interactions. Taken together, vault RNAs have been proposed to be involved in a variety of functions such as cell proliferation, nucleocytoplasmic transport, intracellular detoxification processes, multidrug resistance, apoptosis, and autophagy, and serve as microRNA precursors and signaling pathways. Despite decades of investigations devoted, the biological function of the vault particle or the vault RNAs is not yet completely cleared. In this review, the current scientific assertions of the vital vault RNAs functions were discussed.

Over the last three decades, our view of RNA has changed from a simple intermediate supporting protein synthesis to a major regulator of biological processes. In the expanding area of RNA research, peptide nucleic acid (PNA) is emerging as a promising ligand for triple-helical recognition of complex RNAs. As discussed in this feature article, the key advantages of PNAs are high sequence specificity and affinity for RNA (>10 fold higher than for DNA) that are difficult to achieve with small molecule ligands. Emerging studies demonstrate that triple-helical binding of PNAs can modulate biological function and control dynamic conformational equilibria of complex folded RNAs. These results suggest that PNA has a unique potential as a research tool and therapeutic compound targeting RNA. The remaining problems hampering advances in these directions are limitations of sequences that can be recognized by Hoogsteen triplexes (typically purine rich tracts), poor cellular uptake and bioavailability of PNA, and potential off-target effects in biological systems. Recent exciting studies are discussed that illustrate how synthetic nucleic acid chemistry provides innovative solutions for these problems.

Long non-coding RNAs (lncRNAs) have begun to receive overdue attention for their regulatory roles in gene expression and other cellular processes. Although most lncRNAs are lowly expressed and tissue-specific, notable exceptions include MALAT1 and its genomic neighbor NEAT1, two highly and ubiquitously expressed oncogenes with roles in transcriptional regulation and RNA splicing. Previous studies have suggested that NEAT1 is found only in mammals, while MALAT1 is present in all gnathostomes (jawed vertebrates) except birds. Here we show that these assertions are incomplete, likely due to the challenges associated with properly identifying these two lncRNAs. Using phylogenetic analysis and structure-aware annotation of publicly available genomic and RNA-seq coverage data, we show that NEAT1 is a common feature of tetrapod genomes except birds and squamates. Conversely, we identify MALAT1 in representative species of all major gnathostome clades, including birds. Our in-depth examination of MALAT1, NEAT1, and their genomic context in a wide range of vertebrate species allows us to reconstruct the series of events that led to the formation of the locus containing these genes in taxa from cartilaginous fish to mammals. This evolutionary history includes the independent loss of NEAT1 in birds and squamates, since NEAT1 is found in the closest living relatives of both clades (crocodilians and tuataras, respectively). These data clarify the origins and relationships of MALAT1 and NEAT1 and highlight an opportunity to study the change and continuity in lncRNA structure and function over deep evolutionary time.

MicroRNAs (miRNAs) have emerged as pivotal regulators of gene expression, playing essential roles in diverse cellular processes, including the development and progression of cancer. Among the numerous proteins influenced by miRNAs, the MARCKS/MARCKSL1 protein, a key regulator of cellular cytoskeletal dynamics and membrane-cytosol communication, has garnered significant attention due to its multifaceted involvement in various cancer-related processes, including cell migration, invasion, metastasis, and drug resistance. Motivated by the encouraging early clinical success of peptides targeting MARCKS in several pathological conditions, this review article delves into the intricate interplay between miRNAs and the MARCKS protein in cancer. Herein, we have highlighted the latest findings on specific miRNAs that modulate MARCKS/MARCKSL1 expression, providing a comprehensive overview of their roles in different cancer types. We have underscored the need for in-depth investigations into the therapeutic feasibility of targeting the miRNA-MARCKS axis in cancer, taking cues from the successes witnessed in related fields. Unlocking the full potential of miRNA-mediated MARCKS regulation could pave the way for innovative and effective therapeutic interventions against various cancer types.

Pigs play important roles in agriculture and bio-medicine; however, porcine viral infections have caused huge losses to the pig industry and severely affected the animal welfare and social public safety. During viral infections, many non-coding RNAs are induced or repressed by viruses and regulate viral infection. Many viruses have, therefore, developed a number of mechanisms that use ncRNAs to evade the host immune system. Understanding how ncRNAs regulate host immunity during porcine viral infections is critical for the development of antiviral therapies. In this review, we provide a summary of the classification, production and function of ncRNAs involved in regulating porcine viral infections. Additionally, we outline pathways and modes of action by which ncRNAs regulate viral infections and highlight the therapeutic potential of artificial microRNA. Our hope is that this information will aid in the development of antiviral therapies based on ncRNAs for the pig industry.

We aimed to investigate the interaction between the transcript levels of taurine-upregulated gene 1 (TUG1) and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and the Cholesterol-Saturated Fat Index (CSI) in relation to the visceral adiposity index (VAI) and body adiposity index (BAI). This cross-sectional study involved 346 women classified as obese and overweight, aged between 18 and 48 years. Dietary intake and the quality of dietary fat were assessed using a validated and reliable 147-item semi-quantitative food frequency questionnaire, with the Cholesterol-Saturated Fat Index (CSI) used as an indicator. Transcription levels of MALAT1 and TUG1 were evaluated through real-time polymerase chain reaction following the criteria outlined in the Minimum Information for Publication of Quantitative standards. Serum profiles were measured using standard protocols. We observed a positive association between transcription level of MALAT1 and VAI in both crude (β = 3.646, 95% CI 1.950-5.341, p < 0.001) and adjusted (β = 8.338, 95% CI 6.110-10.566, p < 0.001) models. Furthermore, after adjusting for confounders, a significant positive interaction was noted between MALAT1 expression and CSI on BAI (β: 0.130, 95% CI 0.019, 0.240, p = 0.022), with a marginal positive interaction observed on VAI (β: 0.718, 95% CI - 0.028, 1.463, p = 0.059). It seems that there may be a positive interaction between MALAT1 transcription level and CSI on VAI and BAI among overweight and obese women. However, no associations were seen between TUG1 mRNA level and the above-mentioned outcomes. Further functional studies are still required to elucidate this concept.

Revealing the role of non-coding RNAs (ncRNAs) in inducing dysregulated pathological responses to external signals may identify therapeutic targets for inhibiting the progression of clear cell renal cell carcinoma (ccRCC). Non-coding RNAs belong to a class of RNA molecules that do not encode proteins but possess diverse biological functions, playing essential roles in the occurrence and development of metastatic and proliferative tumors. To investigate the impact of the upstream interaction between miR-142-3p and lncRNA MAGI2-AS3 on the tumor-suppressive activity of the STAM gene, we firstly conducted bioinformatics analysis to predict the upstream miRNAs of STAM and the upstream lncRNAs of the miRNAs through online databases (miRanda, miRDB, TargetScan, LncBase v2), which were further validated by the starBasev2.0 database. Subsequently, multiple experimental techniques were employed to validate these findings, including RT-qPCR, Western blotting, measurement of cellular functional activity, and luciferase reporter assays. Through these experimental methods, we provided compelling evidence regarding the role of miR-142-3p and MAGI2-AS3 in regulating STAM gene expression and functionality, revealing their potential significance in tumor suppression. Our research demonstrates the importance of the MAGI2-AS3/miR-142-3p/STAM signaling pathway axis in ccRCC. MAGI2-AS3 competes for binding with miR-142-3p, resulting in upregulated STAM gene expression. This upregulation inhibits tumor proliferation and metastasis in ccRCC cells. Conversely, overexpression of miR-142-3p or silencing of MAGI2-AS3 promotes tumor behavior, while downregulation of miR-142-3p inhibits the development of ccRCC. Targeting the MAGI2-AS3/miR-142-3p/STAM axis holds promise as a therapeutic strategy for ccRCC treatment.

Lung adenocarcinoma (LUAD) has a high mortality rate. Ferroptosis is linked to tumor initiation and progression.

This study aims to develop prognostic models of ferroptosis-related lncRNAs, evaluate the correlation between differentially expressed genes and tumor microenvironment, and identify prospective drugs for managing LUAD.

In this study, transcriptomic and clinical data were downloaded from the TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the LASSO algorithm for constructing a prognostic model, we found that ferroptosis-related lncRNA-based gene signatures (FLncSig) had a strong prognostic predicting ability in the LUAD patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments reconfirmed that ferroptosis is related to receptor-ligand activity, enzyme inhibitor activity, and the IL-17 signaling pathway. Next, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) algorithms, and pRRophetic were used to predict immunotherapy response and chemotherapy sensitivity. The IMvigor210 cohort was also used to validate the prognostic model. In the tumor microenvironment, Type_II_IFN_Response and HLA were found to be a group of low-risk pathways, while MHC_class_I was a group of high-risk pathways. Patients in the high-risk subgroup had lower TIDE scores. Exclusion, MDSC, CAF, and TAMM2 were significantly and positively correlated with risk scores. In addition, we found 15 potential therapeutic drugs for LUAD. Finally, differential analysis of stemness index based on mRNA expression (mRNAsi) indicated that mRNAsi was correlated with gender, primary tumor (T), distant metastasis (M), and the tumor, node, and metastasis (TNM) stage in LUAD patients.

In conclusion, the prognostic model based on FLncSig can alleviate the difficulty in predicting the prognosis and immunotherapy of LUAD patients. The identified FLncSig and the screened drugs exhibit potential for clinical application and provide references for the treatment of LUAD.

circRNAs play an important role in drug resistance and cancer development. Recently, many studies have shown that the expressions of circRNAs in human cells can affect the sensitivity of cells to therapeutic drugs, thus significantly influencing the therapeutic effects of these drugs. Traditional biomedical experiments required to verify this sensitivity relationship are not only time-consuming but also expensive. Hence, the development of an efficient computational approach that can accurately predict the novel associations between drug sensitivities and circRNAs is a crucial and pressing need.

In this research, we present a novel computational framework called MNCLCDA, which aims to predict the potential associations between drug sensitivities and circRNAs to assist with medical research. First, MNCLCDA quantifies the similarity between the given drug and circRNA using drug structure information, circRNA gene sequence information, and GIP kernel information. Due to the existence of noise in similarity information, we employ a preprocessing approach based on random walk with restart for similarity networks to efficiently capture the useful features of circRNAs and drugs. Second, we use a mixed neighbourhood graph convolutional network to obtain the neighbourhood information of nodes. Then, a graph-based contrastive learning method is used to enhance the robustness of the model, and finally, a double Laplace-regularized least-squares method is used to predict potential circRNA-drug associations through the kernel matrices in the circRNA and drug spaces.

Numerous experimental results show that MNCLCDA outperforms six other advanced methods. In addition, the excellent performance of our proposed model in case studies illustrates that MNCLCDA also has the ability to predict the associations between drug sensitivity and circRNA in practical situations.

After a large number of experiments, it is illustrated that MNCLCDA is an efficient tool for predicting the potential associations between drug sensitivities and circRNAs, thereby can provide some guidance for clinical trials.

Patinopecten yessoensis, a large and old molluscan group, has been one of the most important aquaculture shellfish in Asian countries because of its high economic value. However, the aquaculture of the species has recently been seriously affected by the frequent outbreaks of Polydora disease, causing great economic losses. Long non-coding RNAs (lncRNAs) exhibit exhibit crucial effects on diverse biological processes, but still remain poorly studied in scallops, limiting our understanding of the molecular regulatory mechanism of P. yessoensis in response to Polydora infestation.

In this study, a high-throughput transcriptome analysis was conducted in the mantles of healthy and Polydora-infected P. yessoensis by RNA sequencing. A total of 19,133 lncRNAs with 2,203 known and 16,930 novel were identified. The genomic characterizations of lncRNAs showed shorter sequence and open reading frame (ORF) length, fewer number of exons and lower expression levels in comparison with mRNAs. There were separately 2280 and 1636 differentially expressed mRNAs and lncRNAs (DEGs and DELs) detected in diseased individuals. The target genes of DELs were determined by both co-location and co-expression analyses. Functional enrichment analysis revealed that DEGs involved in melanization and biomineralization were significantly upregulated; further, obviously increased melanin granules were observed in epithelial cells of the edge mantle in diseased scallops by histological and TEM study, indicating the crucial role of melanizaiton and biomineralization in P. yessoensis to resist against Polydora infestation. Moreover, many key genes, such as Tyrs, Frizzled, Wnts, calmodulins, Pifs, perlucin, laccase, shell matrix protein, mucins and chitins, were targeted by DELs. Finally, a core lncRNA-mRNA interactive network involved in melanization and biomineralization was constructed and validated by qRT-PCR.

This work provides valuable resources for studies of lncRNAs in scallops, and adds a new insight into the molecular regulatory mechanisms of P. yessoensis defending against Polydora infestation, which will contribute to Polydora disease control and breeding of disease-resistant varieties in molluscs.

Glioma is the most common primary malignancy of the central nervous system. Glioblastoma (GBM) has the highest degree of malignancy among the gliomas and the strongest resistance to chemotherapy and radiotherapy. Vasculogenic mimicry (VM) provides tumor cells with a blood supply independent of endothelial cells and greatly restricts the therapeutic effect of anti-angiogenic tumor therapy for glioma patients. Vascular endothelial growth factor receptor 2 (VEGFR2) and vascular endothelial cadherin (VE-cadherin) are currently recognized molecular markers of VM in tumors. In the present study, we show that pseudogene MAPK6P4 deficiency represses VEGFR2 and VE-cadherin protein expression levels, as well as inhibits the proliferation, migration, invasion, and VM development of GBM cells. The MAPK6P4-encoded functional peptide P4-135aa phosphorylates KLF15 at the S238 site, promoting KLF15 protein stability and nuclear entry to promote GBM VM formation. KLF15 was further confirmed as a transcriptional activator of LDHA, where LDHA binds and promotes VEGFR2 and VE-cadherin lactylation, thereby increasing their protein expression. Finally, we used orthotopic and subcutaneous xenografted nude mouse models of GBM to verify the inhibitory effect of the above factors on GBM VM development. In summary, this study may represent new targets for the comprehensive treatment of glioma.