Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with late-stage diagnoses frequently leading to poor outcomes. This underscores the need for effective early-stage gastric cancer (ESGC) diagnostics.

We introduce ESGCmiRD, an innovative artificial intelligence-driven strategy that identifies a miRNA signature for ESGC detection by integrating robust expression patterns, ESGC relevance, and regulatory capabilities of microRNA (miRNA) based on multiple networks. Expression and biological roles of miRNAs in GC were validated and explored via bioinformatics analysis and in vitro studies. miRNA-target interaction was confirmed by dual-luciferase reporter assay. Molecular docking predicted miRNA-drug binding affinities, assessing the miRNA signature's therapeutic potential.

ESGCmiRD identified a blood miRNA signature (miR-320b, miR-222-3p, miR-181a-5p, miR-103a-3p, miR-107) for ESGC detection, demonstrated high diagnostic accuracy with AUC values of 0.986, 0.977, 0.815, and 0.811 in the test and three validation sets (GSE211692, TCGA-STAD, and our cohort), respectively. The five miRNAs were overexpressed in ESGC plasma and directly target PTEN, promoting GC cell proliferation, migration, and invasion. Molecular docking suggested Paclitaxel had the strongest potential interaction with these miRNAs.

This method identifies a robust miRNA signature for ESGC detection and sheds light on gastric carcinogenesis mechanisms, opening doors for potential therapeutic strategies.

Estrogen's impact on Alzheimer's disease (AD) is multifaceted, with its receptors potentially influencing AD pathology in both beneficial and detrimental ways. This study aims to dissect the intricate cross-talk between estrogen receptor alpha (ERα) and microRNAs (miRNAs) in AD-affected human hippocampus. Through a comprehensive literature review in the PubMed database, coupled with a GeneCards database search, we obtained AD-related key miRNAs and genes in the hippocampus. Using bioinformatics tools, we predicted target genes and miRNAs of ERα, and the targets of the identified miRNAs. The integration of these elements resulted in the construction of an ERα-related FFL network, which includes 13 miRNAs and 56 core genes. Gene ontology (GO) and pathway enrichment analyses were conducted, revealing significant enrichment in biological processes such as neuron death and response to metal ions, and cellular components like membrane microdomains. Notably, the AKT-associated signaling pathway was prominently highlighted, with key genes including GSK3A, CDKN1A, AKT2, and MDM2, and key miRNAs including miR-485 and let-7f, suggesting a potential role of ERα in modulating this pathway in AD. The findings of this study provide a novel perspective on the regulatory network of ERα in the hippocampal region of AD and may pave the way for future research into the therapeutic potential of targeting the ERα pathway in neurodegenerative diseases.

Metastasis, the leading cause of cancer-associated deaths, is promoted by transcription factors SNAIL, SLUG, ZEB1 and TWIST through the activation of epithelial-mesenchymal transition (EMT). MicroRNAs can suppress EMT, emerging as candidate molecular biomarkers and novel therapeutic targets. Herein, we evaluated microRNAs downregulated in breast cancer (BC) tissues expressing EMT transcription factors, to find new potential regulators of EMT.

Candidate microRNAs were selected from microarray data by their inversely correlated expression with SNAIL, SLUG, ZEB1 and TWIST, evaluated in BC tissues through immunohistochemistry. We selected eight microRNAs predicted in silico as probable modulators of SNAIL, SLUG, ZEB1 and TWIST, and validate their interaction through the 3'UTR region in luciferase reporter gene assays. MDA-MB-231 cells were transfected with selected microRNAs to perform migration, invasion and cell proliferation assays, and western blot was used to evaluate protein levels.

MiR-30a-5p, miR-1271-5p, miR-196a-5p, miR-202-3p, miR-210-3p, miR-22-3p and miR-331-3p decreased luciferase activity through SNAIL, SLUG, ZEB1 and/or TWIST 3'UTR. These microRNAs, including miR-34b-3p, decreased migration, invasion and cell proliferation in MDA-MB-231 cells. MiR-30a-5p, miR-202-3p and miR-22-3p decreased vimentin expression, whereas miR-196a-5p and miR-22-3p decreased endogenous ZEB1 levels. MiR-196a-5p, miR-202-3p and miR-30a-5p also decreased CCR7 expression, a chemokine receptor involved in lymph node metastasis.

microRNAs selected in this work can regulate gene expression trough 3'UTR region of EMT-transcription factors. In BC cells, miR-196a-5p and miR-22-3p decrease ZEB1 levels, being novel modulators of EMT. Also, the eight evaluated microRNAs, reduced the metastatic hallmarks in BC cells.

MicroRNAs (miRNAs) represent a vital class of small non-coding RNAs that play key regulatory roles in gene expression. Accurate identification of miRNA-mRNA interactions is essential for understanding their biological functions. However, current computational prediction tools suffer from several limitations, including species-specific biases, suboptimal accuracy, high false discovery rates, and incomplete target gene coverage. To address these challenges, we present TarP, a novel miRNA target prediction algorithm employing a Polymorphic structured alignment (PMS) approach. Our method mimics the natural binding process between miRNAs and their target mRNAs by integrating key biological interaction features. The algorithm utilizes five distinct nucleotide-binding motifs to perform a structured decomposition and alignment of potential mRNA targets. Predictions are then rigorously evaluated through a dual scoring system: a Structure (St) coefficient assessing binding conformation and an Energy (En) coefficient evaluating thermodynamic stability, ensuring high-confidence target selection. Using experimentally validated human miRNA-mRNA interaction datasets, we benchmarked TarP against four widely used prediction tools (miRanda, RNAhybrid, PITA, and TargetScan). Comparative analyses demonstrate that TarP achieves superior performance in both sensitivity and specificity, exhibiting enhanced accuracy in positive target identification and improved discrimination between true and false interactions. The TarP algorithm is freely available at: https://github.com/Whimonk/TarP.

Insect spermatogenesis is a complex process. Numerous genes are involved in sperm motility, which is crucial for male fertility. Few long non-coding RNAs (lncRNAs) in the testis regulate insect spermatogenesis. We previously identified 364 testis-enriched lncRNAs in the globally invasive pest Zeugodacus cucurbitae Coquillett. One of these lncRNAs, lnc94641, is abundantly expressed in the testis; however, its role in spermatogenesis remains unknown.

Suppression of lnc94641 expression led to a 60% decrease in spermatozoa count and a 29% decrease in offspring hatchability. A microRNA (miRNA), miR-957-3p, was experimentally demonstrated to bind to lnc94641 competitively. miR-957-3p overexpression recapitulated reproductive defect phenotypes similar to those caused by lnc94641 knockdown. Furthermore, target gene predictions combined with quantitative reverse transcription PCR, RNA pull-down, and dual luciferase reporter assays confirmed that miR-957-3p targets voltage-gated potassium channel 5 (VGKC5) and odorant receptor 85c (OR85c), elucidating a functional lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory axis. Fluorescence in situ hybridization (FISH) assays demonstrated the co-localization of lnc94641, miR-957-3p, and VGKC5/OR85c in the mature and transformed regions of the testes. Suppression of VGKC5/OR85c expression resulted in a 68% and 50% decrease in spermatozoa number and an 18% and 21% decrease in offspring hatchability, mirroring the phenotype observed with lnc94641-silencing, thereby reinforcing the mechanistic coherence of this regulatory network.

These results revealed a ceRNA axis mediated by 'lnc94641-miR957-3p-VGKC5/OR85c' involved in spermatogenesis that impairs male fertility in the melon fly. Molecular perturbations (lncRNA knockdown or miRNA overexpression) consistently impair sperm production and offspring viability by dysregulating ion channels and chemosensory genes. This mechanistically resolved pathway, centered on the core components VGKC5 and OR85c, revealed conserved reproductive vulnerabilities that could enable the targeted genetic control of this agricultural pest. © 2025 Society of Chemical Industry.

The sea louse, Caligus rogercresseyi, is one of the main concerns in the Chilean salmon industry. The free-living copepodid stage can recognize the host and initiate the parasitic phase, where environmental factors can shape the host recognition process. This study aimed to explore the ecological influence on the transcriptome of copepodids infesting Atlantic salmon experimentally exposed to different salinity and temperature (S/T) conditions. Herein, 200 salmon were infested with 35 copepodids per fish previously acclimatized to four S/T treatments: 32 and 26 PSU; 8 and 16°C. After 48 h of infestation, the attached copepodids from each experimental group were counted and digitalized for geometric morphometric analysis. Copepodids were then collected for RNA sequencing to analyze transcriptome modulation and gene regulation. Morphological changes in copepodids were mainly associated with temperature rather than salinity conditions. The transcriptome survey revealed molecular signatures related to salinity and temperature changes, where salinity drives the gene expression of copepodids. Notably, specific genes, such as those encoding cuticle proteins and trypsin-like kinases, were regulated by all three post-transcriptional mechanisms assessed: alternative splicing, miRNA, and gene fusion. The transcriptome analysis revealed that trypsin-like kinase genes exhibited upregulation and downregulation across the various S/T conditions. In contrast, cuticle protein genes were consistently downregulated in the 32 PSU/8°C, 26 PSU/8°C, and 26 PSU/16°C groups compared to the 32 PSU/16°C control. This suggests that the three post-transcriptional mechanisms may exert a combined influence on the expression of specific genes, potentially driven by salinity and temperature environmental conditions in sea lice biology.

Gene drive technology presents a promising approach to controlling malaria vector populations. Suppression drives are intended to disrupt essential mosquito genes whereas modification drives aim to reduce the individual vectorial capacity of mosquitoes. Here we present a highly efficient homing gene drive in the African malaria vector Anopheles gambiae that targets the microRNA gene mir-184 and combines suppression with modification. Homozygous gene drive (miR-184D) individuals incur significant fitness costs, including high mortality following a blood meal, that curtail their propensity for malaria transmission. We attribute this to a role of miR-184 in regulating solute transport in the mosquito gut. However, females remain fully fertile, and pure-breeding miR-184D populations suitable for large-scale releases can be reared under laboratory conditions. Cage invasion experiments show that miR-184D can spread to fixation thereby reducing population fitness, while being able to propagate a separate antimalarial effector gene at the same time. Modelling indicates that the miR-184D drive integrates aspects of population suppression and population replacement strategies into a candidate strain that should be evaluated further as a tool for malaria eradication.

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by base-pairing to complementary sites in messenger RNAs (mRNAs). The primary element for site recognition is the seed region (nucleotides 2-8 in the miRNA), but for a minority of sites pairing outside the seed increases efficiency, with the supplementary region (nucleotides 13-16) typically having the greatest impact. However, the structural determinants of effective pairing outside the seed are not fully understood. Here, we use abasic modified nucleotides to disrupt pairing to residues 13 and 14 of miR-34a and measure the effect of this modification compared to wild-type miR-34a on the cellular transcriptome and proteome using RNA-seq and mass spectrometry. We find that a subset of sites with predicted supplementary pairing are affected by miRNA transfection, with up to two-fold decreases in site repression at the mRNA level. We show that miR-34a 3'-pairing is sensitive to GU wobble pairs in a position-specific manner and favors bulges in the miRNA over the target. These results were validated with luciferase reporter assays. Overall, this study demonstrates a novel methodological approach for elucidating the role of specific miRNA residues in target site selection, advancing our understanding of miRNA-mediated gene regulation.

MicroRNAs, abbreviated as miRNAs, have a substantial impact on viral infections through their ability to control gene expression and influence the interactions between the host and the virus. This work investigates the capacity of miRNAs to selectively inhibit the expression of rabies virus genes, specifically Nucleoprotein N, Phosphoprotein M1 and M2, Transmembrane Glycoprotein G, and L protein. The 7mer-m8 model was utilized to identify human miRNAs that target these viral genes. The interactions between the miRNAs and the genes were then assessed based on binding energy, GC content, and stability. The findings indicated that miRNAs, including miR-1279, miR-4251, miR-4288, and miR-12117, successfully target the N gene. In addition, other miRNAs target the remaining viral genes, indicating their capacity to bind and potentially inhibit viral replication. In addition, docking experiments have verified the stability of miRNA-mRNA duplexes, as evidenced by the high free energy values that indicate strong and reliable contacts between miRNA and gene. These findings indicate that certain human miRNAs have the potential to be effective therapeutic agents against the rabies virus by suppressing gene expression. This offers a new and innovative strategy to fight against this deadly infection.

In plants and animals, the microRNA (miRNA) class of small regulatory RNA plays an essential role in controlling gene expression in all aspects of development, to respond to environmental stress, or to defend against pathogen attack. This well-established master regulatory role for miRNAs has led to each protein-mediated step of both the plant and animal miRNA pathways being thoroughly characterized. Furthermore, this degree of characterization has led to the development of a suite of miRNA-based technologies for gene expression manipulation for fundamental research or for use in industrial or medical applications. In direct contrast, molecular research on the miRNA pathway of macroalgae, specifically seaweeds (marine macroalgae), remains in its infancy. However, the molecular research conducted to date on the seaweed miRNA pathway has shown that it shares functional features specific to either the plant or animal miRNA pathway. In addition, of the small number of seaweed species where miRNA data is available, little sequence conservation of individual miRNAs exists. These preliminary findings show the pressing need for substantive research into the seaweed miRNA pathway to advance our current understanding of this essential gene expression regulatory process. Such research will also generate the knowledge required to develop novel miRNA-based technologies for use in seaweeds. In this review, we compare and contrast the seaweed miRNA pathway to those well-characterized pathways of plants and animals and outline the low degree of miRNA sequence conservation across the polyphyletic group known as the seaweeds.

Autism spectrum disorder (ASD) is a brain developmental disability with a not-fully clarified etiogenesis. Current ASD research largely focuses on coding regions of the genome, but up to date much less is known about the contribution of non-coding elements to ASD risk. The non-coding genome is largely made of DNA repetitive sequences (RS). Although RS were considered slightly more than "junk DNA", today RS have a recognized role in almost every aspect of human biology, especially in developing human brain. Our aim was to test if RS transcription may play a role in ASD.

Global RS transcription was firstly investigated in postmortem dorsolateral prefrontal cortex of 13 ASD patients and 39 matched controls. Results were validated in independent datasets.

AmnSINE1 was the only RS significantly downregulated in ASD specimens. The role of AmnSINE1 in ASD has been investigated at multiple levels, showing that the 1,416 genes containing AmnSINE1 are associated with nervous system development and autism susceptibility. This has been confirmed in a different experimental setting, such as in organoid models of the human cerebral cortex, harboring different ASD causative mutations. AmnSINE1 related genes are transcriptionally co-regulated and are involved not only in brain formation but can specifically be involved in ASD development. Looking for a possible direct role of AmnSINE1 non-coding transcripts in ASD, we report that AmnSINE1 transcripts may alter the miRNA regulatory landscape for genes involved in neurogenesis.

Our findings provide preliminary evidence supporting a role for AmnSINE1 in ASD development.

Coral reefs are increasingly threatened by disease outbreaks, yet little is known about the genetic mechanisms underlying disease resistance. Since the 1970s, White Band Disease (WBD) has decimated the Caribbean staghorn coral Acropora cervicornis. However, 15% or more of individuals are highly disease-resistant, and the genes controlling the production of Argonaut proteins, involved in microRNA (miRNA) post-transcriptional gene silencing, are up-regulated in WBD-resistant corals. This suggests that miRNAs may be key regulators of coral immunity. In this study, we conducted an in situ disease transmission experiment with five healthy-exposed control tanks and five WBD-exposed tanks, each containing 50 A. cervicornis genotypes, sampled over 7 days and then sequenced miRNAs from 12 replicate genotypes, including 12 WBD-exposed and 12 healthy-exposed control fragments from two time points. We identified 67 bona fide miRNAs in A. cervicornis, 3 of which are differentially expressed in disease-resistant corals. We performed a phylogenetic comparison of miRNAs across cnidarians and found greater conservation of miRNAs in more closely related taxa, including all three differentially expressed miRNAs being conserved in more than one Acropora coral. One of the three miRNAs has putative genomic targets involved in the cnidarian innate immunity. In addition, community detection coupled with over-representation analysis of our miRNA-messenger RNA (mRNA) target network found two key unique A. cervicornis miRNAs regulating multiple important immune-related pathways such as Toll-like receptor pathway, endocytosis, and apoptosis. These findings highlight how multiple miRNAs may help the coral host maintain immune homeostasis in the presence of environmental stress including disease.

Oral squamous cell carcinoma (OSCC) remains a formidable challenge due to its high recurrence rates and poor prognosis. This study focuses on miR-876, a microRNA significantly associated with OSCC recurrence and clinical outcomes. Analysis of miRNA expression profiles from recurrent OSCC patients revealed that miR-876-5p is markedly upregulated in recurrent tumor tissues and the high expression of miR-876-5p correlates with reduced disease-free and overall survival. Functional assays demonstrated that miR-876 enhances OSCC cell growth, migration, and stemness, contributing to chemoresistance. Mechanistically, miR-876-5p directly targets SOCS4, leading to increased STAT3 activation and subsequent upregulation of PD-L1, which facilitates immune evasion. Additionally, exposure to the tobacco-specific carcinogen NNK was found to induce miR-876 expression and STAT3 activation, implicating environmental factors in miR-876 regulation and promote cancer recurrent. These findings identify the miR-876-5p-SOCS4-STAT3 axis as a critical pathway in OSCC progression, highlighting miR-876-5p as a potential biomarker and therapeutic target to improve treatment outcomes in OSCC patients.

(1) Background: MicroRNAs are non-coding RNA sequences that regulate cellular functions by targeting messenger RNAs and inhibiting protein synthesis. Identifying their target sites is vital to understanding their roles. However, it is challenging due to the high cost and time demands of experimental methods and the high false-positive rates of computational approaches. (2) Methods: We introduce a Multi-Input Neural Network (MINN) algorithm that integrates diverse biologically relevant features, including the microRNA duplex structure, substructures, minimum free energy, and base-pairing probabilities. For each feature derived from a microRNA target-site duplex, we create a corresponding image. These images are processed in parallel by the MINN algorithm, allowing it to learn a comprehensive and precise representation of the underlying biological mechanisms. (3) Results: Our method, on an experimentally validated test set, detects target sites with an AUPRC of 0.9373, Precision of 0.8725, and Recall of 0.8703 and outperforms several commonly used computational methods of microRNA target-site predictions. (4) Conclusions: Incorporating diverse biologically explainable features, such as duplex structure, substructures, their MFEs, and binding probabilities, enables our model to perform well on experimentally validated test data. These features, rather than nucleotide sequences, enhance our model to generalize beyond specific sequence contexts and perform well on sequentially distant samples.

Background/Objectives: microRNAs are small non-coding RNAs that regulate gene expression by inducing mRNA degradation or inhibiting translation. A growing body of evidence suggests that miRNAs may be utilized as anti-cancer therapeutics by targeting expression of key genes involved in cancerous transformation and progression. Renal cell cancer (RCC) is the most common kidney malignancy. The most efficient RCC treatments involve blockers of immune checkpoints, including antibodies targeting PD-L1 (Programmed Death Ligand 1). Interestingly, recent studies revealed the cross-kingdom horizontal transfer of plant miRNAs into mammalian cells, contributing to the modulation of gene expression by food ingestion. Here, we hypothesized that PD-L1 expression may be modulated by miRNAs originating from edible plants. Methods: To verify this hypothesis, we performed bioinformatic analysis to identify mes-miR395e from Manihot esculenta (cassava) as a promising candidate miRNA that could target PD-L1. To verify PD-L1 regulation mediated by the predicted plant miRNA, synthetic mes-miR395 mimics were transfected into cell lines derived from RCC tumors, followed by evaluation of PD-L1 expression using qPCR and Western blot. Results: Transfection of mes-miR395e mimics into RCC-derived cell lines confirmed that this miRNA decreases expression of PD-L1 in RCC cells at both mRNA and protein levels. Conclusions: This preliminary study shows the promise of plant miRNA as potential adjuvants supporting RCC treatment.

Paratuberculosis (Johne's disease, JD) is a chronic and enteric disease in a range of ruminants, often caused by Mycobacterium avium subspecies paratuberculosis (MAP) infection, leading to substantial economic losses worldwide. Yet, the molecular underpinning of paratuberculosis remains elusive. Here we performed RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) of the jejunum tissues from the Holstein cows with three distinct statuses of paratuberculosis, i.e., healthy, subclinical, and clinical to screen potential genes, lncRNAs, and miRNAs associated with the resistance or susceptibility to MAP infection and build ceRNA regulatory networks via miRNAs.

We applied whole transcriptome sequencing analysis to examine the jejunum tissue in nine Holstein cows. Starting with 19,994 expressed genes, 13,529 lncRNAs, and 735 miRNAs, we screened out differentially expressed genes (DEGs), lncRNAs, and miRNAs of three comparison groups, i.e., clinical vs. healthy, subclinical vs. healthy, and clinical vs. subclinical, subsequently identifying ceRNA pairs. Ultimately, we detected 76, 74, and 24 DEGs, 19, 39, and 10 lncRNAs, as well as 28, 61, and 20 miRNAs across the three comparison groups, respectively. Through integrating these DEGs with functional annotation, previously reported QTLs, and GWAS results, we proposed eight genes (LYZ, LYZ1, BOLA-DQB, BOLA-DQA1, TAP, CATD, VNN1, and PPARG), six lncRNAs, 48 miRNAs, and 107 ceRNA pairs implying their potential associations with susceptibility to MAP infection.

The present study provided a global view of the dynamics in transcriptomes of the bovine jejunum tissues in terms of JD status. Our results demonstrated that not only mRNAs but also lncRNAs and miRNAs played important roles in regulating MAP infection in dairy cattle. This study provided a valuable resource for understanding the molecular basis of JD, potentially contributing to the genetic improvement of JD resistance in dairy cattle.

The important role of PIWI-interacting RNAs (piRNAs) in tumors has garnered increasing attention. However, research on their role in lung adenocarcinoma (LUAD) remains limited. Elevated levels of piRNA-137463 have been linked to poor prognosis in LUAD patients. Inhibition of piRNA-137463 curbed the proliferation, migration, and invasion of LUAD cells, enhanced T cell cytotoxicity through increased IFN-γ secretion, disrupted cholesterol metabolism, and reduced intracellular cholesterol, lipid raft content, and PD-L1 expression in LUAD cells. Bioinformatic prediction identified a potential interaction between piRNA-137463 and lncRNA LOC100128494. Inhibiting piRNA-137463 increased the stability and expression of LOC100128494, which further modulated insulin-induced gene 1 protein (INSIG1) levels via a competitive endogenous RNA network involving LOC100128494 and miR-24-3p. Notably, the effect of piRNA-137463 in LUAD cells is dependent on the expression of LOC100128494 and INSIG1. Inhibiting the expression of piRNA-137463 with AntagopiRNA-137463 suppressed tumor growth and metastasis via LOC100128494 in nude mice and enhanced the response of LUAD to anti-PD-1 therapy in immune-competent mice. In summary, this study elucidates the role of piRNA-137463 in the reprogramming of cholesterol metabolism, which drives the progression of LUAD, thereby identifying a new target for the comprehensive clinical management of LUAD.

The interaction relationship between miRNAs and genes is important as miRNAs play a crucial role in regulating gene expression. In the literature, several databases have been constructed to curate known miRNA target genes, which are valuable resources but likely only represent a small fraction of all miRNA-gene interactions. In this study, we constructed machine learning models to predict miRNA target genes that have not been previously reported. Using the miRNA and gene expression data from TCGA, we performed a correlation analysis between all miRNAs and all genes across multiple cancer types. The correlations served as features to describe each miRNA-gene pair. Using the existing databases of curated miRNA targets, we labeled the miRNA-gene pairs, and trained machine learning models to predict novel miRNA-gene interactions. For the miRNA-gene pairs that were consistently predicted across the models, we called them significant miRNA-gene pairs. Using held-out miRNA target databases and a literature survey, we validated 5.5% of the predicted significant miRNA-gene pairs. The remaining predicted miRNA-gene pairs could serve as hypotheses for experimental validation. Additionally, we explored several additional datasets that provided gene expression data before and after a specific miRNA perturbation and observed consistency between the correlation direction of predicted miRNA-gene pairs and their regulatory patterns. Together, this analysis revealed a novel framework for uncovering previously unidentified miRNA-gene relationships, enhancing the collective comprehension of miRNA-mediated gene regulation.

Non-coding RNAs (ncRNAs) are RNA molecules that are transcribed from DNA but are not translated into proteins. Studies over the past decades have revealed that ncRNAs can be classified into small RNAs, long non-coding RNAs and circular RNAs by genomic size and structure. Accumulated evidences have eludicated the critical roles of these non-coding transcripts in regulating gene expression through transcription and translation, thereby shaping cellular function and disease pathogenesis. Notably, recent studies have investigated the function of ncRNAs as competitive endogenous RNAs (ceRNAs) that sequester miRNAs and modulate mRNAs expression. The ceRNAs network emerges as a pivotal regulatory function, with significant implications in various diseases such as cancer and neurodegenerative disease. Therefore, we highlighted multiple bioinformatics tools and databases that aim to predict ceRNAs interaction. Furthermore, we discussed limitations of using current technologies and potential improvement for ceRNAs network detection. Understanding of the dynamic interplay within ceRNAs may advance the biological comprehension, as well as providing potential targets for therapeutic intervention.

Phytoplasma, a potentially hazardous pathogen associated with witches' broom, is an economically harmful disease-producing bacteria that damages chilli cultivation. Phytoplasma-infected plants display various symptoms that indicate significant disruptions in normal plant physiology and behaviour. Diseases caused by phytoplasma are widespread and have a major economic impact on crop quality and yield. This work focuses on identifying and examining chilli microRNAs (miRNAs) as potential targets against the 16S rRNA and secA gene of "Candidatus Phytoplasma trifolii" ("Ca. P. trifolii") through plant miRNA prediction algorithms. Mature chilli miRNAs (CA-miRNAs) were collected and used to hybridise the 16S rRNA and secA genes. A total of four common CA-miRNAs were picked according to genetic consensus. Three algorithms applied in the present study suggested that the physiologically relevant, top-ranked miR169b_2 has a possibly specific site at nucleotide position 1,006 for targeting the 'Ca. P. trifolii' 16S rRNA gene. The circos algorithm was then utilised to create the miRNA-mRNA regulatory network. The free energy between the miRNA:mRNA duplex was also computed, and the best value of -17.46 kcal/mol was obtained for CA-miR166c_2. Currently, there are no suitable commercial 'Ca. P. trifolii'-resistant chilli crops. As a result, the expected biological data provide useful evidence for developing 'Ca. P. trifolii'-resistant chilli plants.

Lactation is a complex physiological process regulated by numerous genes and factors. Circular RNA (circRNA), a non-coding RNA, acts as a molecular sponge that sequesters microRNAs (miRNAs) to regulate target gene expression. Although circRNA has been linked to mammary gland lactation, its specific role in yaks remains underexplored. This study employed circular RNA sequencing (circRNA-seq) to examine the differential expression of circRNAs in yak mammary tissues during lactation and the dry period. Additionally, an enrichment analysis of the differentially expressed circRNAs (DECs) was performed. A competing endogenous RNA (ceRNA) network was then constructed to explore the potential of their roles in lactation and mammary gland development. We detected 18,905 circRNAs in yak mammary tissue, among which 302 showed differential expression. The host genes of these DECs were enriched in functions and pathways associated with yak milk synthesis and composition. Through the construction of a ceRNA network and the enrichment analysis of associated mRNAs, this study identified ceRNAs potentially involved in regulating lactation and mammary gland development. In conclusion, circRNAs in yak mammary tissues were identified and analyzed across lactation and dry periods, establishing a ceRNA network related to lactation regulation. These findings provide novel insights into the regulatory mechanisms governing lactation in yaks (Bos grunniens).

Non-coding RNAs (ncRNAs) play crucial roles in gene expression regulation, translation, and disease development, including cancer. They are classified by size in short and long non-coding RNAs. This chapter focuses on the functional implications of adenosine-to-inosine (A-to-I) RNA editing in both short (e.g., miRNAs) and long ncRNAs. RNA editing dynamically alters the sequence and structure of primary transcripts, impacting ncRNA biogenesis and function. Notable findings include the role of miRNA editing in promoting glioblastoma invasiveness, characterizing RNA editing hotspots across cancers, and its implications in thyroid cancer and ischemia. This chapter also highlights bioinformatics resources and next-generation sequencing (NGS) technologies that enable comprehensive ncRNAome studies and genome-wide RNA editing detection. Dysregulation of RNA editing machinery has been linked to various human diseases, emphasizing the potential of RNA editing as a biomarker and therapeutic target. This overview integrates current knowledge and computational tools for studying ncRNA editing, providing insights into its biological significance and clinical applications.

Parasites may suppress the immune function of infected hosts using microRNAs (miRNAs) to prevent protein production. Nonetheless, little is known about the diversity of miRNAs and their mode(s) of action. In this study, we investigated the effects of infection by a parasitic lungworm (Rhabdias pseudosphaerocephala) on miRNA and mRNA expression of its host, the invasive cane toad (Rhinella marina). To investigate the cane toad's innate and adaptive immune response to this parasite, we compared miRNA and mRNA expression in naïve toads that had never been infected by lungworms to toads that were infected with lungworms for the first time in their lives, and toads that were infected the second time in their lives (i.e., had two consecutive infections). In total, we identified 101 known miRNAs and 86 potential novel miRNAs. Compared to uninfected and single-infection toads, multiple-infection animals drastically downregulated three miRNAs. These miRNAs were associated with gene pathways related to the immune response, potentially reflecting the immunosuppression of cane toads by their parasites. Infected hosts did not respond with substantially differential mRNA transcription; only one gene was differentially expressed between control and single-infection hosts. Our study suggests that miRNA may play an important role in mediating host-parasite interactions in a system in which an ongoing range expansion by the host has generated substantial divergence in host-parasite interactions.

Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics. LINKED ARTICLES: This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc.

Background/Objectives: Chronic venous insufficiency (CVI), a chronic vascular dysfunction, is a common health problem that causes serious complications such as painful varicose veins and even skin ulcers. Identifying the underlying genetic and epigenetic factors is important for improving the quality of life of individuals with CVI. In the literature, many genes, variants, and miRNAs associated with CVI have been identified through genomic and transcriptomic studies. Despite molecular pathogenesis studies, how the genes associated with CVI are regulated by miRNAs and the effect of variants in binding regions on expression levels are still not fully understood. In this study, previously identified genes, variants, and miRNAs associated with CVI, common variants in the mRNA-miRNA binding regions, were investigated using in silico analyses. Methods: For this purpose, miRNA research tools, MBS (miRNA binding site) database, genome browsers, and the eQTL Calculator in the GTEx portal were used. Results: We identified SNVs associated with CVI that may play a direct role in the miRNA-mediated regulation of the ZNF664, COL1A2, HFE, MDN, MTHFR, SRPX, TDRD5, TSPYL4, VEGFA, and APOE genes. In addition, when the common SNVs in the mRNA binding region of 75 unique CVI related-miRNAs in five candidate genes associated with CVI were examined, seven miRNAs associated with the expression profiles of ABCA1, PIEZO1, and CASZ1 genes were identified. Conclusions: In conclusion, the relationship between genetic markers identified in the literature that play a role in the pathogenesis of the CVI and the expression profiles was evaluated for the first time in the mRNA-miRNA interaction axis.

Artificial insemination (AI), as an efficient assisted reproduction technology, can help the livestock industry to improve livestock and poultry breeds, optimize production performance and improve reproductive efficiency. AI technology has been widely used in pig production in China, but boar fertility affects the effectiveness of AI, and more and more studies have shown that there are significant differences in the fertility of boars with similar semen quality indicators. Therefore, this study aimed to identify biomarker molecules that indicate the level of boar fertility, which is important for improving the efficiency of AI. In this study, we collected 40 mL of ejaculates per boar used for extracellular vesicle (EV) characterization in 20 boars and identified 53 differentially expressed miRNAs by small RNA sequencing, of which 44 miRNAs were up-regulated in the high-fertility seminal EVs compared with low-fertility seminal EVs, and nine miRNAs were down-regulated. miR-26a was most significantly down-regulated in the high-fertility group compared to the low-fertility group, and it was hypothesized that this miRNA could be used as a biomolecular marker of semen reproductive performance. To further determine the effect of miR-26a on sperm function, we successfully established a miR-26a overexpression model and found that miR-26a reduced sperm viability, motility, acrosome integrity, plasma membrane integrity and ATP levels. Bioinformatics analysis and dual luciferase reporter analysis revealed that miR-26a directly targets High mobility group A1 (HMGA1). In conclusion, miR-26a can be used as a biomarker to identify high and low fertility in boar semen.

Acute Kidney Injury (AKI) is a multifaceted condition characterised by rapid deterioration of renal function, often precipitated by diverse etiologies. A comprehensive understanding of the molecular underpinnings of AKI is pivotal for identifying potential diagnostic markers and therapeutic targets. This study utilised bioinformatics to elucidate gene expression and immune infiltration in AKI. Publicly available mRNA and miRNA datasets were harnessed to discern differentially expressed genes (DEGs) and miRNAs in AKI. The CIBERSORT algorithm was employed to quantify immune cell infiltration in AKI samples. Functional enrichment analyses were conducted to unravel the implicated biological processes. Furthermore, the expression of identified genes and miRNAs was validated by quantitative real-time PCR in an AKI model. Our study revealed significant dysregulation of three genes (Aspn, Clec2h, Tmigd1) and two miRNAs (mmu-miR-21a-3p, mmu-miR-223-3p) in AKI, each with p < 0.0001. These molecular markers are implicated in immune responses, tissue remodelling, and inflammation. We observed notable disturbances in specific immune cells, including activated and immature dendritic cells, M1 macrophages, and subsets of T cells (Treg, Th1, Th17). These alterations correlated significantly with AKI pathology, with dendritic cells and M1 macrophages showing p < 0.01, and T cell subsets demonstrating p < 0.05. These results highlight the intricate involvement of the immune system in AKI and indicate significant enrichment of pathways related to immune response, inflammation, and tissue remodelling, pointing to their pivotal roles in AKI pathophysiology. Our study underscored the significance of immune cell infiltration and dysregulated gene and miRNA expression in AKI. The identified genes (Clec2h, Aspn, and Tmigd1) and miRNAs (mmu-miR-21a-3p and mmu-miR-223-3p) offer potential diagnostic markers and therapeutic avenues for AKI. Subsequent investigations targeting these genes and miRNAs, along with the elucidated pathways, may augment the clinical management and outcomes for AKI patients.

MicroRNAs (miRNAs) regulate gene expression post-transcriptionally, primarily through binding sites in 3' untranslated regions (3' UTRs). While computational and biochemical approaches have been developed to predict miRNA binding sites on target messenger RNAs, reliable and high-throughput assessment of the regulatory effects of miRNAs on full-length 3' UTRs can still be challenging. Utilizing a miniaturized and high-throughput reporter assay, we present a 'pilot miRNA-targeting map', containing 4,994 successfully measured miRNA:3' UTR regulatory outputs by pairwise assays between 461 miRNAs and eleven 3' UTRs. This collection represents a large experimental miRNA:3' UTR dataset to date on a single platform. The methodology can be generally applied to studies of miRNA-mediated regulation of critical genes. We found that seedless sites can lead to substantial downregulation. We utilized this dataset in the development of a quantitative total score for modeling the total regulatory effects by both seed and seedless sites on a full-length 3' UTR. To assess the predictive value of the total score, we analyzed data from mRNA expression and proteomics studies. We found that the score can discriminate the potent miRNA inhibition from the weak inhibition and is thus useful for quantitative prediction of miRNA regulation. The score has been added to the STarMir program of the Sfold package now available via GitHub at https://github.com/Ding-RNA-Lab/Sfold.

Juvenile hormone (JH) represses insect metamorphosis and stimulates reproduction. JH titers are generally low in juveniles, drop to a nadir during metamorphosis, increase after eclosion and peak in vitellogenic phase. We found that Jhamt, a rate-limiting enzyme in JH biosynthesis, mirrors JH titer patterns in the migratory locust. Knocking down Jhamt reduced JH titers, led to precocious nymphal ecdysis, metamorphosis and impaired vitellogenesis. Jhamt is negatively regulated by miR-276 and positively by miR-182013-5p. miR-276 is abundant in late nymphal but low in adults, while miR-182013-5p shows the opposite pattern. In nymphs, miR-276 binds more to Jhamt, while in adults, miR-182013-5p dominates. Functionally, miR-276 reduced Jhamt and JH levels, shortening nymphal development and inhibiting Vg expression. Conversely, miR-182013-5p increased Jhamt and JH levels, prolonging nymphal development and enhancing Vg expression. Our findings identify miR-276 and miR-182013-5p as dual regulators in JH biosynthesis, acting as "brake" and "accelerator," respectively. This study provides new insights into JH titer fluctuations and miRNA regulation in insect metamorphosis and reproduction.

Multiple sclerosis is believed to be an autoimmune disease that is influenced by T helper (Th) cell differentiation. GATA3 plays an important role in reducing the development and severity of MS by shifting the differentiation of Th cells to Th2 and regulatory T cells while inhibiting the differentiation of Th1 and Th17 cells. Considering the functional role of rs1058240 SNP in the 3'-UTR of GATA3 mRNA, the association of target SNP with the risk of RRMS was examined.

Genomic DNA was extracted from whole blood samples of 200 RRMS patients and 226 healthy individuals as a control group. Different genotypes of rs1058240 SNP were determined using the RFLP-PCR technique. Statistical analysis was performed using SPSS software and χ2 and logistic regression tests. The stability of GATA3 mRNA secondary structures and the binding patterns of GATA3-miRNAs with different alleles were evaluated using RNAfold and RNAhybrid programs, respectively.

The results indicated that the GATA3 rs1058240 G allele (p value = 0.010, OR = 1.45, CI = 1.09-1.93) and GG genotype (adjusted p value = 0.017, OR = 2.27, 95%CI = 1.16-4.44) increased the risk of RRMS, particularly in women (adjusted p value = 0.006, OR = 2.99, 95%CI = 1.37-6.52). Bioinformatics analysis revealed that although the allelic variation of this polymorphism had only a slight effect on mRNA stability (-177 to -177.20), the G allele significantly increased miRNA binding strength and miRNA-mRNA thermodynamic stability for hsa-miR-337-5p, hsa-miR-4445-3p, hsa-miR-4485-3p, hsa-miR-95-3p (ΔMFE > 0) compared to the A allele.

The G allele and GG genotype of rs1058240 in GATA3 mRNA 3'-UTR were found to be risk factors for increasing the susceptibility to RRMS.

Current medical research has been demonstrating the roles of miRNAs in a variety of cellular mechanisms, lending credence to the association between miRNA dysregulation and multiple diseases. Understanding the mechanisms of miRNA is critical for developing effective diagnostic and therapeutic strategies. miRNA-mRNA interactions emerge as the most important mechanism to be understood despite their experimental validation constraints. Accordingly, several computational models have been developed to predict miRNA-mRNA interactions, albeit presenting limited predictive capabilities, poor characterisation of miRNA-mRNA interactions, and low usability. To address these drawbacks, we developed PRIMITI, a PRedictive model for the Identification of novel miRNA-Target mRNA Interactions. PRIMITI is a novel machine learning model that utilises CLIP-seq and expression data to characterise functional target sites in 3'-untranslated regions (3'-UTRs) and predict miRNA-target mRNA repression activity. The model was trained using a reliable negative sample selection approach and the robust extreme gradient boosting (XGBoost) model, which was coupled with newly introduced features, including sequence and genetic variation information. PRIMITI achieved an area under the receiver operating characteristic (ROC) curve (AUC) up to 0.96 for a prediction of functional miRNA-target site binding and 0.96 for a prediction of miRNA-target mRNA repression activity on cross-validation and an independent blind test. Additionally, the model outperformed state-of-the-art methods in recovering miRNA-target repressions in an unseen microarray dataset and in a collection of validated miRNA-mRNA interactions, highlighting its utility for preliminary screening. PRIMITI is available on a reliable, scalable, and user-friendly web server at https://biosig.lab.uq.edu.au/primiti.

The modeling of miRNA-mRNA interactions holds significant implications for synthetic biology and human health. However, this research area presents specific challenges due to the multifaceted nature of mRNA downregulation by miRNAs, influenced by numerous factors including competition or synergism among miRNAs and mRNAs. In this study, we present an improved computational model for predicting miRNA-mRNA interactions, addressing aspects not previously modeled. Firstly, we integrated a novel set of features that significantly enhanced the predictor's performance. Secondly, we demonstrated the cell-specific nature of certain aspects of miRNA-mRNA interactions, highlighting the importance of designing models tailored to specific cell types for improved accuracy. Moreover, we introduce a miRNA binding site interaction model (miBSIM) that, for the first time, accounts for both the distribution of miRNA binding sites along the mRNA and their respective strengths in regulating mRNA stability. Our analysis suggests that distant miRNA sites often compete with each other, revealing the intricate interplay of binding site interactions. Overall, our new predictive model shows a significant improvement of up to 6.43% over previous models in the field. The code of our model is available at https://www.cs.tau.ac.il/~tamirtul/miBSIM.

Lung adenocarcinoma is highly heterogeneous at the molecular level between different stages; therefore, understanding molecular mechanisms contributing to such heterogeneity is needed. In addition, multiple stages of progression are critical factors for lung adenocarcinoma treatment. However, previous studies showed that cancer progression is associated with altered lncRNA expression, highlighting the tissue-specific and developmental stage-specific nature of lncRNAs in various diseases. Therefore, a study using an integrated network approach to explore the role of lncRNA in carcinogenesis was done using expression profiles revealing stage-specific and conserved lncRNA biomarkers in lung adenocarcinoma. We constructed ceRNA networks for each stage of lung adenocarcinoma and analysed them using network topology, differential co-expression network, protein-protein interaction network, functional enrichment, survival analysis, genomic analysis and deep learning to identify potential lncRNA biomarkers. The co-expression networks of healthy and three successive stages of lung adenocarcinoma have shown different network properties. One conserved and four stage-specific lncRNAs are identified as genome regulatory biomarkers. These lncRNAs can successfully identify lung adenocarcinoma and different stages of progression using deep learning. In addition, we identified five mRNAs, four miRNAs and twelve novel carcinogenic interactions associated with the progression of lung adenocarcinoma. These lncRNA biomarkers will provide a novel perspective into the underlying mechanism of adenocarcinoma progression and may be further helpful in early diagnosis, treatment and prognosis of this deadly disease.

Cardiovascular diseases contribute significantly to global morbidity and mortality. MicroRNAs are crucial in the development and progression of these diseases by regulating gene expression in various cells and tissues. Their roles in conditions like atherosclerosis, heart failure, myocardial infarction, and arrhythmias have been widely researched.

The present study provides an overview of existing evidence regarding miRNAs' role in cardiovascular disease pathogenesis. Furthermore, the study examines current state-of-the-art technologies used in the study of miRNAs in cardiovascular disease. As a final point, we examine how miRNAs may serve as disease biomarkers, therapeutic targets, and prognostic indicators.

In cardiology, microRNAs, small noncoding RNA molecules, are crucial to the posttranscriptional regulation of genes. Their role in regulating cardiac cell differentiation and maturation is critical during the development of the heart. They maintain the cardiac function of an adult heart by contributing to its electrical and contractile activity. By binding to messenger RNA molecules, they inhibit protein translation or degrade mRNA. Several cardiovascular diseases are associated with dysregulation of miRNAs, including arrhythmias, hypertension, atherosclerosis, and heart failure. miRNAs can be used as biomarkers to diagnose and predict diseases as well as therapeutic targets. A variety of state-of-the-art technologies have aided researchers in discovering, profiling, and analyzing miRNAs, including microarray analysis, next-generation sequencing, and others.

Developing new diagnostics and therapeutic approaches is becoming more feasible as researchers refine their understanding of miRNA function. Ultimately, this will reduce the burden of cardiovascular disease around the world.

RNA interference (RNAi) has become a widely used experimental approach for post-transcriptional regulation and is increasingly showing its potential as future targeted drugs. However, the prediction of highly efficient siRNAs (small interfering RNAs) is still hindered by dataset biases, the inadequacy of prediction methods, and the presence of off-target effects. To overcome these limitations, we propose an accurate and robust prediction method, OligoFormer, for siRNA design.

OligoFormer comprises three different modules including thermodynamic calculation, RNA-FM module, and Oligo encoder. Oligo encoder is the core module based on the transformer encoder. Taking siRNA and mRNA sequences as input, OligoFormer can obtain thermodynamic parameters, RNA-FM embedding, and Oligo embedding through these three modules, respectively. We carefully benchmarked OligoFormer against six comparable methods on siRNA efficacy datasets. OligoFormer outperforms all the other methods, with an average improvement of 9% in AUC, 6.6% in PRC, 9.8% in F1 score, and 5.1% in PCC compared to the best method among them in our inter-dataset validation. We also provide a comprehensive pipeline with prediction of siRNA efficacy and off-target effects using PITA score and TargetScan score. The ablation study shows RNA-FM module and thermodynamic parameters improved the performance and accelerated convergence of OligoFormer. The saliency maps by gradient backpropagation and base preference maps show certain base preferences in initial and terminal region of siRNAs.

The source code of OligoFormer is freely available on GitHub at: https://github.com/lulab/OligoFormer. Docker image of OligoFormer is freely available on the docker hub at https://hub.docker.com/r/yilanbai/oligoformer.

Small RNA (sRNAs)- mediated RNA silencing is emerging as a key player in host-microbe interactions. However, its role in fungus-plant interactions relevant to biocontrol of plant diseases is yet to be explored. This study aimed to investigate Dicer (DCL)-mediated endogenous and cross-kingdom gene expression regulation in the biocontrol fungus Clonostachys rosea and wheat roots during interactions.

C. rosea Δdcl2 strain exhibited significantly higher root colonization than the WT, whereas no significant differences were observed for Δdcl1 strains. Dual RNA-seq revealed the upregulation of CAZymes, membrane transporters, and effector coding genes in C. rosea, whereas wheat roots responded with the upregulation of stress-related genes and the downregulation of growth-related genes. The expression of many of these genes was downregulated in wheat during the interaction with DCL deletion strains, underscoring the influence of fungal DCL genes on wheat defense response. sRNA sequencing identified 18 wheat miRNAs responsive to C. rosea, and three were predicted to target the C. rosea polyketide synthase gene pks29. Two of these miRNAs (mir_17532_x1 and mir_12061_x13) were observed to enter C. rosea from wheat roots with fluorescence analyses and to downregulate the expression of pks29, showing plausible cross-kingdom RNA silencing of the C. rosea gene by wheat miRNAs.

We provide insights into the mechanisms underlying the interaction between biocontrol fungi and plant roots. Moreover, the study sheds light on the role of sRNA-mediated gene expression regulation in C. rosea-wheat interactions and provides preliminary evidence of cross-kingdom RNA silencing between plants and biocontrol fungi.

RNA-sequencing technology provides an effective tool for understanding miRNA regulation in complex human diseases, including cancers. A large number of computational methods have been developed to make use of bulk and single-cell RNA-sequencing data to identify miRNA regulations at the resolution of multiple samples (i.e. group of cells or tissues). However, due to the heterogeneity of individual samples, there is a strong need to infer miRNA regulation specific to individual samples to uncover miRNA regulation at the single-sample resolution level.

Here, we develop a framework, Scan, for scanning sample-specific miRNA regulation. Since a single network inference method or strategy cannot perform well for all types of new data, Scan incorporates 27 network inference methods and two strategies to infer tissue-specific or cell-specific miRNA regulation from bulk or single-cell RNA-sequencing data. Results on bulk and single-cell RNA-sequencing data demonstrate the effectiveness of Scan in inferring sample-specific miRNA regulation. Moreover, we have found that incorporating the prior information of miRNA targets can generally improve the accuracy of miRNA target prediction. In addition, Scan can contribute to construct cell/tissue correlation networks and recover aggregate miRNA regulatory networks. Finally, the comparison results have shown that the performance of network inference methods is likely to be data-specific, and selecting optimal network inference methods is required for more accurate prediction of miRNA targets.

Scan provides a useful method to help infer sample-specific miRNA regulation for new data, benchmark new network inference methods and deepen the understanding of miRNA regulation at the resolution of individual samples.

Apelin is an endogenous prepropeptide that regulates cardiac homeostasis and various physiological processes. Intravenous injection has been shown to improve cardiac contractility in patients with heart failure. However, its short half-life prevents studying its impact on left ventricular remodeling in the long term. Here, we aim to study whether microparticle-mediated slow release of apelin improves heart function and left ventricular remodeling in mice with myocardial infarction (MI).

A cardiac patch was fabricated by embedding apelin-containing microparticles in a fibrin gel scaffold. MI was induced via permanent ligation of the left anterior descending coronary artery in adult C57BL/6J mice followed by epicardial patch placement immediately after (acute MI) or 28 days (chronic MI) post-MI. Four groups were included in this study, namely sham, MI, MI plus empty microparticle-embedded patch treatment, and MI plus apelin-containing microparticle-embedded patch treatment. Cardiac function was assessed by transthoracic echocardiography. Cardiomyocyte morphology, apoptosis, and cardiac fibrosis were evaluated by histology. Cardioprotective pathways were determined by RNA sequencing, quantitative polymerase chain reaction, and Western blot.

The level of endogenous apelin was largely reduced in the first 7 days after MI induction and it was normalized by day 28. Apelin-13 encapsulated in poly(lactic-co-glycolic acid) microparticles displayed a sustained release pattern for up to 28 days. Treatment with apelin-containing microparticle-embedded patch inhibited cardiac hypertrophy and reduced scar size in both acute and chronic MI models, which is associated with improved cardiac function. Data from cellular and molecular analyses showed that apelin inhibits the activation and proliferation of cardiac fibroblasts by preventing transforming growth factor-β-mediated activation of Smad2/3 (supporessor of mothers against decapentaplegic 2/3) and downstream profibrotic gene expression.

Poly(lactic-co-glycolic acid) microparticles prolonged the apelin release time in the mouse hearts. Epicardial delivery of the apelin-containing microparticle-embedded patch protects mice from both acute and chronic MI-induced cardiac dysfunction, inhibits cardiac fibrosis, and improves left ventricular remodeling.

The combination of morphogenetic and transcription factors together with the synergic aid of noncoding RNAs and their cognate RNA binding proteins contribute to shape motor neurons (MN) identity. Here, we extend the noncoding perspective of human MN, by detailing the molecular and biological activity of CyCoNP (as Cytoplasmic Coordinator of Neural Progenitors) a highly expressed and MN-enriched human lncRNA. Through in silico prediction, in vivo RNA purification and loss of function experiments followed by RNA-sequencing, we found that CyCoNP sustains a specific neuron differentiation program, required for the physiology of both neuroblastoma cells and hiPSC-derived MN, which mainly involves miR-4492 and NCAM1 mRNA. We propose a novel lncRNA-mediated 'dual mode' of action, in which CyCoNP acts in trans as a classical RNA sponge by sequestering miR-4492 from its pro-neuronal targets, including NCAM1 mRNA, and at the same time it plays an additional role in cis by interacting with NCAM1 mRNA and regulating the availability and localization of the miR-4492 in its proximity. These data highlight novel insights into the noncoding RNA-mediated control of human neuron physiology and point out the importance of lncRNA-mediated interactions for the spatial distribution of regulatory molecules.