miRmine: a database of human miRNA expression profiles

Bioinformatic Analysis of Autism-Related miRNAs and Their PoTential as Biomarkers for Autism Epigenetic Inheritance

BACKGROUND/OBJECTIVES

The dysregulation of miRNA expression in samples from autistic individuals indicates that they are involved in autism. The participation of miRNAs in paternal epigenetic inheritance has also been reported. This study used bioinformatics tools to analyze the literature and genetic databases to search for miRNAs associated with autism, aiming to explore their suitability to investigate paternal epigenetic inheritance.

METHODS

Autism-related miRNAs were searched in public databases using bioinformatic tools (miRNA-to-genes analysis). The genes targeted by these autism-related miRNAs, which are common to neurons, sperm, and PBMCs, were identified. Enrichment analyses were performed to identify the biological processes regulated by the candidate miRNAs. Autism-related miRNAs were also identified by an inverse analysis (genes-to-miRNA analysis), starting from autism-related genes.

RESULTS

In the miRNA-to-gene analysis, 416 miRNAs involved in autism were found, of which 77 were expressed in sperm, PBMCs, and neurons. From these, 18 were differentially expressed in the brain and in at least one peripheral sample (saliva or blood), suggesting that they might be suitable to be used in the investigation of autism biomarkers and inheritance. In the genes-to-miRNA analysis, 36 miRNAs were identified, from which 9 coincided with the results of direct analysis.

CONCLUSIONS

Although there is no consensus about miRNAs related to autism, there are candidate miRNAs that show clear potential to be explored as biomarkers. The coincidence in the expression of miRNAs in sperm, neurons, and PBMCs indicates that they are valuable biological samples to study the role of miRNAs in the paternal epigenetic inheritance of autism.

Multiplexed assays of human disease-relevant mutations reveal UTR dinucleotide composition as a major determinant of RNA stability

Untranslated regions (UTRs) contain crucial regulatory elements for RNA stability, translation and localization, so their integrity is indispensable for gene expression. Approximately 3.7% of genetic variants associated with diseases occur in UTRs, yet a comprehensive understanding of UTR variant functions remains limited due to inefficient experimental and computational assessment methods. To systematically evaluate the effects of UTR variants on RNA stability, we established a massively parallel reporter assay on 6555 UTR variants reported in human disease databases. We examined the RNA degradation patterns mediated by the UTR library in two cell lines, and then applied LASSO regression to model the influential regulators of RNA stability. We found that UA dinucleotides and UA-rich motifs are the most prominent destabilizing element. Gain of UA dinucleotide outlined mutant UTRs with reduced stability. Studies on endogenous transcripts indicate that high UA-dinucleotide ratios in UTRs promote RNA degradation. Conversely, elevated GC content and protein binding on UA dinucleotides protect high-UA RNA from degradation. Further analysis reveals polarized roles of UA-dinucleotide-binding proteins in RNA protection and degradation. Furthermore, the UA-dinucleotide ratio of both UTRs is a common characteristic of genes in innate immune response pathways, implying a coordinated stability regulation through UTRs at the transcriptomic level. We also demonstrate that stability-altering UTRs are associated with changes in biobank-based health indices, underscoring the importance of precise UTR regulation for wellness. Our study highlights the importance of RNA stability regulation through UTR primary sequences, paving the way for further exploration of their implications in gene networks and precision medicine.

RNA sequence analysis landscape: A comprehensive review of task types, databases, datasets, word embedding methods, and language models

Deciphering information of RNA sequences reveals their diverse roles in living organisms, including gene regulation and protein synthesis. Aberrations in RNA sequence such as dysregulation and mutations can drive a diverse spectrum of diseases including cancers, genetic disorders, and neurodegenerative conditions. Furthermore, researchers are harnessing RNA's therapeutic potential for transforming traditional treatment paradigms into personalized therapies through the development of RNA-based drugs and gene therapies. To gain insights of biological functions and to detect diseases at early stages and develop potent therapeutics, researchers are performing diverse types RNA sequence analysis tasks. RNA sequence analysis through conventional wet-lab methods is expensive, time-consuming and error prone. To enable large-scale RNA sequence analysis, empowerment of wet-lab experimental methods with Artificial Intelligence (AI) applications necessitates scientists to have a comprehensive knowledge of both DNA and AI fields. While molecular biologists encounter challenges in understanding AI methods, computer scientists often lack basic foundations of RNA sequence analysis tasks. Considering the absence of a comprehensive literature that bridges this research gap and promotes the development of AI-driven RNA sequence analysis applications, the contributions of this manuscript are manifold: It equips AI researchers with biological foundations of 47 distinct RNA sequence analysis tasks. It sets a stage for development of benchmark datasets related to 47 distinct RNA sequence analysis tasks by facilitating cruxes of 64 different biological databases. It presents word embeddings and language models applications across 47 distinct RNA sequence analysis tasks. It streamlines the development of new predictors by providing a comprehensive survey of 58 word embeddings and 70 language models based predictive pipelines performance values as well as top performing traditional sequence encoding based predictors and their performances across 47 RNA sequence analysis tasks.

Omics Data Integration Uncovers mRNA-miRNA Interaction Regions in Genes Associated with Chronic Venous Insufficiency

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.

Leishmania donovani modulates host miRNAs regulating cholesterol biosynthesis for its survival

Cholesterol reduction by intracellular protozoan parasite Leishmania donovani (L. donovani), causative agent of leishmaniasis, impairs antigen presentation, pro-inflammatory cytokine secretion and host-protective membrane-receptor signaling in macrophages. Here, we studied the miRNA mediated regulation of cholesterol biosynthetic genes to understand the possible mechanism of L. donovani-induced cholesterol reduction and therapeutic importance of miRNAs in leishmaniasis. System-scale genome-wide microtranscriptome screening was performed to identify the miRNAs involved in the regulation of expression of key cholesterol biosynthesis regulatory genes through miRanda3.0. 11 miRNAs out of 2823, showing complementarity with cholesterol biosynthetic genes were finally selected for expression analysis. These selected miRNAs were differentially regulated in THP-1 derived macrophages and in primary human macrophages by L. donovani. Correlation of expression and target validation through luciferase assay suggested two key miRNAs, hsa-miR-1303 and hsa-miR-874-3p regulating the key genes hmgcr and hmgcs1 respectively. Inhibition of hsa-mir-1303 and hsa-miR-874-3p augmented the expression of targets and reduced the parasitemia in macrophages. This study will also provide the platform for the development of miRNA-based therapy against leishmaniasis.

Characterization of residual microRNAs in AAV vector batches produced in HEK293 mammalian cells and Sf9 insect cells

With more than 130 clinical trials and 8 approved gene therapy products, adeno-associated virus (AAV) stands as one of the most popular vehicles to deliver therapeutic DNA in vivo. One critical quality attribute analyzed in AAV batches is the presence of residual DNA, as it could pose genotoxic risks or induce immune responses. Surprisingly, the presence of small cell-derived RNAs, such as microRNAs (miRNAs), has not been investigated previously. In this study, we examined the presence of miRNAs in purified AAV batches produced in mammalian or in insect cells. Our findings revealed that miRNAs were present in all batches, regardless of the production cell line or capsid serotype (2 and 8). Quantitative assays indicated that miRNAs were co-purified with the recombinant AAV particles in a proportion correlated with their abundance in the production cells. The level of residual miRNAs was reduced via an immunoaffinity chromatography purification process including a tangential flow filtration step or by RNase treatment, suggesting that most miRNA contaminants are likely non-encapsidated. In summary, we demonstrate, for the first time, that miRNAs are co-purified with AAV particles. Further investigations are required to determine whether these miRNAs could interfere with the safety or efficacy of AAV-mediated gene therapy.

Quantifying the massive pleiotropy of microRNA: a human microRNA-disease causal association database generated with ChatGPT

MicroRNAs (miRNAs) are recognized as key regulatory factors in numerous human diseases, with the same miRNA often involved in several diseases simultaneously or being identified as a biomarker for dozens of separate diseases. While of evident biological importance, miRNA pleiotropy remains poorly understood, and quantifying this could greatly aid in understanding the broader role miRNAs play in health and disease. To this end, we introduce miRAIDD (miRNA Artificial Intelligence Disease Database), a comprehensive database of human miRNA-disease causal associations constructed using large language models (LLM). Through this endeavor, we provide two entirely novel contributions: 1) we systematically quantify miRNA pleiotropy, a property of evident translational importance; and 2) describe biological and bioinformatic characteristics of miRNAs which lead to increased pleiotropy. Further, we provide our code, database, and experience using AI LLMs to the broader research community.

Long noncoding RNA TUG1 promotes cisplatin resistance in ovarian cancer via upregulation of DNA polymerase eta

Chemoresistance is a major cause of high mortality and poor survival in patients with ovarian cancer (OVCA). Understanding the mechanisms of chemoresistance is urgently required to develop effective therapeutic approaches to OVCA. Here, we show that expression of the long noncoding RNA, taurine upregulated gene 1 (TUG1), is markedly upregulated in samples from OVCA patients who developed resistance to primary platinum-based therapy. Depletion of TUG1 increased sensitivity to cisplatin in the OVCA cell lines, SKOV3 and KURAMOCHI. Combination therapy of cisplatin with antisense oligonucleotides targeting TUG1 coupled with a drug delivery system effectively relieved the tumor burden in xenograft mouse models. Mechanistically, TUG1 acts as a competing endogenous RNA by downregulating miR-4687-3p and miR-6088, both of which target DNA polymerase eta (POLH), an enzyme required for translesion DNA synthesis. Overexpression of POLH reversed the effect of TUG1 depletion on cisplatin-induced cytotoxicity. Our data suggest that TUG1 upregulation allows OVCA to tolerate DNA damage via upregulation of POLH; this provides a strong rationale for targeting TUG1 to overcome cisplatin resistance in OVCA.

CMC: Cancer miRNA Census - a list of cancer-related miRNA genes

A growing body of evidence indicates an important role of miRNAs in cancer; however, there is no definitive, convenient-to-use list of cancer-related miRNAs or miRNA genes that may serve as a reference for analyses of miRNAs in cancer. To this end, we created a list of 165 cancer-related miRNA genes called the Cancer miRNA Census (CMC). The list is based on a score, built on various types of functional and genetic evidence for the role of particular miRNAs in cancer, e.g. miRNA-cancer associations reported in databases, associations of miRNAs with cancer hallmarks, or signals of positive selection of genetic alterations in cancer. The presence of well-recognized cancer-related miRNA genes, such as MIR21, MIR155, MIR15A, MIR17 or MIRLET7s, at the top of the CMC ranking directly confirms the accuracy and robustness of the list. Additionally, to verify and indicate the reliability of CMC, we performed a validation of criteria used to build CMC, comparison of CMC with various cancer data (publications and databases), and enrichment analyses of biological pathways and processes such as Gene Ontology or DisGeNET. All validation steps showed a strong association of CMC with cancer/cancer-related processes confirming its usefulness as a reference list of miRNA genes associated with cancer.

miRNA cargo in circulating vesicles from neurons is altered in individuals with schizophrenia and associated with severe disease

While RNA expression appears to be altered in several brain disorders, the constraints of postmortem analysis make it impractical for well-powered population studies and biomarker development. Given that the unique molecular composition of neurons are reflected in their extracellular vesicles (EVs), we hypothesized that the fractionation of neuron derived EVs provides an opportunity to specifically profile their encapsulated contents noninvasively from blood. To investigate this hypothesis, we determined miRNA expression in microtubule associated protein 1B (MAP1B)-enriched serum EVs derived from neurons from a large cohort of individuals with schizophrenia and nonpsychiatric comparison participants. We observed dysregulation of miRNA in schizophrenia subjects, in particular those with treatment-resistance and severe cognitive deficits. These data support the hypothesis that schizophrenia is associated with alterations in posttranscriptional regulation of synaptic gene expression and provides an example of the potential utility of tissue-specific EV analysis in brain disorders.

Resequencing of the TMF-1 (TATA Element Modulatory Factor) regulated protein (TRNP1) gene in domestic and wild canids

BACKGROUND

Cortical folding is related to the functional organization of the brain. The TMF-1 regulated protein (TRNP1) regulates the expansion and folding of the mammalian cerebral cortex, a process that may have been accelerated by the domestication of dogs. The objectives of this study were to sequence the TRNP1 gene in dogs and related canid species, provide evidence of its expression in dog brain and compare the genetic variation within dogs and across the Canidae. The gene was located in silico to dog chromosome 2. The sequence was experimentally confirmed by amplifying and sequencing the TRNP1 exonic and promoter regions in 72 canids (36 purebred dogs, 20 Gy wolves and wolf-dog hybrids, 10 coyotes, 5 red foxes and 1 Gy fox).

RESULTS

A partial TRNP1 transcript was isolated from several regions in the dog brain. Thirty genetic polymorphisms were found in the Canis sp. with 17 common to both dogs and wolves, and only one unique to dogs. Seven polymorphisms were observed only in coyotes. An additional 9 variants were seen in red foxes. Dogs were the least genetically diverse. Several polymorphisms in the promoter and 3'untranslated region were predicted to alter TRNP1 function by interfering with the binding of transcriptional repressors and miRNAs expressed in neural precursors. A c.259_264 deletion variant that encodes a polyalanine expansion was polymorphic in all species studied except for dogs. A stretch of 15 nucleotides that is found in other mammalian sequences (corresponding to 5 amino acids located between Pro58 and Ala59 in the putative dog protein) was absent from the TRNP1 sequences of all 5 canid species sequenced. Both of these aforementioned coding sequence variations were predicted to affect the formation of alpha helices in the disordered region of the TRNP1 protein.

CONCLUSIONS

Potentially functionally important polymorphisms in the TRNP1 gene are found within and across various Canis species as well as the red fox, and unique differences in protein structure have evolved and been conserved in the Canidae compared to all other mammalian species.

Diagnostic applications and therapeutic option of Cascade CRISPR/Cas in the modulation of miRNA in diverse cancers: promises and obstacles

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas technology is a molecular tool specific to sequences for engineering genomes. Among diverse clusters of Cas proteins, the class 2/type II CRISPR/Cas9 system, despite several challenges, such as off-target effects, editing efficiency, and efficient delivery, has shown great promise for driver gene mutation discovery, high-throughput gene screening, epigenetic modulation, nucleic acid detection, disease modeling, and more importantly for therapeutic purposes. CRISPR-based clinical and experimental methods have applications across a wide range of areas, especially for cancer research and, possibly, anticancer therapy. On the other hand, given the influential role of microRNAs (miRNAs) in the regulations of cellular division, carcinogenicity, tumorigenesis, migration/invasion, and angiogenesis in diverse normal and pathogenic cellular processes, in different stages of cancer, miRNAs are either oncogenes or tumor suppressors, according to what type of cancer they are involved in. Hence, these noncoding RNA molecules are conceivable biomarkers for diagnosis and therapeutic targets. Moreover, they are suggested to be adequate predictors for cancer prediction. Conclusive evidence proves that CRISPR/Cas system can be applied to target small non-coding RNAs. However, the majority of studies have highlighted the application of the CRISPR/Cas system for targeting protein-coding regions. In this review, we specifically discuss diverse applications of CRISPR-based tools for probing miRNA gene function and miRNA-based therapeutic involvement in different types of cancers.

Impact of liver failure on the circulating extracellular vesicle miRNA repertoire

BACKGROUND & AIMS

Cell-derived small extracellular vesicles (sEVs) participate in cell-cell communication via the transfer of molecular cargo including selectively enriched microRNAs (miRNAs). Utilizing advances in sEV isolation and characterization, this study investigates the impact of liver injury and dysfunction on the circulating EV-miRNA profile.

METHODS

High-throughput screening of 799 sEV-miRNAs isolated from plasma was performed in patients across a spectrum of liver disorders including compensated and decompensated chronic liver disease, acute-on-chronic liver failure (ACLF), and acute liver failure, in addition to healthy controls and those with severe sepsis. miRNA levels were compared with clinical and biochemical parameters, composite scores of liver disease, and patient outcomes.

RESULTS

miRNA screening revealed the degree of hepatic dysfunction to be the main determinant of changes in circulating sEV-miRNA profile, with liver-specific miRNA-122 being among the most highly dysregulated in severe injury. Principal components analyses of the 215 differentially expressed miRNAs showed differing profiles, particularly among those with acute liver injury and ACLF. A distinct profile of dysregulated miRNA, but not circulating cytokines, was shown to characterize ACLF, with four consensus miRNAs identified-miR-320e, miR-374-5p, miR-202-3p, and miR-1910-5p. High miR-320e was associated with poorer 90-day survival (p = 0.014) and regulated the functional gene targets IK, RPS5, MANBAL, and PEBP1.

CONCLUSIONS

This first comprehensive analysis to the best of our knowledge of patients with varying degrees and stages of liver failure demonstrates miRNA profiles specifically within the sEV compartment to be significantly altered in progressive liver disease and highlights the diagnostic and prognostic potential of sEV-miRNA in ACLF while also establishing downstream gene targets.

Diesel exhaust particles exposure induces liver dysfunction: Exploring predictive potential of human circulating microRNAs signature relevant to liver injury risk

Diesel exhaust particles (DEP) pollution should be taken seriously because it is an extensive environmental and occupational health concern. Exploring early effect biomarkers is crucial for monitoring and managing DEP-associated health risk assessment. Here, we found that serum levels of 67 miRNAs were dysregulated in DEP exposure group. Notably, 20 miRNAs were identified as each having a significant dose-response relationship with the internal exposure level of DEP. Further, we revealed that the DEP exposure could affect the liver function of subjects and that 7 miRNAs (including the well-known liver injury indicator, miR-122-5p) could serve as the novel epigenetic-biomarkers (epi-biomarkers) to reflect the liver-specific response to the DEP exposure. Importantly, an unprecedented prediction model using these 7 miRNAs was established for the assessment of DEP-induced liver injury risk. Finally, bioinformatic analysis indicated that the unique set of miRNA panel in serum might also contribute to the molecular mechanism of DEP exposure-induced liver damage. These results broaden our understanding of the adverse health outcomes of DEP exposure. Noteworthy, we believe this study could shed light on roles and functions of epigenetic biomarkers from environmental exposure to health outcomes by revealing the full chain of exposure-miRNAs-molecular pathways-disease evidence.

Wheel drive-based DNA sensing system for highly specific and rapid one-step detection of MiRNAs at the attomolar level

With the use of DNA as building blocks, a variety of microRNA amplification-based sensing systems have been developed. Nevertheless, ultrasensitive, selective and rapid detection of microRNAs with a high signal-to-background ratio and point mutation discrimination ability remains a challenge. Herein, we propose a novel wheel drive-based DNA sensing system (NWDS) based on a self-assembled, self-quenched nanoprobe (SQP) to conduct highly specific and ultrasensitive one-step measurement of microRNAs. In this work, a signalling recognition DNA hairpin (DH) sequence with a self-complementary stem domain of 14 base pairs was used, which contained three functional regions, namely a recognition region for the target miRNA-21, a sticky region with 9 complementary nucleotides to the 3'terminus of a DNA wheel (DW) and a region for the hybridization with a quenching DNA primer (DP). The SQP was ingeniously self-assembled at room temperature by the DH and DP, which was capable of eliminating unwanted background signals. MiRNA-21 was employed as a target model to specifically activate the SQP, leading to specific hybridization between the HP and DW. With the assistance of a polymerase, an SQP-based wheel driving took place to induce hybridization/polymerization displacement cycles, initiating target recycling and DP displacement. As a result, a large amount of the newly formed hybrid SQP/DW accumulated to generate a substantially enhanced fluorescence signal. In this way, the newly proposed NWDS exhibits ultrasensitivity with a detection limit of 5.62 aM across a wide linear dynamic response range up to 200 nM, excellent selectivity with the capability to discriminate homologous miRNAs and one-base, two-base and three-base mismatched sequences, and an outstanding analytical performance in complex systems. In addition, the significant simultaneous advantages of one-step operation, rapid detection within 15 min and a high signal-to-background ratio of 26 offer a unique opportunity to promote the early diagnosis of cancer-related diseases and molecular biological analysis.

MyBrain-Seq: A Pipeline for MiRNA-Seq Data Analysis in Neuropsychiatric Disorders

High-throughput sequencing of small RNA molecules such as microRNAs (miRNAs) has become a widely used approach for studying gene expression and regulation. However, analyzing miRNA-Seq data can be challenging because it requires multiple steps, from quality control and preprocessing to differential expression and pathway-enrichment analyses, with many tools and databases available for each step. Furthermore, reproducibility of the analysis pipeline is crucial to ensure that the results are accurate and reliable. Here, we present myBrain-Seq, a comprehensive and reproducible pipeline for analyzing miRNA-Seq data that incorporates miRNA-specific solutions at each step of the analysis. The pipeline was designed to be flexible and user-friendly, allowing researchers with different levels of expertise to perform the analysis in a standardized and reproducible manner, using the most common and widely used tools for each step. In this work, we describe the implementation of myBrain-Seq and demonstrate its capacity to consistently and reproducibly identify differentially expressed miRNAs and enriched pathways by applying it to a real case study in which we compared schizophrenia patients who responded to medication with treatment-resistant schizophrenia patients to obtain a 16-miRNA treatment-resistant schizophrenia profile.

Reassessing the Abundance of miRNAs in the Human Pancreas and Rodent Cell Lines and Its Implication

miRNAs are critical for pancreas development and function. However, we found that there are discrepancies regarding pancreatic miRNA abundance in published datasets. To obtain a more relevant profile that is closer to the true profile, we profiled small RNAs from human islets cells, acini, and four rodent pancreatic cell lines routinely used in diabetes and pancreatic research using a bias reduction protocol for small RNA sequencing. In contrast to the previous notion that miR-375-3p is the most abundant pancreatic miRNA, we found that miR-148a-3p and miR-7-5p were also abundant in islets. In silico studies using predicted and validated targets of these three miRNAs revealed that they may work cooperatively in endocrine and exocrine cells. Our results also suggest, compared to the most-studied miR-375, that both miR-148a-3p and miR-7-5p may play more critical roles in the human pancreas. Moreover, according to in silico-predicted targets, we found that miR-375-3p had a much broader target spectrum by targeting the coding sequence and the 5' untranslated region, rather than the conventional 3' untranslated region, suggesting additional unexplored roles of miR-375-3p beyond the pancreas. Our study provides a valuable new resource for studying miRNAs in pancreata.

Improving miRNA Disease Association Prediction Accuracy Using Integrated Similarity Information and Deep Autoencoders

MicroRNAs (miRNAs) are short endogenous non-encoding RNA molecules (22nt) that have a vital role in many biological and molecular processes inside the human body. Abnormal and dysregulated expressions of miRNAs are correlated with many complex disorders. Time-consuming wet-lab biological experiments are costly and labour-intensive. So, the situation demands feasible and efficient computational approaches for predicting promising miRNAs associated with diseases. Here a two-stage feature pruning approach based on miRNA feature similarity fusion that uses deep attention autoencoder and recursive feature elimination with cross-validation (RFECV) is proposed for predicting unknown miRNA-disease associations. In the first stage, an attention autoencoder captures highly influential features from the fused feature vector. For further pruning of features, RFECV is applied. The resultant features were given to a Random Forest classifier for association prediction. The Highest AUC of 94.41% is attained when all miRNA similarity measures are merged with disease similarities. Case studies were done on two diseases-lymphoma and leukaemia, to examine the reliability of the approach. Comparative analysis shows that the proposed approach outperforms recent methodologies for predicting miRNA-disease associations.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

Machine learning in the development of targeting microRNAs in human disease

A microRNA is a small, single-stranded, non-coding ribonucleic acid that plays a crucial role in RNA silencing and can regulate gene expression. With the in-depth study of miRNA in development and disease, miRNA has become an attractive target for novel therapeutic strategies. Exploring miRNA targeting therapy only through experiments is expensive and laborious, so it is essential to develop novel and efficient computational methods to narrow down the search. Recent advances in machine learning applied in biomedical informatics provide opportunities to explore miRNA-targeting drugs, thus promoting miRNA therapeutics. This review provides an overview of recent advancements in miRNA targeting therapeutic using machine learning. First, we mainly describe the basics of predicting miRNA targeting drugs, including pharmacogenomic data resources and data preprocessing. Then we present primary machine learning algorithms and elaborate their application in discovering relationships among miRNAs, drugs, and diseases. Along with the progress of miRNA targeting therapeutics, we finally analyze and discuss the current challenges and opportunities that machine learning confronts.

Overview of Computational and Experimental Methods to Identify Tissue-Specific MicroRNA Targets

As ubiquitous posttranscriptional regulators of gene expression, microRNAs (miRNAs) play key roles in cell physiology and function across taxa. In the last two decades, we have gained a good understanding about miRNA biogenesis pathways, modes of action, and consequences of miRNA-mediated gene regulation. More recently, research has focused on exploring causes for miRNA dysregulation, miRNA-mediated crosstalk between genes and signaling pathways, and the role of miRNAs in disease.This chapter discusses methods for the identification of miRNA-target interactions and causes for tissue-specific miRNA-target regulation. Computational approaches for predicting miRNA target sites and assessing tissue-specific target regulation are discussed. Moreover, there is an emphasis on features that affect miRNA target recognition and how high-throughput sequencing protocols can help in assessing miRNA-mediated gene regulation on a genome-wide scale. In addition, this chapter introduces some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA-target interactions.

Microfluidics for Profiling miRNA Biomarker Panels in AI-Assisted Cancer Diagnosis and Prognosis

Early detection of cancers and their precise subtyping are essential to patient stratification and effective cancer management. Data-driven identification of expression biomarkers coupled with microfluidics-based detection shows promise to revolutionize cancer diagnosis and prognosis. MicroRNAs play key roles in cancers and afford detection in tissue and liquid biopsies. In this review, we focus on the microfluidics-based detection of miRNA biomarkers in AI-based models for early-stage cancer subtyping and prognosis. We describe various subclasses of miRNA biomarkers that could be useful in machine-based predictive modeling of cancer staging and progression. Strategies for optimizing the feature space of miRNA biomarkers are necessary to obtain a robust signature panel. This is followed by a discussion of the issues in model construction and validation towards producing Software-as-Medical-Devices (SaMDs). Microfluidic devices could facilitate the multiplexed detection of miRNA biomarker panels, and an overview of the different strategies for designing such microfluidic systems is presented here, with an outline of the detection principles used and the corresponding performance measures. Microfluidics-based profiling of miRNAs coupled with SaMD represent high-performance point-of-care solutions that would aid clinical decision-making and pave the way for accessible precision personalized medicine.

Systematic characterization of seed overlap microRNA cotargeting associated with lupus pathogenesis

BACKGROUND

Combinatorial gene regulation by multiple microRNAs (miRNAs) is widespread and closely spaced target sites often act cooperatively to achieve stronger repression ("neighborhood" miRNA cotargeting). While miRNA cotarget sites are suggested to be more conserved and implicated in developmental control, the pathological significance of miRNA cotargeting remains elusive.

RESULTS

Here, we report the pathogenic impacts of combinatorial miRNA regulation on inflammation in systemic lupus erythematosus (SLE). In the SLE mouse model, we identified the downregulation of two miRNAs, miR-128 and miR-148a, by TLR7 stimulation in plasmacytoid dendritic cells. Functional analyses using human cell lines demonstrated that miR-128 and miR-148a additively target KLF4 via extensively overlapping target sites ("seed overlap" miRNA cotargeting) and suppress the inflammatory responses. At the transcriptome level, "seed overlap" miRNA cotargeting increases susceptibility to downregulation by two miRNAs, consistent with additive but not cooperative recruitment of two miRNAs. Systematic characterization further revealed that extensive "seed overlap" is a prevalent feature among broadly conserved miRNAs. Highly conserved target sites of broadly conserved miRNAs are largely divided into two classes-those conserved among eutherian mammals and from human to Coelacanth, and the latter, including KLF4-cotargeting sites, has a stronger association with both "seed overlap" and "neighborhood" miRNA cotargeting. Furthermore, a deeply conserved miRNA target class has a higher probability of haplo-insufficient genes.

CONCLUSIONS

Our study collectively suggests the complexity of distinct modes of miRNA cotargeting and the importance of their perturbations in human diseases.

JSCSNCP-LMA: a method for predicting the association of lncRNA-miRNA

Non-coding RNAs (ncRNAs) have long been considered the "white elephant" on the genome because they lack the ability to encode proteins. However, in recent years, more and more biological experiments and clinical reports have proved that ncRNAs account for a large proportion in organisms. At the same time, they play a decisive role in the biological processes such as gene expression and cell growth and development. Recently, it has been found that short sequence non-coding RNA(miRNA) and long sequence non-coding RNA(lncRNA) can regulate each other, which plays an important role in various complex human diseases. In this paper, we used a new method (JSCSNCP-LMA) to predict lncRNA-miRNA with unknown associations. This method combined Jaccard similarity algorithm, self-tuning spectral clustering similarity algorithm, cosine similarity algorithm and known lncRNA-miRNA association networks, and used the consistency projection to complete the final prediction. The results showed that the AUC values of JSCSNCP-LMA in fivefold cross validation (fivefold CV) and leave-one-out cross validation (LOOCV) were 0.9145 and 0.9268, respectively. Compared with other models, we have successfully proved its superiority and good extensibility. Meanwhile, the model also used three different lncRNA-miRNA datasets in the fivefold CV experiment and obtained good results with AUC values of 0.9145, 0.9662 and 0.9505, respectively. Therefore, JSCSNCP-LMA will help to predict the associations between lncRNA and miRNA.

Viral and Host Small RNA Response to SARS-CoV-2 Infection

After two years into the pandemic of the coronavirus disease 2019 (COVID-19), it remains unclear how the host RNA interference (RNAi) pathway and host miRNAs regulate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and impact the development of COVID-19. In this study, we profiled small RNAs in SARS-CoV-2-infected human ACE2-expressing HEK293T cells and observed dysregulated host small RNA groups, including specific host miRNAs that are altered in response to SARS-CoV-2 infection. By comparing dysregulated miRNAs in different SARS-CoV-2-infected samples, we identified miRNA-210-3p, miRNA-30-5p, and miR-146a/b as key host miRNAs that may be involved in SARS-CoV-2 infection. Furthermore, by comparing virally derived small RNAs (vsmRNAs) in different SARS-CoV-2-infected samples, we observed multiple hot spots in the viral genome that are prone to generating vsmRNAs, and their biogenesis can be dependent on the antiviral isoform of Dicer. Moreover, we investigated the biogenesis of a recently identified SARS-CoV-2 viral miRNA encoded by ORF7a and found that it is differentially expressed in different infected cell lines or in the same cell line with different viral doses. Our results demonstrate the involvement of both host small RNAs and vsmRNAs in SARS-CoV-2 infection and identify these small RNAs as potential targets for anti-COVID-19 therapeutic development.

Signatures of genetic variation in human microRNAs point to processes of positive selection and population-specific disease risks

The occurrence of natural variation in human microRNAs has been the focus of numerous studies during the last 20 years. Most of them have been focused on the role of specific mutations in disease, while a minor proportion seek to analyse microRNA diversity in the genomes of human populations. We analyse the latest human microRNA annotations in the light of the most updated catalogue of genetic variation provided by the 1000 Genomes Project. By means of the in silico analysis of microRNA genetic variation we show that the level of evolutionary constraint of these sequences is governed by the interplay of different factors, like their evolutionary age or genomic location. The role of mutations in the shaping of microRNA-driven regulatory interactions is emphasized with the acknowledgement that, while the whole microRNA sequence is highly conserved, the seed region shows a pattern of higher genetic diversity that appears to be caused by the dramatic frequency shifts of a fraction of human microRNAs. We highlight the participation of these microRNAs in population-specific processes by identifying that not only the seed, but also the loop, are particularly differentiated regions among human populations. The quantitative computational comparison of signatures of population differentiation showed that candidate microRNAs with the largest differences are enriched in variants implicated in gene expression levels (eQTLs), selective sweeps and pathological processes. We explore the implication of these evolutionary-driven microRNAs and their SNPs in human diseases, such as different types of cancer, and discuss their role in population-specific disease risk.

mRNA-miRNA networks identify metabolic pathways associated to the anti-tumorigenic effect of thyroid hormone on preneoplastic nodules and hepatocellular carcinoma

Background

Thyroid hormones (THs) inhibit hepatocellular carcinoma (HCC) through different mechanisms. However, whether microRNAs play a role in the antitumorigenic effect of THs remains unknown.

Methods

By next generation sequencing (NGS) we performed a comprehensive comparative miRNomic and transcriptomic analysis of rat hepatic preneoplastic lesions exposed or not to a short-term treatment with triiodothyronine (T3). The expression of the most deregulated miRs was also investigated in rat HCCs, and in human hepatoma cell lines, treated or not with T3.

Results

Among miRs down-regulated in preneoplastic nodules following T3, co-expression networks revealed those targeting thyroid hormone receptor-β (Thrβ) and deiodinase1, and Oxidative Phosphorylation. On the other hand, miRs targeting members of the Nrf2 Oxidative Pathway, Glycolysis, Pentose Phosphate Pathway and Proline biosynthesis – all involved in the metabolic reprogramming displayed by preneoplastic lesions– were up-regulated. Notably, while the expression of most miRs deregulated in preneoplastic lesions was not altered in HCC or in hepatoma cells, miR-182, a miR known to target Dio1 and mitochondrial complexes, was down-deregulated by T3 treatment at all stages of hepatocarcinogenesis and in hepatocarcinoma cell lines. In support to the possible critical role of miR-182 in hepatocarcinogenesis, exogenous expression of this miR significantly impaired the inhibitory effect of T3 on the clonogenic growth capacity of human HCC cells.

Conclusions

This work identified several miRNAs, so far never associated to T3. In addition, the precise definition of the miRNA-mRNA networks elicited by T3 treatment gained in this study may provide a better understanding of the key regulatory events underlying the inhibitory effect of T3 on HCC development. In this context, T3-induced down-regulation of miR-182 appears as a promising tool.

AntiVIRmiR: A repository of host antiviral miRNAs and their expression along with experimentally validated viral miRNAs and their targets

miRNAs play an essential role in promoting viral infections as well as modulating the antiviral defense. Several miRNA repositories have been developed for different species, e.g., human, mouse, and plant. However, 'VIRmiRNA' is the only existing resource for experimentally validated viral miRNAs and their targets. We have developed a 'AntiVIRmiR' resource encompassing data on host/virus miRNA expression during viral infection. This resource with 22,741 entries is divided into four sub-databases viz., 'DEmiRVIR', 'AntiVmiR', 'VIRmiRNA2' and 'VIRmiRTar2'. 'DEmiRVIR' has 10,033 differentially expressed host-viral miRNAs for 21 viruses. 'AntiVmiR' incorporates 1,642 entries for host miRNAs showing antiviral activity for 34 viruses. Additionally, 'VIRmiRNA2' includes 3,340 entries for experimentally validated viral miRNAs from 50 viruses along with 650 viral isomeric sequences for 14 viruses. Further, 'VIRmiRTar2' has 7,726 experimentally validated targets for viral miRNAs against 21 viruses. Furthermore, we have also performed network analysis for three sub-databases. Interactions between up/down-regulated human miRNAs and viruses are displayed for 'AntiVmiR' as well as 'DEmiRVIR'. Moreover, 'VIRmiRTar2' interactions are shown among different viruses, miRNAs, and their targets. We have provided browse, search, external hyperlinks, data statistics, and useful analysis tools. The database available at https://bioinfo.imtech.res.in/manojk/antivirmir would be beneficial for understanding the host-virus interactions as well as viral pathogenesis.

MicroRNA expression in male infertility

Male infertility is a multifactorial disorder that involves different physiopathological mechanisms and multiple genes. In this sense, we analyse the role of miRNAs in this pathology. Gene expression analysis can provide relevant information to detect biomarkers, signalling pathways, pathologic mechanisms, and potential therapeutic targets for the disease. In this review, we describe four miRNA microarrays related to patients who present infertility diseases, including azoospermia, asthenozoospermia, and oligoasthenozoospermic. We selected 13 miRNAs with altered expressions in testis tissue (hsa-miR-122-5p, hsa-miR-145-5p, hsa-miR-16-5p, hsa-miR-193a-3p, hsa-miR-19a-3p, hsa-miR-23a-3p, hsa-miR-30b-5p, hsa-miR-34b-5p, hsa-miR-34c-5p, hsa-miR-374b-5p, hsa-miR-449a, hsa-miR-574-3p and hsa-miR-92a-3p), and systematically examine the mechanisms of four relevant miRNAs (hsa-miR-16-5p, hsa-miR-19a-3p, hsa-miR-92a-3p and hsa-miR-30b-5p) which we found that regulated a large number of proteins. An interaction network was generated, and its connections allowed us to identify signalling pathways and interactions between proteins associated with male infertility. In this way, we confirm that the most affected and relevant pathway is the PI3K-Akt signalling.

Comparative Profiling of Circulating Exosomal Small RNAs Derived From Peruvian Patients With Tuberculosis and Pulmonary Adenocarcinoma

Tuberculosis (TB) is one of the most fatal infectious diseases, caused by the aerobic bacteria Mycobacterium tuberculosis. It is estimated that one-third of the world’s population is infected with the latent (LTB) version of this disease, with only 5-10% of infected individuals developing its active (ATB) form. Pulmonary adenocarcinoma (PA) is the most common and diverse form of primary lung carcinoma. The simultaneous or sequential occurrence of TB and lung cancer in patients has been widely reported and is known to be an issue for diagnosis and surgical treatment. Raising evidence shows that patients cured of TB represent a group at risk for developing PA. In this work, using sRNA-sequencing, we evaluated the expression patterns of circulating small RNAs available in exosomes extracted from blood samples of Peruvian patients affected by latent tuberculosis, active tuberculosis, or pulmonary adenocarcinoma. Differential expression analysis revealed a set of 24 microRNAs perturbed in these diseases, revealing potential biomarker candidates for the Peruvian population. Most of these miRNAs are normally expressed in healthy lung tissue and are potential regulators of different shared and unique KEGG pathways related to cancers, infectious diseases, and immunology.

MiRLog and dbmiR: prioritization and functional annotation tools to study human microRNA sequence variants

The recent identification of noncoding variants with pathogenic effects suggests that these variations could underlie a significant number of undiagnosed cases. Several computational methods have been developed to predict the functional impact of noncoding variants, but they exhibit only partial concordance and are not integrated with functional annotation resources, making the interpretation of these variants still challenging. MicroRNAs (miRNAs) are small noncoding RNA molecules that act as fine regulators of gene expression and play crucial functions in several biological processes, such as cell proliferation and differentiation. An increasing number of studies demonstrate a significant impact of miRNA single nucleotide variants (SNVs) both in Mendelian diseases and complex traits. To predict the functional effect of miRNA SNVs, we implemented a new meta‐predictor, MiRLog, and we integrated it into a comprehensive database, dbmiR, which includes a precompiled list of all possible miRNA allelic SNVs, providing their biological annotations at nucleotide and miRNA levels. MiRLog and dbmiR were used to explore the genetic variability of miRNAs in 15,708 human genomes included in the gnomAD project, finding several ultra‐rare SNVs with a potentially deleterious effect on miRNA biogenesis and function representing putative contributors to human phenotypes.

Altered Expression of Brain-specific Autism-Associated miRNAs in the Han Chinese Population

Autism is a complex neurodevelopmental disorder. However, its etiology is still unknown. MicroRNAs (miRNAs) are key post-transcriptional regulators. They play an important role in neurodevelopment and brain functions and may be involved in the pathogenesis of autism. Previous studies indicated altered expression of miRNAs in patients with autism. However, the findings were not consistent, and further explorations were needed. This study aimed to investigate whether miRNAs were dysregulated in autism. We examined the expression of 30 brain-specific autism-associated miRNAs in 110 patients with autism and 113 controls in the Han Chinese population using quantitative reverse transcription–polymerase chain reaction. The results demonstrated that 10 miRNAs (hsa-miR-191-5p, hsa-miR-151a-3p, hsa-miR-139-5p, hsa-miR-181a-5p, hsa-miR-432-5p, hsa-miR-181b-5p, hsa-miR-195-5p, hsa-miR-328-3p, hsa-miR-106a-5p, and hsa-miR-484) were significantly differentially expressed (false discovery rate <0.05). All of them were up-regulated in patients with autism compared with controls. The targets of these miRNAs were enriched for genes and pathways related to neurodevelopment, brain functions and autism. These findings suggested the participation of these 10 miRNAs in the pathogenesis of autism in the Han Chinese population.

MicroRNAs as Biomarkers for Ionizing Radiation Injury

Accidental radiation exposures such as industrial accidents and nuclear catastrophes pose a threat to human health, and the potential or substantial injury caused by ionizing radiation (IR) from medical treatment that cannot be ignored. Although the mechanisms of IR-induced damage to various organs have been gradually investigated, medical treatment of irradiated individuals is still based on clinical symptoms. Hence, minimally invasive biomarkers that can predict radiation damage are urgently needed for appropriate medical management after radiation exposure. In the field of radiation biomarker, finding molecular biomarkers to assess different levels of radiation damage is an important direction. In recent years, microRNAs have been widely reported as several diseases’ biomarkers, such as cancer and cardiovascular diseases, and microRNAs are also of interest to the ionizing radiation field as radiation response molecules, thus researchers are turning attention to the potential of microRNAs as biomarkers in tumor radiation response and the radiation toxicity prediction of normal tissues. In this review, we summarize the distribution of microRNAs, the progress on research of microRNAs as markers of IR, and make a hypothesis about the origin and destination of microRNAs in vivo after IR.

miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles

Formation of mature miRNAs and their expression is a highly controlled process. It is very much dependent upon the post-transcriptional regulatory events. Recent findings suggest that several RNA binding proteins beyond Drosha/Dicer are involved in the processing of miRNAs. Deciphering of conditional networks for these RBP-miRNA interactions may help to reason the spatio-temporal nature of miRNAs which can also be used to predict miRNA profiles. In this direction, >25TB of data from different platforms were studied (CLIP-seq/RNA-seq/miRNA-seq) to develop Bayesian causal networks capable of reasoning miRNA biogenesis. The networks ably explained the miRNA formation when tested across a large number of conditions and experimentally validated data. The networks were modeled into an XGBoost machine learning system where expression information of the network components was found capable to quantitatively explain the miRNAs formation levels and their profiles. The models were developed for 1,204 human miRNAs whose accurate expression level could be detected directly from the RNA-seq data alone without any need of doing separate miRNA profiling experiments like miRNA-seq or arrays. A first of its kind, miRbiom performed consistently well with high average accuracy (91%) when tested across a large number of experimentally established data from several conditions. It has been implemented as an interactive open access web-server where besides finding the profiles of miRNAs, their downstream functional analysis can also be done. miRbiom will help to get an accurate prediction of human miRNAs profiles in the absence of profiling experiments and will be an asset for regulatory research areas. The study also shows the importance of having RBP interaction information in better understanding the miRNAs and their functional projectiles where it also lays the foundation of such studies and software in future.

miR‑383 increases the cisplatin sensitivity of lung adenocarcinoma cells through inhibition of the RBM24‑mediated NF‑κB signaling pathway

The expression of microRNA-383 (miR-383) is downregulated in a variety of tumor tissues, and it exhibits antiproliferative activity in non-small cell lung cancer cells. In the present study, an association between the downregulation of miR-383 expression and the deletion of chr8p22 in patients with lung adenocarcinoma was identified. The promoting effect of miR-383 on cisplatin sensitivity was verified both in vivo and in vitro. Additionally, it was revealed that the expression of RNA binding motif protein 24 (RBM24) protein was regulated by and negatively correlated with miR-383 expression. Ectopic expression of RBM24 or inhibition of miR-383 decreased the chemosensitivity of parental A549 cells, whereas knockdown of RBM24 in cisplatin-resistant A549 cells increased chemosensitivity. Mechanistically, miR-383 interfered with the activation of nuclear factor κB (NF-κB) signaling through repression of RBM24-mediated phosphorylation of Rel-like domain-containing protein A and inhibitor α of NF-κB. Taken together, the downregulation of miR-383 induced RBM24 expression, which was mediated through the activation of NF-κB signaling, to contribute to chemotherapy resistance in lung adenocarcinoma cells. The results of the present study highlight potential therapeutic targets for the clinical reversal of the chemotherapy resistance in lung adenocarcinoma.

miR-1 coordinately regulates lysosomal v-ATPase and biogenesis to impact proteotoxicity and muscle function during aging

Muscle function relies on the precise architecture of dynamic contractile elements, which must be fine-tuned to maintain motility throughout life. Muscle is also plastic, and remodeled in response to stress, growth, neural and metabolic inputs. The conserved muscle-enriched microRNA, miR-1, regulates distinct aspects of muscle development, but whether it plays a role during aging is unknown. Here we investigated Caenorhabditis elegans miR-1 in muscle function in response to proteostatic stress. mir-1 deletion improved mid-life muscle motility, pharyngeal pumping, and organismal longevity upon polyQ35 proteotoxic challenge. We identified multiple vacuolar ATPase subunits as subject to miR-1 control, and the regulatory subunit vha-13/ATP6V1A as a direct target downregulated via its 3'UTR to mediate miR-1 physiology. miR-1 further regulates nuclear localization of lysosomal biogenesis factor HLH-30/TFEB and lysosomal acidification. Our studies reveal that miR-1 coordinately regulates lysosomal v-ATPase and biogenesis to impact muscle function and health during aging.

Sequence-based correction of barcode bias in massively parallel reporter assays

Massively parallel reporter assays (MPRAs) are a high-throughput method for evaluating in vitro activities of thousands of candidate cis-regulatory elements (CREs). In these assays, candidate sequences are cloned upstream or downstream from a reporter gene tagged by unique DNA sequences. However, tag sequences may themselves affect reporter gene expression and lead to major potential biases in the measured cis-regulatory activity. Here, we present a sequence-based method for correcting tag-sequence-specific effects and show that our method can significantly reduce this source of variation and improve the identification of functional regulatory variants by MPRAs. We also show that our model captures sequence features associated with post-transcriptional regulation of mRNA. Thus, this new method helps not only to improve detection of regulatory signals in MPRA experiments but also to design better MPRA protocols.

LDAH2V: Exploring Meta-Paths Across Multiple Networks for lncRNA-Disease Association Prediction

Accumulating evidence has demonstrated dysfunctions of long non-coding RNAs (lncRNAs) are involved in various complex human diseases. However, even today, the relationships between lncRNAs and diseases remain unknown in most cases. Developing effective computational approaches to identify potential lncRNA-disease associations has become a hot topic. Existing network-based approaches are usually focused on the intrinsic features of lncRNAs and diseases but ignore the heterogeneous information of biological networks. Considering the limitations in previous methods, we propose LDAH2V, an efficient computational framework for predicting potential lncRNA-disease associations. LDAH2V uses the HIN2Vec to calculate the meta-path and feature vector for each lncRNA-disease pair in the heterogeneous information network (HIN), which consists of lncRNA similarity network, disease similarity network, miRNA similarity network, and the associations between them. Then, a Gradient Boosting Tree (GBT) classifier to predict lncRNA-disease associations is built with the feature vectors. The results show that LDAH2V performs significantly better than the four existing state-of-the-art methods and gains an AUC of 0.97 in the 10-fold cross-validation test. Furthermore, case studies of colon cancer and ovarian cancer-related lncRNAs have been confirmed in related databases and medical literature.

Plasma MicroRNA Profiling of Plasmodium falciparum Biomass and Association with Severity of Malaria Disease

Severe malaria (SM) is a major public health problem in malaria-endemic countries. Sequestration of Plasmodium falciparum–infected erythrocytes in vital organs and the associated inflammation leads to organ dysfunction. MicroRNAs (miRNAs), which are rapidly released from damaged tissues into the host fluids, constitute a promising biomarker for the prognosis of SM. We applied next-generation sequencing to evaluate the differential expression of miRNAs in SM and in uncomplicated malaria (UM. Six miRNAs were associated with in vitro P. falciparum cytoadhesion, severity in children, and P. falciparum biomass. Relative expression of hsa-miR-4497 quantified by TaqMan-quantitative reverse transcription PCR was higher in plasma of children with SM than those with UM (p<0.048) and again correlated with P. falciparum biomass (p = 0.033). These findings suggest that different physiopathological processes in SM and UM lead to differential expression of miRNAs and pave the way for future studies to assess their prognostic value in malaria.

Bioinformatics Accelerates the Major Tetrad: A Real Boost for the Pharmaceutical Industry

With advanced technology and its development, bioinformatics is one of the avant-garde fields that has managed to make amazing progress in the pharmaceutical-medical field by modeling the infrastructural dimensions of healthcare and integrating computing tools in drug innovation, facilitating prevention, detection/more accurate diagnosis, and treatment of disorders, while saving time and money. By association, bioinformatics and pharmacovigilance promoted both sample analyzes and interpretation of drug side effects, also focusing on drug discovery and development (DDD), in which systems biology, a personalized approach, and drug repositioning were considered together with translational medicine. The role of bioinformatics has been highlighted in DDD, proteomics, genetics, modeling, miRNA discovery and assessment, and clinical genome sequencing. The authors have collated significant data from the most known online databases and publishers, also narrowing the diversified applications, in order to target four major areas (tetrad): DDD, anti-microbial research, genomic sequencing, and miRNA research and its significance in the management of current pandemic context. Our analysis aims to provide optimal data in the field by stratification of the information related to the published data in key sectors and to capture the attention of researchers interested in bioinformatics, a field that has succeeded in advancing the healthcare paradigm by introducing developing techniques and multiple database platforms, addressed in the manuscript.

MicroRNA as a Novel Biomarker in the Diagnosis of Head and Neck Cancer

Head and neck squamous cell carcinoma is the sixth most common cancer worldwide, with 890,000 new cases and 450,000 deaths in 2018, and although the survival statistics for some patient groups are improving, there is still an urgent need to find a fast and reliable biomarker that allows early diagnosis. This niche can be filled by microRNA, small single-stranded non-coding RNA molecules, which are expressed in response to specific events in the body. This article presents the potential use of microRNAs in the diagnosis of HNSCC, compares the advances in this field to other diseases, especially other cancers, and discusses the detailed use of miRNA as a biomarker in profiling and predicting the treatment outcome with radiotherapy and immunotherapy. Potential problems and difficulties related to the development of this promising technology, and areas on which future research should be focused in order to overcome these difficulties, were also indicated.

Lack of Conserved miRNA Deregulation in HPV-Induced Squamous Cell Carcinomas

Squamous cell carcinomas (SCCs) in the anogenital and head and neck regions are associated with high-risk types of human papillomaviruses (HR-HPV). Deregulation of miRNA expression is an important contributor to carcinogenesis. This study aimed to pinpoint commonly and uniquely deregulated miRNAs in cervical, anal, vulvar, and tonsillar tumors of viral or non-viral etiology, searching for a common set of deregulated miRNAs linked to HPV-induced carcinogenesis. RNA was extracted from tumors and nonmalignant tissues from the same locations. The miRNA expression level was determined by next-generation sequencing. Differential expression of miRNAs was calculated, and the patterns of miRNA deregulation were compared between tumors. The total of deregulated miRNAs varied between tumors of different locations by two orders of magnitude, ranging from 1 to 282. The deregulated miRNA pool was largely tumor-specific. In tumors of the same location, a low proportion of miRNAs were exclusively deregulated and no deregulated miRNA was shared by all four types of HPV-positive tumors. The most significant overlap of deregulated miRNAs was found between tumors which differed in location and HPV status (HPV-positive cervical tumors vs. HPV-negative vulvar tumors). Our results imply that HPV infection does not elicit a conserved miRNA deregulation in SCCs.

SPMLMI: predicting lncRNA-miRNA interactions in humans using a structural perturbation method

Long non-coding RNA (lncRNA)-microRNA (miRNA) interactions are quickly emerging as important mechanisms underlying the functions of non-coding RNAs. Accordingly, predicting lncRNA-miRNA interactions provides an important basis for understanding the mechanisms of action of ncRNAs. However, the accuracy of the established prediction methods is still limited. In this study, we used structural consistency to measure the predictability of interactive links based on a bilayer network by integrating information for known lncRNA-miRNA interactions, an lncRNA similarity network, and an miRNA similarity network. In particular, by using the structural perturbation method, we proposed a framework called SPMLMI to predict potential lncRNA-miRNA interactions based on the bilayer network. We found that the structural consistency of the bilayer network was higher than that of any single network, supporting the utility of bilayer network construction for the prediction of lncRNA-miRNA interactions. Applying SPMLMI to three real datasets, we obtained areas under the curves of 0.9512 ± 0.0034, 0.8767 ± 0.0033, and 0.8653 ± 0.0021 based on 5-fold cross-validation, suggesting good model performance. In addition, the generalizability of SPMLMI was better than that of the previously established methods. Case studies of two lncRNAs (i.e., SNHG14 and MALAT1) further demonstrated the feasibility and effectiveness of the method. Therefore, SPMLMI is a feasible approach to identify novel lncRNA-miRNA interactions underlying complex biological processes.

Variation of microRNA expression in the human placenta driven by population identity and sex of the newborn

BACKGROUND

Analysis of lymphocyte cell lines revealed substantial differences in the expression of mRNA and microRNA (miRNA) among human populations. The extent of such population-associated differences in actual human tissues remains largely unexplored. The placenta is one of the few solid human tissues that can be collected in substantial numbers in a controlled manner, enabling quantitative analysis of transient biomolecules such as RNA transcripts. Here, we analyzed microRNA (miRNA) expression in human placental samples derived from 36 individuals representing four genetically distinct human populations: African Americans, European Americans, South Asians, and East Asians. All samples were collected at the same hospital following a unified protocol, thus minimizing potential biases that might influence the results.

RESULTS

Sequence analysis of the miRNA fraction yielded 938 annotated and 70 novel miRNA transcripts expressed in the placenta. Of them, 82 (9%) of annotated and 11 (16%) of novel miRNAs displayed quantitative expression differences among populations, generally reflecting reported genetic and mRNA-expression-based distances. Several co-expressed miRNA clusters stood out from the rest of the population-associated differences in terms of miRNA evolutionary age, tissue-specificity, and disease-association characteristics. Among three non-environmental influenced demographic parameters, the second largest contributor to miRNA expression variation after population was the sex of the newborn, with 32 miRNAs (3% of detected) exhibiting significant expression differences depending on whether the newborn was male or female. Male-associated miRNAs were evolutionarily younger and correlated inversely with the expression of target mRNA involved in neuron-related functions. In contrast, both male and female-associated miRNAs appeared to mediate different types of hormonal responses. Demographic factors further affected reported imprinted expression of 66 placental miRNAs: the imprinting strength correlated with the mother's weight, but not height.

CONCLUSIONS

Our results showed that among 12 assessed demographic variables, population affiliation and fetal sex had a substantial influence on miRNA expression variation among human placental samples. The effect of newborn-sex-associated miRNA differences further led to expression inhibition of the target genes clustering in specific functional pathways. By contrast, population-driven miRNA differences might mainly represent neutral changes with minimal functional impacts.

Candidate Alzheimer's Disease Biomarker miR-483-5p Lowers TAU Phosphorylation by Direct ERK1/2 Repression

MicroRNAs have been demonstrated as key regulators of gene expression in the etiology of a range of diseases including Alzheimer's disease (AD). Recently, we identified miR-483-5p as the most upregulated miRNA amongst a panel of miRNAs in blood plasma specific to prodromal, early-stage Alzheimer's disease patients. Here, we investigated the functional role of miR-483-5p in AD pathology. Using TargetScan and miRTarBase, we identified the microtubule-associated protein MAPT, often referred to as TAU, and the extracellular signal-regulated kinases 1 and 2 (ERK1 and ERK2), known to phosphorylate TAU, as predicted direct targets of miR-483-5p. Employing several functional assays, we found that miR-483-5p regulates ERK1 and ERK2 at both mRNA and protein levels, resulting in lower levels of phosphorylated forms of both kinases. Moreover, miR-483-5p-mediated repression of ERK1/2 resulted in reduced phosphorylation of TAU protein at epitopes associated with TAU neurofibrillary pathology in AD. These results indicate that upregulation of miR-483-5p can decrease phosphorylation of TAU via ERK pathway, representing a compensatory neuroprotective mechanism in AD pathology. This miR-483-5p/ERK1/TAU axis thus represents a novel target for intervention in AD.

Pilot study identifying circulating miRNA signature specific to alcoholic chronic pancreatitis and its implication on alcohol-mediated pancreatic tissue injury

Background and Aim

Alcohol exerts its effects on organs in multiple ways. Alcoholic chronic pancreatitis (ACP) is a disease in which alcohol triggers the pathological changes in pancreas, leading to chronic inflammation and fibrosis. The molecular mechanism behind these changes is not clear. Identification of key circulating miRNA changes in ACP patients and determination of the fraction that is secreted from diseased pancreas not only could serve as potential biomarker for assessing disease severity, but also could help identifying the molecular alterations prevailing in the organ precipitating the disease, to some extent.

Methods

We performed microRNA microarray using the Affymetrix miRNA 4.0 platform to identify differentially expressed miRNAs in serum of ACP patients as compared to alcoholic control individuals and then found out how many of them could be pancreas-specific and exosomally secreted. We further analyzed a pancreatitis-specific gene expression data set to find out the differentially expressed genes in diseased pancreas and explored the possible role of those selected miRNAs in regulation of gene expression in ACP.

Results

We identified 14 miRNAs differentially expressed in both serum and pancreas and also identified their experimentally validated targets. Transcription factors modulating the miRNA expression in an alcohol-dependent manner were also identified and characterized to derive the miRNA-gene-TF interaction network responsible for progression of the disease.

Conclusions

Differentially expressed miRNA signature demonstrated significant changes in both pro- and anti-inflammatory pathways probably balancing the chronic inflammation in the pancreas. Our findings also suggested possible involvement of pancreatic stellate cells in disease progression.

Pervasive Selection against MicroRNA Target Sites in Human Populations

MicroRNA target sites are often conserved during evolution and purifying selection to maintain such sites is expected. On the other hand, comparative analyses identified a paucity of microRNA target sites in coexpressed transcripts, and novel target sites can potentially be deleterious. We proposed that selection against novel target sites pervasive. The analysis of derived allele frequencies revealed that, when the derived allele is a target site, the proportion of nontarget sites is higher than expected, particularly for highly expressed microRNAs. Thus, new alleles generating novel microRNA target sites can be deleterious and selected against. When we analyzed ancestral target sites, the derived (nontarget) allele frequency does not show statistical support for microRNA target allele conservation. We investigated the joint effects of microRNA conservation and expression and found that selection against microRNA target sites depends mostly on the expression level of the microRNA. We identified microRNA target sites with relatively high levels of population differentiation. However, when we analyze separately target sites in which the target allele is ancestral to the population, the proportion of single-nucleotide polymorphisms with high F_st significantly increases. These findings support that population differentiation is more likely in target sites that are lost than in the gain of new target sites. Our results indicate that selection against novel microRNA target sites is prevalent and, although individual sites may have a weak selective pressure, the overall effect across untranslated regions is not negligible and should be accounted when studying the evolution of genomic sequences.

HAHmiR.DB: a server platform for high-altitude human miRNA-gene coregulatory networks and associated regulatory circuits

Around 140 million people live in high-altitude (HA) conditions! and even a larger number visit such places for tourism, adventure-seeking or sports training. Rapid ascent to HA can cause severe damage to the body organs and may lead to many fatal disorders. During induction to HA, human body undergoes various physiological, biochemical, hematological and molecular changes to adapt to the extreme environmental conditions. Several literature references hint that gene-expression-regulation and regulatory molecules like miRNAs and transcription factors (TFs) control adaptive responses during HA stress. These biomolecules are known to interact in a complex combinatorial manner to fine-tune the gene expression and help in controlling the molecular responses during this stress and ultimately help in acclimatization. High-Altitude Human miRNA Database (HAHmiR.DB) is a unique, comprehensive and curated collection of miRNAs that have been experimentally validated to be associated with HA stress, their level of expression in different altitudes, fold change, experiment duration, biomarker association, disease and drug association, tissue-specific expression level, Gene Ontology (GO) and Kyoto Encyclopaedia of Gene and Genomes (KEGG) pathway associations. As a server platform, it also uniquely constructs and analyses interactive miRNA-TF-gene coregulatory networks and extracts regulatory circuits/feed-forward loops (FFLs). These regulatory circuits help to offer mechanistic insights into complex regulatory mechanisms during HA stress. The server can also build these regulatory networks between two and more miRNAs of the database and also identify the regulatory circuits from this network. Hence, HAHmiR.DB is the first-of-its-kind database in HA research, which is a reliable platform to explore, compare, analyse and retrieve miRNAs associated with HA stress, their coregulatory networks and FFL regulatory-circuits. HAHmiR.DB is freely accessible at http://www.hahmirdb.in.

Predicting miRNA-disease associations using a hybrid feature representation in the heterogeneous network

BACKGROUND

Studies have found that miRNAs play an important role in many biological activities involved in human diseases. Revealing the associations between miRNA and disease by biological experiments is time-consuming and expensive. The computational approaches provide a new alternative. However, because of the limited knowledge of the associations between miRNAs and diseases, it is difficult to support the prediction model effectively.

METHODS

In this work, we propose a model to predict miRNA-disease associations, MDAPCOM, in which protein information associated with miRNAs and diseases is introduced to build a global miRNA-protein-disease network. Subsequently, diffusion features and HeteSim features, extracted from the global network, are combined to train the prediction model by eXtreme Gradient Boosting (XGBoost).

RESULTS

The MDAPCOM model achieves AUC of 0.991 based on 10-fold cross-validation, which is significantly better than that of other two state-of-the-art methods RWRMDA and PRINCE. Furthermore, the model performs well on three unbalanced data sets.

CONCLUSIONS

The results suggest that the information behind proteins associated with miRNAs and diseases is crucial to the prediction of the associations between miRNAs and diseases, and the hybrid feature representation in the heterogeneous network is very effective for improving predictive performance.

miRViz: a novel webserver application to visualize and interpret microRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in the regulation of major pathways in eukaryotic cells through their binding to and repression of multiple mRNAs. With high-throughput methodologies, various outcomes can be measured that produce long lists of miRNAs that are often difficult to interpret. A common question is: after differential expression or phenotypic screening of miRNA mimics, which miRNA should be chosen for further investigation? Here, we present miRViz (http://mirviz.prabi.fr/), a webserver application designed to visualize and interpret large miRNA datasets, with no need for programming skills. MiRViz has two main goals: (i) to help biologists to raise data-driven hypotheses and (ii) to share miRNA datasets in a straightforward way through publishable quality data representation, with emphasis on relevant groups of miRNAs. MiRViz can currently handle datasets from 11 eukaryotic species. We present real-case applications of miRViz, and provide both datasets and procedures to reproduce the corresponding figures. MiRViz offers rapid identification of miRNA families, as demonstrated here for the miRNA-320 family, which is significantly exported in exosomes of colon cancer cells. We also visually highlight a group of miRNAs associated with pluripotency that is particularly active in control of a breast cancer stem-cell population in culture.