miRCarta: a central repository for collecting miRNA candidates

The intricacies of isomiRs: from classification to clinical relevance

MicroRNAs (miRNAs) and isoforms of their archetype, called isomiRs, regulate gene expression via complementary base-pair binding to messenger RNAs (mRNAs). The partially evolutionarily conserved isomiR sequence variations are differentially expressed among tissues, populations, and genders, and between healthy and diseased states. Aiming towards the clinical use of isomiRs as diagnostic biomarkers and for therapeutic purposes, several challenges need to be addressed, including (i) clarification of isomiR definition, (ii) improved annotation in databases with new standardization (such as the mirGFF3 format), and (iii) improved methods of isomiR detection, functional verification, and in silico analysis. In this review we discuss the respective challenges, and highlight the opportunities for clinical use of isomiRs, especially in the light of increasing amounts of next-generation sequencing (NGS) data.

Exosomal miR-122-3p represses the growth and metastasis of MCF-7/ADR cells by targeting GRK4-mediated activation of the Wnt/β-catenin pathway

Breast cancer (BC) is a common cancer whose incidence continues to grow while its medical progress has stagnated. miRNAs are vital messengers that facilitate communications among different cancer cells. This study was to reveal the correlation of miR-122-3p expression with BC metastasis and Adriamycin (ADM) resistance and its mechanism of inhibiting BC metastasis. We found that expression of miR-122-3p is negatively correlated with BC metastasis and is lower in MCF-7/ADR cells. Overexpression of miR-122-3p in MCF-7/ADR cancer cells impairs their ability to migrate, invade, and stimulate blood vessel formation. Further research found that miR-122-3p directly binds to the 3' UTR of GRK4, reducing the phosphorylation of LRP6, which activates the Wnt/β-catenin signaling pathway, facilitating BC development and metastasis. In addition, we observed that miR-122-3p is present in MCF-7  cells, and treatment of MCF-7/ADR cells with MCF-7-derived exosomes, but not with exosomes from miR-122-3p-deficient MCF-7 cells, has identical effects to miR-122-3p overexpression. Data from xenograft experiments further suggest that excess miR-122-3p and MCF-7-derived exosomes inhibit the growth and metastasis of MCF-7/ADR cancer cells in vivo. In conclusion our data reveal that exosomal miR-122-3p may negatively regulate BC growth and metastasis, potentially serving as a diagnostic and druggable target for BC treatment.

Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome

MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression. This article offers the salient and current aspects of machine learning (ML) tools and approaches from genome to phenome in miRNA research. First, we underline that the complexity in the analysis of miRNA function ranges from their modes of biogenesis to the target diversity in diverse biological conditions. Therefore, it is imperative to first ascertain the miRNA coding potential of genomes and understand the regulatory mechanisms of their expression. This knowledge enables the efficient classification of miRNA precursors and the identification of their mature forms and respective target genes. Second, and because one miRNA can target multiple mRNAs and vice versa, another challenge is the assessment of the miRNA-mRNA target interaction network. Furthermore, long-noncoding RNA (lncRNA)and circular RNAs (circRNAs) also contribute to this complexity. ML has been used to tackle these challenges at the high-dimensional data level. The present expert review covers more than 100 tools adopting various ML approaches pertaining to, for example, (1) miRNA promoter prediction, (2) precursor classification, (3) mature miRNA prediction, (4) miRNA target prediction, (5) miRNA- lncRNA and miRNA-circRNA interactions, (6) miRNA-mRNA expression profiling, (7) miRNA regulatory module detection, (8) miRNA-disease association, and (9) miRNA essentiality prediction. Taken together, we unpack, critically examine, and highlight the cutting-edge synergy of ML approaches and miRNA research so as to develop a dynamic and microlevel understanding of human health and diseases.

Convergent and divergent evolution of microRNA-mediated regulation in metazoans

The evolution of microRNAs (miRNAs) has been studied extensively to understand their roles in gene regulation and evolutionary processes. This review focuses on how miRNA-mediated regulation has evolved in bilaterian animals, highlighting both convergent and divergent evolution. Since animals and plants display significant differences in miRNA biogenesis and target recognition, the 'independent origin' hypothesis proposes that miRNA pathways in these groups independently evolved from the RNA interference (RNAi) pathway, leading to modern miRNA repertoires through convergent evolution. However, recent evidence raises the alternative possibility that the miRNA pathway might have already existed in the last common ancestor of eukaryotes, and that the differences in miRNA pathway and miRNA repertoires among animal and plant lineages arise from lineage-specific innovations and losses of miRNA pathways, miRNA acquisition, and loss of miRNAs after eukaryotic divergence. The repertoire of miRNAs has considerably expanded during bilaterian evolution, primarily through de novo creation and duplication processes, generating new miRNAs. Although ancient functionally established miRNAs are rarely lost, many newly emerged miRNAs are transient and lineage specific, following a birth-death evolutionary pattern aligning with the 'out-of-the-testis' and 'transcriptional control' hypotheses. Our focus then shifts to the convergent molecular evolution of miRNAs. We summarize how miRNA clustering and seed mimicry contribute to this phenomenon, and we review how miRNAs from different sources converge to degrade maternal messenger RNAs (mRNAs) during animal development. Additionally, we describe how miRNAs evolve across species due to changes in sequence, seed shifting, arm switching, and spatiotemporal expression patterns, which can result in variations in target sites among orthologous miRNAs across distant strains or species. We also provide a summary of the current understanding regarding how the target sites of orthologous miRNAs can vary across strains or distantly related species. Although many paralogous miRNAs retain their seed or mature sequences after duplication, alterations can occur in the seed or mature sequences or expression patterns of paralogous miRNAs, leading to functional diversification. We discuss our current understanding of the functional divergence between duplicated miRNAs, and illustrate how the functional diversification of duplicated miRNAs impacts target site evolution. By investigating these topics, we aim to enhance our current understanding of the functions and evolutionary dynamics of miRNAs. Additionally, we shed light on the existing challenges in miRNA evolutionary studies, particularly the complexity of deciphering the role of miRNA-mediated regulatory network evolution in shaping gene expression divergence and phenotypic differences among species.

Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases

RNA editing, a common and potentially highly functional form of RNA modification, encompasses two different RNA modifications, namely adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. As inosines are interpreted as guanosines by the cellular machinery, both A-to-I and C-to-U editing change the nucleotide sequence of the RNA. Editing events in coding sequences have the potential to change the amino acid sequence of proteins, whereas editing events in noncoding RNAs can, for example, affect microRNA target binding. With advancing RNA sequencing technology, more RNA editing events are being discovered, studied, and reported. However, RNA editing events are still often overlooked or discarded as sequence read quality defects. With this position paper, we aim to provide guidelines and recommendations for the detection, validation, and follow-up experiments to study RNA editing, taking examples from the fields of cardiovascular and brain disease. We discuss all steps, from sample collection, storage, and preparation, to different strategies for RNA sequencing and editing-sensitive data analysis strategies, to validation and follow-up experiments, as well as potential pitfalls and gaps in the available technologies. This paper may be used as an experimental guideline for RNA editing studies in any disease context.

RFEM: A framework for essential microRNA identification in mice based on rotation forest and multiple feature fusion

With the increasing number of microRNAs (miRNAs), identifying essential miRNAs has become an important task that needs to be solved urgently. However, there are few computational methods for essential miRNA identification. Here, we proposed a novel framework called Rotation Forest for Essential MicroRNA identification (RFEM) to predict the essentiality of miRNAs in mice. We first constructed 1,264 miRNA features of all miRNA samples by fusing 38 miRNA features obtained from the PESM paper and 1,226 miRNA functional features calculated based on miRNA-target gene interactions. Then, we employed 182 training samples with 1,264 features to train the rotation forest model, which was applied to compute the essentiality scores of the candidate samples. The main innovations of RFEM were as follows: 1) miRNA functional features were introduced to enrich the diversity of miRNA features; 2) the rotation forest model used decision tree as the base classifier and could increase the difference among base classifiers through feature transformation to achieve better ensemble results. Experimental results show that RFEM significantly outperformed two previous models with the AUC (AUPR) of 0.942 (0.944) in three comparison experiments under 5-fold cross validation, which proved the model's reliable performance. Moreover, ablation study was further conducted to demonstrate the effectiveness of the novel miRNA functional features. Additionally, in the case studies of assessing the essentiality of unlabeled miRNAs, experimental literature confirmed that 7 of the top 10 predicted miRNAs have crucial biological functions in mice. Therefore, RFEM would be a reliable tool for identifying essential miRNAs.

The miRNA-target interactions: An underestimated intricacy

MicroRNAs (miRNAs) play indispensable roles in posttranscriptional gene regulation. Their cellular regulatory impact is determined not solely by their sheer number, which likely amounts to >2000 individual miRNAs in human, than by the regulatory effectiveness of single miRNAs. Although, one begins to develop an understanding of the complex mechanisms underlying miRNA-target interactions (MTIs), the overall knowledge of MTI functionality is still rather patchy. In this critical review, we summarize key features of mammalian MTIs. We especially highlight latest insights on (i) the dynamic make-up of miRNA binding sites including non-canonical binding sites, (ii) the cooperativity between miRNA binding sites, (iii) the adaptivity of MTIs through sequence modifications, (iv) the bearing of intra-cellular miRNA localization changes and (v) the role of cell type and cell status specific miRNA interaction partners. The MTI biology is discussed against the background of state-of-the-art approaches with particular emphasis on experimental strategies for evaluating miRNA functionality.

Comparative Analysis of Published Database Predicting MicroRNA Binding in 3'UTR of mRNA in Diverse Species

BACKGROUND

Micro-RNAs are endogenous non-coding RNA moieties of 22-27 nucleotides that play a crucial role in the regulation of various biological processes and make them useful prognostic and diagnostic biomarkers. Discovery and experimental validation of miRNA is a laborious and time-consuming process. For early prediction, multiple bioinformatics databases are available for miRNA target prediction; however, their utility can confuse amateur researchers in selecting the most appropriate tools for their study.

OBJECTIVE

This descriptive review aimed to analyse the usability of the existing database based on the following criteria: accessibility, efficiency, interpretability, updatability, and flexibility for miRNA target prediction of 3'UTR of mRNA in diverse species so that the researchers can utilize the database most appropriate to their research.

METHODS

A systematic literature search was performed in PubMed, Google Scholar and Scopus databases up to November 2022. ≥10,000 articles found online, including ⁓130 miRNA tools, which contain various information on miRNA. Out of them, 31 databases that provide information on validated 3'UTR miRNAs target databases were included and analysed in this review.

RESULTS

These miRNA database tools are being used in varied areas of biological research to select the most suitable miRNA for their experimental validation. These databases, updated until the year 2021, consist of miRNA-related data from humans, animals, mice, plants, viruses etc. They contain 525-29806351 data entries, and information from most databases is freely available on the online platform.

CONCLUSION

Reviewed databases provide significant information, but not all information is accurate or up-to-date. Therefore, Diana-TarBase and miRWalk are the most comprehensive and up-to-date databases.

Generation of de novo miRNAs from template switching during DNA replication

The mechanisms generating novel genes and genetic information are poorly known, even for microRNA (miRNA) genes with an extremely constrained design. All miRNA primary transcripts need to fold into a stem-loop structure to yield short gene products ([Formula: see text]22 nt) that bind and repress their mRNA targets. While a substantial number of miRNA genes are ancient and highly conserved, short secondary structures coding for entirely novel miRNA genes have been shown to emerge in a lineage-specific manner. Template switching is a DNA-replication-related mutation mechanism that can introduce complex changes and generate perfect base pairing for entire hairpin structures in a single event. Here, we show that the template-switching mutations (TSMs) have participated in the emergence of over 6,000 suitable hairpin structures in the primate lineage to yield at least 18 new human miRNA genes, that is 26% of the miRNAs inferred to have arisen since the origin of primates. While the mechanism appears random, the TSM-generated miRNAs are enriched in introns where they can be expressed with their host genes. The high frequency of TSM events provides raw material for evolution. Being orders of magnitude faster than other mechanisms proposed for de novo creation of genes, TSM-generated miRNAs enable near-instant rewiring of genetic information and rapid adaptation to changing environments.

A web-based platform for the annotation and analysis of NAR-published databases

Biological databases are essential resources for life science research, but finding and selecting the most relevant and up-to-date databases can be challenging due to the large number and diversity of available databases. The Nucleic Acids Research (NAR) journal publishes annual database issues that provide a comprehensive list of databases in the molecular biology domain. However, the information provided by NAR is limited and sometimes does not reflect the current status and quality of the databases. In this article, we present a web-based platform for the annotation and analysis of NAR-published databases. The platform allows users to manually curate and enrich the NAR entries with additional information such as availability, downloadability, source code links, cross-references, and duplicates. Statistics and visualizations on various aspects of the database landscape, such as recency, status, category, and curation history are also provided. Currently, it contains a total of 2,246 database entries of which 2,025 are unique with the majority updated within the last five years. Around 75% of all databases are still available and more than half provide a download option. Cross references to Database Commons are available for 1,889 entries. The platform is freely available online at https://nardbstatus.kalis-amts.de and aims to help researchers in database selection and decision-making. It also provides insights into the current state and challenges of a subset of all databases in the life sciences.

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs.

Extracellular Vesicles and MicroRNA in Myelodysplastic Syndromes

The bone marrow niche plays an increasing role in the pathophysiogenesis of myelodysplastic syndromes. More specifically, mesenchymal stromal cells, which can secrete extracellular vesicles and their miRNA contents, modulate the fate of hematopoietic stem cells leading to leukemogenesis. Extracellular vesicles can mediate their miRNA and protein contents between nearby cells but also in the plasma of the patients, being potent tools for diagnosis and prognostic markers in MDS. They can be targeted by antisense miRNA or by modulators of the secretion of extracellular vesicles and could lead to future therapeutic directions in MDS.

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.

Dynamic and static circulating cancer microRNA biomarkers - a validation study

For cancers and other pathologies, early diagnosis remains the most promising path to survival. Profiling of longitudinal cohorts facilitates insights into trajectories of biomarkers. We measured microRNA expression in 240 serum samples from patients with colon, lung, and breast cancer and from cancer-free controls. Each patient provided at least two serum samples, one prior to diagnosis and one following diagnosis. The median time interval between the samples was 11.6 years. Using computational models, we evaluated the circulating profiles of 21 microRNAs. The analysis yielded two sets of biomarkers, static ones that show an absolute difference between certain cancer types and controls and dynamic ones where the level over time provided higher diagnostic information content. In the first group, miR-99a-5p stands out for all three cancer types. In the second group, miR-155-5p allows to predict lung cancers and colon cancers. Classification in samples from cancer and non-cancer patients using gradient boosted trees reached an average accuracy of 79.9%. The results suggest that individual change over time or an absolute value at one time point may predict a disease with high specificity and sensitivity.

MirDIP 5.2: tissue context annotation and novel microRNA curation

MirDIP is a well-established database that aggregates microRNA-gene human interactions from multiple databases to increase coverage, reduce bias, and improve usability by providing an integrated score proportional to the probability of the interaction occurring. In version 5.2, we removed eight outdated resources, added a new resource (miRNATIP), and ran five prediction algorithms for miRBase and mirGeneDB. In total, mirDIP 5.2 includes 46 364 047 predictions for 27 936 genes and 2734 microRNAs, making it the first database to provide interactions using data from mirGeneDB. Moreover, we curated and integrated 32 497 novel microRNAs from 14 publications to accelerate the use of these novel data. In this release, we also extend the content and functionality of mirDIP by associating contexts with microRNAs, genes, and microRNA-gene interactions. We collected and processed microRNA and gene expression data from 20 resources and acquired information on 330 tissue and disease contexts for 2657 microRNAs, 27 576 genes and 123 651 910 gene-microRNA-tissue interactions. Finally, we improved the usability of mirDIP by enabling the user to search the database using precursor IDs, and we integrated miRAnno, a network-based tool for identifying pathways linked to specific microRNAs. We also provide a mirDIP API to facilitate access to its integrated predictions. Updated mirDIP is available at https://ophid.utoronto.ca/mirDIP.

Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.

Bioinformatic Tools for the Identification of MicroRNAs Regulating the Transcription Factors in Patients with β-Thalassemia

β-thalassemia is a significant health issue worldwide, with approximately 7% of the world’s population having defective hemoglobin genes. MicroRNAs (miRNAs) are short noncoding RNAs regulating gene expression at the post-transcriptional level by targeting multiple gene transcripts. The levels of fetal hemoglobin (HbF) can be increased by regulating the expression of the γ-globin gene using the suppressive effects of miRNAs on several transcription factors such as MYB, BCL11A, GATA1, and KLF. An early step in discovering miRNA:mRNA target interactions is the computational prediction of miRNA targets that can be later validated with wet-lab investigations. This review highlights some commonly employed computational tools such as miRBase, Target scan, DIANA-microT-CDS, miRwalk, miRDB, and micro-TarBase that can be used to predict miRNA targets. Upon comparing the miRNA target prediction tools, 4 main aspects of the miRNA:mRNA target interaction are shown to include a few common features on which most target prediction is based: conservation sites, seed match, free energy, and site accessibility. Understanding these prediction tools’ usage will help users select the appropriate tool and interpret the results accurately. This review will, therefore, be helpful to peers to quickly choose a list of the best miRNAs associated with HbF induction. Researchers will obtain significant results using these bioinformatics tools to establish a new important concept in managing β-thalassemia and delivering therapeutic strategies for improving their quality of life.

Urinary microRNAome in healthy cats and cats with pyelonephritis or other urological conditions

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene expression at the post-transcriptional level. miRNAs have been found in urine and have shown diagnostic potential in human nephropathies. Here, we aimed to characterize, for the first time, the feline urinary miRNAome and explore the use of urinary miRNA profiles as non-invasive biomarkers for feline pyelonephritis (PN). Thirty-eight cats were included in a prospective case-control study and classified in five groups: healthy Control cats (n = 11), cats with PN (n = 10), cats with subclinical bacteriuria or cystitis (SB/C, n = 5), cats with ureteral obstruction (n = 7) and cats with chronic kidney disease (n = 5). By small RNA sequencing we identified 212 miRNAs in cat urine, including annotated (n = 137) and putative novel (n = 75) miRNAs. The 15 most highly abundant urinary miRNAs accounted for nearly 71% of all detected miRNAs, most of which were previously identified in feline kidney. Ninety-nine differentially abundant (DA) miRNAs were identified when comparing Control cats to cats with urological conditions and 102 DA miRNAs when comparing PN to other urological conditions. Tissue clustering analysis revealed that the majority of urine samples clustered close to kidney, which confirm the likely cellular origin of the secreted urinary miRNAs. Relevant DA miRNAs were verified by quantitative real-time PCR (qPCR). Eighteen miRNAs discriminated Control cats from cats with a urological condition. Of those, seven miRNAs were DA by both RNAseq and qPCR methods between Control and PN cats (miR-125b-5p, miR-27a-3p, miR-21-5p, miR-27b-3p, miR-125a-5p, miR-17-5p and miR-23a-3p) or DA between Control and SB/C cats (miR-125b-5p). Six additional miRNAs (miR-30b-5p, miR-30c, miR-30e-5p, miR-27a-3p, miR-27b-39 and miR-222) relevant for discriminating PN from other urological conditions were identified by qPCR alone (n = 4) or by both methods (n = 2) (P<0.05). This panel of 13 miRNAs has potential as non-invasive urinary biomarkers for diagnostic of PN and other urological conditions in cats.

The limits of human microRNA annotation have been met

Over the last few years, the number of microRNAs in the human genome has become a controversially debated issue. Several publications reported thousands of putative novel microRNAs not included in the curated microRNA gene database MirGeneDB and the repository miRBase. Recently, by using sequencing of ∼300 human tissues and cell lines, the human RNA atlas, an expanded inventory of human RNA annotations, was published, reporting thousands of putative microRNAs. We, the developers of established microRNA prediction tools and hosts of MirGeneDB, raise concerns about the frequently applied prediction and functional validation strategies, briefly discussing the drawbacks of false positive detections. By means of quantifying well-established biogenesis-derived features, we show that the reported novel microRNAs essentially represent false-positives and argue that the human microRNA complement, at about 550 microRNA genes, is already near complete. Output of available tools must be curated as false predictions will misguide scientists looking for biomarkers or therapeutic targets.

Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA

MicroRNAs (miRNAs) are important regulators of gene expression. The large-scale detection and profiling of miRNAs have been accelerated with the development of high-throughput small RNA sequencing (sRNA-Seq) techniques and bioinformatics tools. However, generating high-quality comprehensive miRNA annotations remains challenging due to the intrinsic complexity of sRNA-Seq data and inherent limitations of existing miRNA prediction tools. Here, we present iwa-miRNA, a Galaxy-based framework that can facilitate miRNA annotation in plant species by combining computational analysis and manual curation. iwa-miRNA is specifically designed to generate a comprehensive list of miRNA candidates, bridging the gap between already annotated miRNAs provided by public miRNA databases and new predictions from sRNA-Seq datasets. It can also assist users in selecting promising miRNA candidates in an interactive mode, contributing to the accessibility and reproducibility of genome-wide miRNA annotation. iwa-miRNA is user-friendly and can be easily deployed as a web application for researchers without programming experience. With flexible, interactive, and easy-to-use features, iwa-miRNA is a valuable tool for the annotation of miRNAs in plant species with reference genomes. We also illustrate the application of iwa-miRNA for miRNA annotation using data from plant species with varying genomic complexity. The source codes and web server of iwa-miRNA are freely accessible at http://iwa-miRNA.omicstudio.cloud/.

Implication of genetic variants in primary microRNA processing sites in the risk of multiple sclerosis

Background

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system with a well-established genetic contribution to susceptibility. Over 200 genetic regions have been linked to the inherited risk of developing MS, but the disease-causing variants and their functional effects at the molecular level are still largely unresolved. We hypothesised that MS-associated single-nucleotide polymorphisms (SNPs) affect the recognition and enzymatic cleavage of primary microRNAs (pri-miRNAs).

Methods

Our study focused on 11 pri-miRNAs (9 primate-specific) that are encoded in genetic risk loci for MS. The levels of mature miRNAs and potential isoforms (isomiRs) produced from those pri-miRNAs were measured in B cells obtained from the peripheral blood of 63 MS patients and 28 healthy controls. We tested for associations between SNP genotypes and miRNA expression in cis using quantitative trait locus (cis-miR-eQTL) analyses. Genetic effects on miRNA stem-loop processing efficiency were verified using luciferase reporter assays. Potential direct miRNA target genes were identified by transcriptome profiling and computational binding site assessment.

Findings

Mature miRNAs and isomiRs from hsa-mir-26a-2, hsa-mir-199a-1, hsa-mir-4304, hsa-mir-4423, hsa-mir-4464 and hsa-mir-4492 could be detected in all B-cell samples. When MS patient subgroups were compared with healthy controls, a significant differential expression was observed for miRNAs from the 5’ and 3’ strands of hsa-mir-26a-2 and hsa-mir-199a-1. The cis-miR-eQTL analyses and reporter assays pointed to a slightly more efficient Drosha-mediated processing of hsa-mir-199a-1 when the MS risk allele T of SNP rs1005039 is present. On the other hand, the MS risk allele A of SNP rs817478, which substitutes the first C in a CNNC sequence motif, was found to cause a markedly lower efficiency in the processing of hsa-mir-4423. Overexpression of hsa-mir-199a-1 inhibited the expression of 60 protein-coding genes, including IRAK2, MIF, TNFRSF12A and TRAF1. The only target gene identified for hsa-mir-4423 was TMEM47.

Interpretation

We found that MS-associated SNPs in sequence determinants of pri-miRNA processing can affect the expression of mature miRNAs. Our findings complement the existing literature on the dysregulation of miRNAs in MS. Further studies on the maturation and function of miRNAs in different cell types and tissues may help to gain a more detailed functional understanding of the genetic basis of MS.

Funding

This study was funded by the Rostock University Medical Center (FORUN program, grant: 889002), Sanofi Genzyme (grant: GZ-2016-11560) and Merck Serono GmbH (Darmstadt, Germany, an affiliate of Merck KGaA, CrossRef Funder ID: 10.13039/100009945, grant: 4501860307). NB was supported by the Stiftung der Deutschen Wirtschaft (sdw) and the FAZIT foundation. EP was supported by the Landesgraduiertenförderung Mecklenburg-Vorpommern.

OUHP: an optimized universal hairpin primer system for cost-effective and high-throughput RT-qPCR-based quantification of microRNA (miRNA) expression

MicroRNAs (miRNAs or miRs) are single-stranded, ∼22-nucleotide noncoding RNAs that regulate many cellular processes. While numerous miRNA quantification technologies are available, a recent analysis of 12 commercial platforms revealed high variations in reproducibility, sensitivity, accuracy, specificity and concordance within and/or between platforms. Here, we developed a universal hairpin primer (UHP) system that negates the use of miRNA-specific hairpin primers (MsHPs) for quantitative reverse transcription PCR (RT-qPCR)-based miRNA quantification. Specifically, we analyzed four UHPs that share the same hairpin structure but are anchored with two, three, four and six degenerate nucleotides at 3'-ends (namely UHP2, UHP3, UHP4 and UHP6), and found that the four UHPs yielded robust RT products and quantified miRNAs with high efficiency. UHP-based RT-qPCR miRNA quantification was not affected by long transcripts. By analyzing 14 miRNAs, we demonstrated that UHP4 closely mimicked MsHPs in miRNA quantification. Fine-tuning experiments identified an optimized UHP (OUHP) mix with a molar composition of UHP2:UHP4:UHP6 = 8:1:1, which closely recapitulated MsHPs in miRNA quantification. Using synthetic LET7 isomiRs, we demonstrated that the OUHP-based qPCR system exhibited high specificity and sensitivity. Collectively, our results demonstrate that the OUHP system can serve as a reliable and cost-effective surrogate of MsHPs for RT-qPCR-based miRNA quantification for basic research and precision medicine.

Marathon-Induced Cardiac Strain as Model for the Evaluation of Diagnostic microRNAs for Acute Myocardial Infarction

Background: The current gold standard biomarker for myocardial infarction (MI), cardiac troponin (cTn), is recognized for its high sensitivity and organ specificity; however, it lacks diagnostic specificity. Numerous studies have introduced circulating microRNAs as potential biomarkers for MI. This study investigates the MI-specificity of these serum microRNAs by investigating myocardial stress/injury due to strenuous exercise. Methods: MicroRNA biomarkers were retrieved by comprehensive review of 109 publications on diagnostic serum microRNAs for MI. MicroRNA levels were first measured by next-generation sequencing in pooled sera from runners (n = 46) before and after conducting a full competitive marathon. Hereafter, reverse transcription quantitative real-time PCR (qPCR) of 10 selected serum microRNAs in 210 marathon runners was performed (>10,000 qPCR measurements). Results: 27 potential diagnostic microRNA for MI were retrieved by the literature review. Eight microRNAs (miR-1-3p, miR-21-5p, miR-26a-5p, miR-122-5p, miR-133a-3p, miR-142-5p, miR-191-5p, miR-486-3p) showed positive correlations with cTnT in marathon runners, whereas two miRNAs (miR-134-5p and miR-499a-5p) showed no correlations. Upregulation of miR-133a-3p (p = 0.03) and miR-142-5p (p = 0.01) went along with elevated cTnT after marathon. Conclusion: Some MI-associated microRNAs (e.g., miR-133a-3p and miR-142-5p) have similar kinetics under strenuous exercise and MI as compared to cTnT, which suggests that their diagnostic specificity could be limited. In contrast, several MI-associated microRNAs (miR-26a-5p, miR-134-5p, miR-191-5p) showed different release behavior; hence, combining cTnT with these microRNAs within a multi-marker strategy may add diagnostic accuracy in MI.

Identifying Putative Causal Links between MicroRNAs and Severe COVID-19 Using Mendelian Randomization

The SARS-CoV-2 (COVID-19) pandemic has caused millions of deaths worldwide. Early risk assessment of COVID-19 cases can help direct early treatment measures that have been shown to improve the prognosis of severe cases. Currently, circulating miRNAs have not been evaluated as canonical COVID-19 biomarkers, and identifying biomarkers that have a causal relationship with COVID-19 is imperative. To bridge these gaps, we aim to examine the causal effects of miRNAs on COVID-19 severity in this study using two-sample Mendelian randomization approaches. Multiple studies with available GWAS summary statistics data were retrieved. Using circulating miRNA expression data as exposure, and severe COVID-19 cases as outcomes, we identified ten unique miRNAs that showed causality across three phenotype groups of COVID-19. Using expression data from an independent study, we validated and identified two high-confidence miRNAs, namely, hsa-miR-30a-3p and hsa-miR-139-5p, which have putative causal effects on developing cases of severe COVID-19. Using existing literature and publicly available databases, the potential causative roles of these miRNAs were investigated. This study provides a novel way of utilizing miRNA eQTL data to help us identify potential miRNA biomarkers to make better and early diagnoses and risk assessments of severe COVID-19 cases.

In silico identification of variations in microRNAs with a potential impact on dairy traits using whole ruminant genome SNP datasets

MicroRNAs are small noncoding RNAs that have important roles in the lactation process and milk biosynthesis. Some polymorphisms have been studied in various livestock species from the perspective of pathology or production traits. To target variants that could be the causal variants of dairy traits, genetic variants of microRNAs expressed in the mammary gland or present in milk and localized in dairy quantitative trait loci (QTLs) were investigated in bovine, caprine, and ovine species. In this study, a total of 59,124 (out of 28 millions), 13,427 (out of 87 millions), and 4761 (out of 38 millions) genetic variants in microRNAs expressed in the mammary gland or present in milk were identified in bovine, caprine, and ovine species, respectively. A total of 4679 of these detected bovine genetic variants are located in dairy QTLs. In caprine species, 127 genetic variants are localized in dairy QTLs. In ovine species, no genetic variant was identified in dairy QTLs. This study leads to the detection of microRNA genetic variants of interest in the context of dairy production, taking advantage of whole genome data to identify microRNA genetic variants expressed in the mammary gland and localized in dairy QTLs.

miRge3.0: a comprehensive microRNA and tRF sequencing analysis pipeline

MicroRNAs and tRFs are classes of small non-coding RNAs, known for their roles in translational regulation of genes. Advances in next-generation sequencing (NGS) have enabled high-throughput small RNA-seq studies, which require robust alignment pipelines. Our laboratory previously developed miRge and miRge2.0, as flexible tools to process sequencing data for annotation of miRNAs and other small-RNA species and further predict novel miRNAs using a support vector machine approach. Although miRge2.0 is a leading analysis tool in terms of speed with unique quantifying and annotation features, it has a few limitations. We present miRge3.0 that provides additional features along with compatibility to newer versions of Cutadapt and Python. The revisions of the tool include the ability to process Unique Molecular Identifiers (UMIs) to account for PCR duplicates while quantifying miRNAs in the datasets, correct erroneous single base substitutions in miRNAs with miREC and an accurate mirGFF3 formatted isomiR tool. miRge3.0 also has speed improvements benchmarked to miRge2.0, Chimira and sRNAbench. Finally, miRge3.0 output integrates into other packages for a streamlined analysis process and provides a cross-platform Graphical User Interface (GUI). In conclusion miRge3.0 is our third generation small RNA-seq aligner with improvements in speed, versatility and functionality over earlier iterations.

LAMTOR5 expression level is a biomarker for colorectal cancer and lncRNA LAMTOR5-AS1 predicting miRNA sponging effect

BACKGROUND

Strong evidence indicated that high expression of HBXIP (also known as LAMTOR5) promotes cancer cells proliferation and helps cancer progression. Long non-coding RNAs (lncRNA) have also a crucial role in developing cancer. In this study, we aimed to determine the expression of LAMTOR5 and its nearby lncRNA, LAMTOR5-AS1 and investigate their potential as a biomarker in colorectal cancer (CRC) patients.

METHODS

75 tissues of colorectal tumors and non-tumor adjacent normal sampled in this study. After RNA procedure then RT-qPCR was applied for expression analysis. Moreover, in silico investigation also enrolled for predicting sponging effect of lncRNA with miRNAs.

RESULTS

LAMTOR5 transcription level significantly overexpressed (p value < 0.001) and has shown a diagnostic potential (AUC = 0.8) in CRC. LAMTOR5-AS1 did not indicate any remarkable expression change overall, but showed a significant overexpressed in elderly patients (> 60) with CRC (p value < 0.0097). Moreover, the correlation analysis between LAMTOR5 and LAMTOR5-AS1 revealed a significant association in CRC (p value = 0.0074) which can be partly explained by its predicting act as a mediator with sponging effect on hsa-miR-let-7b-3p and hsa-miR-20a-5p.

CONCLUSION

LAMTOR5 gene can be considered as prognostic biomarker for CRC. LAMTOR5-AS5 which is a nearby lncRNA of this gene could play a regulatory impact through its sponging effect on hsa-miR-let-7b-3p and hsa-miR-20a-5p which both have shown a significant impact on overall survival rate in CRC patients in high expression levels.

rs73092672 allele T is significantly associated with the higher risk of breast cancer incidence

Breast cancer is the most common cancer in women worldwide with remarkable proportion of the patients in advanced stage. Recently the importance of genetic mutations in cancers are well established and also the role of tumor suppressor genes such as FHIT gene in both heritable and non-heritable cancer. MicroRNAs are a class of non-coding RNAs which can interfere with cellular regulation. In this study, the association of rs73092672 which is located within the FHIT gene and the 3'UTR of hsa-miR-509-5p with the susceptibility to breast cancer risk has been studied in the Iranian population. By using the PCR_RFLP, the genotype rs73092672 was determined in 90 patients and 100 control subjects. The genotypes of the individuals were analyzed statistically to find the association between rs73092672 and the breast cancer incidence. The results revealed that due to the dominance of the C allele, the frequency of CC + CT genotypes, as compared with TT, had a significant correlation with the incidence of this disease in controls and cases (p = 0.02; OR= 3.6). Moreover, Bioinformatics analysis suggests rs73092672 as a polymorphism in the 3'UTR of hsa-miR-509-5p with higher binding affinity in the presence of T allele than C allele.

Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells

Molecular single cell analyses provide insights into physiological and pathological processes. Here, in a stepwise approach, we first evaluate 19 protocols for single cell small RNA sequencing on MCF7 cells spiked with 1 pg of 1,006 miRNAs. Second, we analyze MCF7 single cell equivalents of the eight best protocols. Third, we sequence single cells from eight different cell lines and 67 circulating tumor cells (CTCs) from seven SCLC patients. Altogether, we analyze 244 different samples. We observe high reproducibility within protocols and reads covered a broad spectrum of RNAs. For the 67 CTCs, we detect a median of 68 miRNAs, with 10 miRNAs being expressed in 90% of tested cells. Enrichment analysis suggested the lung as the most likely organ of origin and enrichment of cancer-related categories. Even the identification of non-annotated candidate miRNAs was feasible, underlining the potential of single cell small RNA sequencing.

Technologies for small non-coding RNA sequencing at the single-cell level are less mature than for sequencing mRNAs. Here the authors evaluate available protocols for analysis of circulating lung cancer tumour cells.

The RNA Atlas expands the catalog of human non-coding RNAs

Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

Variability in porcine microRNA genes and its association with mRNA expression and lipid phenotypes

BACKGROUND

Mature microRNAs (miRNAs) play an important role in repressing the expression of a wide range of mRNAs. The presence of polymorphic sites in miRNA genes and their corresponding 3'UTR binding sites can disrupt canonical conserved miRNA-mRNA pairings, and thus modify gene expression patterns. However, to date such polymorphic sites in miRNA genes and their association with gene expression phenotypes and complex traits are poorly characterized in pigs.

RESULTS

By analyzing whole-genome sequences from 120 pigs and wild boars from Europe and Asia, we identified 285 single nucleotide polymorphisms (SNPs) that map to miRNA loci, and 109,724 SNPs that are located in predicted 7mer-m8 miRNA binding sites within porcine 3'UTR. In porcine miRNA genes, SNP density is reduced compared with their flanking non-miRNA regions. By sequencing the genomes of five Duroc boars, we identified 12 miRNA SNPs that were subsequently genotyped in their offspring (N = 345, Lipgen population). Association analyses of miRNA SNPs with 38 lipid-related traits and hepatic and muscle microarray expression phenotypes recorded in the Lipgen population were performed. The most relevant detected association was between the genotype of the rs319154814 (G/A) SNP located in the apical loop of the ssc-miR-326 hairpin precursor and PPP1CC mRNA levels in the liver (q-value = 0.058). This result was subsequently confirmed by qPCR (P-value = 0.027). The rs319154814 (G/A) genotype was also associated with several fatty acid composition traits.

CONCLUSIONS

Our findings show a reduced variability of porcine miRNA genes, which is consistent with strong purifying selection, particularly in the seed region that plays a critical role in miRNA binding. Although it is generally assumed that SNPs mapping to the seed region are those with the most pronounced consequences on mRNA expression, we show that a SNP mapping to the apical region of ssc-miR-326 is significantly associated with hepatic mRNA levels of the PPP1CC gene, one of its predicted targets. Although experimental confirmation of such an interaction is reported in humans but not in pigs, this result highlights the need to further investigate the functional effects of miRNA polymorphisms that are located outside the seed region on gene expression in pigs.

Deep sequencing of sncRNAs reveals hallmarks and regulatory modules of the transcriptome during Parkinson’s disease progression

Noncoding RNAs have diagnostic and prognostic importance in Parkinson's disease (PD). We studied circulating small noncoding RNAs (sncRNAs) in two large-scale longitudinal PD cohorts (Parkinson's Progression Markers Initiative (PPMI) and Luxembourg Parkinson's Study (NCER-PD)) and modeled their impact on the transcriptome. Sequencing of sncRNAs in 5,450 blood samples of 1,614 individuals in PPMI yielded 323 billion reads, most of which mapped to microRNAs but covered also other RNA classes such as piwi-interacting RNAs, ribosomal RNAs and small nucleolar RNAs. Dysregulated microRNAs associated with disease and disease progression occur in two distinct waves in the third and seventh decade of life. Originating predominantly from immune cells, they resemble a systemic inflammation response and mitochondrial dysfunction, two hallmarks of PD. Profiling 1,553 samples from 1,024 individuals in the NCER-PD cohort validated biomarkers and main findings by an independent technology. Finally, network analysis of sncRNA and transcriptome sequencing from PPMI identified regulatory modules emerging in patients with progressing PD.

Overview of host miRNA properties and their association with epigenetics, long non-coding RNAs, and Xeno-infectious factors

MicroRNA-derived structures play impressive roles in various biological processes. So dysregulation of miRNAs can lead to different human diseases. Recent studies have extended our comprehension of the control of miRNA function and features. Here, we overview some remarkable miRNA properties that have potential implications for the miRNA functions, including different variants of a miRNA called isomiRs, miRNA arm selection/arm switching, and the effect of these factors on miRNA target selection. Besides, we review some aspects of miRNA interactions such as the interaction between epigenetics and miRNA (different miRNAs and their related processing enzymes are epigenetically regulated by multiple DNA methylation enzymes. moreover, DNA methylation could be controlled by diverse mechanisms related to miRNAs), direct and indirect crosstalk between miRNA and lnc (Long Non-Coding) RNAs as a further approach to conduct intercellular regulation called "competing endogenous RNA" (ceRNA) that is involved in the pathogenesis of different diseases, and the interaction of miRNA activities and some Xeno-infectious (virus/bacteria/parasite) factors, which result in modulation of the pathogenesis of infections. This review provides some related studies to a better understanding of miRNA involvement mechanisms and overcoming the complexity of related diseases that may be applicable and useful to prognostic, diagnostic, therapeutic purposes and personalized medicine in the future.

CoolMPS: evaluation of antibody labeling based massively parallel non-coding RNA sequencing

Results of massive parallel sequencing-by-synthesis vary depending on the sequencing approach. CoolMPS™ is a new sequencing chemistry that incorporates bases by labeled antibodies. To evaluate the performance, we sequenced 240 human non-coding RNA samples (dementia patients and controls) with and without CoolMPS. The Q30 value as indicator of the per base sequencing quality increased from 91.8 to 94%. The higher quality was reached across the whole read length. Likewise, the percentage of reads mapping to the human genome increased from 84.9 to 86.2%. For both technologies, we computed similar distributions between different RNA classes (miRNA, piRNA, tRNA, snoRNA and yRNA) and within the classes. While standard sequencing-by-synthesis allowed to recover more annotated miRNAs, CoolMPS yielded more novel miRNAs. The correlation between the two methods was 0.97. Evaluating the diagnostic performance, we observed lower minimal P-values for CoolMPS (adjusted P-value of 0.0006 versus 0.0004) and larger effect sizes (Cohen's d of 0.878 versus 0.9). Validating 19 miRNAs resulted in a correlation of 0.852 between CoolMPS and reverse transcriptase-quantitative polymerase chain reaction. Comparison to data generated with Illumina technology confirmed a known shift in the overall RNA composition. With CoolMPS we evaluated a novel sequencing-by-synthesis technology showing high performance for the analysis of non-coding RNAs.

Validation of human microRNA target pathways enables evaluation of target prediction tools

MicroRNAs are regulators of gene expression. A wide-spread, yet not validated, assumption is that the targetome of miRNAs is non-randomly distributed across the transcriptome and that targets share functional pathways. We developed a computational and experimental strategy termed high-throughput miRNA interaction reporter assay (HiTmIR) to facilitate the validation of target pathways. First, targets and target pathways are predicted and prioritized by computational means to increase the specificity and positive predictive value. Second, the novel webtool miRTaH facilitates guided designs of reporter assay constructs at scale. Third, automated and standardized reporter assays are performed. We evaluated HiTmIR using miR-34a-5p, for which TNF- and TGFB-signaling, and Parkinson's Disease (PD)-related categories were identified and repeated the pipeline for miR-7-5p. HiTmIR validated 58.9% of the target genes for miR-34a-5p and 46.7% for miR-7-5p. We confirmed the targeting by measuring the endogenous protein levels of targets in a neuronal cell model. The standardized positive and negative targets are collected in the new miRATBase database, representing a resource for training, or benchmarking new target predictors. Applied to 88 target predictors with different confidence scores, TargetScan 7.2 and miRanda outperformed other tools. Our experiments demonstrate the efficiency of HiTmIR and provide evidence for an orchestrated miRNA-gene targeting.

IsoMiRmap-fast, deterministic, and exhaustive mining of isomiRs from short RNA-seq datasets

MOTIVATION

MicroRNA (miRNA) precursor arms give rise to multiple isoforms simultaneously called "isomiRs." IsomiRs from the same arm typically differ by a few nucleotides at either their 5´ or 3´ termini, or both. In humans, the identities and abundances of isomiRs depend on a person's sex, population of origin, race/ethnicity, and on tissue type, tissue state, and disease type/subtype. Moreover, nearly half of the time the most abundant isomiR differs from the miRNA sequence found in public databases. Accurate mining of isomiRs from deep sequencing data is thus important.

RESULTS

We developed isoMiRmap, a fast, standalone, user-friendly mining tool that identifies and quantifies all isomiRs by directly processing short RNA-seq datasets. IsoMiRmap is a portable "plug-and-play" tool, requires minimal setup, has modest computing and storage requirements, and can process an RNA-seq dataset with 50 million reads in just a few minutes on an average laptop. IsoMiRmap deterministically and exhaustively reports all isomiRs in a given deep sequencing dataset and quantifies them accurately (no double-counting). IsoMiRmap comprehensively reports all miRNA precursor locations from which an isomiR may be transcribed, tags as 'ambiguous' isomiRs whose sequences exist both inside and outside of the space of known miRNA sequences and reports the public identifiers of common single-nucleotide polymorphisms and documented somatic mutations that may be present in an isomiR. IsoMiRmap also identifies isomiRs with 3´ non-templated post-transcriptional additions. Compared to similar tools, isoMiRmap is the fastest, reports more bona fide isomiRs, and provides the most comprehensive information related to an isomiR's transcriptional origin.

AVAILABILITY

The codes for isoMiRmap are freely available at https://cm.jefferson.edu/isoMiRmap/ and https://github.com/TJU-CMC-Org/isoMiRmap/. IsomiR profiles for the datasets of the 1000 Genomes Project, spanning five population groups, and The Cancer Genome Atlas (TCGA), spanning 33 cancer studies, are also available at https://cm.jefferson.edu/isoMiRmap/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ancient microRNA profiles of a 14,300-year-old canid samples confirm taxonomic origin and give glimpses into tissue-specific gene regulation from the Pleistocene

DNA sequencing is the current key technology for historic or ancient biological samples and has led to many exciting discoveries in the field of paleogenomics. However, functional insights into tissue identity, cellular composition or gene regulation cannot be gained from DNA. Recent analyses have shown that, under favorable conditions, RNA can also be sequenced from ancient samples, enabling studies at the transcriptomic and regulatory level. Analyzing ancient RNA data from a Pleistocene canid, we find hundreds of intact microRNAs that are taxonomically informative, show tissue-specificity and have functionally predictive characteristics. With an extraordinary age of 14,300 years, these microRNA sequences are by far the oldest ever reported. The authenticity of the sequences is further supported by a) the presence of canid / Caniformia-specific sequences that never evolved outside of this clade, b) tissue-specific expression patterns (cartilage, liver and muscle) that resemble those of modern dogs and c) RNA damage patterns that are clearly distinct from those of fresh samples. By performing computational microRNA-target enrichment analyses on the ancient sequences, we predict microRNA functions consistent with their tissue pattern of expression. For instance, we find a liver-specific microRNA that regulates carbohydrate metabolism and starvation responses in canids. In summary, we show that straightforward paleotranscriptomic microRNA analyses can give functional glimpses into tissue identity, cellular composition and gene regulatory activity of ancient samples and biological processes that took place in the Pleistocene, thus holding great promise for deeper insights into gene regulation in extinct animals based on ancient RNA sequencing. .

Encyclopedia of tools for the analysis of miRNA isoforms

RNA sequencing data sets rapidly increase in quantity. For microRNAs (miRNAs), frequently dozens to hundreds of billion reads are generated per study. The quantification of annotated miRNAs and the prediction of new miRNAs are leading computational tasks. Now, the increased depth of coverage allows to gain deeper insights into the variability of miRNAs. The analysis of isoforms of miRNAs (isomiRs) is a trending topic, and a range of computational tools for the analysis of isomiRs has been developed. We provide an overview on 27 available computational solutions for the analysis of isomiRs. These include both stand-alone programs (17 tools) and web-based solutions (10 tools) and span a publication time range from 2010 to 2020. Seven of the tools were published in 2019 and 2020, confirming the rising importance of the topic. While most of the analyzed tools work for a broad range of organisms or are completely independent of a reference organism, several tools have been tailored for the analysis of human miRNA data or for plants. While 14 of the tools are general analysis tools of miRNAs, and isomiR analysis is one of their features, the remaining 13 tools have specifically been developed for isomiR analysis. A direct comparison on 20 deep sequencing data sets for selected tools provides insights into the heterogeneity of results. With our work, we provide users a comprehensive overview on the landscape of isomiR analysis tools and in that support the selection of the most appropriate tool for their respective research task.

miEAA 2.0: integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson’s disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

HumiR: Web Services, Tools and Databases for Exploring Human microRNA Data

For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway prediction and miRNA pathway enrichment are common tasks. Additionally, databases and resources containing expression profiles, e.g., from different tissues, organs or cell types, are generated. This information in turn leads to improved miRNA repositories. While most of the respective tools are implemented in a species-independent manner, we focused on tools for human small non-coding RNAs. This includes four aspects: (1) miRNA analysis tools (2) databases on miRNAs and variations thereof (3) databases on expression profiles (4) miRNA helper tools facilitating frequent tasks such as naming conversion or reporter assay design. Although dependencies between the tools exist and several tools are jointly used in studies, the interoperability is limited. We present HumiR, a joint web presence for our tools. HumiR facilitates an entry in the world of miRNA research, supports the selection of the right tool for a research task and represents the very first step towards a fully integrated knowledge-base for human small non-coding RNA research. We demonstrate the utility of HumiR by performing a very comprehensive analysis of Alzheimer's miRNAs.

miRSwitch: detecting microRNA arm shift and switch events

Arm selection, the preferential expression of a 3′ or 5′ mature microRNA (miRNA), is a highly dynamic and tissue-specific process. Time-dependent expression shifts or switches between the arms are also relevant for human diseases. We present miRSwitch, a web server to facilitate the analysis and interpretation of arm selection events. Our species-independent tool evaluates pre-processed small non-coding RNA sequencing (sncRNA-seq) data, i.e. expression matrices or output files from miRNA quantification tools (miRDeep2, miRMaster, sRNAbench). miRSwitch highlights potential changes in the distribution of mature miRNAs from the same precursor. Group comparisons from one or several user-provided annotations (e.g. disease states) are possible. Results can be dynamically adjusted by choosing from a continuous range of highly specific to very sensitive parameters. Users can compare potential arm shifts in the provided data to a human reference map of pre-computed arm shift frequencies. We created this map from 46 tissues and 30 521 samples. As case studies we present novel arm shift information in a Alzheimer’s disease biomarker data set and from a comparison of tissues in Homo sapiens and Mus musculus. In summary, miRSwitch offers a broad range of customized arm switch analyses along with comprehensive visualizations, and is freely available at: https://www.ccb.uni-saarland.de/mirswitch/.

A mouse tissue atlas of small noncoding RNA

We report a systematic unbiased analysis of small RNA molecule expression in 11 different tissues of the model organism mouse. We discovered uncharacterized noncoding RNA molecules and identified that ∼30% of total noncoding small RNA transcriptome are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. Distinct distribution patterns of small RNA across the body suggest the existence of tissue-specific mechanisms involved in noncoding RNA processing.

Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to “arm switching” between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

MOTIVATION

MicroRNAs (miRNAs) are small RNA molecules (∼22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods.

RESULTS

To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification.

AVAILABILITY AND IMPLEMENTATION

https://github.com/miRTop/mirGFF3/ and https://github.com/miRTop/mirtop.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A review of Cloud computing technologies for comprehensive microRNA analyses

Cloud computing revolutionized many fields that require ample computational power. Cloud platforms may also provide huge support for microRNA analysis mainly through disclosing scalable resources of different types. In Clouds, these resources are available as services, which simplifies their allocation and releasing. This feature is especially useful during the analysis of large volumes of data, like the one produced by next generation sequencing experiments, which require not only extended storage space but also a distributed computing environment. In this paper, we show which of the Cloud properties and service models can be especially beneficial for microRNA analysis. We also explain the most useful services of the Cloud (including storage space, computational power, web application hosting, machine learning models, and Big Data frameworks) that can be used for microRNA analysis. At the same time, we review several solutions for microRNA and show that the utilization of the Cloud in this field is still weak, but can increase in the future when the awareness of their applicability grows.

Computational Methods and Software Tools for Functional Analysis of miRNA Data

miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in biological processes. Enrichment analysis of miRNA targets is the standard technique for functional analysis, but this approach carries limitations and bias; alternatives are currently being proposed, based on direct and curated annotations. In this review, we describe the two workflows of miRNAs enrichment analysis, based on target gene or miRNA annotations, highlighting statistical tests, software tools, up-to-date databases, and functional annotations resources in the study of metazoan miRNAs.

Understanding the Interplay Between Health Disparities and Epigenomics

Social epigenomics has emerged as an integrative field of research focused on identification of socio-environmental factors, their influence on human biology through epigenomic modifications, and how they contribute to current health disparities. Several health disparities studies have been published using genetic-based approaches; however, increasing accessibility and affordability of molecular technologies have allowed for an in-depth investigation of the influence of external factors on epigenetic modifications (e.g., DNA methylation, micro-RNA expression). Currently, research is focused on epigenetic changes in response to environment, as well as targeted epigenetic therapies and environmental/social strategies for potentially minimizing certain health disparities. Here, we will review recent findings in this field pertaining to conditions and diseases over life span encompassing prenatal to adult stages.

MirGeneDB 2.0: the metazoan microRNA complement

Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database - MirGeneDB - to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.

sRNAPrimerDB: comprehensive primer design and search web service for small non-coding RNAs

MOTIVATION

Small non-coding RNAs (ncRNAs), especially microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs), play key roles in many biological processes. However, only a few tools can be used to develop the optimal primer or probe design for the expression profile of small ncRNAs. Here, we developed sRNAPrimerDB, the first automated primer designing and query web service for small ncRNAs.

RESULTS

The primer online designing module of sRNAPrimerDB is composed of primer design algorithms and quality evaluation of the polymerase chain reaction (PCR) primer. Five types of primers, namely, generic or specific reverse transcription primers, specific PCR primers pairs, TaqMan probe, double-hairpin probe and hybridization probe for different small ncRNA detection methods, can be designed and searched using this service. The quality of PCR primers is further evaluated using melting temperature, primer dimer, hairpin structure and specificity. Moreover, the sequence and size of each amplicon are also provided for the subsequent experiment verification. At present, 531 306 and 2 941 669 primer pairs exist across 223 species for miRNAs and piRNAs, respectively, according to sRNAPrimerDB. Several primers designed by sRNAPrimerDB are further successfully validated by subsequent experiments.

AVAILABILITY AND IMPLEMENTATION

sRNAPrimerDB is a valuable platform that can be used to detect small ncRNAs. This module can be publicly accessible at http://www.srnaprimerdb.com or http://123.57.239.141.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quo vadis microRNAs?

Since 2002, published miRNAs have been collected and named by the online repository miRBase. However, with 11 000 annual publications this has become challenging. Recently, four specialized miRNA databases were published, addressing particular needs for diverse scientific communities. This development provides major opportunities for the future of miRNA annotation and nomenclature.