Bias in recent miRBase annotations potentially associated with RNA quality issues

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.

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.

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.

Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy

The metabolic efficiency of mammalian cells depends on the attenuation of intrinsic translation noise by microRNAs. We devised a metric of cellular metabolic rate (cMR), rMR/Mexp optimally fit to the number of microRNA families (mirFam), that is robust to variation in mass and sensitive to body temperature (Tb), consistent with the heat dissipation limit theory of Speakman and Król (2010). Using mirFam as predictor, an Ornstein-Uhlenbeck process of stabilizing selection, with an adaptive shift at the divergence of Boreoeutheria, accounted for 95% of the variation in cMR across mammals. Branchwise rates of evolution of cMR, mirFam and Tb concurrently increased 6- to 7-fold at the divergence of Boreoeutheria, independent of mass. Cellular MR variation across placental mammals was also predicted by the sum of model conserved microRNA-target interactions, revealing an unexpected degree of integration of the microRNA-target apparatus into the energy economy of the mammalian cell.

Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues

Molecular mechanisms of organismal and cell aging remain incompletely understood. We, therefore, generated a body-wide map of noncoding RNA (ncRNA) expression in aging (16 organs at ten timepoints from 1 to 27 months) and rejuvenated mice. We found molecular aging trajectories are largely tissue-specific except for eight broadly deregulated microRNAs (miRNAs). Their individual abundance mirrors their presence in circulating plasma and extracellular vesicles (EVs) whereas tissue-specific ncRNAs were less present. For miR-29c-3p, we observe the largest correlation with aging in solid organs, plasma and EVs. In mice rejuvenated by heterochronic parabiosis, miR-29c-3p was the most prominent miRNA restored to similar levels found in young liver. miR-29c-3p targets the extracellular matrix and secretion pathways, known to be implicated in aging. We provide a map of organism-wide expression of ncRNAs with aging and rejuvenation and identify a set of broadly deregulated miRNAs, which may function as systemic regulators of aging via plasma and EVs.

Accurate microRNA annotation of animal genomes using trained covariance models of curated microRNA complements in MirMachine

The annotation of microRNAs depends on the availability of transcriptomics data and expert knowledge. This has led to a gap between the availability of novel genomes and high-quality microRNA complements. Using >16,000 microRNAs from the manually curated microRNA gene database MirGeneDB, we generated trained covariance models for all conserved microRNA families. These models are available in our tool MirMachine, which annotates conserved microRNAs within genomes. We successfully applied MirMachine to a range of animal species, including those with large genomes and genome duplications and extinct species, where small RNA sequencing is hard to achieve. We further describe a microRNA score of expected microRNAs that can be used to assess the completeness of genome assemblies. MirMachine closes a long-persisting gap in the microRNA field by facilitating automated genome annotation pipelines and deeper studies into the evolution of genome regulation, even in extinct organisms.

miRador: a fast and precise tool for the prediction of plant miRNAs

Plant microRNAs (miRNAs) are short, noncoding RNA molecules that restrict gene expression via posttranscriptional regulation and function in several essential pathways, including development, growth, and stress responses. Accurately identifying miRNAs in populations of small RNA sequencing libraries is a computationally intensive process that has resulted in the misidentification of inaccurately annotated miRNA sequences. In recent years, criteria for miRNA annotation have been refined with the aim to reduce these misannotations. Here, we describe miRador, a miRNA identification tool that utilizes the most up-to-date, community-established criteria for accurate identification of miRNAs in plants. We combined target prediction and Parallel Analysis of RNA Ends (PARE) data to assess the precision of the miRNAs identified by miRador. We compared miRador to other commonly used miRNA prediction tools and found that miRador is at least as precise as other prediction tools while being substantially faster than other tools. miRador should be broadly useful for the plant community to identify and annotate miRNAs in plant genomes.

Comprehensive re-analysis of hairpin small RNAs in fungi reveals loci with conserved links

RNA interference is an ancient mechanism with many regulatory roles in eukaryotic genomes, with small RNAs acting as their functional element. While there is a wide array of classes of small-RNA-producing loci, those resulting from stem-loop structures (hairpins) have received profuse attention. Such is the case of microRNAs (miRNAs), which have distinct roles in plants and animals. Fungi also produce small RNAs, and several publications have identified miRNAs and miRNA-like (mi/milRNA) hairpin RNAs in diverse fungal species using deep sequencing technologies. Despite this relevant source of information, relatively little is known about mi/milRNA features in fungi, mostly due to a lack of established criteria for their annotation. To systematically assess mi/milRNA characteristics and annotation confidence, we searched for publications describing mi/milRNA loci and re-assessed the annotations for 41 fungal species. We extracted and normalized the annotation data for 1727 reported mi/milRNA loci and determined their abundance profiles, concluding that less than half of the reported loci passed basic standards used for hairpin RNA discovery. We found that fungal mi/milRNA are generally more similar in size to animal miRNAs and were frequently associated with protein-coding genes. The compiled genomic analyses identified 25 mi/milRNA loci conserved in multiple species. Our pipeline allowed us to build a general hierarchy of locus quality, identifying more than 150 loci with high-quality annotations. We provide a centralized annotation of identified mi/milRNA hairpin RNAs in fungi which will serve as a resource for future research and advance in understanding the characteristics and functions of mi/milRNAs in fungal organisms.

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.

Genetic Variants of MIR27A, MIR196A2 May Impact the Risk for the Onset of Coronary Artery Disease in the Pakistani Population

Genetic variants in microRNA genes have a detrimental effect on miRNA-mediated regulation of gene expression and may contribute to coronary artery disease (CAD). CAD is the primary cause of mortality worldwide. Several environmental, genetic, and epigenetic factors are responsible for CAD susceptibility. The contribution of protein-coding genes is extensively studied. However, the role of microRNA genes in CAD is at infancy. The study is aimed to investigate the impact of rs895819, rs11614913, and rs2168518 variants in MIR27A, MIR196A2, and MIR4513, respectively, in CAD using allele-specific PCR. Results: For variant rs11614913, significant distribution of the genotypes among the cases and controls was determined by co-dominant [χ² = 54.4; p value ≤ 0.0001], dominant (C/C vs. C/T + T/T) [OR = 0.257 (0.133-0.496); p value ≤ 0.0001], recessive (T/T vs. C/T + C/C) [OR = 1.56 (0.677-0.632); p value = 0.398], and additive models [OR = 0.421 (0.262-0.675); p value = 0.0004]. Similarly, a significant association of rs895819 was determined by co-dominant [χ² = 9.669; p value ≤ 0.008], dominant (A/A vs. A/G + G/G) [OR = 0.285 (0.1242-0.6575); p value ≤ 0.0034], recessive (G/G vs. A/G + A/A) [OR = 0.900 (0.3202-3.519); p value = 1.000], and additive models [OR = 0.604 (0.3640-1.002); p value = 0.05] while no significant association of rs2168518 with CAD was found. Conclusion: The variants rs895819 and rs11614913 are the susceptibility factors for CAD.

Creating and maintaining a high-confidence microRNA repository for crop research: A brief review and re-examination of the current crop microRNA registries

miRBase was established as an authoritative microRNA (miRNA) database with a uniform nomenclature system and a searchable web interface. Recent popularization of the next-generation sequencing technology in small RNA cloning led to an explosive growth of the miRNA repository. Although a specific definition system has been proposed for the plant miRNAs, the quality of the plant miRNA registries deposited in miRBase is largely dependent on the submitters. With the growing concerns over the annotation quality, a set of criteria for identification of the high-confidence (HC) miRNAs was recently developed by miRBase. Since miRNAs could serve as a powerful tool for crop genetic improvement and breeding, we present a brief overview of the miRBase-registered crop miRNAs in this study. A total of 54 plants were identified from the 82 Viridiplantae species in the current version of miRBase, and were regarded as the crops. A total of 6316 precursors encoding 7422 mature miRNAs (miRBase release 22.1) were included in our survey. Based on the HC annotation criteria, we performed structure- and sequencing data-based analyses of the confidence of the crop miRNAs. According to the results, we propose suggestions for improvements of the HC annotation system and, moreover, discuss strategies for creating and maintaining an HC miRNA repository of crops. Finally, we hope that this study inspires more efforts devoted to HC miRNA discoveries for crop research.

Selection of reference genes for quantitative analysis of microRNA expression in three different types of cancer

MicroRNAs (miRNAs) are promising biomarkers in cancer research. Quantitative PCR (qPCR), also known as real-time PCR, is the most frequently used technique for measuring miRNA expression levels. The use of this technique, however, requires that expression data be normalized against reference genes. The problem is that a universal internal control for quantitative analysis of miRNA expression by qPCR has yet to be known. The aim of this work was to find the miRNAs with stable expression in the thyroid gland, brain and bone marrow according to NanoString nCounter miRNA quantification data. As a results, the most stably expressed miRNAs were as follows: miR-361-3p, -151a-3p and -29b-3p in the thyroid gland; miR-15a-5p, -194-5p and -532-5p in the brain; miR-140-5p, -148b-3p and -362-5p in bone marrow; and miR-423-5p, -28-5p and -532-5p, no matter what tissue type. These miRNAs represent promising reference genes for miRNA quantification by qPCR.

MirGeneDB 2.1: toward a complete sampling of all major animal phyla

We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.

Ulipristal Acetate Modifies miRNA Expression in Both Superficial and Basal Layers of the Human Endometrium

(1) Background: Ulipristal acetate (UPA) is a selective progesterone receptor modulator (SPRM) widely used for emergency contraception and mid- to long-term leiomyoma treatment. The aim of this study was to identify modifications of miRNA expression in superficial and basal layers of the human endometrium at the end of the UPA treatment for at least 3 months. (2) Methods: Microarray miRNA analysis of formalin-fixed, paraffin-embedded hysterectomy tissue samples was conducted, followed by an Ingenuity Pathway Analysis. Samples were divided into three groups: women having had 3 months of UPA treatment (n = 7); and two control groups of UPA-naïve women in the proliferative (n = 8) or secretory (n = 6) phase. (3) Results: The UPA modified the expression of 59 miRNAs involved in the processes of cell cycle, carcinogenesis, and inflammation. Their expression profiles were different in the basal and superficial layers. Most of the processes influenced by the UPA in the basal layer were connected to the cell cycle and immune regulation. (4) Conclusion: Specific changes were observed in both layers of the endometrium in the UPA group. However, the miRNA expression in the basal layer was not consistent with that in the superficial layer. Other large studies analysing the long-term impact of SPRM on endometrial miRNA expression are necessary.

miRNATissueAtlas2: an update to the human miRNA tissue atlas

Small non-coding RNAs (sncRNAs) are pervasive regulators of physiological and pathological processes. We previously developed the human miRNA Tissue Atlas, detailing the expression of miRNAs across organs in the human body. Here, we present an updated resource containing sequencing data of 188 tissue samples comprising 21 organ types retrieved from six humans. Sampling the organs from the same bodies minimizes intra-individual variability and facilitates the making of a precise high-resolution body map of the non-coding transcriptome. The data allow shedding light on the organ- and organ system-specificity of piwi-interacting RNAs (piRNAs), transfer RNAs (tRNAs), microRNAs (miRNAs) and other non-coding RNAs. As use case of our resource, we describe the identification of highly specific ncRNAs in different organs. The update also contains 58 samples from six tissues of the Tabula Muris collection, allowing to check if the tissue specificity is evolutionary conserved between Homo sapiens and Mus musculus. The updated resource of 87 252 non-coding RNAs from nine non-coding RNA classes for all organs and organ systems is available online without any restrictions (https://www.ccb.uni-saarland.de/tissueatlas2).

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.

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/.

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/.

miRBase: from microRNA sequences to function

miRBase catalogs, names and distributes microRNA gene sequences. The latest release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 hairpin precursors and 48 860 mature microRNAs. We describe improvements to the database and website to provide more information about the quality of microRNA gene annotations, and the cellular functions of their products. We have collected 1493 small RNA deep sequencing datasets and mapped a total of 5.5 billion reads to microRNA sequences. The read mapping patterns provide strong support for the validity of between 20% and 65% of microRNA annotations in different well-studied animal genomes, and evidence for the removal of >200 sequences from the database. To improve the availability of microRNA functional information, we are disseminating Gene Ontology terms annotated against miRBase sequences. We have also used a text-mining approach to search for microRNA gene names in the full-text of open access articles. Over 500 000 sentences from 18 542 papers contain microRNA names. We score these sentences for functional information and link them with 12 519 microRNA entries. The sentences themselves, and word clouds built from them, provide effective summaries of the functional information about specific microRNAs. miRBase is publicly and freely available at http://mirbase.org/.

A Post-Processing Algorithm for miRNA Microarray Data

One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison.

Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach

Despite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miRNA identification in the yet poorly annotated porcine genome and demonstrated the usefulness of implementing a motif search positional refinement strategy for the accurate determination of precursor miRNA boundaries. The small RNA fraction from gluteus medius skeletal muscle of 48 Duroc gilts was sequenced and used for the prediction of novel miRNA loci. Additionally, we selected the human miRNA annotation for a homology-based search of porcine miRNAs with orthologous genes in the human genome. A total of 20 novel expressed miRNAs were identified in the porcine muscle transcriptome and 27 additional novel porcine miRNAs were also detected by homology-based search using the human miRNA annotation. The existence of three selected novel miRNAs (ssc-miR-483, ssc-miR484 and ssc-miR-200a) was further confirmed by reverse transcription quantitative real-time PCR analyses in the muscle and liver tissues of Göttingen minipigs. In summary, the eMIRNA pipeline presented in the current work allowed us to expand the catalogue of porcine miRNAs and showed better performance than other commonly used miRNA prediction approaches. More importantly, the flexibility of our pipeline makes possible its application in other yet poorly annotated non-model species.

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previously, we published high-throughput sequencing based microRNA (miRNA) signatures in Alzheimer’s disease (AD) patients in the United States (US) and Germany. Here, we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR. We computed models to assess the relation between miRNA expression and phenotypes, gender, age, or disease severity (Mini-Mental State Examination; MMSE). Of the 21 miRNAs, expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts. 18 miRNAs were significantly correlated with neurodegeneration (Benjamini-Hochberg adjusted P < 0.05) with highest significance for miR-532-5p (Benjamini-Hochberg adjusted P = 4.8 × 10⁻³⁰). Machine learning models reached an area under the curve (AUC) value of 87.6% in differentiating AD patients from controls. Further, ten miRNAs were significantly correlated with MMSE, in particular miR-26a/26b-5p (adjusted P = 0.0002). Interestingly, the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells, while those up-regulated in AD were enriched in serum, exosomes, cytotoxic t-cells, and B-cells. Our study represents the next important step in translational research for a miRNA-based AD test.

Challenges in microRNAs' targetome prediction and validation

MicroRNAs (miRNAs) are small RNA molecules with important roles in post-transcriptional regulation of gene expression. In recent years, the predicted number of miRNAs has skyrocketed, largely as a consequence of high-throughput sequencing technologies becoming ubiquitous. This dramatic increase in miRNA candidates poses multiple challenges in terms of data deposition, curation, and validation. Although multiple databases containing miRNA annotations and targets have been developed, ensuring data quality by validating miRNA-target interactions requires the efforts of the research community. In order to generate databases containing biologically active miRNAs, it is imperative to overcome a multitude of hurdles, including restricted miRNA expression patterns, distinct miRNA biogenesis machineries, and divergent miRNA-mRNA interaction dynamics. In the present review, we discuss recent advances and limitations in miRNA prediction, identification, and validation. Lastly, we focus on the most enriched neuronal miRNA, miR-124, and its gene regulatory network in human neurons, which has been revealed using a combined computational and experimental approach.

miRCarta: a central repository for collecting miRNA candidates

The continuous increase of available biological data as consequence of modern high-throughput technologies poses new challenges for analysis techniques and database applications. Especially for miRNAs, one class of small non-coding RNAs, many algorithms have been developed to predict new candidates from next-generation sequencing data. While the amount of publications describing novel miRNA candidates keeps steadily increasing, the current gold standard database for miRNAs - miRBase - has not been updated since June 2014. As a result, publications describing new miRNA candidates in the last three to five years might have a substantial overlap of candidates without noticing. With miRCarta we implemented a database to collect novel miRNA candidates and augment the information provided by miRBase. In the first stage, miRCarta is thought to be a highly sensitive collection of potential miRNA candidates with a high degree of analysis functionality, annotations and details on each miRNA. We added-besides the full content of the miRBase-12,857 human miRNA precursors to miRCarta. Users can match their own predictions to the entries of miRCarta to reduce potential redundancies in their studies. miRCarta provides the most comprehensive collection of human miRNAs and miRNA candidates to form a basis for further refinement and validation studies. The database is freely accessible at https://mircarta.cs.uni-saarland.de/.

Using miRNAs and circRNAs to estimate PMI in advanced stage

In our previous study, we evaluated the stability of multi-RNA markers in heart, liver and skeletal muscle tissues of mice within 8 days after death and concluded that microRNAs (miRNAs) and circular (circRNAs) were more stable as reference genes in dead bodies than other kinds of RNAs. Based on their tissue-specific expression, we obtained reference genes for three kinds of tissues: miR-122, miR-133a and 18S in heart tissues; LC-Ogdh, circ-AFF1 and miR-122 in liver tissues; and miR-133a, circ-AFF1 in skeletal muscle tissues. For the estimation of post mortem interval (PMI), we also selected suitable biomarkers, which exhibited the best correlation coefficient with PMI. In our stability analysis of multi-RNA markers, Gapdh, Rps18, U6 and β-actin were unstable and selected as candidate target biomarkers. By analyzing the correlation between the expression levels of candidate target biomarkers and PMI, we obtained suitable target biomarkers for the three kinds of tissues, respectively. Finally, we established mathematical models of PMI estimation using the above selected reference genes and target biomarkers. The low estimated error in the validated samples demonstrated that PMI in advanced stage could be accurately predicted by real-time quantitative polymerase chain reaction (qPCR) through systematically selected effective reference genes and target biomarkers. Besides, combining the estimated results of various tissues and multi-biomarkers could improve the accuracy of PMI estimation.

Verification of miRNAs in ginseng decoction by high-throughput sequencing and quantitative real-time PCR

Panax ginseng C. A. Meyer is a precious traditional Chinese medicine that has been clinically used for over thousands of years. In general, ginseng needs to be prepared to ginseng decoction before taking it. MicroRNAs are a class of small (18–24 nt), single-stranded molecules that regulate gene expression at the post-transcriptional level. Considering that ginseng miRNAs may be bioactive compounds, we used Illumina high-throughput sequencing and quantitative real-time PCR (qRT-PCR) to validate the existence of miRNAs in fresh ginseng decoction which have been boiled at high temperature. Our previous studies have demonstrated that there are several miRNAs in fresh ginseng. The roots of fresh Panax ginseng were prepared according to routine methods, from which miRNAs were extracted and sequenced. A total of 43 miRNAs were identified from water decoction by Illumina high-throughput sequencing, belonging to 71 miRNA families. The target genes of these miRNAs were predicted by sequencing, and were annotated by GO, KEGG and Nr databases. The functions of these target genes mainly included plant hormone signal transduction, transcription regulation, macromolecular metabolism and auxin signaling. Nine highly expressed miRNAs (miR159, miR167, miR396, miR166, miR168, miR156, miR165, miR162 and miR394) were verified by qRT-PCR, and the results of Illumina high-throughput sequencing and qRT-PCR were consistent. Results from this study indicate that miRNAs remained stable in P. ginseng after high-temperature boiling. Additionally, Illumina high-throughput sequencing was superior in the acquisition of higher amount of small RNAs.

Opportunities for microRNAs in the Crowded Field of Cardiovascular Biomarkers

Cardiovascular diseases exist across all developed countries. Biomarkers that can predict or diagnose diseases early in their pathogeneses can reduce their morbidity and mortality in afflicted individuals. microRNAs are small regulatory RNAs that modulate translation and have been identified as potential fluid-based biomarkers across numerous maladies. We describe the current state of cardiovascular disease biomarkers across a range of diseases, including myocardial infarction, acute coronary syndrome, myocarditis, hypertension, heart failure, heart transplantation, aortic stenosis, diabetic cardiomyopathy, atrial fibrillation, and sepsis. We present the current understanding of microRNAs as possible biomarkers in these categories and where their best opportunities exist to enter clinical practice.

Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity

The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. Since respective validation is frequently not performed, miRNA repositories likely still contain a substantial fraction of false positive candidates while true miRNAs are not stored in the repositories yet. Especially if downstream analyses are performed with these candidates (e.g. target or pathway prediction), the results may be misleading. In the present study, we evaluated 558 mature miRNAs from miRBase and 1,709 miRNA candidates from next generation sequencing experiments by amplification-free hybridization and investigated their distributions in patients with various disease conditions. Notably, the most significant miRNAs in diseases are often not contained in the miRBase. However, these candidates are evolutionary highly conserved. From the expression patterns, target gene and pathway analyses and evolutionary conservation analyses, we were able to shed light on the complexity of miRNAs in humans. Our data also highlight that a more thorough validation of miRNAs identified by next generation sequencing is required. The results are available in miRCarta ( https://mircarta.cs.uni-saarland.de ).

Small Nucleolar RNA Score: An Assay to Detect Formalin-Overfixed Tissue

Although there are millions of formalin-fixed paraffin-embedded (FFPE) tissue blocks potentially available for scientific research, many are of questionable quality, partly due to unknown fixation conditions. We analyzed FFPE tissue biospecimens as part of the NCI Biospecimen Preanalytical Variables (BPV) program to identify microRNA (miRNA) markers for fixation time. miRNA was extracted from kidney and ovary tumor FFPE blocks (19 patients, cold ischemia ≤2 hours) with 6, 12, 24, and 72 hours fixation times, then analyzed using the WaferGen SmartChip platform (miRNA chip with 1036 miRNA targets). For fixation time, principal component analysis of miRNA chip expression data separated 72 hours fixed samples from 6 to 24 hours fixed samples. A set of small nuclear RNA (snRNA) targets was identified that best determines fixation time and was validated using a second independent cohort of seven different tissue types. A customized assay was then developed, based on a set of 24 miRNA and snRNA targets, and a simple “snoRNA score” defined. This score detects FFPE tissue samples with fixation for 72 hours or more, with 79% sensitivity and 80% specificity. It can therefore be used to assess the fitness-for-purpose of FFPE samples for DNA or RNA-based research or clinical assays, which are known to be of limited robustness to formalin overfixation.

Genome-wide MicroRNA Expression Profiles in COPD: Early Predictors for Cancer Development

Chronic obstructive pulmonary disease (COPD) significantly increases the risk of developing cancer. Biomarker studies frequently follow a case-control set-up in which patients diagnosed with a disease are compared to controls. Longitudinal cohort studies such as the COPD-centered German COPD and SYstemic consequences-COmorbidities NETwork (COSYCONET) study provide the patient and biomaterial base for discovering predictive molecular markers. We asked whether microRNA (miRNA) profiles in blood collected from COPD patients prior to a tumor diagnosis could support an early diagnosis of tumor development independent of the tumor type. From 2741 participants of COSYCONET diagnosed with COPD, we selected 534 individuals including 33 patients who developed cancer during the follow-up period of 54 months and 501 patients who did not develop cancer, but had similar age, gender and smoking history. Genome-wide miRNA profiles were generated and evaluated using machine learning techniques. For patients developing cancer we identified nine miRNAs with significantly decreased abundance (two-tailed unpaired t-test adjusted for multiple testing P < 0.05), including members of the miR-320 family. The identified miRNAs regulate different cancer-related pathways including the MAPK pathway (P = 2.3 × 10⁻⁵). We also observed the impact of confounding factors on the generated miRNA profiles, underlining the value of our matched analysis. For selected miRNAs, qRT-PCR analysis was applied to validate the results. In conclusion, we identified several miRNAs in blood of COPD patients, which could serve as candidates for biomarkers to help identify COPD patients at risk of developing cancer.

Small ncRNA-Seq Results of Human Tissues: Variations Depending on Sample Integrity

BACKGROUND

Although mature miRNAs are relatively stable in vivo, RNA degradation can have a substantial influence on small noncoding RNA (sncRNA) profiles.

METHODS

Using different tissue storage conditions and RNA isolation procedures, we analyzed the integrity and quality of RNA isolates from human lung and heart tissues. We sequenced a total of 64 RNA samples and quantified the effect of RNA degradation, DNA contamination, and other confounding factors on the sncRNA-seq data. Besides microRNAs, other noncoding RNA species (piRNAs, tRNAs, snoRNAs, rRNAs) were investigated.

RESULTS

Consistent with previous results, we found that the tissue specificity of microRNAs is generally well preserved. The distribution of microRNA isoforms was similar to the distribution of canonical forms. New miRNAs were more frequently discovered in degraded samples. sncRNA Reads generated from degraded samples mapped frequently to piRNAs, tRNAs, snoRNAs, or scaRNAs. Sequencing reads that were depleted of sncRNAs showed an increased mapping frequency to bacterial species.

CONCLUSIONS

Our data emphasize the importance of sample integrity, especially for next-generation sequencing (NGS)-based high-throughput sncRNA profiles. For the prediction of novel miRNAs in particular, only samples with the highest RNA integrity should be used in order to avoid identification of false "miRNAs."