miRMOD: a tool for identification and analysis of 5' and 3' miRNA modifications in Next Generation Sequencing small RNA data

Pseudouridine guides germline small RNA transport and epigenetic inheritance

Epigenetic modifications that arise during plant and animal development, such as DNA and histone modification, are mostly reset during gamete formation, but some are inherited from the germline including those marking imprinted genes1. Small RNAs guide these epigenetic modifications, and some are also inherited by the next generation2,3. In C. elegans, these inherited small RNAs have poly (UG) tails4, but how inherited small RNAs are distinguished in other animals and plants is unknown. Pseudouridine (Ψ) is the most abundant RNA modification but has not been explored in small RNAs. Here, we develop novel assays to detect Ψ in short RNA sequences, demonstrating its presence in mouse and Arabidopsis microRNAs and their precursors. We also detect substantial enrichment in germline small RNAs, namely epigenetically activated siRNAs (easiRNAs) in Arabidopsis pollen, and piwi-interacting piRNAs in mouse testis. In pollen, pseudouridylated easiRNAs are localized to sperm cells, and we found that PAUSED/HEN5 (PSD), the plant homolog of Exportin-t, interacts genetically with Ψ and is required for transport of easiRNAs into sperm cells from the vegetative nucleus. We further show that Exportin-t is required for the triploid block: chromosome dosage-dependent seed lethality that is epigenetically inherited from pollen. Thus, Ψ has a conserved role in marking inherited small RNAs in the germline.

miR319 and its target TCP4 involved in plant architecture regulation in Brassica napus

Plant architecture is a collection of genetically controlled crop productivity and adaptation. MicroRNAs (miRNAs) have been proved to function in various biological processes, but little is known about how miRNA regulates plant architecture in rapeseed (Brassica napus L.). In this study, four small RNA libraries and two degradome libraries from shoot apex of normal and rod-like plants were sequenced. A total of 639 miRNA precursors and 16 differentially expressed miRNAs were identified in this study. In addition, 322 targets were identified through degradome sequencing. Among them, 14 targets were further validated via RNA ligase-mediated 5' rapid amplification of cDNA ends. Transgenic approach showed that increased TCP4 activity in Arabidopsis resulted in premature onset of maturation and reduced plant size along with early flowering and shortened flowering time. miR319-OE lines in Brassica napus exhibited serrated leaves and abnormal development of shoot apical meristem (SAM), which led to the deformed growth of stem and reduced plant height. In conclusion, our study lays the foundation for elucidating miRNA regulate plant architecture and provides new insight into the miR319/TCP4 module regulates plant architecture in rapeseed.

MicroRNA Databases and Tools

In this era of big data, sets of methodologies and strategies are designed to extract knowledge from huge volumes of data. However, the cost of where and how to get this information accurately and quickly is extremely important, given the diversity of genomes and the different ways of representing that information. Among the huge set of information and relationships that the genome carries, there are sequences called miRNAs (microRNAs). These sequences were described in the 1990s and are mainly involved in mechanisms of regulation and gene expression. Having this in mind, this chapter focuses on exploring the available literature and providing useful and practical guidance on the miRNA database and tools topic. For that, we organized and present this text in two ways: (a) the update reviews and articles, which best summarize and discuss the theme; and (b) our update investigation on miRNA literature and portals about databases and tools. Finally, we present the main challenge and a possible solution to improve resources and tools.

Extracellular microRNA 3' end modification across diverse body fluids

microRNAs (miRNAs) are small non-coding RNAs that play critical roles in gene regulation. The presence of miRNAs in extracellular biofluids is increasingly recognized. However, most previous characterization of extracellular miRNAs focused on their overall expression levels. Alternative sequence isoforms and modifications of miRNAs were rarely considered in the extracellular space. Here, we developed a highly accurate bioinformatic method, called miNTA, to identify 3' non-templated additions (NTAs) of miRNAs using small RNA-sequencing data. Using miNTA, we conducted an in-depth analysis of miRNA 3' NTA profiles in 1047 extracellular RNA-sequencing data sets of 4 types of biofluids. This analysis identified hundreds of miRNAs with 3' uridylation or adenylation, with the former being more prevalent. Among these miRNAs, up to 53% (22%) had an average 3' uridylation (adenylation) level of at least 10% in a specific biofluid. Strikingly, we found that 3' uridylation levels enabled segregation of different types of biofluids, more effectively than overall miRNA expression levels. This observation suggests that 3' NTA levels possess fluid-specific information relatively robust to batch effects. In addition, we observed that extracellular miRNAs with 3' uridylations are enriched in processes related to angiogenesis, apoptosis, and inflammatory response, and this type of modification may stabilize base-pairing between miRNAs and their target genes. Together, our study provides a comprehensive landscape of miRNA NTAs in human biofluids, which paves way for further biomarker discoveries. The insights generated in our work built a foundation for future functional, mechanistic, and translational discoveries.

MEF2C shapes the microtranscriptome during differentiation of skeletal muscles

Myocyte enhancer factor 2C (MEF2C) is a transcription factor that regulates heart and skeletal muscle differentiation and growth. Several protein-encoding genes were identified as targets of this factor; however, little is known about its contribution to the microtranscriptome composition and dynamics in myogenic programs. In this report, we aimed to address this question. Deep sequencing of small RNAs of human muscle cells revealed a set of microRNAs (miRNAs), including several muscle-specific miRNAs, that are sensitive to MEF2C depletion. As expected, in cells with knockdown of MEF2C, we found mostly downregulated miRNAs; nevertheless, as much as one-third of altered miRNAs were upregulated. The majority of these changes are driven by transcription efficiency. Moreover, we found that MEF2C affects nontemplated 3′-end nucleotide addition of miRNAs, mainly oligouridylation. The rate of these modifications is associated with the level of TUT4 which mediates RNA 3′-uridylation. Finally, we found that a quarter of miRNAs which significantly changed upon differentiation of human skeletal myoblasts is inversely altered in MEF2C deficient cells. We concluded that MEF2C is an essential factor regulating both the quantity and quality of the microtranscriptome, leaving an imprint on the stability and perhaps specificity of many miRNAs during the differentiation of muscle cells.

IsomiR_Window: a system for analyzing small-RNA-seq data in an integrative and user-friendly manner

BACKGROUND

IsomiRs are miRNA variants that vary in length and/or sequence when compared to their canonical forms. These variants display differences in length and/or sequence, including additions or deletions of one or more nucleotides (nts) at the 5' and/or 3' end, internal editings or untemplated 3' end additions. Most available tools for small RNA-seq data analysis do not allow the identification of isomiRs and often require advanced knowledge of bioinformatics. To overcome this, we have developed IsomiR Window, a platform that supports the systematic identification, quantification and functional exploration of isomiR expression in small RNA-seq datasets, accessible to users with no computational skills.

METHODS

IsomiR Window enables the discovery of isomiRs and identification of all annotated non-coding RNAs in RNA-seq datasets from animals and plants. It comprises two main components: the IsomiR Window pipeline for data processing; and the IsomiR Window Browser interface. It integrates over ten third-party softwares for the analysis of small-RNA-seq data and holds a new algorithm that allows the detection of all possible types of isomiRs. These include 3' and 5'end isomiRs, 3' end tailings, isomiRs with single nucleotide polymorphisms (SNPs) or potential RNA editings, as well as all possible fuzzy combinations. IsomiR Window includes all required databases for analysis and annotation, and is freely distributed as a Linux virtual machine, including all required software.

RESULTS

IsomiR Window processes several datasets in an automated manner, without restrictions of input file size. It generates high quality interactive figures and tables which can be exported into different formats. The performance of isomiR detection and quantification was assessed using simulated small-RNA-seq data. For correctly mapped reads, it identified different types of isomiRs with high confidence and 100% accuracy. The analysis of a small RNA-seq data from Basal Cell Carcinomas (BCCs) using isomiR Window confirmed that miR-183-5p is up-regulated in Nodular BCCs, but revealed that this effect was predominantly due to a novel 5'end variant. This variant displays a different seed region motif and 1756 isoform-exclusive mRNA targets that are significantly associated with disease pathways, underscoring the biological relevance of isomiR-focused analysis. IsomiR Window is available at https://isomir.fc.ul.pt/ .

isomiRs-Hidden Soldiers in the miRNA Regulatory Army, and How to Find Them?

Numerous studies on microRNAs (miRNA) in cancer and other diseases have been accompanied by diverse computational approaches and experimental methods to predict and validate miRNA biological and clinical significance as easily accessible disease biomarkers. In recent years, the application of the next-generation deep sequencing for the analysis and discovery of novel RNA biomarkers has clearly shown an expanding repertoire of diverse sequence variants of mature miRNAs, or isomiRs, resulting from alternative post-transcriptional processing events, and affected by (patho)physiological changes, population origin, individual's gender, and age. Here, we provide an in-depth overview of currently available bioinformatics approaches for the detection and visualization of both mature miRNA and cognate isomiR sequences. An attempt has been made to present in a systematic way the advantages and downsides of in silico approaches in terms of their sensitivity and accuracy performance, as well as used methods, workflows, and processing steps, and end output dataset overlapping issues. The focus is given to the challenges and pitfalls of isomiR expression analysis. Specifically, we address the availability of tools enabling research without extensive bioinformatics background to explore this fascinating corner of the small RNAome universe that may facilitate the discovery of new and more reliable disease biomarkers.

The epitranscriptome landscape of small noncoding RNAs in stem cells

Stem cells (SCs) are unique cells that have an inherent ability to self‐renew or differentiate. Both fate decisions are strongly regulated at the molecular level via intricate signaling pathways. The regulation of signaling networks promoting self‐renewal or differentiation was thought to be largely governed by the action of transcription factors. However, small noncoding RNAs (ncRNAs), such as vault RNAs, and their post‐transcriptional modifications (the epitranscriptome) have emerged as additional regulatory layers with essential roles in SC fate decisions. RNA post‐transcriptional modifications often modulate RNA stability, splicing, processing, recognition, and translation. Furthermore, modifications on small ncRNAs allow for dual regulation of RNA activity, at both the level of biogenesis and RNA‐mediated actions. RNA post‐transcriptional modifications act through structural alterations and specialized RNA‐binding proteins (RBPs) called writers, readers, and erasers. It is through SC‐context RBPs that the epitranscriptome coordinates specific functional roles. Small ncRNA post‐transcriptional modifications are today exploited by different mechanisms to facilitate SC translational studies. One mechanism readily being studied is identifying how SC‐specific RBPs of small ncRNAs regulate fate decisions. Another common practice of using the epitranscriptome for regenerative applications is using naturally occurring post‐transcriptional modifications on synthetic RNA to generate induced pluripotent SCs. Here, we review exciting insights into how small ncRNA post‐transcriptional modifications control SC fate decisions in development and disease. We hope, by illustrating how essential the epitranscriptome and their associated proteome are in SCs, they would be considered as novel tools to propagate SCs for regenerative medicine.

Direct microRNA Sequencing Using Nanopore-Induced Phase-Shift Sequencing

MicroRNAs (miRNAs) are a class of short non-coding RNAs that function in RNA silencing and post-transcriptional gene regulation. However, direct characterization of miRNA is challenging due to its unique properties such as its low abundance, sequence similarities, and short length. Although urgently needed, single molecule sequencing of miRNA has never been demonstrated, to the best of our knowledge. Nanopore-induced phase-shift sequencing (NIPSS), which is a variant form of nanopore sequencing, could directly sequence any short analytes including miRNA. In practice, NIPSS clearly discriminates between different identities, isoforms, and epigenetic variants of model miRNA sequences. This work thus demonstrates direct sequencing of miRNA, which serves as a complement to existing miRNA sensing routines by the introduction of the single molecule resolution. Future engineering of this technique may assist miRNA-based early stage diagnosis or inspire novel cancer therapeutics.

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The first demonstration of single molecule miRNA sequencing

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miRNA sequencing by NIPSS can directly identify epigenetic modifications

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Enzymatic conjugation enables NIPSS sequencing of natural miRNAs

Identifying and characterizing functional 3' nucleotide addition in the miRNA pathway

Over the past decade, modifications to microRNAs (miRNAs) via 3' end nucleotide addition have gone from a deep-sequencing curiosity to experimentally confirmed drivers of a range of regulatory activities. Here we overview the methods that have been deployed by researchers seeking to untangle these diverse functional roles and include characterizing not only the nucleotidyl transferases catalyzing the additions but also the nucleotides being added, and the timing of their addition during the miRNA pathway. These methods and their further development are key to clarifying the diverse and sometimes contradictory functional findings presently attributed to these nucleotide additions.

Mapping the microRNA Expression Profiles in Glyoxalase Over-expressing Salinity Tolerant Rice

In the recent years, glyoxalase pathway has been an active area of research in both human and plants. This pathway is reported to confer stress tolerance in plants, by modulating the glutathione homeostasis to achieve detoxification of a potent cytotoxic and mutagenic compound, methylglyoxal. The microRNAs (miRNAs) are also reported to play significant role in stress tolerance for plants. However, the cross-talk of miRNAs with the metabolism regulated by glyoxalase in the salinity-tolerance is unexplored. We therefore investigated whether expression profiles of miRNAs are altered in response to glyoxalase overexpression, and if any of these are also responsible for modulating the stress responses of plants. In this study, the Next Generation Sequencing (NGS) was employed to profile miRNA expression levels from glyoxalase overexpressing transgenic lines. The associated targets of differentially expressed miRNAs were predicted and their functional annotation was carried out using Gene Ontology (GO) and KEGG Orthology (KO), which showed their involvement in several crucial biological pathways. The analysis of NGS datasets also identified other isoforms or isomiRs of selected miRNAs, which may have an active role in developing tolerance against salt stress. Different aspects of miRNA modifications were also studied in glyoxalase overexpressing lines.

Comparative miRomics of Salt-Tolerant and Salt-Sensitive Rice

Increase in soil salt causes osmotic and ionic stress to plants, which inhibits their growth and productivity. Rice production is also hampered by salinity and the effect of salt is most severe at the seedling and reproductive stages. Salainity tolerance is a quantitative property controlled by multiple genes coding for signaling molecules, ion transporters, metabolic enzymes and transcription regulators. MicroRNAs are key modulators of gene-expression that act at the post-transcriptional level by translation repression or transcript cleavage. They also play an important role in regulating plant's response to salt-stress. In this work we adopted the approach of comparative and integrated data-mining to understand the miRNA-mediated regulation of salt-stress in rice. We profiled and compared the miRNA regulations using natural varieties and transgenic lines with contrasting behaviors in response to salt-stress. The information obtained from sRNAseq, RNAseq and degradome datasets was integrated to identify the salt-deregulated miRNAs, their targets and the associated metabolic pathways. The analysis revealed the modulation of many biological pathways, which are involved in salt-tolerance and play an important role in plant phenotype and physiology. The end modifications of the miRNAs were also studied in our analysis and isomiRs having a dynamic role in salt-tolerance mechanism were identified.

Computational and Experimental Identification of Tissue-Specific MicroRNA Targets

In this chapter we discuss computational methods for the prediction of microRNA (miRNA) targets. More specifically, we consider machine learning-based approaches and explain why these methods have been relatively unsuccessful in reducing the number of false positive predictions. Further we suggest approaches designed to improve their performance by considering tissue-specific target regulation. We argue that the miRNA targetome differs depending on the tissue type and introduce a novel algorithm that predicts miRNA targets specifically for colorectal cancer. We discuss features of miRNAs and target sites that affect target recognition, and how next-generation sequencing data can support the identification of novel miRNAs, differentially expressed miRNAs and their tissue-specific mRNA targets. In addition, we introduce some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA target interactions.