HAMR: high-throughput annotation of modified ribonucleotides

Analysis of tRNA-derived RNA fragments (tRFs) in Cryptococcus spp.: RNAi-independent generation and possible compensatory effects in a RNAi-deficient genotype

Small RNAs (sRNAs) are key factors in the regulation of gene expression. Recently, a new class of regulatory sRNAs derived from tRNAs was described, the tRNA-derived RNA fragments (tRFs). Such RNAs range in length from 14 to 30 nucleotides and are produced from both mature and primary tRNA transcripts, with very specific cleavage sites along the tRNA sequence. Although several mechanisms have been proposed for how tRFs mediate regulation of gene expression, the exact mechanism of tRF biogenesis and its dependency upon the RNAi pathway remain unclear. Cryptococcus gattii and Cryptococcus neoformans are basidiomycetous yeasts and important human pathogens. While C. neoformans is RNAi proficient, C. gattii VGII has lost essential RNAi genes. Here, we sought to identify the tRF production profile in C. gattii VGII and C. neoformans in order to assess the RNAi-dependency of tRF production in these fungal species. We developed a RNA-sequencing-based tRF prediction workflow designed to improve the currently available prediction tools. Using this methodology, we were able to identify tRFs in both organisms. Despite the loss of the RNAi pathway, C. gattii VGII displayed a number of identified tRFs that did not differ significantly from those observed in C. neoformans. The analysis of predicted tRF targets revealed that a higher number of targets was found for C. gattii VGII tRFs compared to C. neoformans tRFs. These results support the idea that tRFs are at least partially independent of the canonical RNAi machinery, raising questions about possible compensatory roles of alternative regulatory RNAs in the absence of a functional RNAi pathway.

The epitranscriptome beyond m6A

Following its transcription, RNA can be modified by >170 chemically distinct types of modifications - the epitranscriptome. In recent years, there have been substantial efforts to uncover and characterize the modifications present on mRNA, motivated by the potential of such modifications to regulate mRNA fate and by discoveries and advances in our understanding of N ⁶-methyladenosine (m⁶A). Here, we review our knowledge regarding the detection, distribution, abundance, biogenesis, functions and possible mechanisms of action of six of these modifications - pseudouridine (Ψ), 5-methylcytidine (m⁵C), N ¹-methyladenosine (m¹A), N ⁴-acetylcytidine (ac⁴C), ribose methylations (N_m) and N ⁷-methylguanosine (m⁷G). We discuss the technical and analytical aspects that have led to inconsistent conclusions and controversies regarding the abundance and distribution of some of these modifications. We further highlight shared commonalities and important ways in which these modifications differ with respect to m⁶A, based on which we speculate on their origin and their ability to acquire functions over evolutionary timescales.

Manganese Ions Individually Alter the Reverse Transcription Signature of Modified Ribonucleosides

Reverse transcription of RNA templates containing modified ribonucleosides transfers modification-related information as misincorporations, arrest or nucleotide skipping events to the newly synthesized cDNA strand. The frequency and proportion of these events, merged from all sequenced cDNAs, yield a so-called RT signature, characteristic for the respective RNA modification and reverse transcriptase (RT). While known for DNA polymerases in so-called error-prone PCR, testing of four different RTs by replacing Mg²⁺ with Mn²⁺ in reaction buffer revealed the immense influence of manganese chloride on derived RT signatures, with arrest rates on m¹A positions dropping from 82% down to 24%. Additionally, we observed a vast increase in nucleotide skipping events, with single positions rising from 4% to 49%, thus implying an enhanced read-through capability as an effect of Mn²⁺ on the reverse transcriptase, by promoting nucleotide skipping over synthesis abortion. While modifications such as m¹A, m²₂G, m¹G and m³C showed a clear influence of manganese ions on their RT signature, this effect was individual to the polymerase used. In summary, the results imply a supporting effect of Mn²⁺ on reverse transcription, thus overcoming blockades in the Watson-Crick face of modified ribonucleosides and improving both read-through rate and signal intensity in RT signature analysis.

Accurate characterization of Escherichia coli tRNA modifications with a simple method of deep-sequencing library preparation

In conventional RNA high-throughput sequencing, modified bases prevent a large fraction of tRNA transcripts to be converted into cDNA libraries. Recent proposals aiming at resolving this issue take advantage of the interference of base modifications with RT enzymes to detect and identify them by establishing signals from aborted cDNA transcripts. Because some modifications, such as methyl groups, do almost not allow RT bypassing, demethylation and highly processive RT enzymes have been used to overcome these obstacles. Working with Escherichia coli as a model system, we show that with a conventional (albeit still engineered) RT enzyme and key optimizations in library preparation, all RT-impairing modifications can be highlighted along the entire tRNA length without demethylation procedure. This is achieved by combining deep-sequencing samples, which allows to establish aborted transcription signal of higher accuracy and reproducibility, with the potential for differentiating tiny differences in the state of modification of all cellular tRNAs. In addition, our protocol provides estimates of the relative tRNA abundance.

A Census and Categorization Method of Epitranscriptomic Marks

In the past few years, thorough investigation of chemical modifications operated in the cells on ribonucleic acid (RNA) molecules is gaining momentum. This new field of research has been dubbed “epitranscriptomics”, in analogy to best-known epigenomics, to stress the potential of ensembles of RNA modifications to constitute a post-transcriptional regulatory layer of gene expression orchestrated by writer, reader, and eraser RNA-binding proteins (RBPs). In fact, epitranscriptomics aims at identifying and characterizing all functionally relevant changes involving both non-substitutional chemical modifications and editing events made to the transcriptome. Indeed, several types of RNA modifications that impact gene expression have been reported so far in different species of cellular RNAs, including ribosomal RNAs, transfer RNAs, small nuclear RNAs, messenger RNAs, and long non-coding RNAs. Supporting functional relevance of this largely unknown regulatory mechanism, several human diseases have been associated directly to RNA modifications or to RBPs that may play as effectors of epitranscriptomic marks. However, an exhaustive epitranscriptome’s characterization, aimed to systematically classify all RNA modifications and clarify rules, actors, and outcomes of this promising regulatory code, is currently not available, mainly hampered by lack of suitable detecting technologies. This is an unfortunate limitation that, thanks to an unprecedented pace of technological advancements especially in the sequencing technology field, is likely to be overcome soon. Here, we review the current knowledge on epitranscriptomic marks and propose a categorization method based on the reference ribonucleotide and its rounds of modifications (“stages”) until reaching the given modified form. We believe that this classification scheme can be useful to coherently organize the expanding number of discovered RNA modifications.

Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics

Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.

Comparative tRNA sequencing and RNA mass spectrometry for surveying tRNA modifications

Chemical modifications of the nucleosides that comprise transfer RNAs are diverse. However, the structure, location and extent of modifications have been systematically charted in very few organisms. Here, we describe an approach in which rapid prediction of modified sites through reverse transcription-derived signatures in high-throughput transfer RNA-sequencing (tRNA-seq) data is coupled with identification of tRNA modifications through RNA mass spectrometry. Comparative tRNA-seq enabled prediction of several Vibrio cholerae modifications that are absent from Escherichia coli and also revealed the effects of various environmental conditions on V. cholerae tRNA modification. Through RNA mass spectrometric analyses, we showed that two of the V. cholerae-specific reverse transcription signatures reflected the presence of a new modification (acetylated acp³U (acacp³U)), while the other results from C-to-Ψ RNA editing, a process not described before. These findings demonstrate the utility of this approach for rapid surveillance of tRNA modification profiles and environmental control of tRNA modification.

PRMdb: A Repository of Predicted RNA Modifications in Plants

Evidence is mounting that RNA modifications play essential roles in posttranscriptional regulation of gene expression. So far, over 150 RNA modifications catalyzed by distinct enzymes have been documented. In plants, genome-wide identification of RNA modifications is largely limited to the model species Arabidopsis thaliana, while lacking in diverse non-model plants. Here, we present PRMdb, a plant RNA modification database, based on the analysis of thousands of RNA-seq, degradome-seq and small RNA-seq data from a wide range of plant species using the well-documented tool HAMR (high-throughput analysis of modified ribonucleotide). PRMdb provides a user-friendly interface that enables easy browsing and searching of the tRNA and mRNA modification data. We show that PRMdb collects high-confidence RNA modifications including novel RNA modification sites that can be validated by genomic PCR and reverse transcription PCR. In summary, PRMdb provides a valuable web resource for deciphering the epitranscriptomes in diverse plant species and will facilitate functional studies of RNA modifications in plants. RPMdb is available via http://www.biosequencing.cn/PRMdb/.

RNAmod: an integrated system for the annotation of mRNA modifications

Dynamic and reversible RNA modifications such as N⁶-methyladenosine (m⁶A) can play important roles in regulating messenger RNA (mRNA) splicing, export, stability and translation. Defective mRNA modification through altered expression of the methyltransferase and/or demethylases results in developmental defects and cancer progression. Identifying modified mRNAs, annotating the distribution of modification sites across the mRNA, as well as characterizing and comparing other modification features are essential for studying the function and elucidating the mechanism of mRNA modifications. Several methods including methylated RNA immunoprecipitation and sequencing (MeRIP-seq) are available for the detection of mRNA modifications. However, a convenient and comprehensive tool to annotate diverse kinds of mRNA modifications in different species is lacking. Here, we developed RNAmod (https://bioinformatics.sc.cn/RNAmod), an interactive, one-stop, web-based platform for the automated analysis, annotation, and visualization of mRNA modifications in 21 species. RNAmod provides intuitive interfaces to show outputs including the distribution of RNA modifications, modification coverage for different gene features, functional annotation of modified mRNAs, and comparisons between different groups or specific gene sets. Furthermore, sites of known RNA modification, as well as binding site data for hundreds of RNA-binding proteins (RBPs) are integrated in RNAmod to help users compare their modification data with known modifications and to explore the relationship with the binding sites of known RBPs. RNAmod is freely available and meets the emerging need for a convenient and comprehensive analysis tool for the fast-developing RNA modification field.

Machine learning of reverse transcription signatures of variegated polymerases allows mapping and discrimination of methylated purines in limited transcriptomes

Reverse transcription (RT) of RNA templates containing RNA modifications leads to synthesis of cDNA containing information on the modification in the form of misincorporation, arrest, or nucleotide skipping events. A compilation of such events from multiple cDNAs represents an RT-signature that is typical for a given modification, but, as we show here, depends also on the reverse transcriptase enzyme. A comparison of 13 different enzymes revealed a range of RT-signatures, with individual enzymes exhibiting average arrest rates between 20 and 75%, as well as average misincorporation rates between 30 and 75% in the read-through cDNA. Using RT-signatures from individual enzymes to train a random forest model as a machine learning regimen for prediction of modifications, we found strongly variegated success rates for the prediction of methylated purines, as exemplified with N1-methyladenosine (m1A). Among the 13 enzymes, a correlation was found between read length, misincorporation, and prediction success. Inversely, low average read length was correlated to high arrest rate and lower prediction success. The three most successful polymerases were then applied to the characterization of RT-signatures of other methylated purines. Guanosines featuring methyl groups on the Watson-Crick face were identified with high confidence, but discrimination between m1G and m22G was only partially successful. In summary, the results suggest that, given sufficient coverage and a set of specifically optimized reaction conditions for reverse transcription, all RNA modifications that impede Watson-Crick bonds can be distinguished by their RT-signature.

Arabidopsis TRM5 encodes a nuclear-localised bifunctional tRNA guanine and inosine-N1-methyltransferase that is important for growth

Modified nucleosides in tRNAs are critical for protein translation. N1-methylguanosine-37 and N1-methylinosine-37 in tRNAs, both located at the 3'-adjacent to the anticodon, are formed by Trm5. Here we describe Arabidopsis thaliana AtTRM5 (At3g56120) as a Trm5 ortholog. Attrm5 mutant plants have overall slower growth as observed by slower leaf initiation rate, delayed flowering and reduced primary root length. In Attrm5 mutants, mRNAs of flowering time genes are less abundant and correlated with delayed flowering. We show that AtTRM5 complements the yeast trm5 mutant, and in vitro methylates tRNA guanosine-37 to produce N1-methylguanosine (m1G). We also show in vitro that AtTRM5 methylates tRNA inosine-37 to produce N1-methylinosine (m1I) and in Attrm5 mutant plants, we show a reduction of both N1-methylguanosine and N1-methylinosine. We also show that AtTRM5 is localized to the nucleus in plant cells. Proteomics data showed that photosynthetic protein abundance is affected in Attrm5 mutant plants. Finally, we show tRNA-Ala aminoacylation is not affected in Attrm5 mutants. However the abundance of tRNA-Ala and tRNA-Asp 5' half cleavage products are deduced. Our findings highlight the bifunctionality of AtTRM5 and the importance of the post-transcriptional tRNA modifications m1G and m1I at tRNA position 37 in general plant growth and development.

Antibody cross-reactivity accounts for widespread appearance of m1A in 5'UTRs

N1-methyladenosine (m1A) was proposed to be a highly prevalent modification in mRNA 5'UTRs based on mapping studies using an m1A-binding antibody. We developed a bioinformatic approach to discover m1A and other modifications in mRNA throughout the transcriptome by analyzing preexisting ultra-deep RNA-Seq data for modification-induced misincorporations. Using this approach, we detected appreciable levels of m1A only in one mRNA: the mitochondrial MT-ND5 transcript. As an alternative approach, we also developed an antibody-based m1A-mapping approach to detect m1A at single-nucleotide resolution, and confirmed that the commonly used m1A antibody maps sites to the transcription-start site in mRNA 5'UTRs. However, further analysis revealed that these were false-positives caused by binding of the antibody to the m7G-cap. A different m1A antibody that lacks cap-binding cross-reactivity does not show enriched binding in 5'UTRs. These results demonstrate that high-stoichiometry m1A sites are exceedingly rare in mRNAs and that previous mappings of m1A to 5'UTRs were the result of antibody cross-reactivity to the 5' cap.

Graphical Workflow System for Modification Calling by Machine Learning of Reverse Transcription Signatures

Modification mapping from cDNA data has become a tremendously important approach in epitranscriptomics. So-called reverse transcription signatures in cDNA contain information on the position and nature of their causative RNA modifications. Data mining of, e.g. Illumina-based high-throughput sequencing data, is therefore fast growing in importance, and the field is still lacking effective tools. Here we present a versatile user-friendly graphical workflow system for modification calling based on machine learning. The workflow commences with a principal module for trimming, mapping, and postprocessing. The latter includes a quantification of mismatch and arrest rates with single-nucleotide resolution across the mapped transcriptome. Further downstream modules include tools for visualization, machine learning, and modification calling. From the machine-learning module, quality assessment parameters are provided to gauge the suitability of the initial dataset for effective machine learning and modification calling. This output is useful to improve the experimental parameters for library preparation and sequencing. In summary, the automation of the bioinformatics workflow allows a faster turnaround of the optimization cycles in modification calling.

Discovering and Mapping the Modified Nucleotides That Comprise the Epitranscriptome of mRNA

An important mechanism of gene expression regulation is the regulated modification of nucleotides in messenger RNA (mRNA). These modified nucleotides affect mRNA translation, stability, splicing, and other processes. A cluster of nucleotide modifications is found adjacent to the mRNA cap structure and another set can be found internally within transcripts. The most prominent modifications are methylations of adenosine to form either N ⁶-methyladenosine (m⁶A), an internal modified nucleotide, or N ⁶,2'-O-dimethyladenosine (m⁶Am), which is found exclusively at the first templated nucleotide of certain mRNAs. In addition, other rare modified nucleotides have been identified and together these form the epitranscriptomic code of mRNA. In the case of some modified nucleotides, the presence, location, or abundance is a subject of debate. Here, we review the methods that enable the discovery of modified nucleotides and how these approaches can be used to map epitranscriptomic modifications in mRNA.

HAMR: High-Throughput Annotation of Modified Ribonucleotides

Ribonucleotides can be decorated with over 100 types of covalent chemical modifications. These modifications change the structure, function, and catalytic activity of RNAs, forming a layer of posttranscriptional regulation termed the epitranscriptome. Recent advances in high-throughput mapping have demonstrated these modifications are abundant and mark nearly all classes of RNAs, including messenger RNAs. Here, we outline one such technique called high-throughput annotation of modified ribonucleotides (HAMR). HAMR exploits the tendency of certain modified ribonucleotides to interfere with base pairing, leading to errors in complementary DNA synthesis during RNA sequencing library preparation. In total, we present a computational protocol for in silico identification of modifications with HAMR, which can be retroactively applied to a variety of RNA sequencing techniques.

Detection and analysis of RNA methylation

Our understanding of the expanded genetic alphabet has been growing rapidly over the last two decades, and many of these developments came more than 80 years after the original discovery of a modified guanine in tuberculosis DNA. These new understandings, leading to the field of epigenetics, have led to exciting new fundamental and applied knowledge and to the development of novel classes of drugs exploiting this new biology. The number of methyl modifications to RNA is about seven times greater than those found on DNA, and our ability to interrogate these enigmatic nucleobases has lagged significantly until recent years as an explosion in technologies and understanding has revealed the roles and regulation of RNA methylation in several fundamental and disease-associated biological processes. Here, we outline how the technology has evolved and which strategies are commonly used in the modern epitranscriptomics revolution and give a foundation in the understanding and application of the rich variety of these methods to novel biological questions.

Differential expression of human tRNA genes drives the abundance of tRNA-derived fragments

The human genome encodes hundreds of transfer RNA (tRNA) genes but their individual contribution to the tRNA pool is not fully understood. Deep sequencing of tRNA transcripts (tRNA-Seq) can estimate tRNA abundance at single gene resolution, but tRNA structures and posttranscriptional modifications impair these analyses. Here we present a bioinformatics strategy to investigate differential tRNA gene expression and use it to compare tRNA-Seq datasets from cultured human cells and human brain. We find that sequencing caveats affect quantitation of only a subset of human tRNA genes. Unexpectedly, we detect several cases where the differences in tRNA expression among samples do not involve variations at the level of isoacceptor tRNA sets (tRNAs charged with the same amino acid but using different anticodons), but rather among tRNA genes within the same isodecoder set (tRNAs having the same anticodon sequence). Because isodecoder tRNAs are functionally equal in terms of genetic translation, their differential expression may be related to noncanonical tRNA functions. We show that several instances of differential tRNA gene expression result in changes in the abundance of tRNA-derived fragments (tRFs) but not of mature tRNAs. Examples of differentially expressed tRFs include PIWI-associated RNAs, tRFs present in tissue samples but not in cells cultured in vitro, and somatic tissue-specific tRFs. Our data support that differential expression of tRNA genes regulate noncanonical tRNA functions performed by tRFs.

Nucleotide resolution sequencing of N4-acetylcytidine in RNA

Posttranscriptional modifications of RNA represent an emerging class of regulatory elements in human biology. Improved methods for studying how these elements are controlled and where they occur has the potential to transform our understanding of gene expression in development and disease. Here we describe a chemical method for nucleotide resolution sequencing of N4-acetylcytidine (ac4C), a highly conserved modified nucleobase whose formation is catalyzed by the essential cytidine acetyltransferase enzyme NAT10. This approach enables the sensitive, PCR-amplifiable detection of individual ac4C sites from nanograms of unfractionated cellular RNA. The sensitive and quantitative nature of this assay provides a powerful tool to understand how cytidine acetylation is targeted, profile RNA acetyltransferase dynamics, and validate the sites and stoichiometry of ac4C in novel RNA species.

Novel molecules lncRNAs, tRFs and circRNAs deciphered from next-generation sequencing/RNA sequencing: computational databases and tools

Powerful next-generation sequencing (NGS) technologies, more specifically RNA sequencing (RNA-seq), have been pivotal toward the detection and analysis and hypotheses generation of novel biomolecules, long noncoding RNAs (lncRNAs), tRNA-derived fragments (tRFs) and circular RNAs (circRNAs). Experimental validation of the occurrence of these biomolecules inside the cell has been reported. Their differential expression and functionally important role in several cancers types as well as other diseases such as Alzheimer's and cardiovascular diseases have garnered interest toward further studies in this research arena. In this review, starting from a brief relevant introduction to NGS and RNA-seq and the expression and role of lncRNAs, tRFs and circRNAs in cancer, we have comprehensively analyzed the current landscape of databases developed and computational software used for analyses and visualization for this emerging and highly interesting field of these novel biomolecules. Our review will help the end users and research investigators gain information on the existing databases and tools as well as an understanding of the specific features which these offer. This will be useful for the researchers in their proper usage thereby guiding them toward novel hypotheses generation and saving time and costs involved in extensive experimental processes in these three different novel functional RNAs.

Methods for RNA Modification Mapping Using Deep Sequencing: Established and New Emerging Technologies

New analytics of post-transcriptional RNA modifications have paved the way for a tremendous upswing of the biological and biomedical research in this field. This especially applies to methods that included RNA-Seq techniques, and which typically result in what is termed global scale modification mapping. In this process, positions inside a cell’s transcriptome are receiving a status of potential modification sites (so called modification calling), typically based on a score of some kind that issues from the particular method applied. The resulting data are thought to represent information that goes beyond what is contained in typical transcriptome data, and hence the field has taken to use the term “epitranscriptome”. Due to the high rate of newly published mapping techniques, a significant number of chemically distinct RNA modifications have become amenable to mapping, albeit with variegated accuracy and precision, depending on the nature of the technique. This review gives a brief overview of known techniques, and how they were applied to modification calling.

Accurate mapping of tRNA reads

Motivation

Many repetitive DNA elements are transcribed at appreciable expression levels. Mapping the corresponding RNA sequencing reads back to a reference genome is notoriously difficult and error-prone task, however. This is in particular true if chemical modifications introduce systematic mismatches, while at the same time the genomic loci are only approximately identical, as in the case of tRNAs.

Results

We therefore developed a dedicated mapping strategy to handle RNA-seq reads that map to tRNAs relying on a modified target genome in which known tRNA loci are masked and instead intronless tRNA precursor sequences are appended as artificial 'chromosomes'. In a first pass, reads that overlap the boundaries of mature tRNAs are extracted. In the second pass, the remaining reads are mapped to a tRNA-masked target that is augmented by representative mature tRNA sequences. Using both simulated and real life data we show that our best-practice workflow removes most of the mapping artefacts introduced by simpler mapping schemes and makes it possible to reliably identify many of chemical tRNA modifications in generic small RNA-seq data. Using simulated data the FDR is only 2%. We find compelling evidence for tissue specific differences of tRNA modification patterns.

Availability and implementation

The workflow is available both as a bash script and as a Galaxy workflow from https://github.com/AnneHoffmann/tRNA-read-mapping.

Contact

fabian@tbi.univie.ac.at.

Supplementary information

Supplementary data are available at Bioinformatics online.

New insights into the plant epitranscriptome

Throughout all kingdoms of life, ribonucleotides are marked with covalent chemical modifications that change the structure and binding properties of modified RNA molecules. These marks are deposited by 'writer' proteins, recognized by 'readers', and removed by 'erasers', thus forming an epitranscriptomic system of marks and binding proteins directly analogous to the epigenome. Recent advances in marrying classical biochemical techniques with high-throughput sequencing have enabled detailed mapping of plant epitranscriptomic marks, which in turn yielded insights into how these marks regulate a host of biological processes, from shoot stem cell fate to floral transition and from leaf development to viral activity. In this review, we highlight recent developments in the study of plant epitranscriptomics, with an emphasis on N6-methyladenosine (m6A) and 5-methylcytosine (m5C). These studies have advanced the field beyond descriptive mapping or isolated genetic studies, and produced a more nuanced understanding of how components of the epitranscriptome and their binding proteins directly regulate critical aspects of plant biology.

Limitations of alignment-free tools in total RNA-seq quantification

Background

Alignment-free RNA quantification tools have significantly increased the speed of RNA-seq analysis. However, it is unclear whether these state-of-the-art RNA-seq analysis pipelines can quantify small RNAs as accurately as they do with long RNAs in the context of total RNA quantification.

Result

We comprehensively tested and compared four RNA-seq pipelines for accuracy of gene quantification and fold-change estimation. We used a novel total RNA benchmarking dataset in which small non-coding RNAs are highly represented along with other long RNAs. The four RNA-seq pipelines consisted of two commonly-used alignment-free pipelines and two variants of alignment-based pipelines. We found that all pipelines showed high accuracy for quantifying the expression of long and highly-abundant genes. However, alignment-free pipelines showed systematically poorer performance in quantifying lowly-abundant and small RNAs.

Conclusion

We have shown that alignment-free and traditional alignment-based quantification methods perform similarly for common gene targets, such as protein-coding genes. However, we have identified a potential pitfall in analyzing and quantifying lowly-expressed genes and small RNAs with alignment-free pipelines, especially when these small RNAs contain biological variations.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4869-5) contains supplementary material, which is available to authorized users.

SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs

High-throughput RNA-seq has revolutionized the process of small RNA (sRNA) discovery, leading to a rapid expansion of sRNA categories. In addition to the previously well-characterized sRNAs such as microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and small nucleolar RNA (snoRNAs), recent emerging studies have spotlighted on tRNA-derived sRNAs (tsRNAs) and rRNA-derived sRNAs (rsRNAs) as new categories of sRNAs that bear versatile functions. Since existing software and pipelines for sRNA annotation are mostly focused on analyzing miRNAs or piRNAs, here we developed the sRNA annotation pipelineoptimized for rRNA- and tRNA-derived sRNAs (SPORTS1.0). SPORTS1.0 is optimized for analyzing tsRNAs and rsRNAs from sRNA-seq data, in addition to its capacity to annotate canonical sRNAs such as miRNAs and piRNAs. Moreover, SPORTS1.0 can predict potential RNA modification sites based on nucleotide mismatches within sRNAs. SPORTS1.0 is precompiled to annotate sRNAs for a wide range of 68 species across bacteria, yeast, plant, and animal kingdoms, while additional species for analyses could be readily expanded upon end users' input. For demonstration, by analyzing sRNA datasets using SPORTS1.0, we reveal that distinct signatures are present in tsRNAs and rsRNAs from different mouse cell types. We also find that compared to other sRNA species, tsRNAs bear the highest mismatch rate, which is consistent with their highly modified nature. SPORTS1.0 is an open-source software and can be publically accessed at https://github.com/junchaoshi/sports1.0.

In Silico Identification of RNA Modifications from High-Throughput Sequencing Data Using HAMR

RNA molecules are often altered post-transcriptionally by the covalent modification of their nucleotides. These modifications are known to modulate the structure, function, and activity of RNAs. When reverse transcribed into cDNA during RNA sequencing library preparation, atypical (modified) ribonucleotides that affect Watson-Crick base pairing will interfere with reverse transcriptase (RT), resulting in cDNA products with mis-incorporated bases or prematurely terminated RNA products. These interactions with RT can therefore be inferred from mismatch patterns in the sequencing reads, and are distinguishable from simple base-calling errors, single-nucleotide polymorphisms (SNPs), or RNA editing sites. Here, we describe a computational protocol for the in silico identification of modified ribonucleotides from RT-based RNA-seq read-out using the High-throughput Analysis of Modified Ribonucleotides (HAMR) software. HAMR can identify these modifications transcriptome-wide with single nucleotide resolution, and also differentiate between different types of modifications to predict modification identity. Researchers can use HAMR to identify and characterize RNA modifications using RNA-seq data from a variety of common RT-based sequencing protocols such as Poly(A), total RNA-seq, and small RNA-seq.

Modifications and functional genomics of human transfer RNA

Transfer RNA (tRNA) is present at tens of millions of transcripts in a human cell and is the most abundant RNA in moles among all cellular RNAs. tRNA is also the most extensively modified RNA with, on an average, 13 modifications per molecule. The primary function of tRNA as the adaptor of amino acids and the genetic code in protein synthesis is well known. tRNA modifications play multi-faceted roles in decoding and other cellular processes. The abundance, modification, and aminoacylation (charging) levels of tRNAs contribute to mRNA decoding in ways that reflect the cell type and its environment; however, how these factors work together to maximize translation efficiency remains to be understood. tRNAs also interact with many proteins not involved in translation and this may coordinate translation activity and other processes in the cell. This review focuses on the modifications and the functional genomics of human tRNA and discusses future perspectives on the explorations of human tRNA biology.

Engineering of a DNA Polymerase for Direct m6 A Sequencing

Methods for the detection of RNA modifications are of fundamental importance for advancing epitranscriptomics. N6 -methyladenosine (m6 A) is the most abundant RNA modification in mammalian mRNA and is involved in the regulation of gene expression. Current detection techniques are laborious and rely on antibody-based enrichment of m6 A-containing RNA prior to sequencing, since m6 A modifications are generally "erased" during reverse transcription (RT). To overcome the drawbacks associated with indirect detection, we aimed to generate novel DNA polymerase variants for direct m6 A sequencing. Therefore, we developed a screen to evolve an RT-active KlenTaq DNA polymerase variant that sets a mark for N6 -methylation. We identified a mutant that exhibits increased misincorporation opposite m6 A compared to unmodified A. Application of the generated DNA polymerase in next-generation sequencing allowed the identification of m6 A sites directly from the sequencing data of untreated RNA samples.

tRex: A Web Portal for Exploration of tRNA-Derived Fragments in Arabidopsis thaliana

tRNA-derived fragments (tRFs) constitute a new class of short regulatory RNAs that are a product of nascent or mature tRNA processing. tRF sequences have been identified in all domains of life; however, most published research pertains to human, yeast and some bacterial organisms. Despite growing interest in plant tRFs and accumulating evidence of their function in plant development and stress responses, no public, web-based repository dedicated to these molecules is currently available. Here, we introduce tRex (http://combio.pl/trex)-the first comprehensive data-driven online resource specifically dedicated to tRFs in the model plant Arabidopsis thaliana. The portal is based on verified Arabidopsis tRNA annotation and includes in-house-generated and publicly available small RNA sequencing experiments from various tissues, ecotypes, genotypes and stress conditions. The provided web-based tools are designed in a user-friendly manner and allow for seamless exploration of the data that are presented in the form of dynamic tables and cumulative coverage profiles. The tRex database is connected to external genomic and citation resources, which makes it a one-stop solution for Arabidopsis tRF-related research.

The RNA modification landscape in human disease

RNA modifications have been historically considered as fine-tuning chemo-structural features of infrastructural RNAs, such as rRNAs, tRNAs, and snoRNAs. This view has changed dramatically in recent years, to a large extent as a result of systematic efforts to map and quantify various RNA modifications in a transcriptome-wide manner, revealing that RNA modifications are reversible, dynamically regulated, far more widespread than originally thought, and involved in major biological processes, including cell differentiation, sex determination, and stress responses. Here we summarize the state of knowledge and provide a catalog of RNA modifications and their links to neurological disorders, cancers, and other diseases. With the advent of direct RNA-sequencing technologies, we expect that this catalog will help prioritize those RNA modifications for transcriptome-wide maps.

Protein folding and tRNA biology

Polypeptides can fold into tertiary structures while they are synthesized by the ribosome. In addition to the amino acid sequence, protein folding is determined by several factors within the cell. Among others, the folding pathway of a nascent polypeptide can be affected by transient interactions with other proteins, ligands, or the ribosome, as well as by the translocation through membrane pores. Particularly, the translation machinery and the population of tRNA under different physiological or adaptive responses can dramatically affect protein folding. This review summarizes the scientific evidence describing the role of translation kinetics and tRNA populations on protein folding and addresses current efforts to better understand tRNA biology. It is organized into three main parts, which are focused on: (i) protein folding in the cellular context; (ii) tRNA biology and the complexity of the tRNA population; and (iii) available methods and technical challenges in the characterization of tRNA pools. In this manner, this work illustrates the ways by which functional properties of proteins may be modulated by cellular tRNA populations.

Reverse Transcription Past Products of Guanine Oxidation in RNA Leads to Insertion of A and C opposite 8-Oxo-7,8-dihydroguanine and A and G opposite 5-Guanidinohydantoin and Spiroiminodihydantoin Diastereomers

Reactive oxygen species, both endogenous and exogenous, can damage nucleobases of RNA and DNA. Among the nucleobases, guanine has the lowest redox potential, making it a major target of oxidation. Although RNA is more prone to oxidation than DNA is, oxidation of guanine in RNA has been studied to a significantly lesser extent. One of the reasons for this is that many tools that were previously developed to study oxidation of DNA cannot be used on RNA. In the study presented here, the lack of a method for seeking sites of modification in RNA where oxidation occurs is addressed. For this purpose, reverse transcription of RNA containing major products of guanine oxidation was used. Extension of a DNA primer annealed to an RNA template containing 8-oxo-7,8-dihydroguanine (OG), 5-guanidinohydantoin (Gh), or the R and S diastereomers of spiroiminodihydantoin (Sp) was studied under standing start conditions. SuperScript III reverse transcriptase is capable of bypassing these lesions in RNA inserting predominantly A opposite OG, predominantly G opposite Gh, and almost an equal mixture of A and G opposite the Sp diastereomers. These data should allow RNA sequencing of guanine oxidation products by following characteristic mutation signatures formed by the reverse transcriptase during primer elongation past G oxidation sites in the template RNA strand.

Detection of a Subset of Posttranscriptional Transfer RNA Modifications in Vivo with a Restriction Fragment Length Polymorphism-Based Method

Transfer RNAs (tRNAs) are among the most heavily modified RNA species. Posttranscriptional tRNA modifications (ptRMs) play fundamental roles in modulating tRNA structure and function and are being increasingly linked to human physiology and disease. Detection of ptRMs is often challenging, expensive, and laborious. Restriction fragment length polymorphism (RFLP) analyses study the patterns of DNA cleavage after restriction enzyme treatment and have been used for the qualitative detection of modified bases on mRNAs. It is known that some ptRMs induce specific and reproducible base "mutations" when tRNAs are reverse transcribed. For example, inosine, which derives from the deamination of adenosine, is detected as a guanosine when an inosine-containing tRNA is reverse transcribed, amplified via polymerase chain reaction (PCR), and sequenced. ptRM-dependent base changes on reverse transcription PCR amplicons generated as a consequence of the reverse transcription reaction might create or abolish endonuclease restriction sites. The suitability of RFLP for the detection and/or quantification of ptRMs has not been studied thus far. Here we show that different ptRMs can be detected at specific sites of different tRNA types by RFLP. For the examples studied, we show that this approach can reliably estimate the modification status of the sample, a feature that can be useful in the study of the regulatory role of tRNA modifications in gene expression.

RNA structure, binding, and coordination in Arabidopsis

From the moment of transcription, up through degradation, each RNA transcript is bound by an ever-changing cohort of RNA binding proteins. The binding of these proteins is regulated by both the primary RNA sequence, as well as the intramolecular RNA folding, or secondary structure, of the transcript. Thus, RNA secondary structure regulates many post-transcriptional processes. With the advent of next generation sequencing, several techniques have been developed to generate global landscapes of both RNA-protein interactions and RNA secondary structure. In this review, we describe the current state of the field detailing techniques to globally interrogate RNA secondary structure and/or RNA-protein interaction sites, as well as our current understanding of these features in the transcriptome of the model plant Arabidopsis thaliana. WIREs RNA 2017, 8:e1426. doi: 10.1002/wrna.1426 For further resources related to this article, please visit the WIREs website.

RiboMeth-seq: Profiling of 2'-O-Me in RNA

RiboMeth-seq is a sequencing-based method for mapping and quantitation of one of the most abundant RNA modifications, ribose methylation. It is based on a simple chemical principle, namely the several orders of magnitude difference in nucleophilicity of a 2'-OH and a 2'-O-Me. Thus, the method combines alkaline fragmentation and a specialized library construction protocol based on 5'-OH and 2',3' cyclic phosphate ends to prepare RNA for sequencing. The read-ends of library fragments are used for mapping with nucleotide resolution and calculation of the fraction of molecules methylated at the 2'-O-Me sites.

tRNA biology in the omics era: Stress signalling dynamics and cancer progression

Recent years have seen a burst in the number of studies investigating tRNA biology. With the transition from a gene-centred to a genome-centred perspective, tRNAs and other RNA polymerase III transcripts surfaced as active regulators of normal cell physiology and disease. Novel strategies removing some of the hurdles that prevent quantitative tRNA profiling revealed that the differential exploitation of the tRNA pool critically affects the ability of the cell to balance protein homeostasis during normal and stress conditions. Furthermore, growing evidence indicates that the adaptation of tRNA synthesis to cellular dynamics can influence translation and mRNA stability to drive carcinogenesis and other pathological disorders. This review explores the contribution given by genomics, transcriptomics and epitranscriptomics to the discovery of emerging tRNA functions, and gives insights into some of the technical challenges that still limit our understanding of the RNA polymerase III transcriptional machinery.

CoverageAnalyzer (CAn): A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

Combination of reverse transcription (RT) and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn) was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq) data, up to sophisticated modification analysis with significance-based modification candidate calling.

tRNA base methylation identification and quantification via high-throughput sequencing

Eukaryotic transfer RNAs contain on average 14 modifications. Investigations of their biological functions require the determination of the modification sites and the dynamic variations of the modification fraction. Base methylation represents a major class of tRNA modification. Although many approaches have been used to identify tRNA base methylations, including sequencing, they are generally qualitative and do not report the information on the modification fraction. Dynamic mRNA modifications have been shown to play important biological roles; yet, the extent of tRNA modification fractions has not been reported systemically. Here we take advantage of a recently developed high-throughput sequencing method (DM-tRNA-seq) to identify and quantify tRNA base methylations located at the Watson-Crick face in HEK293T cells at single base resolution. We apply information derived from both base mutations and positional stops from sequencing using a combination of demethylase treatment and cDNA synthesis by a thermophilic reverse transcriptase to compile a quantitative "Modification Index" (MI) for six base methylations in human tRNA and rRNA. MI combines the metrics for mutational and stop components from alignment of sequencing data without demethylase treatment, and the modifications are validated in the sequencing data upon demethylase treatment. We identify many new methylation sites in both human nuclear and mitochondrial-encoded tRNAs not present in the RNA modification databases. The potentially quantitative nature of the MI values obtained from sequencing is validated by primer extension of several tRNAs. Our approach should be widely applicable to identify tRNA methylation sites, analyze comparative fractional modifications, and evaluate the modification dynamics between different samples.

Next-generation sequencing technologies for detection of modified nucleotides in RNAs

Our ability to map and quantify RNA modifications at a genome-wide scale have revolutionized our understanding of the pervasiveness and dynamic regulation of diverse RNA modifications. Recent efforts in the field have demonstrated the presence of modified residues in almost any type of cellular RNA. Next-generation sequencing (NGS) technologies are the primary choice for transcriptome-wide RNA modification mapping. Here we provide an overview of approaches for RNA modification detection based on their RT-signature, specific chemicals, antibody-dependent (Ab) enrichment, or combinations thereof. We further discuss sources of artifacts in genome-wide modification maps, and experimental and computational considerations to overcome them. The future in this field is tightly linked to the development of new specific chemical reagents, highly specific Ab against RNA modifications and use of single-molecule RNA sequencing techniques.

Deciphering the epitranscriptome: A green perspective

The advent of high-throughput sequencing technologies coupled with new detection methods of RNA modifications has enabled investigation of a new layer of gene regulation - the epitranscriptome. With over 100 known RNA modifications, understanding the repertoire of RNA modifications is a huge undertaking. This review summarizes what is known about RNA modifications with an emphasis on discoveries in plants. RNA ribose modifications, base methylations and pseudouridylation are required for normal development in Arabidopsis, as mutations in the enzymes modifying them have diverse effects on plant development and stress responses. These modifications can regulate RNA structure, turnover and translation. Transfer RNA and ribosomal RNA modifications have been mapped extensively and their functions investigated in many organisms, including plants. Recent work exploring the locations, functions and targeting of N⁶ -methyladenosine (m⁶ A), 5-methylcytosine (m⁵ C), pseudouridine (Ψ), and additional modifications in mRNAs and ncRNAs are highlighted, as well as those previously known on tRNAs and rRNAs. Many questions remain as to the exact mechanisms of targeting and functions of specific modified sites and whether these modifications have distinct functions in the different classes of RNAs.

Gld2-catalyzed 3' monoadenylation of miRNAs in the hippocampus has no detectable effect on their stability or on animal behavior

Gld2, a noncanonical cytoplasmic poly(A) polymerase, interacts with the RNA binding protein CPEB1 to mediate polyadenylation-induced translation in dendrites of cultured hippocampal neurons. Depletion of Gld2 from the hippocampus leads to a deficit in long-term potentiation evoked by theta burst stimulation. At least in mouse liver and human primary fibroblasts, Gld2 also 3' monoadenylates and thereby stabilizes specific miRNAs, which enhance mRNA translational silencing and eventual destruction. These results suggest that Gld2 would be likely to monoadenylate and stabilize miRNAs in the hippocampus, which would produce measurable changes in animal behavior. We now report that using Gld2 knockout mice, there are detectable alterations in specific miRNA monoadenylation in the hippocampus when compared to wild type, but that these modifications produce no detectable effect on miRNA stability. Moreover, we surprisingly find no overt change in animal behavior when comparing Gld2 knockout to wild-type mice. These data indicate that miRNA monoadenylation-mediated stability is cell type-specific and that monoadenylation has no measurable effect on higher cognitive function.

Noncoding RNA: Current Deep Sequencing Data Analysis Approaches and Challenges

One of the most significant biological discoveries of the last decade is represented by the reality that the vast majority of the transcribed genomic output comprises diverse classes of noncoding RNAs (ncRNAs) that may play key roles and/or be affected by many biochemical cellular processes (i.e., RNA editing), with implications in human health and disease. With 90% of the human genome being transcribed and novel classes of ncRNA emerging (tRNA-derived small RNAs and circular RNAs among others), the great majority of the human transcriptome suggests that many important ncRNA functions/processes are yet to be discovered. An approach to filling such vast void of knowledge has been recently provided by the increasing application of next-generation sequencing (NGS), offering the unprecedented opportunity to obtain a more accurate profiling with higher resolution, increased throughput, sequencing depth, and low experimental complexity, concurrently posing an increasing challenge in terms of efficiency, accuracy, and usability of data analysis software. This review provides an overview of ncRNAs, NGS technology, and the most recent/popular computational approaches and the challenges they attempt to solve, which are essential to a more sensitive and comprehensive ncRNA annotation capable of furthering our understanding of this still vastly uncharted genomic territory.

Diastereoselectivity of 5-Methyluridine Osmylation Is Inverted inside an RNA Chain

In this study, we investigated the reaction of the osmium tetroxide-bipyridine complex with pyrimidines in RNA. This reagent, which reacts with the diastereotopic 5-6 double bond, thus leading to the formation of two diastereomers, was used in the past to label thymidine and 5-methylcytosine in DNA. In light of the growing interest in post-transcriptional RNA modifications, we addressed the question of whether this reagent could be used for labeling of the naturally occurring RNA modifications 5-methylcytosine and 5-methyluridine. On nucleoside level, 5-methylcytosine and 5-methyluridine revealed a 5- and 12-fold preference, respectively, over their nonmethylated equivalents. Performing the reaction on an RNA level, we could show that the steric environment of a pentanucleotide has a major detrimental impact on the reaction rate of osmylation. Interestingly, this drop in reactivity was due to a dramatic change in diastereoselectivity, which in turn resulted from impediment of the preferred attack via the si side. Thus, while on the nucleoside level, the absolute configuration of the major product of osmylation of 5-methyluridine was (5R,6S)-5-methyluridine glycol-dioxoosmium-bipyridine, reaction with an RNA pentanucleotide afforded the corresponding (5S,6R)-diastereomer as the major product. The change in diastereoselectivity lead to an almost complete loss of selectivity toward 5-methylcytosine in a pentanucleotide context, while 5-methyluridine remained about 8 times more reactive than the canonical pyrimidines. On the basis of these findings, we evaluate the usefulness of osmium tetroxide-bipyridine as a potential label for the 5-methyluridine modification in transcriptome-wide studies.

Evolving specificity of tRNA 3-methyl-cytidine-32 (m3C32) modification: a subset of tRNAsSer requires N6-isopentenylation of A37

Post-transcriptional modifications of anticodon loop (ACL) nucleotides impact tRNA structure, affinity for the ribosome, and decoding activity, and these activities can be fine-tuned by interactions between nucleobases on either side of the anticodon. A recently discovered ACL modification circuit involving positions 32, 34, and 37 is disrupted by a human disease-associated mutation to the gene encoding a tRNA modification enzyme. We used tRNA-HydroSeq (-HySeq) to examine (3)methyl-cytidine-32 (m(3)C32), which is found in yeast only in the ACLs of tRNAs(Ser) and tRNAs(Thr) In contrast to that reported for Saccharomyces cerevisiae in which all m(3)C32 depends on a single gene, TRM140, the m(3)C32 of tRNAs(Ser) and tRNAs(Thr) of the fission yeast S. pombe, are each dependent on one of two related genes, trm140(+) and trm141(+), homologs of which are found in higher eukaryotes. Interestingly, mammals and other vertebrates contain a third homolog and also contain m(3)C at new sites, positions 32 on tRNAs(Arg) and C47:3 in the variable arm of tRNAs(Ser) More significantly, by examining S. pombe mutants deficient for other modifications, we found that m(3)C32 on the three tRNAs(Ser) that contain anticodon base A36, requires N(6)-isopentenyl modification of A37 (i(6)A37). This new C32-A37 ACL circuitry indicates that i(6)A37 is a pre- or corequisite for m(3)C32 on these tRNAs. Examination of the tRNA database suggests that such circuitry may be more expansive than observed here. The results emphasize two contemporary themes, that tRNA modifications are interconnected, and that some specific modifications on tRNAs of the same anticodon identity are species-specific.

High-throughput sequencing for 1-methyladenosine (m(1)A) mapping in RNA

Detection and mapping of modified nucleotides in RNAs is a difficult and laborious task. Several physico-chemical approaches based on differential properties of modified nucleotides can be used, however, most of these methods do not allow high-throughput analysis. Here we describe in details a method for mapping of rather common 1-methyladenosine (m(1)A) residues using high-throughput next generation sequencing (NGS). Since m(1)A residues block primer extension during reverse transcription (RT), the accumulation of abortive products as well as the nucleotide misincorporation can be detected in the sequencing data. The described library preparation protocol allows to capture both types of cDNA products essential for further bioinformatic analysis. We demonstrate that m(1)A residues produce characteristic arrest and mismatch rates and combination of both can be used for their detection as well as for discrimination of m(1)A from other modified A residues present in RNAs.