Accurate mapping of tRNA reads

Targeting tRNA methyltransferases: from molecular mechanisms to drug discovery

Transfer RNA methyltransferases (tRNA MTases) catalyze site-specific methylation on tRNAs, a critical process that ensures the stability and functionality of tRNA molecules, thereby maintaining cellular homeostasis of tRNA methylation. Recent studies have illuminated the structural diversity, specific substrate recognition, and conserved catalytic mechanisms of tRNA MTases, revealing how their dysregulation contributes to various diseases, including cancers and neurodevelopmental disorders. This review integrates these advances, exploring the challenges of achieving precise substrate recognition and modification in the context of complex and specific tRNA modification landscape, while emphasizing the crucial role of tRNA MTases in disease pathogenesis. The identification of small-molecule inhibitors targeting specific tRNA MTases marks a promising step toward the development of novel therapies. With continued research into the broader biological functions and regulatory mechanisms of tRNA MTases, these insights hold great potential to drive clinical advancements and therapeutic innovations.

Influenza virus antagonizes self sensing by RIG-I to enhance viral replication

Innate immune sensors must finely distinguish pathogens from the host to mount a response only during infection. RIG-I is cytoplasmic sensor that surveils for foreign RNAs. When activated, RIG-I triggers a broad antiviral response that is a major regulator of RNA virus infection. Here were show that RIG-I not only bound viral RNAs, but was activated by host RNAs to amplify the antiviral state. These were primarily non-coding RNAs transcribed by RNA polymerase III. They were benign under normal conditions but became immunogenic during influenza virus infection where they signaled via RIG-I to suppress viral replication. This same class of RNAs was bound by influenza virus nucleoprotein (NP), which normally functions to encapsidate the viral genome. NP interacted with RIG-I and antagonized sensing of self RNAs to counter innate immune responses. Overall, these results demonstrate that self sensing is strategically deployed by the cell to amplify the antiviral response and reveal a newly identified viral countermeasure that disrupts RIG-I activation by host RNAs.

tRNA expression and modification landscapes, and their dynamics during zebrafish embryo development

tRNA genes exist in multiple copies in the genome of all organisms across the three domains of life. Besides the sequence differences across tRNA copies, extensive post-transcriptional modification adds a further layer to tRNA diversification. Whilst the crucial role of tRNAs as adapter molecules in protein translation is well established, whether all tRNAs are actually expressed, and whether the differences across isodecoders play any regulatory role is only recently being uncovered. Here we built upon recent developments in the use of NGS-based methods for RNA modification detection and developed tRAM-seq, an experimental protocol and in silico analysis pipeline to investigate tRNA expression and modification. Using tRAM-seq, we analysed the full ensemble of nucleo-cytoplasmic and mitochondrial tRNAs during embryonic development of the model vertebrate zebrafish. We show that the repertoire of tRNAs changes during development, with an apparent major switch in tRNA isodecoder expression and modification profile taking place around the start of gastrulation. Taken together, our findings suggest the existence of a general reprogramming of the expressed tRNA pool, possibly gearing the translational machinery for distinct stages of the delicate and crucial process of embryo development.

Temperature-Dependent tRNA Modifications in Bacillales

Transfer RNA (tRNA) modifications are essential for the temperature adaptation of thermophilic and psychrophilic organisms as they control the rigidity and flexibility of transcripts. To further understand how specific tRNA modifications are adjusted to maintain functionality in response to temperature fluctuations, we investigated whether tRNA modifications represent an adaptation of bacteria to different growth temperatures (minimal, optimal, and maximal), focusing on closely related psychrophilic (P. halocryophilus and E. sibiricum), mesophilic (B. subtilis), and thermophilic (G. stearothermophilus) Bacillales. Utilizing an RNA sequencing approach combined with chemical pre-treatment of tRNA samples, we systematically profiled dihydrouridine (D), 4-thiouridine (s4U), 7-methyl-guanosine (m7G), and pseudouridine (Ψ) modifications at single-nucleotide resolution. Despite their close relationship, each bacterium exhibited a unique tRNA modification profile. Our findings revealed increased tRNA modifications in the thermophilic bacterium at its optimal growth temperature, particularly showing elevated levels of s4U8 and Ψ55 modifications compared to non-thermophilic bacteria, indicating a temperature-dependent regulation that may contribute to thermotolerance. Furthermore, we observed higher levels of D modifications in psychrophilic and mesophilic bacteria, indicating an adaptive strategy for cold environments by enhancing local flexibility in tRNAs. Our method demonstrated high effectiveness in identifying tRNA modifications compared to an established tool, highlighting its potential for precise tRNA profiling studies.

A robust method for measuring aminoacylation through tRNA-Seq

Current methods to quantify the fraction of aminoacylated tRNAs, also known as the tRNA charge, are limited by issues with either low throughput, precision, and/or accuracy. Here, we present an optimized charge transfer RNA sequencing (tRNA-Seq) method that combines previous developments with newly described approaches to establish a protocol for precise and accurate tRNA charge measurements. We verify that this protocol provides robust quantification of tRNA aminoacylation and we provide an end-to-end method that scales to hundreds of samples including software for data processing. Additionally, we show that this method supports measurements of relative tRNA expression levels and can be used to infer tRNA modifications through reverse transcription misincorporations, thereby supporting multipurpose applications in tRNA biology.

A robust method for measuring aminoacylation through tRNA-Seq

Current methods to quantify the fraction of aminoacylated tRNAs, also known as the tRNA charge, are limited by issues with either low throughput, precision, and/or accuracy. Here, we present an optimized charge tRNA-Seq method that combines previous developments with newly described approaches to establish a protocol for precise and accurate tRNA charge measurements. We verify that this protocol provides robust quantification of tRNA aminoacylation and we provide an end-to-end method that scales to hundreds of samples including software for data processing. Additionally, we show that this method supports measurements of relative tRNA expression levels and can be used to infer tRNA modifications through reverse transcription misincorporations, thereby supporting multipurpose applications in tRNA biology.

Global and single-nucleotide resolution detection of 7-methylguanosine in RNA

RNA modifications, including N-7-methylguanosine (m7G), are pivotal in governing RNA stability and gene expression regulation. The accurate detection of internal m7G modifications is of paramount significance, given recent associations between altered m7G deposition and elevated expression of the methyltransferase METTL1 in various human cancers. The development of robust m7G detection techniques has posed a significant challenge in the field of epitranscriptomics. In this study, we introduce two methodologies for the global and accurate identification of m7G modifications in human RNA. We introduce borohydride reduction sequencing (Bo-Seq), which provides base resolution mapping of m7G modifications. Bo-Seq achieves exceptional performance through the optimization of RNA depurination and scission, involving the strategic use of high concentrations of NaBH4, neutral pH and the addition of 7-methylguanosine monophosphate (m7GMP) during the reducing reaction. Notably, compared to NaBH4-based methods, Bo-Seq enhances the m7G detection performance, and simplifies the detection process, eliminating the necessity for intricate chemical steps and reducing the protocol duration. In addition, we present an antibody-based approach, which enables the assessment of m7G relative levels across RNA molecules and biological samples, however it should be used with caution due to limitations associated with variations in antibody quality between batches. In summary, our novel approaches address the pressing need for reliable and accessible methods to detect RNA m7G methylation in human cells. These advancements hold the potential to catalyse future investigations in the critical field of epitranscriptomics, shedding light on the complex regulatory roles of m7G in gene expression and its implications in cancer biology.

Multi-omic profiling reveals an RNA processing rheostat that predisposes to prostate cancer

Prostate cancer is the most commonly diagnosed malignancy and the third leading cause of cancer deaths. GWAS have identified variants associated with prostate cancer susceptibility; however, mechanistic and functional validation of these mutations is lacking. We used CRISPR-Cas9 genome editing to introduce a missense variant identified in the ELAC2 gene, which encodes a dually localised nuclear and mitochondrial RNA processing enzyme, into the mouse Elac2 gene as well as to generate a prostate-specific knockout of Elac2. These mutations caused enlargement and inflammation of the prostate and nodule formation. The Elac2 variant or knockout mice on the background of the transgenic adenocarcinoma of the mouse prostate (TRAMP) model show that Elac2 mutation with a secondary genetic insult exacerbated the onset and progression of prostate cancer. Multiomic profiling revealed defects in energy metabolism that activated proinflammatory and tumorigenic pathways as a consequence of impaired noncoding RNA processing and reduced protein synthesis. Our physiologically relevant models show that the ELAC2 variant is a predisposing factor for prostate cancer and identify changes that underlie the pathogenesis of this cancer.

tncRNA Toolkit: A pipeline for convenient identification of RNA (tRNA)-derived non-coding RNAs

Insights into the eukaryotic gene regulation networks have improved due to the advent of diverse classes of non-coding RNAs. The transfer RNA (tRNA)-derived non-coding RNAs or tncRNAs is a novel class of non-coding RNAs, shown to regulate gene expression at transcription and translation levels. Here, we present a pipeline 'tncRNA Toolkit' for accurately identifying tncRNAs using small RNA sequencing (sRNA-seq) data. Previously, we identified tncRNA in six major angiosperms by utilizing our pipeline and highlighted the significant points regarding their generation and functions. The 'tncRNA Toolkit' is available at the URL: http://www.nipgr.ac.in/tncRNA. The scripts are written in bash and Python3 programming languages. The program can be efficiently run as a standalone command-line tool and installed in any Linux-based Operating System (OS). The user can run this program by providing the input of sRNA-seq data and genome file.The various features of the 'tncRNA Toolkit' are as follows:•Major tncRNA classes identified by this tool include tRF-5, tRF-3, tRF-1, 5'tRH, 3'tRH, and leader tRF. Also, it categorizes miscellaneous tncRNAs as other tRF.•It provides the following information for each identified tncRNA viz. tncRNA class, raw and normalized read count (RPM), read length, progenitor tRNA information (amino acid, anticodon, locus, strand), tncRNA sequence, and tRNA modification sites.•We hope to facilitate quick and reliable tncRNA identification, which will boost the exploration of this novel class of non-coding RNAs and their relevance in the living world, including plants.

tRNA dysregulation and disease

tRNAs are key adaptor molecules that decipher the genetic code during translation of mRNAs in protein synthesis. In contrast to the traditional view of tRNAs as ubiquitously expressed housekeeping molecules, awareness is now growing that tRNA-encoding genes display tissue-specific and cell type-specific patterns of expression, and that tRNA gene expression and function are both dynamically regulated by post-transcriptional RNA modifications. Moreover, dysregulation of tRNAs, mediated by alterations in either their abundance or function, can have deleterious consequences that contribute to several distinct human diseases, including neurological disorders and cancer. Accumulating evidence shows that reprogramming of mRNA translation through altered tRNA activity can drive pathological processes in a codon-dependent manner. This Review considers the emerging evidence in support of the precise control of functional tRNA levels as an important regulatory mechanism that coordinates mRNA translation and protein expression in physiological cell homeostasis, and highlights key examples of human diseases that are linked directly to tRNA dysregulation.

tRNAstudio: facilitating the study of human mature tRNAs from deep sequencing datasets

SUMMARY

High-throughput sequencing of transfer RNAs (tRNA-Seq) is a powerful approach to characterize the cellular tRNA pool. Currently, however, analyzing tRNA-Seq datasets requires strong bioinformatics and programming skills. tRNAstudio facilitates the analysis of tRNA-Seq datasets and extracts information on tRNA gene expression, post-transcriptional tRNA modification levels, and tRNA processing steps. Users need only running a few simple bash commands to activate a graphical user interface that allows the easy processing of tRNA-Seq datasets in local mode. Output files include extensive graphical representations and associated numerical tables, and an interactive html summary report to help interpret the data. We have validated tRNAstudio using datasets generated by different experimental methods and derived from human cell lines and tissues that present distinct patterns of tRNA expression, modification and processing.

AVAILABILITY AND IMPLEMENTATION

Freely available at https://github.com/GeneTranslationLab-IRB/tRNAstudio under an open-source GNU GPL v3.0 license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

tReasure: R-based GUI package analyzing tRNA expression profiles from small RNA sequencing data

BACKGROUND

Recent deep sequencing technologies have proven to be valuable resources to gain insights into the expression profiles of diverse tRNAs. However, despite these technologies, the association of tRNAs with diverse diseases has not been explored in depth because analytical tools are lacking.

RESULTS

We developed a user-friendly tool, tRNA Expression Analysis Software Utilizing R for Easy use (tReasure), to analyze differentially expressed tRNAs (DEtRNAs) from deep sequencing data of small RNAs using R packages. tReasure can quantify individual mature tRNAs, isodecoders, and isoacceptors. By adopting stringent mapping strategies, tReasure supports the precise measurement of mature tRNA read counts. The whole analysis workflow for determining DEtRNAs (uploading FASTQ files, removing adapter sequences and poor-quality reads, mapping and quantifying tRNAs, filtering out low count tRNAs, determining DEtRNAs, and visualizing statistical analysis) can be performed with the tReasure package.

CONCLUSIONS

tReasure is an open-source software available for download at https://treasure.pmrc.re.kr and will be indispensable for users who have little experience with command-line software to explore the biological implication of tRNA expression.

PtncRNAdb: plant transfer RNA-derived non-coding RNAs (tncRNAs) database

Specific endonucleolytic cleavage of tRNA molecules leads to the biogenesis of heterogeneously sized fragments called tRNA-derived non-coding RNAs (tncRNAs). The role of tncRNAs is well studied in human processes, and diseases including different types of cancers and other ailments. They are also generated under stress conditions in plants. Considering the potential role of tncRNAs in the plant system, we have developed a user-friendly, open-access web resource, PtncRNAdb (https://nipgr.ac.in/PtncRNAdb). PtncRNAdb consists of 4,809,503 tncRNA entries identified from ~ 2500 single-end small RNA-seq libraries from six plants, viz., Arabidopsis thaliana, Cicer arietinum, Zea mays, Oryza sativa, Medicago truncatula, and Solanum lycopersicum. It is provided with assorted options to search, browse, visualize, interpret, and download tncRNAs data. Users can perform query search using 'BLASTN' against PtncRNAdb entries. Highcharts have been included for better statistical PtncRNAdb data readability to the users. Additionally, PtncRNAdb includes 'DE tncRNAs' module for differentially expressed tncRNAs under various conditions. Their secondary structure, putative targets, interactive networks of target enrichment, and related publications are also incorporated for further interpretation of their biological functions. PtncRNAdb is an efficient, user-friendly, and exhaustive database, which will aid the ongoing research in plant tncRNAs as well as help in deciphering their role in gene regulation. We hope that it provides a promising platform for researchers to facilitate the understanding of tncRNAs, and their involvement in numerous pathways related to plant development and stress tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03174-7.

DBtRend: A Web-Server of tRNA Expression Profiles from Small RNA Sequencing Data in Humans

Transfer RNA (tRNA), a key component of the translation machinery, plays critical roles in stress conditions and various diseases. While knowledge regarding the importance of tRNA function is increasing, its biological roles are still not well understood. There is currently no comprehensive database or web server providing the expression landscape of tRNAs across a variety of human tissues and diseases. Here, we constructed a user-friendly and interactive database, DBtRend, which provides a profile of mature tRNA expression across various biological conditions by reanalyzing the small RNA or microRNA sequencing data from the Cancer Genome Atlas (TCGA) and NCBI's Gene Expression Omnibus (GEO) in humans. Users can explore not only the expression values of mature individual tRNAs in the human genome, but also those of isodecoders and isoacceptors based on our specific pipelines. DBtRend provides the expressed patterns of tRNAs, the differentially expressed tRNAs in different biological conditions, and the information of samples or patients, tissue types, and molecular subtype of cancers. The database is expected to help researchers interested in functional discoveries of tRNAs.

Transfer RNA-derived non-coding RNAs (tncRNAs): Hidden regulation of plants' transcriptional regulatory circuits

The emergence of distinct classes of non-coding RNAs has led to better insights into the eukaryotic gene regulatory networks. Amongst them, the existence of transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs) demands exploration in the plant kingdom. We have designed a methodology to uncover the entire perspective of tncRNAome in plants. Using this pipeline, we have identified diverse tncRNAs with a size ranging from 14 to 50 nucleotides (nt) by utilizing 2448 small RNA-seq samples from six angiosperms, and studied their various features, including length, codon-usage, cleavage pattern, and modified tRNA nucleosides. Codon-dependent generation of tncRNAs suggests that the tRNA cleavage is highly specific rather than random tRNA degradation. The nucleotide composition analysis of tncRNA cleavage positions indicates that they are generated through precise endoribonucleolytic cleavage machinery. Certain nucleoside modifications detected on tncRNAs were found to be conserved across the plants, and hence may influence tRNA cleavage, as well as tncRNA functions. Pathway enrichment analysis revealed that common tncRNA targets are majorly enriched during metabolic and developmental processes. Further distinct tissue-specific tncRNA clusters highlight their role in plant development. Significant number of tncRNAs differentially expressed under abiotic and biotic stresses highlights their potential role in stress resistance. In summary, this study has developed a platform that will help in the understanding of tncRNAs and their involvement in growth, development, and response to various stresses. The workflow, software package, and results are freely available at http://nipgr.ac.in/tncRNA.

tsRNAsearch: A pipeline for the identification of tRNA and ncRNA fragments from small RNA-sequencing data

MOTIVATION

tRNAs were originally considered uni-functional RNA molecules involved in the delivery of amino acids to growing peptide chains on the ribosome. More recently, the liberation of tRNA fragments from tRNAs via specific enzyme cleavage has been characterized. Detection of tRNA fragments in sequencing data is difficult due to tRNA sequence redundancy and the short length of both tRNAs and their fragments.

RESULTS

Here we introduce tsRNAsearch, a Nextflow pipeline for the identification of differentially abundant tRNA fragments and other non-coding RNAs from small RNA-sequencing data. tsRNAsearch is intended for use when comparing two groups of datasets, such as control and treatment groups. tsRNAsearch comparatively searches for tRNAs and ncRNAs with irregular read distribution profiles (a proxy for RNA cleavage) using a combined score made up of four novel methods and a differential expression analysis, and reports the top ranked results in simple PDF and TEXT files. In this study, we used publicly available small RNA-seq data to replicate the identification of tsRNAs from chronic hepatitis-infected liver tissue data. In addition, we applied tsRNAsearch to pancreatic ductal adenocarcinoma (PDAC) and matched healthy pancreatic tissue small RNA-sequencing data. Our results support the identification of miR135b from the original study as a potential biomarker of PDAC and identify other potentially stronger miRNA biomarkers of PDAC.

AVAILABILITY

https://github.com/GiantSpaceRobot/tsRNAsearch.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Changes of the tRNA Modification Pattern during the Development of Dictyostelium discoideum

Dictyostelium discoideum is a social amoeba, which on starvation develops from a single-cell state to a multicellular fruiting body. This developmental process is accompanied by massive changes in gene expression, which also affect non-coding RNAs. Here, we investigate how tRNAs as key regulators of the translation process are affected by this transition. To this end, we used LOTTE-seq to sequence the tRNA pool of D. discoideum at different developmental time points and analyzed both tRNA composition and tRNA modification patterns. We developed a workflow for the specific detection of modifications from reverse transcriptase signatures in chemically untreated RNA-seq data at single-nucleotide resolution. It avoids the comparison of treated and untreated RNA-seq data using reverse transcription arrest patterns at nucleotides in the neighborhood of a putative modification site as internal control. We find that nucleotide modification sites in D. discoideum tRNAs largely conform to the modification patterns observed throughout the eukaroytes. However, there are also previously undescribed modification sites. We observe substantial dynamic changes of both expression levels and modification patterns of certain tRNA types during fruiting body development. Beyond the specific application to D. discoideum our results demonstrate that the developmental variability of tRNA expression and modification can be traced efficiently with LOTTE-seq.

Translational adaptation of human viruses to the tissues they infect

Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of 502 human-infecting viruses and determine that tropism explains changes in codon usage. Using the tRNA abundances across 23 human tissues from The Cancer Genome Atlas (TCGA), we build an in silico model of translational efficiency that validates the correspondence of the viral codon usage with the translational machinery of their tropism. For instance, we detect that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is specifically adapted to the upper respiratory tract and alveoli. Furthermore, this correspondence is specifically defined in early viral proteins. The observed tissue-specific translational efficiency could be useful for the development of antiviral therapies and vaccines.

The expanding world of tRNA modifications and their disease relevance

Transfer RNA (tRNA) is an adapter molecule that links a specific codon in mRNA with its corresponding amino acid during protein synthesis. tRNAs are enzymatically modified post-transcriptionally. A wide variety of tRNA modifications are found in the tRNA anticodon, which are crucial for precise codon recognition and reading frame maintenance, thereby ensuring accurate and efficient protein synthesis. In addition, tRNA-body regions are also frequently modified and thus stabilized in the cell. Over the past two decades, 16 novel tRNA modifications were discovered in various organisms, and the chemical space of tRNA modification continues to expand. Recent studies have revealed that tRNA modifications can be dynamically altered in response to levels of cellular metabolites and environmental stresses. Importantly, we now understand that deficiencies in tRNA modification can have pathological consequences, which are termed 'RNA modopathies'. Dysregulation of tRNA modification is involved in mitochondrial diseases, neurological disorders and cancer.

Small non-coding RNAs in human cancer: function, clinical utility, and characterization

Small non-coding RNAs (sncRNAs) play critical roles in multiple regulatory processes, including transcription, post-transcription, and translation. Emerging evidence reveals the critical roles of sncRNAs in cancer development and their potential role as biomarkers and/or therapeutic targets. In this paper, we review recent research on four sncRNA species with functional significance in cancer: small nucleolar RNAs, transfer RNA, small nuclear RNAs, and piwi-interacting RNAs. We introduce their functional roles in tumorigenesis and discuss the potential utility of sncRNAs as prognostic and diagnostic biomarkers and therapeutic targets. We further summarize approaches to characterize sncRNAs in a high-throughput manner, including the specific library construction and computational framework. Our review provides a perspective of the functions, clinical utility, and characterization of sncRNAs in cancer.

High-resolution quantitative profiling of tRNA abundance and modification status in eukaryotes by mim-tRNAseq

Measurements of cellular tRNA abundance are hampered by pervasive blocks to cDNA synthesis at modified nucleosides and the extensive similarity among tRNA genes. We overcome these limitations with modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which combines a workflow for full-length cDNA library construction from endogenously modified tRNA with a comprehensive and user-friendly computational analysis toolkit. Our method accurately captures tRNA abundance and modification status in yeast, fly, and human cells and is applicable to any organism with a known genome. We applied mim-tRNAseq to discover a dramatic heterogeneity of tRNA isodecoder pools among diverse human cell lines and a surprising interdependence of modifications at distinct sites within the same tRNA transcript.

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mim-tRNAseq overcomes experimental and computational hurdles to tRNA quantitation

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mim-tRNAseq includes a comprehensive computational toolkit for tRNA read analysis

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tRNA abundance, aminoacylation, and modification status quantified in one reaction

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mim-tRNAseq reveals an interdependence of modifications at distinct tRNA positions

Non-Redundant tRNA Reference Sequences for Deep Sequencing Analysis of tRNA Abundance and Epitranscriptomic RNA Modifications

Analysis of RNA by deep-sequencing approaches has found widespread application in modern biology. In addition to measurements of RNA abundance under various physiological conditions, such techniques are now widely used for mapping and quantification of RNA modifications. Transfer RNA (tRNA) molecules are among the frequent targets of such investigation, since they contain multiple modified residues. However, the major challenge in tRNA examination is related to a large number of duplicated and point-mutated genes encoding those RNA molecules. Moreover, the existence of multiple isoacceptors/isodecoders complicates both the analysis and read mapping. Existing databases for tRNA sequencing provide near exhaustive listings of tRNA genes, but the use of such highly redundant reference sequences in RNA-seq analyses leads to a large number of ambiguously mapped sequencing reads. Here we describe a relatively simple computational strategy for semi-automatic collapsing of highly redundant tRNA datasets into a non-redundant collection of reference tRNA sequences. The relevance of the approach was validated by analysis of experimentally obtained tRNA-sequencing datasets for different prokaryotic and eukaryotic model organisms. The data demonstrate that non-redundant tRNA reference sequences allow improving unambiguous mapping of deep sequencing data.

Functional characterization of the human tRNA methyltransferases TRMT10A and TRMT10B

The TRM10 family of methyltransferases is responsible for the N¹-methylation of purines at position 9 of tRNAs in Archaea and Eukarya. The human genome encodes three TRM10-type enzymes, of which only the mitochondrial TRMT10C was previously characterized in detail, whereas the functional significance of the two presumably nuclear enzymes TRMT10A and TRMT10B remained unexplained. Here we show that TRMT10A is m¹G9-specific and methylates a subset of nuclear-encoded tRNAs, whilst TRMT10B is the first m¹A9-specific tRNA methyltransferase found in eukaryotes and is responsible for the modification of a single nuclear-encoded tRNA. Furthermore, we show that the lack of G9 methylation causes a decrease in the steady-state levels of the initiator tRNA^iMet-CAT and an alteration in its further post-transcriptional modification. Our work finally clarifies the function of TRMT10A and TRMT10B in vivo and provides evidence that the loss of TRMT10A affects the pool of cytosolic tRNAs required for protein synthesis.

Translational efficiency across healthy and tumor tissues is proliferation-related

Different tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon-anticodon co-adaptation in humans is not completely understood, nor is its effect on tissue-specific protein levels. Here, we first validated the accuracy of small RNA-seq for tRNA quantification across five human cell lines. We then analyzed the tRNA abundance of more than 8,000 tumor samples from TCGA, together with their paired mRNA-seq and proteomics data, to determine the Supply-to-Demand Adaptation. We thereby elucidate that the dynamic adaptation of the tRNA pool is largely related to the proliferative state across tissues. The distribution of such tRNA pools over the whole cellular translatome affects the subsequent translational efficiency, which functionally determines a condition-specific expression program both in healthy and tumor states. Furthermore, the aberrant translational efficiency of some codons in cancer, exemplified by ProCCA and GlyGGT, is associated with poor patient survival. The regulation of these tRNA profiles is partly explained by the tRNA gene copy numbers and their promoter DNA methylation.

LOTTE-seq (Long hairpin oligonucleotide based tRNA high-throughput sequencing): specific selection of tRNAs with 3'-CCA end for high-throughput sequencing

Transfer RNAs belong to the most abundant type of ribonucleic acid in the cell, and detailed investigations revealed correlations between alterations in the tRNA pool composition and certain diseases like breast cancer. However, currently available methods do not sample the entire tRNA pool or lack specificity for tRNAs. A specific disadvantage of such methods is that only full-length tRNAs are analysed, while tRNA fragments or incomplete cDNAs due to RT stops at modified nucleosides are lost. Another drawback in certain approaches is that the tRNA fraction has to be isolated and separated from high molecular weight RNA, resulting in considerable labour costs and loss of material. Based on a hairpin-shaped adapter oligonucleotide selective for tRNA transcripts, we developed a highly specific protocol for efficient and comprehensive high-throughput analysis of tRNAs that combines the benefits of existing methods and eliminates their disadvantages. Due to a 3'-TGG overhang, the adapter is specifically ligated to the tRNA 3'-CCA end. Reverse transcription prior to the ligation of a second adapter allows to include prematurely terminated cDNA products, increasing the number of tRNA reads. This strategy renders this approach a powerful and universal tool to analyse the tRNA pool of cells and organisms under different conditions in health and disease.

Maternal circulating syncytiotrophoblast-derived extracellular vesicles contain biologically active 5'-tRNA halves

The placenta releases syncytiotrophoblast-derived extracellular vesicles (STB-EV) into the maternal circulation throughout gestation. STB-EV dependent signalling is believed to contribute to the widespread maternal adaptive physiological changes seen in pregnancy. Transfer RNA (tRNA) halves have been identified in vesicles released from other human and murine organ systems, which alter gene expression in target cells. Here, we characterise tRNA-half expression in STB-EV and demonstrate biological activity of a highly abundant tRNA-half. Short RNA from ex-vivo, dual-lobe placental perfusion STB-EV was sequenced, showing that most (>95%) comprised tRNA species. Whole placental tissue contained <50% tRNA species, suggesting selective packaging and export of tRNA into STB-EV. Most tRNA within STB-EV were 5'-tRNA halves cleaved at 30-32 nucleotides. The pattern of tRNA expression differed depending on the size/origin of the STB-EV; this was confirmed by qPCR. Protein synthesis was suppressed in human fibroblasts when they were cultured with a 5'-tRNA half identified from STB-EV sequencing. This study is the first to evaluate tRNA species in STB-EV. The presence of biologically active 5'-tRNA halves, specific to a vesicular origin, suggests a novel mechanism for maternal-fetal signalling in normal pregnancy.

Enjoy the Silence: Nearly Half of Human tRNA Genes Are Silent

Transfer RNAs (tRNAs) are key components of the translation machinery. They read codons on messenger RNAs (mRNAs) and deliver the appropriate amino acid to the ribosome for protein synthesis. The human genome encodes more than 500 tRNA genes but their individual contribution to the cellular tRNA pool is unclear. In recent years, novel methods were developed to improve the quantification of tRNA gene expression, most of which rely on next-generation sequencing such as small RNA-Seq applied to tRNAs (tRNA-Seq). In a previous study, we presented a bioinformatics strategy to analyse tRNA-Seq datasets that we named 'isodecoder-specific tRNA gene contribution profiling' (Iso-tRNA-CP). Using Iso-tRNA-CP, we showed that tRNA gene expression is cell type- and tissue-specific and that this process can regulate tRNA-derived fragments abundance. An additional observation that stems from that work is that approximately half of human tRNA genes appeared silent or poorly expressed. In this commentary, I discuss this finding in light of the current literature and speculate on potential functions that transcriptionally silent tRNA genes may play. Studying silent tRNA genes may offer a unique opportunity to unravel novel mechanisms of cell regulation associated to tRNA biology.

tRNA Metabolism and Neurodevelopmental Disorders

tRNAs are short noncoding RNAs required for protein translation. The human genome includes more than 600 putative tRNA genes, many of which are considered redundant. tRNA transcripts are subject to tightly controlled, multistep maturation processes that lead to the removal of flanking sequences and the addition of nontemplated nucleotides. Furthermore, tRNAs are highly structured and posttranscriptionally modified. Together, these unique features have impeded the adoption of modern genomics and transcriptomics technologies for tRNA studies. Nevertheless, it has become apparent from human neurogenetic research that many tRNA biogenesis proteins cause brain abnormalities and other neurological disorders when mutated. The cerebral cortex, cerebellum, and peripheral nervous system show defects, impairment, and degeneration upon tRNA misregulation, suggesting that they are particularly sensitive to changes in tRNA expression or function. An integrated approach to identify tRNA species and contextually characterize tRNA function will be imperative to drive future tool development and novel therapeutic design for tRNA-associated disorders.

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.