Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing
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ABSTRACT:
PROVIDER: PRJEB55684 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| ERR10228710.fastq.gz | Fastqsanger.gz | |||
| ERR10228711.fastq.gz | Fastqsanger.gz |
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Project description:Transfer RNAs are the fundamental adapter molecules of protein synthesis and the most abundant and heterogeneous class of noncoding RNA molecules in cells. The study of tRNA repertoires remains challenging, complicated by the presence of dozens of post transcriptional modifications. Nanopore sequencing is an emerging technology with promise for both tRNA sequencing and the detection of RNA modifications; however, such studies have been limited by the throughput and accuracy of direct RNA sequencing methods. Moreover, detection of the complete set of tRNA modifications by nanopore sequencing remains challenging. Here we show that recent updates to nanopore direct RNA sequencing chemistry (RNA004) combined with our own optimizations to tRNA sequencing protocols and analysis workflows enable high throughput coverage of tRNA molecules and characterization of nanopore signals produced by 43 distinct RNA modifications. We share best practices and protocols for nanopore sequencing of tRNA and further report successful detection of low abundance mitochondrial and viral tRNAs, providing proof of concept for use of nanopore sequencing to study tRNA populations in the context of infection and organelle biology. This work provides a roadmap to guide future efforts towards de novo detection of RNA modifications across multiple organisms using nanopore sequencing.
2025-12-01 | GSE272876 | GEO
Project description:tRNAs are important regulators of protein synthesis, and dysregulation of their abundance and modifications status is involved in many human diseases, including cancer. Despite the rapid development of novel tRNA sequencing approaches, due to tRNAs stable secondary structure and abundant modification sites, human tRNA landscape has remained mostly unexplored. Here, we evaluated the new nanopore RNA004 chemistry that is combined with an upgraded Dorado RNA base-caller model for tRNA quantification and site-specific modification determination in human cancer models. We demonstrate that this technology is sensitive to changes in tRNA expression between cancer cell types and response to external stress conditions, with highly reproducible results. We also show that analysis of base-calling error rate confirms the presence of known modifications, among them is the cancer-associated tRNAPhe-Wybutosine modification by TRMT12 (TYW2) . Furthermore, utilizing the new feature of RNA004 chemistry for the detection of common modifications, we show site-specific identification of m5C and pseudouridine at their annotated positions as well as in their known tRNA isoacceptors. We also reveal unique new modification sites and pinpoint a possible limitation of this method in differentiating between m1A and m6A chemical isomers. Overall, RNA004 tRNA-seq has the potential to improve human tRNAome characterization of tRNA abundance and site-specific modifications simultaneously.
2025-12-02 | GSE291699 | GEO
Project description:Dynamic changes in tRNA modifications and abundance during T-cell activation [tRNA-seq]
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Project description:Transfer RNAs (tRNAs) play a central role in protein translation. Studying them has been difficult in part because a simple method to simultaneously quantify their abundance and chemical modifications is lacking. Here we introduce Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations that provides quantitative estimates of both tRNA abundances and modification dynamics in a single experiment. We show that default nanopore sequencing settings discard the vast majority of tRNA reads, leading to poor sequencing yields and biased representations of tRNA abundances based on their transcript length. Re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads and enables recapitulation of accurate tRNA abundances. We then apply Nano-tRNAseq to Saccharomyces cerevisiae tRNA populations, revealing crosstalks and interdependencies between different tRNA modification types within the same molecule and changes in tRNA populations in response to oxidative stress.
| S-EPMC10791586 | biostudies-literature
Project description:Dynamic changes in tRNA modifications and abundance during T-cell activation
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Project description:Transfer RNAs (tRNA) are quintessential in deciphering the genetic code; disseminating nucleic acid triplets into correct amino acid identity. While this decoding function is clear, an emerging theme is that tRNA abundance and functionality can powerfully impact protein production rate, folding, activity, and messenger RNA stability. Importantly, however, the expression pattern of tRNAs (in even simple systems) is obliquely known. Limited analysis suggests tRNA levels change during proliferation, differentiation, cancer, and neurodegeneration; possibly mediating changes in translation efficiency and mRNA stability. A major limitation for the field has been the ability to subject tRNA pools to high-throughput analysis as they are highly structured, modified, and of high sequence similarity. Here we present Quantitative Mature tRNA sequencing (QuantM-tRNA seq), an easily implemented high-throughput technique to monitor tRNA abundance and sequence variants (possibly due to RNA modifications). With QuantM-tRNA seq we provide a comprehensive analysis of the tRNA transcriptome from distinct mammalian tissues. We observe dramatic distinctions in isodecoder expression and likely RNA modifications between unique tissues with a particularly strong signature within the central nervous system. Remarkably, despite dramatic changes in tRNA isodecoder gene expression, the overall anticodon pool of each tRNA family is similar. These findings suggest that anticodon pools are buffered via an unknown mechanism to achieve uniform decoding throughout the body.
2020-08-04 | GSE141436 | GEO
Project description:The tRNA pool determines the efficiency, throughput, and accuracy of translation. Previous studies have identified dynamic changes in the tRNA supply and mRNA demand during cancerous proliferation. Yet, dynamic changes may occur also during physiologically normal proliferation, and these are less characterized. We examined the tRNA and mRNA pools of T-cells during their vigorous proliferation and differentiation upon triggering of the T cell antigen receptor. We observe a global signature of switch in demand for codon at the early proliferation phase of the response, accompanied by corresponding changes in tRNA expression levels. In the later phase, upon differentiation of the T cells, the response of the tRNA pool is relaxed back to basal level, potentially restraining excessive proliferation. Sequencing of tRNAs allowed us to also evaluate their diverse base-modifications. We found that two types of tRNA modifications, Wybutosine and ms2t6A, are reduced dramatically during T-cell activation. These modifications occur in the anti-codon loops of two tRNAs that decode “slippery codons”, that are prone to ribosomal frameshifting. Attenuation of these frameshift-protective modifications is expected to increase proteome-wide frameshifting during T-cell proliferation. Indeed, human cell lines deleted of a Wybutosine writer showed increased ribosomal frameshifting, as detected with a reporter that consists of a critical frameshifting site taken from the HIV gag-pol slippery codon motif. These results may explain HIV’s specificity to proliferating T-Cells since it requires ribosomal frameshift exactly on this codon for infection. The changes in tRNA expression and modifications uncover a new layer of translation regulation during T-cell proliferation and exposes a potential trade-off between cellular growth and translation fidelity.
2021-10-13 | GSE165537 | GEO
Project description:Comparative analysis of 43 distinct RNA modifications by nanopore tRNA sequencing
| PRJNA1139161 | ENA
Project description:A broad diversity of modifications decorate RNA molecules. Originally conceived as static components, evidence is accumulating that some RNA modifications may be dynamic, contributing to cellular responses to external signals and environmental circumstances. A major difficulty in studying these modifications, however, is the need of tailored protocols to map each modification type individually. Here, we present a new approach that uses direct RNA nanopore sequencing to identify diverse RNA modification types present in native RNA molecules. First, we show that each RNA modification type results in a distinct and characteristic base-calling ‘error’ signature, which we validate using a battery of genetic strains lacking either pseudouridine (Ѱ) or 2’-O-methylation (Nm) modifications at known sites. We then demonstrate the value of these signatures for de novo transcriptome-wide prediction of Ѱ modifications, confirming known Ѱ-modified sites in rRNAs, snRNAs and mRNAs, as well as uncovering novel Ѱ sites including a previously unreported Pus4-dependent Ѱ modification in yeast mitochondrial rRNA, which we validate using orthogonal methods. To explore the dynamics of pseudouridylation across environmental stresses, we treat the cells with oxidative, cold and heat stresses, finding that yeast ribosomal rRNA modifications do not change upon environmental exposures. By contrast, our method reveals over a dozen novel heat-sensitive Ѱ-modified sites in snRNAs and snoRNAs, in addition to recovering previously reported sites. Finally, we develop a novel software, nanoRMS, which we show can estimate per-site modification stoichiometries from individual RNA molecules by identifying the reads with altered current intensity profiles, and quantify the RNA modification stoichiometry changes between two conditions. Our work demonstrates that Ѱ RNA modifications can be predicted de novo and in a quantitative manner using native RNA nanopore sequencing.
2021-04-23 | GSE148603 | GEO
Project description:Dynamic changes in tRNA modifications and abundance during T-cell activation [ncRNA-seq]
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