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:Dynamic changes in tRNA modifications and abundance during T-cell activation [tRNA-seq]
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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.
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Project description:Dynamic changes in tRNA modifications and abundance during T-cell activation
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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.
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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.
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Project description:The human genome encodes hundreds of 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 post-transcriptional 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 non-canonical 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 non-canonical tRNA functions performed by tRFs.
2019-04-17 | GSE114904 | GEO
Project description:Dynamic changes in tRNA modifications and abundance during T-cell activation [MARS-seq]
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Project description:Dynamic changes in tRNA modifications and abundance during T-cell activation [ncRNA-seq]
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Project description:This dataset contains Xdrop followed by oxford nanopore long read sequencing performed in target tRNA gene deletion clones in HAP1 (t72) and HepG2 (t15). By applying de novo assembly based approach to Xdrop-LRS data, we identified Cas9-induced on-target genomic alteration.
2022-09-16 | E-MTAB-10652 | biostudies-arrayexpress
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.
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