Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

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

PROVIDER: PRJNA639839 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR12026322.fastq.gz	Fastqsanger.gz
	SRR12026323.fastq.gz	Fastqsanger.gz
	SRR12026324.fastq.gz	Fastqsanger.gz
	SRR12026325.fastq.gz	Fastqsanger.gz
	SRR12026326.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 29

Similar Datasets

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

2021-02-12 | GSE152621 | GEO

tRNA m1A modification regulate hematopoietic stem cell maintenance via mTORC1 signaling [mim-tRNAseq]

Project description:High-resolution quantitative profiling of tRNA abundance and modification status in hematopoietic cells upon Trmt6 deletion by mim-tRNAseq

2024-06-03 | GSE252912 | GEO

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

Project description: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.

| S-EPMC8062790 | biostudies-literature

ALL-tRNAseq enables robust tRNA profiling in tissue samples

Project description:Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. It remains however unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation, for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription, to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity, but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

2023-02-24 | GSE186736 | GEO

tRNA m1A modification regulate hematopoietic stem cell maintenance via mTORC1 signaling [mim-tRNAseq]

Project description:tRNA m1A modification regulate hematopoietic stem cell maintenance via mTORC1 signaling [mim-tRNAseq]

| PRJNA1063221 | ENA

Comparison of mitochondrial tRNA abundance profiling in wild type and mutant mitochondrial RNA polymerase overexpression flies.

Project description:To investigate differential mitochondrial tRNA gene expression in wild type (WT) and mutant (E423P) mitochondrial RNA polymerase (POLRMT) overexpression flies, we performed Drsophila mitochondrial tRNA-seq according to the Hydro-tRNAseq method. tRNA-seq reads were subjected to 3' - adapter filtering , 3' - adapter trimming and quality control. The tRNAs expression levels were measured by tag count. For each tRNA sequence-based profile, the mapped reads number used to estimate the expression level of each tRNA. The tRNAs expression profiling was calculated based on uniquely mapped reads and including mapped reads, respectively. We found no difference in the relative abundance of mitochondrial individual tRNAs between WT and E423P overexpression flies.

2021-01-06 | GSE164324 | GEO

tRNA quantification of five human cell lines by hydro-tRNAseq and small RNA-seq

Project description:We analyze whether tRNA quantifications based on small RNA-seq data are informative enough to distinguish between different human cell lines covering multiple tissue types. We therefore apply both small RNA-seq and Hydro-tRNAseq to HEK293 (kidney), HCT116 (colon), HeLa (cervix), MDA-MB-231 (breast), and BJ fibroblasts. First, the correlations between the two methods of identical samples and computational mapping pipeline range between 0.93 and 0.96 for all cell lines. tRNA quantifications from both protocols are compared and significantly higher Spearman correlations are obtained within matching samples versus mismatching cell lines. In consequence, we demonstrate that small RNA-seq quantifications of sample-specific tRNA profiles show a good agreement with conventional tRNA-seq.

2020-02-28 | GSE137834 | GEO

ALL-tRNAseq enables robust tRNA profiling in tissue samples

Project description:ALL-tRNAseq enables robust tRNA profiling in tissue samples

| PRJNA775872 | ENA

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

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

TRMT1L-catalyzed m22G27 on tyrosine tRNA is required for efficient mRNA translation and cell survival under oxidative stress. [Nano-tRNAseq]

Project description:Mapping of the epitranscriptome has revealed the chemical diversity of RNA modifications and their functional importance in regulating gene expression. Transfer RNAs (tRNAs) are one of the most modified cellular RNAs, containing on average 10-13 modifications per molecule. These modifications have been shown to be critical for several aspects of tRNA functions, such as decoding, folding, and stability. Here we report that the human RNA methyltransferase TRMT1L associates with components of the Rix1 ribosome biogenesis complex and co-sediments with pre-60S ribosomes. Using eCLIP-Seq, we show that TRMT1L binds to a subset of tRNAs and to the 28S rRNA. Additionally, we demonstrate that TRMT1L is responsible for catalyzing N2, N2-dimethylguanosine (m22G) solely at position 27 of tRNA-Tyr-GUA by Nano-tRNAseq and RNA LC-MS. Surprisingly, TRMT1L depletion also impaired the deposition of acp3U and dihydrouridine on tRNA-Tyr-GUA, Cys-GCA, and Ala-CGC. TRMT1L knockout cells have a marked decrease in tRNA-Tyr-GUA levels, coinciding with a reduction in global translation rates and hypersensitivity of oxidative stress. Our results establish TRMT1L as the elusive methyltransferase catalyzing the m22G27 modification on tRNA Tyr, resolving a long-standing gap of knowledge and highlighting its potential role in a tRNA modification circuit crucial for translation regulation and stress response.

2024-05-08 | GSE266588 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data