Browse
Submit Data
Databases
API
Help

Dataset Information

17 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: 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.

SUBMITTER: Behrens A

PROVIDER: S-EPMC8062790 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

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 mature tRNA with a simple-to-use computational analysis toolkit. Our method accurately captures tRNA abundance and modification status in multiple eukaryotes and is applicable to any organism with a known genome.

2021-02-12 | GSE152621 | GEO

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

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

| PRJNA639839 | ENA

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 estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR).

Project description:Quantification of the relative abundance of genetic traits has broad applications for biomarker discovery, diagnostics, and assessing gene expression in biological research. Relative quantification of genes is traditionally done with the 2-ΔΔCT method using quantitative real-time polymerase chain reaction (qPCR) data, which is often limited in resolution beyond orders of magnitude difference. The latest techniques for quantification of nucleic acids employ digital PCR or microarrays which involve lengthy sample preparation and complex instrumentation. In this work, we describe a quantitative ratiometric regression PCR (qRR-PCR) method for computing relative abundance of genetic traits in a sample with high resolution from a single duplexed real-time quantitative PCR assay. Instead of comparing the individual cycle threshold (Ct) values as is done for the 2-ΔΔCT method, our qRR-PCR algorithm leverages the innate relationship of co-amplified PCR targets to measure their relative quantities using characteristic curves derived from the normalized ratios of qPCR fluorescence curves. We demonstrate the utility of this technique for discriminating the fractional abundance of mixed alleles with resolution below 5%.

| S-EPMC8627783 | biostudies-literature

Massively parallel digital high resolution melt for rapid and absolutely quantitative sequence profiling.

Project description:In clinical diagnostics and pathogen detection, profiling of complex samples for low-level genotypes represents a significant challenge. Advances in speed, sensitivity, and extent of multiplexing of molecular pathogen detection assays are needed to improve patient care. We report the development of an integrated platform enabling the identification of bacterial pathogen DNA sequences in complex samples in less than four hours. The system incorporates a microfluidic chip and instrumentation to accomplish universal PCR amplification, High Resolution Melting (HRM), and machine learning within 20,000 picoliter scale reactions, simultaneously. Clinically relevant concentrations of bacterial DNA molecules are separated by digitization across 20,000 reactions and amplified with universal primers targeting the bacterial 16S gene. Amplification is followed by HRM sequence fingerprinting in all reactions, simultaneously. The resulting bacteria-specific melt curves are identified by Support Vector Machine learning, and individual pathogen loads are quantified. The platform reduces reaction volumes by 99.995% and achieves a greater than 200-fold increase in dynamic range of detection compared to traditional PCR HRM approaches. Type I and II error rates are reduced by 99% and 100% respectively, compared to intercalating dye-based digital PCR (dPCR) methods. This technology could impact a number of quantitative profiling applications, especially infectious disease diagnostics.

| S-EPMC5296755 | biostudies-literature

Diversity of tRNA genes in eukaryotes.

Project description:We compare the diversity of chromosomal-encoded transfer RNA (tRNA) genes from 11 eukaryotes as identified by tRNAScan-SE of their respective genomes. They include the budding and fission yeast, worm, fruit fly, fugu, chicken, dog, rat, mouse, chimp and human. The number of tRNA genes are between 170 and 570 and the number of tRNA isoacceptors range from 41 to 55. Unexpectedly, the number of tRNA genes having the same anticodon but different sequences elsewhere in the tRNA body (defined here as tRNA isodecoder genes) varies significantly (10-246). tRNA isodecoder genes allow up to 274 different tRNA species to be produced from 446 genes in humans, but only up to 51 from 275 genes in the budding yeast. The fraction of tRNA isodecoder genes among all tRNA genes increases across the phylogenetic spectrum. A large number of sequence differences in human tRNA isodecoder genes occurs in the internal promoter regions for RNA polymerase III. We also describe a systematic, ligation-based method to detect and quantify tRNA isodecoder molecules in human samples, and show differential expression of three tRNA isodecoders in six human tissues. The large number of tRNA isodecoder genes in eukaryotes suggests that tRNA function may be more diverse than previously appreciated.

| S-EPMC1693877 | biostudies-literature

Quantitative profiling of cortisol metabolites in human urine by high-resolution accurate-mass MS.

Project description:Aim, materials & methods: Urinary cortisol profile has the potential as a diagnostic biomarker. We therefore developed a stable-isotope dilution ultraperformance chromatography multistage MS-based method to quantify cortisol and 16 metabolites in human urines. Results & conclusion: The LOD for cortisol and its metabolites ranges from 0.02 to 5.81 pg/μl urine. The inter- and intraday variations were 3.7-12.9% and 3.5-15.6%, respectively. Among the metabolites analyzed, significant person-to-person heterogeneity was observed, demonstrating the need for comprehensive metabolite profiling in diagnosis. Nevertheless, the glucuronides of dihydrocortisol, dihydrocortisone, tetrahydrocortisol, allo-tetrahydrocortisol and tetrahydrocortisone are the major ones. The sum of the glucuronidated and free forms constitute >93% of the metabolites analyzed, which is termed as total cortisol equivalent. Total cortisol equivalent may serve as a surrogate of cortisol secretion. Clinical trial registration number: NCT02500472.

| S-EPMC6462871 | biostudies-literature

Efficient and quantitative high-throughput tRNA sequencing.

Project description:Despite its biological importance, tRNA has not been adequately sequenced by standard methods because of its abundant post-transcriptional modifications and stable structure, which interfere with cDNA synthesis. We achieved efficient and quantitative tRNA sequencing in HEK293T cells by using engineered demethylases to remove base methylations and a highly processive thermostable group II intron reverse transcriptase to overcome these obstacles. Our method, DM-tRNA-seq, should be applicable to investigations of tRNA in all organisms.

| S-EPMC4624326 | biostudies-literature

tRNA abundance, modification and fragmentation as biomarkers for COVID-19 severity

Project description:Respiratory viruses such as SARS-CoV-2 are pathogens that can reach pandemic proportions. The early human response to respiratory viruses are in the nasal cavity and nasopharyngeal regions. Defining biomarkers of disease trajectory at the time of a positive test is important for opting for treatment and monitoring decisions. We hypothesize that the nasopharyngeal tRNA profiles can be used to predict symptom severity resulting from SARS-CoV-2 infection. We carried out multiplex small RNA sequencing (MSR-seq) on nasopharyngeal swaps to measure the human tRNA response to SARS-CoV-2 infection. Our result simultaneously measured full-length tRNA abundance, tRNA modifications, and tRNA fragmentation among individuals that went on to develop no/mild or severe symptoms. We identified distinct tRNA signatures that can predict the clinical outcome of SARS-CoV-2 infected individual at the time of a positive test. These results highlight the utility of using host tRNA properties as biomarkers for clinical applications.

2022-10-01 | GSE208612 | GEO

AAV-delivered suppressor tRNA overcomes a nonsense mutation in mice (mim-tRNA)

Project description:In this study, we utilized a mouse model of mucopolysaccharidosis type I (MPS-I) carrying a homozygous nonsense mutation in the Idua gene (Idua-W401X, TGG→TAG) to develop rAAV-delivered sup-tRNA therapeutics that can overcome a pathogenic UAG premature termination codon (PTC).

2021-11-30 | GSE179272 | 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