Transcriptomics

Dataset Information

0

Transcriptome-wide RNA processing kinetics revealed using extremely short 4tU labelling


ABSTRACT: RNA levels detected at steady state are the consequence of multiple dynamic processes within the cell. In addition to synthesis and decay, many transcripts undergo processing. For example, in the case of intron-containing transcripts, there is splicing to take into the equation. Metabolic tagging with a nucleotide analogue is one way of determining the relative contributions of synthesis, decay and conversion processes globally. By using a much refined method of 4-thiouracil labelling in Saccharomyces cerevisiae we can isolate RNA produced during as little as 1 min, allowing the detection of RNA species with high turn-over rates, including intron-containing pre-mRNAs and short-lived non-coding RNAs. Nascent RNA labelled for 1.5, 2.5 or 5 minutes was isolated and analysed by reverse transcriptase-quantitative PCR and RNA sequencing. From these data we measured the relative stability of pre-mRNA species with different high turn-over rates and investigated potential correlations with intron features. This extremely brief metabolic labeling method enables the isolation of short-lived RNA species and the production of transcriptome-wide high-resolution kinetic data with some unexpected results . Previous studies using reporter genes suggested that secondary structure in introns is favourable for efficient splicing and may affect splice site usage. In contrast, our data reveal that ribosomal protein transcripts with intron secondary structures that are predicted to be less stable, splice faster. These data, in combination with previous results, indicate that there is an optimal range of stability of intron secondary structures that allows for rapid splicing.

ORGANISM(S): Saccharomyces cerevisiae

PROVIDER: GSE70378 | GEO | 2015/11/19

SECONDARY ACCESSION(S): PRJNA288474

REPOSITORIES: GEO

Similar Datasets

2014-02-21 | E-GEOD-55213 | biostudies-arrayexpress
2014-02-21 | GSE55213 | GEO
2015-04-22 | E-GEOD-64672 | biostudies-arrayexpress
2017-11-25 | GSE99161 | GEO
2019-09-24 | GSE137883 | GEO
2021-06-23 | GSE140679 | GEO
2015-07-13 | E-GEOD-62752 | biostudies-arrayexpress
2021-06-16 | GSE144906 | GEO
2021-06-16 | GSE144905 | GEO
2021-06-16 | GSE144874 | GEO