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Series GSE233546 Query DataSets for GSE233546
Status Public on Apr 23, 2024
Title Nuclear export is a limiting factor in eukaryotic mRNA metabolism
Organism Homo sapiens
Experiment type Other
Summary The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments. We develop a model that reliably quantifies mRNA synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3’UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.
 
Overall design We have performed a SLAM-seq time-series experiment in HeLa-S3 cells, where two replicate samples were taken at t=0, 15, 30, 45, 60, 90, 120 and 180 min after the addition of 500 μM 4sU. After metabolic labeling of RNA, the cells were fractionated to obtain the nuclear and the cytosolic RNA fractions.
To quantify mRNA metabolism, polyadenylated transcripts were captured by targeted sequencing library preparation and sequencing of polyadenylated 3’ ends. Reads were mapped to the human genome using Slamdunk.
We assigned the reads to annotated 3’UTRs. For robustness, we only consider3’UTRs with an average number of at least 30 reads in each cellular compartment and time series experiment.
We performed a refined analysis in which we defined densely covered, highly confined read clusters along the entire genome. We selected such peaks with robust expression, i.e., at least 30 average counts in each cellular compartment and time-series experiment.
 
Contributor(s) Müller JM, Moos K, Baar T, Zumer K, Tresch A
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Submission date May 26, 2023
Last update date Apr 23, 2024
Contact name Achim Tresch
E-mail(s) achim.tresch@uni-koeln.de
Organization name University of Cologne
Department Institute of Medical Statistics and Computational Biology
Street address Paul-Schallueck-Str. 10
City Cologne
State/province North Rhine-Westphalia
ZIP/Postal code 50937
Country Germany
 
Platforms (1)
GPL11154 Illumina HiSeq 2000 (Homo sapiens)
Samples (34)
GSM7429995 Hela, 0min, total, rep1
GSM7429996 Hela, 0min, total, rep2
GSM7429997 Hela, 0min, nucleus, rep1
Relations
BioProject PRJNA976642

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE233546_UTR_counts.csv.gz 5.3 Mb (ftp)(http) CSV
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Raw data are available in SRA
Processed data are available on Series record

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