Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA525707 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10953100_1.fastq.gz | Fastqsanger.gz | |||
| SRR10953100_2.fastq.gz | Fastqsanger.gz | |||
| SRR10953079_1.fastq.gz | Fastqsanger.gz | |||
| SRR10953080_1.fastq.gz | Fastqsanger.gz | |||
| SRR10953081_1.fastq.gz | Fastqsanger.gz |
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Project description:Eukaryotic genes often generate a variety of RNA isoforms that can lead to functionally distinct protein variants. The synthesis and stability of RNA isoforms is however poorly characterized. The reason for this is that current methods to quantify RNA metabolism use short-read sequencing that cannot detect RNA isoforms. Here we present nanopore sequencing-based Isoform Dynamics (nano-ID), a method that detects newly synthesized RNA isoforms and monitors isoform metabolism. nano-ID combines metabolic RNA labeling, long-read nanopore sequencing of native RNA molecules and machine learning. nano-ID derived RNA stability estimates enable a distinctive evaluation of stability determining factors such as sequence, poly(A)-tail length, RNA secondary structure, translation efficiency and RNA binding proteins. Application of nano-ID to the heat shock response in human cells reveals that many RNA isoforms change their stability. nano-ID also shows that the metabolism of individual RNA isoforms differs strongly from that estimated for the combined RNA signal at a specific gene locus. nano-ID enables studies of RNA metabolism on the level of single RNA molecules and isoforms in different cell states and conditions.
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Project description:Eukaryotic genes generate multiple mRNA transcript isoforms though alternative transcription, splicing, and polyadenylation. However, the relationship between human transcript diversity and protein production is complex as each isoform can be translated differently. We fractionated a polysome profile and reconstructed transcript isoforms from each fraction, which we term Transcript Isoforms in Polysomes sequencing (TrIP-seq). Analysis of these data revealed regulatory features that control ribosome occupancy and translational output of each transcript isoform. We extracted a panel of 5′ and 3′ untranslated regions that control protein production from an unrelated gene in cells over a 100-fold range. Select 5′ untranslated regions exert robust translational control between cell lines, while 3′ untranslated regions can confer cell-type-specific expression. These results expose the large dynamic range of transcript-isoform-specific translational control, identify isoform-specific sequences that control protein output in human cells, and demonstrate that transcript isoform diversity must be considered when relating RNA and protein levels.
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