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Lifestyle modifications: coordinating the tRNA epitranscriptome with codon bias to adapt translation during stress responses.

ABSTRACT: Cells adapt to stress by altering gene expression at multiple levels. Here, we propose a new mechanism regulating stress-dependent gene expression at the level of translation, with coordinated interplay between the tRNA epitranscriptome and biased codon usage in families of stress-response genes. In this model, auxiliary genetic information contained in synonymous codon usage enables regulation of codon-biased and functionally related transcripts by dynamic changes in the tRNA epitranscriptome. This model partly explains the association between synchronous stress-dependent epitranscriptomic marks and significant multi-codon usage skewing in families of translationally regulated transcripts. The model also predicts translational adaptation during viral infections.

SUBMITTER: Chan C

PROVIDER: S-EPMC6307160 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Lifestyle modifications: coordinating the tRNA epitranscriptome with codon bias to adapt translation during stress responses.

Chan Cheryl C Pham Phuong P Dedon Peter C PC Begley Thomas J TJ

Genome biology 20181227 1

Cells adapt to stress by altering gene expression at multiple levels. Here, we propose a new mechanism regulating stress-dependent gene expression at the level of translation, with coordinated interplay between the tRNA epitranscriptome and biased codon usage in families of stress-response genes. In this model, auxiliary genetic information contained in synonymous codon usage enables regulation of codon-biased and functionally related transcripts by dynamic changes in the tRNA epitranscriptome. ...[more]

PMID: 30587213

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Project description:tRNA (tRNA) is a key molecule used for protein synthesis, with multiple points of stress-induced regulation that can include transcription, transcript processing, localization and ribonucleoside base modification. Enzyme-catalyzed modification of tRNA occurs at a number of base and sugar positions and has the potential to influence specific anticodon-codon interactions and regulate translation. Notably, altered tRNA modification has been linked to mitochondrial diseases and cancer progression. In this review, specific to Eukaryotic systems, we discuss how recent systems-level analyses using a bioanalytical platform have revealed that there is extensive reprogramming of tRNA modifications in response to cellular stress and during cell cycle progression. Combined with genome-wide codon bias analytics and gene expression studies, a model emerges in which stress-induced reprogramming of tRNA drives the translational regulation of critical response proteins whose transcripts display a distinct codon bias. Termed Modification Tunable Transcripts (MoTTs), (1) we define them as (1) transcripts that use specific degenerate codons and codon biases to encode critical stress response proteins, and (2) transcripts whose translation is influenced by changes in wobble base tRNA modification. In this review we note that the MoTTs translational model is also applicable to the process of stop-codon recoding for selenocysteine incorporation, as stop-codon recoding involves a selective codon bias and modified tRNA to decode selenocysteine during the translation of a key subset of oxidative stress response proteins. Further, we discuss how in addition to RNA modification analytics, the comprehensive characterization of translational regulation of specific transcripts requires a variety of tools, including high coverage codon-reporters, ribosome profiling and linked genomic and proteomic approaches. Together these tools will yield important new insights into the role of translational elongation in cell stress response.

Dataset Information

Lifestyle modifications: coordinating the tRNA epitranscriptome with codon bias to adapt translation during stress responses.

Publications

Lifestyle modifications: coordinating the tRNA epitranscriptome with codon bias to adapt translation during stress responses.

Similar Datasets

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