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Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems
Published on: April 26, 2019
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Mistranslation suppresses mistranscription in eukaryotes
Xiaoyi Zhang1, Gongwang Yu2, Ziyan Guo3
1Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Nature Communications
|February 25, 2026
Summary
Genes with frequent mistranslations show fewer mistranscriptions, suggesting a negative interaction between these two error types. This interaction influences evolutionary selection against mistranscription.
Area of Science:
- Molecular Biology
- Genetics
- Evolutionary Biology
Background:
- Phenotypic mutations arise from non-heritable sequence changes like mistranscription and mistranslation.
- The interplay between mistranscription and mistranslation is not well understood despite their potential impact.
Purpose of the Study:
- To investigate the relationship between mistranscription and mistranslation rates across the genome.
- To explore the underlying mechanisms, such as epistasis, that may govern this interaction.
Main Methods:
- Genome-wide analysis using Circ-Seq and mass spectrometry in five model organisms.
- Systematic experimental measurements to confirm epistasis.
- In silico evolutionary simulations.
- Empirical genomic analyses of gene expression and error purging.
Main Results:
- Genes with high mistranslation rates exhibit lower mistranscription rates.
- Negative epistasis between mistranscription and mistranslation was experimentally confirmed.
- Evolutionary simulations indicated selection against mistranscription in highly mistranslated genes due to epistasis.
- Genes with high mistranslation efficiently purge nonsynonymous mistranscriptions, and highly translated transcripts have fewer mistranscriptions.
Conclusions:
- An unrecognized negative interaction exists between mistranscription and mistranslation.
- This interaction impacts evolutionary dynamics and gene expression regulation.
- The findings highlight a novel layer of molecular error management within cells.
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