Gene Expression and Protein Length Influence Codon Usage and Rates of Sequence Evolution in Populus tremula

Abstract Background Cell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes. While codon usage is known to affect ensemble gene expression, how codon usage influences variation in gene expression between single cells is not well understood. Results Here, we used a Sort-seq based massively parallel strategy to quantify gene expression variation from a green fluorescent protein (GFP) library containing synonymous codons in Escherichia coli. We found that sequences containing codons with higher tRNA Adaptation Index (TAI) scores, and higher codon adaptation index (CAI) scores, have higher GFP variance. This trend is not observed for codons with high Normalized Translation Efficiency Index (nTE) scores nor from the free energy of folding of the mRNA secondary structure. GFP noise, or squared coefficient of variance (CV2), scales with mean protein abundance for low-abundant proteins but does not change at high mean protein abundance. Conclusions Our results suggest that the main source of noise for high-abundance proteins is likely not originating at translation elongation. Additionally, the drastic change in mean protein abundance with small changes in protein noise seen from our library implies that codon optimization can be performed without concerning gene expression noise for biotechnology applications.

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Prediction of gene expression under drought stress in spring wheat using codon usage pattern

Saudi Journal of Biological Sciences ◽

10.1016/j.sjbs.2021.04.015 ◽

2021 ◽

Author(s):

Meshal M. Almutairi ◽

Abdullah A. Alrajhi

Keyword(s):

Gene Expression ◽

Drought Stress ◽

Codon Usage ◽

Spring Wheat ◽

Codon Usage Pattern ◽

Usage Pattern

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Codon replacement in the PGK1 gene of Saccharomyces cerevisiae: experimental approach to study the role of biased codon usage in gene expression

Molecular and Cellular Biology ◽

10.1128/mcb.7.8.2914-2924.1987 ◽

1987 ◽

Vol 7 (8) ◽

pp. 2914-2924

Author(s):

A Hoekema ◽

R A Kastelein ◽

M Vasser ◽

H A de Boer

Keyword(s):

Gene Expression ◽

Saccharomyces Cerevisiae ◽

Steady State ◽

Codon Usage ◽

Experimental Approach ◽

Mrna Translation ◽

Yeast Cells ◽

Expression Level ◽

Start Codon ◽

Mrna Levels

The coding sequences of genes in the yeast Saccharomyces cerevisiae show a preference for 25 of the 61 possible coding triplets. The degree of this biased codon usage in each gene is positively correlated to its expression level. Highly expressed genes use these 25 major codons almost exclusively. As an experimental approach to studying biased codon usage and its possible role in modulating gene expression, systematic codon replacements were carried out in the highly expressed PGK1 gene. The expression of phosphoglycerate kinase (PGK) was studied both on a high-copy-number plasmid and as a single copy gene integrated into the chromosome. Replacing an increasing number (up to 39% of all codons) of major codons with synonymous minor ones at the 5' end of the coding sequence caused a dramatic decline of the expression level. The PGK protein levels dropped 10-fold. The steady-state mRNA levels also declined, but to a lesser extent (threefold). Our data indicate that this reduction in mRNA levels was due to destabilization caused by impaired translation elongation at the minor codons. By preventing translation of the PGK mRNAs by the introduction of a stop codon 3' and adjacent to the start codon, the steady-state mRNA levels decreased dramatically. We conclude that efficient mRNA translation is required for maintaining mRNA stability in S. cerevisiae. These findings have important implications for the study of the expression of heterologous genes in yeast cells.

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Codon usage signatures in the genus Cryptococcus: A complex interplay of gene expression, translational selection and compositional bias

Genomics ◽

10.1016/j.ygeno.2020.10.013 ◽

2020 ◽

Author(s):

Shelly Gupta ◽

Karan Paul ◽

Ayan Roy

Keyword(s):

Gene Expression ◽

Codon Usage ◽

Compositional Bias ◽

Complex Interplay ◽

Translational Selection

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Genome-wide codon usage pattern analysis reveals the correlation between codon usage bias and gene expression in Cuscuta australis

Genomics ◽

10.1016/j.ygeno.2020.03.002 ◽

2020 ◽

Vol 112 (4) ◽

pp. 2695-2702 ◽

Cited By ~ 2

Author(s):

Xu-Yuan Liu ◽

Yu Li ◽

Kai-Kai Ji ◽

Jie Zhu ◽

Peng Ling ◽

...

Keyword(s):

Gene Expression ◽

Codon Usage ◽

Codon Usage Bias ◽

Pattern Analysis ◽

Codon Usage Pattern ◽

Usage Pattern ◽

Genome Wide

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Codon usage is an important determinant of gene expression levels largely through its effects on transcription

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1606724113 ◽

2016 ◽

Vol 113 (41) ◽

pp. E6117-E6125 ◽

Cited By ~ 122

Author(s):

Zhipeng Zhou ◽

Yunkun Dang ◽

Mian Zhou ◽

Lin Li ◽

Chien-hung Yu ◽

...

Keyword(s):

Gene Expression ◽

Codon Usage ◽

Important Determinant ◽

Mrna Translation ◽

Mrna Levels ◽

Protein Coding ◽

Expression Levels ◽

Highly Expressed Genes ◽

The Impact ◽

Gene Expression Levels

Codon usage biases are found in all eukaryotic and prokaryotic genomes, and preferred codons are more frequently used in highly expressed genes. The effects of codon usage on gene expression were previously thought to be mainly mediated by its impacts on translation. Here, we show that codon usage strongly correlates with both protein and mRNA levels genome-wide in the filamentous fungus Neurospora. Gene codon optimization also results in strong up-regulation of protein and RNA levels, suggesting that codon usage is an important determinant of gene expression. Surprisingly, we found that the impact of codon usage on gene expression results mainly from effects on transcription and is largely independent of mRNA translation and mRNA stability. Furthermore, we show that histone H3 lysine 9 trimethylation is one of the mechanisms responsible for the codon usage-mediated transcriptional silencing of some genes with nonoptimal codons. Together, these results uncovered an unexpected important role of codon usage in ORF sequences in determining transcription levels and suggest that codon biases are an adaptation of protein coding sequences to both transcription and translation machineries. Therefore, synonymous codons not only specify protein sequences and translation dynamics, but also help determine gene expression levels.

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Codon usage pattern and predicted gene expression in Arabidopsis thaliana

Gene X ◽

10.1016/j.gene.2019.100012 ◽

2019 ◽

Vol 2 ◽

pp. 100012 ◽

Cited By ~ 1

Author(s):

Satyabrata Sahoo ◽

Shib Sankar Das ◽

Ria Rakshit

Keyword(s):

Gene Expression ◽

Arabidopsis Thaliana ◽

Codon Usage ◽

Codon Usage Pattern ◽

Usage Pattern

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COUSIN (COdon Usage Similarity INdex): A Normalized Measure of Codon Usage Preferences

Genome Biology and Evolution ◽

10.1093/gbe/evz262 ◽

2019 ◽

Vol 11 (12) ◽

pp. 3523-3528 ◽

Cited By ~ 7

Author(s):

Jérôme Bourret ◽

Samuel Alizon ◽

Ignacio G Bravo

Keyword(s):

Gene Expression ◽

Codon Usage ◽

Null Hypothesis ◽

Similarity Index ◽

Bimodal Distribution ◽

Added Value ◽

Complete Analysis ◽

Coding Sequences ◽

Synonymous Codons ◽

User Friendly

Abstract Codon Usage Preferences (CUPrefs) describe the unequal usage of synonymous codons at the gene, chromosome, or genome levels. Numerous indices have been developed to evaluate CUPrefs, either in absolute terms or with respect to a reference. We introduce the normalized index COUSIN (for COdon Usage Similarity INdex), that compares the CUPrefs of a query against those of a reference and normalizes the output over a Null Hypothesis of random codon usage. The added value of COUSIN is to be easily interpreted, both quantitatively and qualitatively. An eponymous software written in Python3 is available for local or online use (http://cousin.ird.fr). This software allows for an easy and complete analysis of CUPrefs via COUSIN, includes seven other indices, and provides additional features such as statistical analyses, clustering, and CUPrefs optimization for gene expression. We illustrate the flexibility of COUSIN and highlight its advantages by analyzing the complete coding sequences of eight divergent genomes. Strikingly, COUSIN captures a bimodal distribution in the CUPrefs of human and chicken genes hitherto unreported with such precision. COUSIN opens new perspectives to uncover CUPrefs specificities in genomes in a practical, informative, and user-friendly way.

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