scholarly journals Relative Codon Adaptation Index, a Sensitive Measure of Codon Usage Bias

2010 ◽  
Vol 6 ◽  
pp. EBO.S4608 ◽  
Author(s):  
Soohyun Lee ◽  
Seyeon Weon ◽  
Sooncheol Lee ◽  
Changwon Kang
Keyword(s):  
Codon Usage ◽  
Codon Usage Bias ◽  
Codon Adaptation Index ◽  
Sensitive Measure ◽  
Adaptation Index

scholarly journals Evolution of Codon Usage Bias in Henipaviruses Is Governed by Natural Selection and Is Host-Specific

Viruses ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 604 ◽  
Author(s):  
Naveen Kumar ◽  
Diwakar Kulkarni ◽  
Benhur Lee ◽  
Rahul Kaushik ◽  
Sandeep Bhatia ◽  
...  
Keyword(s):  
Natural Selection ◽  
Codon Usage ◽  
Codon Usage Bias ◽  
Synonymous Codon ◽  
Similarity Index ◽  
Hendra Virus ◽  
Human Beings ◽  
Mutation Pressure ◽  
Usage Patterns ◽  
Adaptation Index

Hendra virus (HeV) and Nipah virus (NiV) are among a group of emerging bat-borne paramyxoviruses that have crossed their species-barrier several times by infecting several hosts with a high fatality rate in human beings. Despite the fatal nature of their infection, a comprehensive study to explore their evolution and adaptation in different hosts is lacking. A study of codon usage patterns in henipaviruses may provide some fruitful insight into their evolutionary processes of synonymous codon usage and host-adapted evolution. Here, we performed a systematic evolutionary and codon usage bias analysis of henipaviruses. We found a low codon usage bias in the coding sequences of henipaviruses and that natural selection, mutation pressure, and nucleotide compositions shapes the codon usage patterns of henipaviruses, with natural selection being more important than the others. Also, henipaviruses showed the highest level of adaptation to bats of the genus Pteropus in the codon adaptation index (CAI), relative to the codon de-optimization index (RCDI), and similarity index (SiD) analyses. Furthermore, a comparison to recently identified henipa-like viruses indicated a high tRNA adaptation index of henipaviruses for human beings, mainly due to F, G and L proteins. Consequently, the study concedes the substantial emergence of henipaviruses in human beings, particularly when paired with frequent exposure to direct/indirect bat excretions.

scholarly journals A New Look at Codon Usage and Protein Expression

10.29007/d4tz ◽  
2019 ◽  
Author(s):  
Gabriel Wright ◽  
Anabel Rodriguez ◽  
Patricia Clark ◽  
Scott Emrich
Keyword(s):  
Protein Expression ◽  
Codon Usage ◽  
Empirical Data ◽  
Codon Usage Bias ◽  
Elongation Rate ◽  
Translation Rate ◽  
Translation Elongation ◽  
Promising Alternative ◽  
Highly Expressed Genes ◽  
Adaptation Index

%MinMax, a model of intra-gene translational elongation rate, relies on codon usage frequencies. Historically, %MinMax has used tables that measure codon usage bias for all genes in an organism, such as those found at HIVE-CUT. In this paper, we provide evidence that codon usage bias based on all genes is insufficient to accurately measure absolute translation rate. We show that alternative ”High-φ” codon usage tables, generated by another model (ROC-SEMPPR), are a promising alternative. By creating a hybrid model, future codon usage analyses and their applications (e.g., codon harmonization) are likely to more accurately measure the ”tempo” of translation elongation. We also suggest a High- φ alternative to the Codon Adaptation Index (CAI), a classic metric of codon usage bias based on highly expressed genes. Significantly, our new alternative is equally well correlated with empirical data as traditional CAI without using experimentally determined expression counts as input.

scholarly journals Comprehensive Analysis and Comparison on the Codon Usage Pattern of Whole Mycobacterium tuberculosis Coding Genome from Different Area

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Li Gun ◽  
Ren Yumiao ◽  
Pan Haixian ◽  
Zhang Liang
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Codon Usage ◽  
Codon Usage Bias ◽  
Gc Content ◽  
Codon Usage Pattern ◽  
Usage Pattern ◽  
Strong Negative Correlation ◽  
Synonymous Codons ◽  
The Relationship ◽  
Adaptation Index

Phenomenon of unequal use of synonymous codons in Mycobacterium tuberculosis is common. Codon usage bias not only plays an important regulatory role at the level of gene expression, but also helps in improving the accuracy and efficiency of translation. Meanwhile, codon usage pattern of Mycobacterium tuberculosis genome is important for interpreting evolutionary characteristics in species. In order to investigate the codon usage pattern of the Mycobacterium tuberculosis genome, 12 Mycobacterium tuberculosis genomes from different area are downloaded from the GeneBank. The correlations between G3, GC12, whole GC content, codon adaptation index, codon bias index, and so on of Mycobacterium tuberculosis genomes are calculated. The ENC-plot, relationship between A3/(A3+T3) and G3/(G3+C3), GC12 versus GC3 plot, and the RSCU of overall/separated genomes all show that the codon usage bias exists in all 12 Mycobacterium tuberculosis genomes. Lastly, relationship between CBI and the equalization of ENC shows a strong negative correlation between them. The relationship between protein length and GC content (GC3 and GC12) shows that more obvious differences in the GC content may be in shorter protein. These results show that codon usage bias existing in the Mycobacterium tuberculosis genomes could be used for further study on their evolutionary phenomenon.

scholarly journals ICOR: Improving codon optimization with recurrent neural networks

2021 ◽  
Author(s):  
Rishab Jain ◽  
Aditya Jain ◽  
Elizabeth Mauro ◽  
Kevin LeShane ◽  
Douglas Densmore
Keyword(s):  
Escherichia Coli ◽  
Amino Acids ◽  
Heterologous Expression ◽  
Codon Usage ◽  
Dna Sequences ◽  
Codon Optimization ◽  
Optimization Techniques ◽  
Codon Adaptation Index ◽  
Synonymous Codons ◽  
Adaptation Index

In protein sequences—as there are 61 sense codons but only 20 standard amino acids—most amino acids are encoded by more than one codon. Although such synonymous codons do not alter the encoded amino acid sequence, their selection can dramatically affect the expression of the resulting protein. Codon optimization of synthetic DNA sequences is important for heterologous expression. However, existing solutions are primarily based on choosing high-frequency codons only, neglecting the important effects of rare codons. In this paper, we propose a novel recurrent-neural-network based codon optimization tool, ICOR, that aims to learn codon usage bias on a genomic dataset of Escherichia coli. We compile a dataset of over 7,000 non-redundant, high-expression, robust genes which are used for deep learning. The model uses a bidirectional long short-term memory-based architecture, allowing for the sequential context of codon usage in genes to be learned. Our tool can predict synonymous codons for synthetic genes toward optimal expression in Escherichia coli. We demonstrate that sequential context achieved via RNN may yield codon selection that is more similar to the host genome, therefore improving protein expression more than frequency-based approaches. ICOR is evaluated on 1,481 Escherichia coli genes as well as a benchmark set of 40 select DNA sequences whose heterologous expression has been previously characterized. ICOR's performance across five metrics is compared to that of five different codon optimization techniques. The codon adaptation index -- a metric indicative of high real-world expression -- was utilized as the primary benchmark in this study. ICOR is shown to improve the codon adaptation index by 41.69% and 17.25% compared to the original and Genscript's GenSmart-optimized sequences, respectively. Our tool is provided as an open-source software package that includes the benchmark set of sequences used in this study.

scholarly journals Patterns of genome-wide codon usage bias in tobacco, tomato and potato

2021 ◽  
Vol 35 (1) ◽  
pp. 657-664
Author(s):  
Ali Mostafa Anwar ◽  
Maha Aljabri ◽  
Mohamed El-Soda
Keyword(s):  
Codon Usage ◽  
Codon Usage Bias ◽  
Genome Wide

scholarly journals Massively parallel gene expression variation measurement of a synonymous codon library

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Alexander Schmitz ◽  
Fuzhong Zhang
Keyword(s):  
Gene Expression ◽  
Codon Usage ◽  
Single Cells ◽  
Massively Parallel ◽  
Protein Abundance ◽  
Translation Efficiency ◽  
Gene Expression Variation ◽  
Expression Variation ◽  
Change In Mean ◽  
Adaptation Index

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.

scholarly journals Codon usage bias and environmental adaptation in microbial organisms

2021 ◽  
Author(s):  
Davide Arella ◽  
Maddalena Dilucca ◽  
Andrea Giansanti
Keyword(s):  
Codon Usage ◽  
Codon Usage Bias ◽  
Pathogenic Bacteria ◽  
Large Scale ◽  
Synonymous Codon ◽  
Principal Component ◽  
Gene Copy ◽  
Phenotypic Traits ◽  
Translational Efficiency ◽  
Microbial Organisms

AbstractIn each genome, synonymous codons are used with different frequencies; this general phenomenon is known as codon usage bias. It has been previously recognised that codon usage bias could affect the cellular fitness and might be associated with the ecology of microbial organisms. In this exploratory study, we investigated the relationship between codon usage bias, lifestyles (thermophiles vs. mesophiles; pathogenic vs. non-pathogenic; halophilic vs. non-halophilic; aerobic vs. anaerobic and facultative) and habitats (aquatic, terrestrial, host-associated, specialised, multiple) of 615 microbial organisms (544 bacteria and 71 archaea). Principal component analysis revealed that species with given phenotypic traits and living in similar environmental conditions have similar codon preferences, as represented by the relative synonymous codon usage (RSCU) index, and similar spectra of tRNA availability, as gauged by the tRNA gene copy number (tGCN). Moreover, by measuring the average tRNA adaptation index (tAI) for each genome, an index that can be associated with translational efficiency, we observed that organisms able to live in multiple habitats, including facultative organisms, mesophiles and pathogenic bacteria, are characterised by a reduced translational efficiency, consistently with their need to adapt to different environments. Our results show that synonymous codon choices might be under strong translational selection, which modulates the choice of the codons to differently match tRNA availability, depending on the organism’s lifestyle needs. To our knowledge, this is the first large-scale study that examines the role of codon bias and translational efficiency in the adaptation of microbial organisms to the environment in which they live.

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