scholarly journals ΦX174 Attenuation by Whole Genome Codon Deoptimization

2020 ◽  
Author(s):  
James T Van Leuven ◽  
Martina M Ederer ◽  
Katelyn Burleigh ◽  
LuAnn Scott ◽  
Randall A Hughes ◽  
...  
Keyword(s):  
Codon Usage ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Viral Fitness ◽  
Live Attenuated Vaccine ◽  
Protein Coding ◽  
Viral Growth ◽  
Synonymous Mutations ◽  
Genes Encoding ◽  
Codon Deoptimization

Abstract Natural selection acting on synonymous mutations in protein-coding genes influences genome composition and evolution. In viruses, introducing synonymous mutations in genes encoding structural proteins can drastically reduce viral growth, providing a means to generate potent, live attenuated vaccine candidates. However, an improved understanding of what compositional features are under selection and how combinations of synonymous mutations affect viral growth is needed to predictably attenuate viruses and make them resistant to reversion. We systematically recoded all non-overlapping genes of the bacteriophage ΦX174 with codons rarely used in its E. coli host. The fitness of recombinant viruses decreases as additional deoptimizing mutations are made to the genome, although not always linearly, and not consistently across genes. Combining deoptimizing mutations may reduce viral fitness more or less than expected from the effect size of the constituent mutations and we point out difficulties in untangling correlated compositional features. We test our model by optimizing the same genes and find that the relationship between codon usage and fitness does not hold for optimization, suggesting that wild-type ΦX174 is at a fitness optimum. This work highlights the need to better understand how selection acts on patterns of synonymous codon usage across the genome and provides a convenient system to investigate the genetic determinants of virulence.

scholarly journals ΦX174 Attenuation by Whole Genome Codon Deoptimization

2020 ◽  
Author(s):  
James T. Van Leuven ◽  
Martina M. Ederer ◽  
Katelyn Burleigh ◽  
LuAnn Scott ◽  
Randall A. Hughes ◽  
...  
Keyword(s):  
Codon Usage ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Viral Fitness ◽  
Live Attenuated Vaccine ◽  
Protein Coding ◽  
Viral Growth ◽  
Synonymous Mutations ◽  
Genes Encoding ◽  
Codon Deoptimization

AbstractNatural selection acting on synonymous mutations in protein-coding genes influences genome composition and evolution. In viruses, introducing synonymous mutations in genes encoding structural proteins can drastically reduce viral growth, providing a means to generate potent, live attenuated vaccine candidates. However, an improved understanding of what compositional features are under selection and how combinations of synonymous mutations affect viral growth is needed to predictably attenuate viruses and make them resistant to reversion. We systematically recoded all non-overlapping genes of the bacteriophage ΦX174 with codons rarely used in its E. coli host. The fitness of recombinant viruses decreases as additional deoptimizing mutations are made to the genome, although not always linearly, and not consistently across genes. Combining deoptimizing mutations may reduce viral fitness more or less than expected from the effect size of the constituent mutations and we point out difficulties in untangling correlated compositional features. We test our model by optimizing the same genes and find that the relationship between codon usage and fitness does not hold for optimization, suggesting that wild-type ΦX174 is at a fitness optimum. This work highlights the need to better understand how selection acts on patterns of synonymous codon usage across the genome and provides a convenient system to investigate the genetic determinants of virulence.

scholarly journals Prediction of the Effects of Synonymous Variants on SARS-CoV-2 Genome

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1053
Author(s):  
Wan Xin Boon ◽  
Boon Zhan Sia ◽  
Chong Han Ng
Keyword(s):  
Codon Usage ◽  
Rna Structure ◽  
Rna Virus ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Viral Fitness ◽  
Translation Rate ◽  
Synonymous Mutations ◽  
Global Initiative ◽  
The Stability

Background: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple studies had been done to identify and study nonsynonymous mutations, which change amino acid residues of SARS-CoV-2 proteins. On the other hand, there is little study on the effects of SARS-CoV-2 synonymous mutations. Although these mutations do not alter amino acids, some studies suggest that they may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome.   Methods: A total of 30,229 SARS-CoV-2 genomic sequences were retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database and aligned using MAFFT. Then, the mutations and their respective frequency were identified. A prediction of RNA secondary structures and their base pair probabilities was performed to study the effect of synonymous mutations on RNA structure and stability. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2.  Results: A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a, followed by C313U and C9286U mutation in nsp1 and nsp4 of ORF1a, respectively.   Conclusion: Among the synonymous mutations identified, C913U mutation in ORF1a and C26735U in membrane (M) protein may affect RNA secondary structure, reducing the stability of RNA folding and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

scholarly journals Codon clusters with biased synonymous codon usage represent hidden functional domains in protein-coding DNA sequences

2019 ◽  
Author(s):  
Zhen Peng ◽  
Yehuda Ben-Shahar
Keyword(s):  
Amino Acid ◽  
Nucleic Acid ◽  
Codon Usage ◽  
Dna Sequences ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Functional Domains ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Usage Patterns

1.AbstractProtein-coding DNA sequences are thought to primarily affect phenotypes via the peptides they encode. Yet, emerging data suggest that, although they do not affect protein sequences, synonymous mutations can cause phenotypic changes. Previously, we have shown that signatures of selection on gene-specific codons usage bias are common in genomes of diverse eukaryotic species. Thus, synonymous codon usage, just as amino acid usage pattern, is likely a regular target of natural selection. Consequently, here we propose the hypothesis that at least for some protein-coding genes, codon clusters with biased synonymous codon usage patterns might represent “hidden” nucleic-acid-level functional domains that affect the action of the corresponding proteins via diverse hypothetical mechanisms. To test our hypothesis, we used computational approaches to identify over 3,000 putatively functional codon clusters (PFCCs) with biased usage patterns in about 1,500 protein-coding genes in the Drosophila melanogaster genome. Specifically, our data suggest that these PFCCs are likely associated with specific categories of gene function, including enrichment in genes that encode membrane-bound and secreted proteins. Yet, the majority of the PFCCs that we have identified are not associated with previously annotated functional protein domains. Although the specific functional significance of the majority of the PFCCs we have identified remains unknown, we show that in the highly conserved family of voltage-gated sodium channels, the existence of rare-codon cluster(s) in the nucleic-acid region that encodes the cytoplasmic loop that constitutes inactivation gate is conserved across paralogs as well as orthologs across distant animal species. Together, our findings suggest that codon clusters with biased usage patterns likely represent “hidden” nucleic-acid-level functional domains that cannot be simply predicted from the amino acid sequences they encode. Therefore, it is likely that on the evolutionary timescale, protein-coding DNA sequences are shaped by both amino-acid-dependent and codon-usage-dependent selective forces.

scholarly journals Analysis of Codon Usage Patterns in Toxic DinoflagellateAlexandrium tamarensethrough Expressed Sequence Tag Data

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Yi-Yuong Hsiao ◽  
Chorng-Horng Lin ◽  
Jong-Kang Liu ◽  
Tit-Yee Wong ◽  
Jimmy Kuo
Keyword(s):  
Codon Usage ◽  
Expressed Sequence Tag ◽  
Synonymous Codon ◽  
Gc Content ◽  
Synonymous Codon Usage ◽  
Mutational Bias ◽  
Protein Coding ◽  
Reading Frame ◽  
Prediction Program ◽  
Expressed Sequence

We have analyzed synonymous codon usage in the genome ofA. tamarenseCCMP 1598 for protein-coding sequences from 10865 expressed sequence tags (ESTs). We reconstructed a total of 4284 unigenes, including 74 ribosomal protein and 40 plastid-related genes, from ESTs using FrameDP, an open reading frame (ORF) prediction program. Correspondence analysis ofA. tamarensegenes based on codon usage showed that the GC content at the third base of synonymous codons (GC3s) was strongly correlated with the first axis (r=0.93withP<.001). On the other hand, the second axis discriminated between presumed highly and low expressed genes, with expression levels being confirmed by the analysis of EST frequencies (r=−0.89withP<.001). Our results suggest that mutational bias is the major factor in shaping codon usage inA. tamarensegenome, but other factors, namely, translational selection, hydropathy, and aromaticity, also appear to influence the selection of codon usage in this species.

scholarly journals Analysis of Mutation Bias in Shaping Codon Usage Bias and Its Association with Gene Expression Across Species

10.29007/87r9 ◽  
2020 ◽  
Author(s):  
Zhixiu Lu ◽  
Michael Gilchrist ◽  
Scott Emrich
Keyword(s):  
Gene Expression ◽  
Codon Usage ◽  
Codon Usage Bias ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Mutation Bias ◽  
Protein Coding ◽  
E Coli ◽  
Synonymous Codons ◽  
Computation Efficiency

Codon usage bias has been known to reflect the expression level of a protein-coding gene under the evolutionary theory that selection favors certain synonymous codons. Although measuring the effect of selection in simple organisms such as yeast and E. coli has proven to be effective and accurate, codon-based methods perform less well in plants and humans. In this paper, we extend a prior method that incorporates another evolutionary factor, namely mutation bias and its effect on codon usage. Our results indicate that prediction of gene expression is significantly improved under our framework, and suggests that quantification of mutation bias is essential for fully understanding synonymous codon usage. We also propose an improved method, namely MLE-Φ, with much greater computation efficiency and a wider range of applications. An implementation of this method is provided at https://github.com/luzhixiu1996/MLE- Phi.

DNA sequence evolution: the sounds of silence

1995 ◽  
Vol 349 (1329) ◽  
pp. 241-247 ◽  
Keyword(s):  
Natural Selection ◽  
Codon Usage ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Sequence Evolution ◽  
Protein Coding ◽  
Human Genes ◽  
Usage Patterns ◽  
Trna Species ◽  
Multicellular Organisms

Silent sites (positions that can undergo synonymous substitutions) in protein-coding genes can illuminate two evolutionary processes. First, despite being silent, they may be subject to natural selection. Among eukaryotes this is exemplified by yeast, where synonymous codon usage patterns are shaped by selection for particular codons that are more efficiently and/or accurately translated by the most abundant tRNAs; codon usage across the genome, and the abundance of different tRNA species, are highly co-adapted. Second, in the absence of selection, silent sites reveal underlying mutational patterns. Codon usage varies enormously among human genes, and yet silent sites do not appear to be influenced by natural selection, suggesting that mutation patterns vary among regions of the genome. At first, the yeast and human genomes were thought to reflect a dichotomy between unicellular and multicellular organisms. However, it now appears that natural selection shapes codon usage in some multicellular species (e.g. Drosophila and Caenorhabditis ), and that regional variations in mutation biases occur in yeast. Silent sites (in serine codons) also provide evidence for mutational events changing adjacent nucleotides simultaneously.

Codon Usage Bias Covaries With Expression Breadth and the Rate of Synonymous Evolution in Humans, but This Is Not Evidence for Selection

Genetics ◽  
2001 ◽  
Vol 159 (3) ◽  
pp. 1191-1199
Author(s):  
Araxi O Urrutia ◽  
Laurence D Hurst
Keyword(s):  
Codon Usage ◽  
Codon Bias ◽  
Synonymous Codon ◽  
Nucleotide Composition ◽  
Synonymous Codon Usage ◽  
Synonymous Substitutions ◽  
Numerous Species ◽  
Nucleotide Content ◽  
Expression Breadth ◽  
Human Genes

Abstract In numerous species, from bacteria to Drosophila, evidence suggests that selection acts even on synonymous codon usage: codon bias is greater in more abundantly expressed genes, the rate of synonymous evolution is lower in genes with greater codon bias, and there is consistency between genes in the same species in which codons are preferred. In contrast, in mammals, while nonequal use of alternative codons is observed, the bias is attributed to the background variance in nucleotide concentrations, reflected in the similar nucleotide composition of flanking noncoding and exonic third sites. However, a systematic examination of the covariants of codon usage controlling for background nucleotide content has yet to be performed. Here we present a new method to measure codon bias that corrects for background nucleotide content and apply this to 2396 human genes. Nearly all (99%) exhibit a higher amount of codon bias than expected by chance. The patterns associated with selectively driven codon bias are weakly recovered: Broadly expressed genes have a higher level of bias than do tissue-specific genes, the bias is higher for genes with lower rates of synonymous substitutions, and certain codons are repeatedly preferred. However, while these patterns are suggestive, the first two patterns appear to be methodological artifacts. The last pattern reflects in part biases in usage of nucleotide pairs. We conclude that we find no evidence for selection on codon usage in humans.

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