Codon usage bias

Synonymous codon usage varies both between organisms and among genes within a genome, and arises due to differences in G + C content, replication strand skew, or gene expression levels. Correspondence analysis (CA) is widely used to identify major sources of variation in synonymous codon usage among genes and provides a way to identify horizontally transferred or highly expressed genes. Four methods of CA have been developed based on three kinds of input data: absolute codon frequency, relative codon frequency, and relative synonymous codon usage (RSCU) as well as within-group CA (WCA). Although different CA methods have been used in the past, no comprehensive comparative study has been performed to evaluate their effectiveness. Here, the four CA methods were evaluated by applying them to 241 bacterial genome sequences. The results indicate that WCA is more effective than the other three methods in generating axes that reflect variations in synonymous codon usage. Furthermore, WCA reveals sources that were previously unnoticed in some genomes; e.g. synonymous codon usage related to replication strand skew was detected in Rickettsia prowazekii. Though CA based on RSCU is widely used, our evaluation indicates that this method does not perform as well as WCA.

A similarity statistic for codon usage was developed and used to compare novel gene sequences found in clinical isolates of Haemophilus influenzae with a reference set of 80 prokaryotic, eukaryotic and viral genomes. These analyses were performed to obtain an indication as to whether individual genes were Haemophilus-like in nature, or if they probably had more recently entered the H.influenzae gene pool via horizontal gene transfer from other species. The average and SD values were calculated for the similarity statistics from a study of the set of all genes in the H.influenzae Rd reference genome that encoded proteins of 100 amino acids or longer. Approximately 80% of Rd genes gave a statistic indicating that they were most like other Rd genes. Genes displaying codon usage statistics .1 SD above this range were either considered part of the highly expressed group of H.influenzae genes, or were considered of foreign origin. An alternative determinant for identifying genes of foreign origin was when the similarity statistics produced a value that was much closer to a non-H.influenzae reference organism than to any of the Haemophilus species contained in the reference set. Approximately 65% of the novel sequences identified in the H.influenzae clinical isolates displayed codon usages most similar to Haemophilus sp. The remaining novel sequences produced similarity statistics closer to one of the other reference genomes thereby suggesting that these sequences may have entered the H.influenzae gene pool more recently via horizontal transfer.

Using custom software (Inidon) we have examined the initiation codon utilization in 620 complete bacterial genomes downloaded from the National Center for Biotechnology Information (NCBI). The mean utilization of ATG, GTG and TTG codons is 80.1, 11.6 and 7.8 %, respectively. In most cases in which similar species or strains have been analysed the utilization percentages of the three initiation codons are remarkably similar, but in certain cases the results exhibit significant differences.

Using custom software (Inidon) we have examined the initiation codon utilization in 620 complete bacterial genomes downloaded from the National Center for Biotechnology Information (NCBI). The mean utilization of ATG, GTG and TTG codons is 80.1, 11.6 and 7.8 %, respectively. In most cases in which similar species or strains have been analysed the utilization percentages of the three initiation codons are remarkably similar, but in certain cases the results exhibit significant differences.

Duplicate loci offer a very powerful system for understanding the complicated genome structure and adaptive evolution of a gene family. In this study, the genetic variation at paralogs AtHVA22d and AtHVA22e, members of an ABA-and stress-inducible gene family, is examined in the selfing Arabidopsis thaliana. Population genetic analysis indicates contrasting levels of nucleotide diversity at overall exon sequence and nonsynonymous sites between AtHVA22d (p ¼ 0:00337, p rep ¼ 0:00158) and AtHVA22e (p ¼ 0:00054, p rep ¼ 0:00023). The fact of K a =K s ratios significantly less than 1 in all sequences indicates that both genes are functional and subjected to purifying selection. In addition, rooted at barley HVA22, accelerated evolution is detected at replacement changes in the AtHVA22d locus, indicating relaxation of purifying selection after gene duplication. However, relative rate tests reveal no deviation from the neutrality at synonymous sites between the two paralogs. Based on clock-like evolution, the rate of synonymous substitution is estimated at 1.83 Â 10 À9 substitutions per site per year; and the divergence of the two paralogs is traced to 90 MYA, coinciding with a period of the diversification of angiosperms. Given no codon usage bias in both genes, natural selection alone cannot account for the 6.4-fold differences in the nucleotide variation at synonymous sites between the two paralogs. Random processes resulting in different coalescence times, 3.65 MYA at AtHVA22d vs. 1.20 MYA at AtHVA22e, may have predominantly contributed to the evident differences of the genetic diversity. Partially nonoverlapping modes of expression between the two functional paralogs suggest a subfunctionalization hypothesis for explaining the fates of duplicate loci.

Middle East Respiratory Syndrome Coronavirus (MERS CoV) is a new emerging viral disease characterized by high fatality rate. Understanding MERS CoV genetic aspects and codon usage pattern is important to understand MERS CoV survival, adaptation, evolution, resistance to innate immunity, and help in finding the unique aspects of the virus for future drug discovery experiments. In this work, we provide comprehensive analysis of 238 MERS CoV full genomes comprised of human (hMERS) and camel (cMERS) isolates of the virus. MERS CoV genome shaping seems to be under compositional and mutational bias, as revealed by preference of A/T over G/C nucleotides, preferred codons, nucleotides at the third position of codons (NT3s), relative synonymous codon usage, hydropathicity (Gravy), and aromaticity (Aromo) indices. Effective number of codons (ENc) analysis reveals a general slight codon usage bias. Codon adaptation index reveals incomplete adaptation to host environment. MERS CoV showed high ability to resist the innate immune response by showing lower CpG frequencies. Neutrality evolution analysis revealed a more significant role of mutation pressure in cMERS over hMERS. Correspondence analysis revealed that MERS CoV genomes have three genetic clusters, which were distinct in their codon usage, host, and geographic distribution. Additionally, virtual screening and binding experiments were able to identify three new virus-encoded helicase binding compounds. These compounds can be used for further optimization of inhibitors.

) is a recently evolved fatal respiratory disease that poses a concern for a global epidemic. MERS CoV encodes 2 proteases, 3C-like protease (3CLpro) and papain-like protease (PLpro). These proteases share in processing MERS CoV polyproteins at different sites to yield 16 nonstructural proteins. In this work, we provide evidence that MERS CoV 3CLpro and PLpro are subject to different genetic and evolutionary influences that shape the protein sequence, codon usage pattern, and codon usage bias. Compositional bias is present in both proteins due to a preference for AT nucleotides. Thymidine (T) was highly preferred at the third position of codons, preferred and overrepresented codons in PLpro, but was replaced by guanosine (G) in 3CLpro. Compositional constraints were important in PLpro but not in 3CLpro. Directed mutation pressure seems to have a strong influence on 3CLpro codon usage, which is more than 30-fold higher than that in PLpro. Translational selection was evident with PLpro but not with 3CLpro. Both proteins are less immunogenic by showing low CpG frequencies. Correspondence analysis reveals the presence of 3 genetic clusters based on codon usage in PLpro and 3CLpro. Every protein had one common cluster and 2 different clusters. As revealed by correspondence analysis, the number of influences on codon usage are restricted in MERS CoV 3CLpro. In contrast, PLpro is controlled by a broader range of compositional, mutational, and other influences. This may be due to the multifunctional protease, deubiquitination, and innate immunity suppressing profiles of PLpro.

Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 noncoding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.

The GC content of bacterial genomes ranges from 16% to 75% and wide ranges of genomic GC content are observed within many bacterial phyla, including both Gram negative and Gram positive phyla. Thus, divergent genomic GC content has evolved repeatedly in widely separated bacterial taxa. Since genomic GC content influences codon usage, we examined codon usage patterns and predicted protein amino acid content as a function of genomic GC content within eight different phyla or classes of bacteria. We found that similar patterns of codon usage and protein amino acid content have evolved independently in all eight groups of bacteria. For example, in each group, use of amino acids encoded by GC-rich codons increased by approximately 1% for each 10% increase in genomic GC content, while the use of amino acids encoded by ATrich codons decreased by a similar amount. This consistency within every phylum and class studied led us to conclude that GC content appears to be the primary determinant of the codon and amino acid usage patterns observed in bacterial genomes. These results also indicate that selection for translational efficiency of highly expressed genes is constrained by the genomic parameters associated with the GC content of the host genome.

The GC content of bacterial genomes ranges from 16% to 75% and wide ranges of genomic GC content are observed within many bacterial phyla, including both Gram negative and Gram positive phyla. Thus, divergent genomic GC content has evolved repeatedly in widely separated bacterial taxa. Since genomic GC content influences codon usage, we examined codon usage patterns and predicted protein amino acid content as a function of genomic GC content within eight different phyla or classes of bacteria. We found that similar patterns of codon usage and protein amino acid content have evolved independently in all eight groups of bacteria. For example, in each group, use of amino acids encoded by GC-rich codons increased by approximately 1% for each 10% increase in genomic GC content, while the use of amino acids encoded by AT-rich codons decreased by a similar amount. This consistency within every phylum and class studied led us to conclude that GC content appears to be the primary determinant...

Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with...

Bacteriophage Cr30 has proven useful for the transduction of Caulobacter crescentus. Nucleotide sequencing of Cr30 DNA revealed that the Cr30 genome consists of 155,997 bp of DNA that codes for 287 proteins and five tRNAs. In contrast to the 67 % GC content of the host genome, the GC content of the Cr30 genome is only 38 %. This lower GC content causes both the codon usage pattern and the amino acid composition of the Cr30 proteins to be quite different from those of the host bacteria. As a consequence, the Cr30 mRNAs probably are translated at a rate that is slower than the normal rate for host mRNAs. A phylogenetic comparison of the genome indicates that Cr30 is a member of the T4-like family that is most closely related to a new group of T-like phages exemplified by фM12.

Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 noncoding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.

The GC content of bacterial genomes ranges from 16% to 75% and wide ranges of genomic GC content are observed within many bacterial phyla, including both Gram negative and Gram positive phyla. Thus, divergent genomic GC content has evolved repeatedly in widely separated bacterial taxa. Since genomic GC content influences codon usage, we examined codon usage patterns and predicted protein amino acid content as a function of genomic GC content within eight different phyla or classes of bacteria. We found that similar patterns of codon usage and protein amino acid content have evolved independently in all eight groups of bacteria. For example, in each group, use of amino acids encoded by GC-rich codons increased by approximately 1% for each 10% increase in genomic GC content, while the use of amino acids encoded by ATrich codons decreased by a similar amount. This consistency within every phylum and class studied led us to conclude that GC content appears to be the primary determinant of the codon and amino acid usage patterns observed in bacterial genomes. These results also indicate that selection for translational efficiency of highly expressed genes is constrained by the genomic parameters associated with the GC content of the host genome.

InTRoDuCTIon: DNA barcode, a molecular marker, is used to distinguish among the closely related species, and it can be applied across a broad range of taxa to understand ecology and evolution. MaturaseK gene (matK) and rubisco bisphosphate carboxylase/oxygenase form I gene (rbcL) of the chloroplast are highly conserved in a plant system, which are used as core barcode. This present endeavor entails the comprehensive examination of the under threat plant species based on success of discrimination on DNA barcode under selection pressure. ReSulT: The family Dipterocarpaceae comprising of 15 genera is under threat due to some factors, namely, deforestation, habitat alteration, poor seed, pollen dispersal, etc. Species of this family was grouped into 6 clusters for matK and 5 clusters and 2 sub-clusters for rbcL in the phylogenetic tree by using neighbor-joining method. Cluster I to cluster VI of matK and cluster I to cluster V of rbcL genes were analyzed by various codon and substitution bias tools. Mutational pressure guided the codon bias which was favored by the avoidance of higher GC content and significant negative correlation between GC12 and GC3 (in sub-cluster I of cluster I [0.03 < P], cluster I [0.00001 < P], and cluster II [0.01 < P] of rbcL, and cluster IV [0.013 < P] of matK). After refining the results, it could be speculated that the lower null expectation values (R = 0.5 or <0.5) were less divergent from the evolutionary perspective. Apart from that, the higher null expectation values (R = >0.85) also showed the same result, which possibly could be due to the negative impact of very high and low transition rate than transversion. Through the analysis of inter-generic, inter/intra-specific variation and phylogenetic data, it was found that both selection and mutation played an important role in synonymous codon choice in these genes, but they acted inconsistently on the genes, both matK and rbcL. In vitro stable proteins of both matK and rbcL were selected through natural selection rather than mutational selection. matK gene had higher individual discrimination and barcode success compared with rbcL. These discriminatory approaches may describe the problem related to the extinction of plant species. Hence, it becomes very imperative to identify and detect the under threat plant species in advance.

InTRoDuCTIon: DNA barcode, a molecular marker, is used to distinguish among the closely related species, and it can be applied across a broad range of taxa to understand ecology and evolution. MaturaseK gene (matK) and rubisco bisphosphate carboxylase/oxygenase form I gene (rbcL) of the chloroplast are highly conserved in a plant system, which are used as core barcode. This present endeavor entails the comprehensive examination of the under threat plant species based on success of discrimination on DNA barcode under selection pressure. ReSulT: The family Dipterocarpaceae comprising of 15 genera is under threat due to some factors, namely, deforestation, habitat alteration, poor seed, pollen dispersal, etc. Species of this family was grouped into 6 clusters for matK and 5 clusters and 2 sub-clusters for rbcL in the phylogenetic tree by using neighbor-joining method. Cluster I to cluster VI of matK and cluster I to cluster V of rbcL genes were analyzed by various codon and substitution bias tools. Mutational pressure guided the codon bias which was favored by the avoidance of higher GC content and significant negative correlation between GC12 and GC3 (in sub-cluster I of cluster I [0.03 < P], cluster I [0.00001 < P], and cluster II [0.01 < P] of rbcL, and cluster IV [0.013 < P] of matK). After refining the results, it could be speculated that the lower null expectation values (R = 0.5 or <0.5) were less divergent from the evolutionary perspective. Apart from that, the higher null expectation values (R = >0.85) also showed the same result, which possibly could be due to the negative impact of very high and low transition rate than transversion. Through the analysis of inter-generic, inter/intra-specific variation and phylogenetic data, it was found that both selection and mutation played an important role in synonymous codon choice in these genes, but they acted inconsistently on the genes, both matK and rbcL. In vitro stable proteins of both matK and rbcL were selected through natural selection rather than mutational selection. matK gene had higher individual discrimination and barcode success compared with rbcL. These discriminatory approaches may describe the problem related to the extinction of plant species. Hence, it becomes very imperative to identify and detect the under threat plant species in advance.

Introduction: DNA barcode, a molecular marker, is used to distinguish among the closely related species, and it can be applied across a broad range of taxa to understand ecology and evolution. MaturaseK gene (matK) and rubisco bisphosphate carboxylase/oxygenase form I gene (rbcL) of the chloroplast are highly conserved in a plant system, which are used as core barcode. This present endeavor entails the comprehensive examination of the under threat plant species based on success of discrimination on DNA barcode under selection pressure. Result: The family Dipterocarpaceae comprising of 15 genera is under threat due to some factors, namely, deforestation, habitat alteration, poor seed, pollen dispersal, etc. Species of this family was grouped into 6 clusters for matK and 5 clusters and 2 sub-clusters for rbcL in the phylogenetic tree by using neighbor-joining method. Cluster I to cluster VI of matK and cluster I to cluster V of rbcL genes were analyzed by various codon and substitutio...

is published in The Plant Cell Online, The Plant Cell Preview Section, which publishes manuscripts accepted for publication after they have been edited and the authors have corrected proofs, but before the final, complete issue is published online. Early posting of articles reduces normal time to publication by several weeks.

Background: Synonymous codon usage bias (CUB) modulates gene expression by influencing translational efficiency and accuracy, shaped by mutational biases and natural selection. A unified framework is essential to identify lineage-specific codon preferences and optimize expression and sequence design across species. Methods: Nuclear CDSs from 30 angiosperm species, with a focus on Fabaceae, were analyzed using CodonW to compute gene-level indices (GC/GC3s, ENc, CAI, CBI, Fop). Codon preference patterns were examined through hierarchical clustering, PCA, and analyses of mutational and selective influences using ENc-GC3s plots, neutrality plots, and PR2-bias. Results: Substantial variation in GC3s, ENc, and CAI/CBI/Fop was observed, with patterns aligned with phylogenetic differentiation. PCA revealed clear lineage-level clustering based on codon preferences, with Fabaceae species distinctly separated from Poaceae and other groups. Strong correlations between GC and GC3s, as well as between GC and CBI/Fop, highlighted the pivotal role of base composition in shaping codon preference. Additional analyses indicated that selective pressures, alongside mutational biases, contribute to codon usage, with expression-related indices providing evidence of translation-associated selection. This study establishes a comprehensive framework for understanding codon usage across 30 angiosperms, offering valuable insights for codon optimization and heterologous expression in the molecular breeding of legume crops and other species.

The modest correlation between mRNA expression and protein abundance in large-scale data sets is explained in part by experimental challenges, such as technological limitations, and in part by fundamental biological factors in the transcription and translation processes. Among various factors affecting the mRNA-protein correlation, the roles of biological factors related to translation are poorly understood. In this study, using experimental mRNA expression and protein abundance data collected from Desulfovibrio vulgaris by DNA microarray and liquid chromatography coupled with tandem mass spectrometry (LC-MS/ MS) proteomic analysis, we quantitatively examined the effects of several translational-efficiency-related sequence features on mRNA-protein correlation. Three classes of sequence features were investigated according to different translational stages: (i) initiation, Shine-Dalgarno sequences, start codon identity, and start codon context; (ii) elongation, codon usage and amino acid usage; and (iii) termination, stop codon identity and stop codon context. Surprisingly, although it is widely accepted that translation initiation is the rate-limiting step for translation, our results showed that the mRNA-protein correlation was affected the most by the features at elongation stages, i.e., codon usage and amino acid composition (5.3-15.7% and 5.8-11.9% of the total variation of mRNA-protein correlation, respectively), followed by stop codon context and the Shine-Dalgarno sequence (3.7-5.1% and 1.9-3.8%, respectively). Taken together, all sequence features contributed to 15.2-26.2% of the total variation of mRNA-protein correlation. This study provides the first comprehensive quantitative analysis of the mRNA-protein correlation in bacterial D. vulgaris and adds new insights into the relative importance of various sequence features in prokaryotic protein translation.

Codon optimization' is a general approach that seeks to improve heterologous expression when a gene is moved into a foreign genome that exhibits different codon usage from its native genome. However, it is still unclear exactly what it means to optimize codons for protein expression: diverse interpretations exist, and exploratory research continues. Thus, to facilitate flexible redesign of genes for heterologous expression, we have developed a bona fide web application: the "Synthetic Gene Designer". Compared with existing codon optimization software, the Synthetic Gene Designer provides greater flexibility in several key features of codon optimization strategy. The software, together with online tutorials and help, is available at .

Codon optimization' is a general approach that seeks to improve heterologous expression when a gene is moved into a foreign genome that exhibits different codon usage from its native genome. However, it is still unclear exactly what it means to optimize codons for protein expression: diverse interpretations exist, and exploratory research continues. Thus, to facilitate flexible redesign of genes for heterologous expression, we have developed a bona fide web application: the "Synthetic Gene Designer". Compared with existing codon optimization software, the Synthetic Gene Designer provides greater flexibility in several key features of codon optimization strategy. The software, together with online tutorials and help, is available at .

The manuscript clearly demonstrates that codon optimization improves expression and hence provides a simple but effective way to increase expression levels of the target antigen in a host organism. The underlying approach of expressing Mycobacterium avium paratuberculosis (MAP) genes in Lactobacillus strains is also an interesting idea which has the potential to help immunize cattle against Johne's disease. As this was the first direct assessment of the impact of MAP codon bias on expression in a heterologous host, this study is of importance to the field.

It is well documented that open reading frames containing high GC content show poor expression in A+T rich hosts. Specifically, G+C-rich codon usage is a limiting factor in heterologous expression of Mycobacterium avium subsp. paratuberculosis (MAP) proteins using Lactobacillus salivarius. However, re-engineering opening reading frames through synonymous substitutions can offset codon bias and greatly enhance MAP protein production in this host. In this report, we demonstrate that codon-usage manipulation of MAP2121c can enhance the heterologous expression of the major membrane protein (MMP), analogous to the form in which it is produced natively by MAP bacilli. When heterologously over-expressed, antigenic determinants were preserved in synthetic MMP proteins as shown by monoclonal antibody mediated ELISA. Moreover, MMP is a membrane protein in MAP, which is also targeted to the cellular surface of recombinant L. salivarius at levels comparable to MAP. Additionally, we previously engineered MAP3733c (encoding MptD) and show herein that MptD displays the tendency to associate with the cytoplasmic membrane boundary under confocal microscopy and the intracellularly accumulated protein selectively adheres to the MptD-specific bacteriophage fMptD. This work demonstrates there is potential for L. salivarius as a viable antigen delivery vehicle for MAP, which may provide an effective mucosal vaccine against Johne's disease.

Codon optimization is a commonly used tool in many fields of scientific research to optimize the expression profile of recombinant proteins in a target organism. It seeks to swap synonymous codons in a recombinant gene to reflect the specific codon usage bias of the expression system. While many tools for codon optimization exist, they cannot optimize a single gene for expression in multiple species and are typically limited in their ability to process large sets of genes. Additionally, these tools often only provide a single interface for running optimizations, making them incompatible with existing bioinformatics tools and pipelines. To address these shortcomings we created Optipyzer: an online codon optimization web server with an accompanying web interface and Python package for multi-species codon optimizations. Optipyzer was designed to be fast, flexible, and extensible - providing numerous interfaces for query submission. We believe that Optipyzer can be a powerful tool for t...

Aldehyde dehydrogenase 3B2 (ALDH3B2) gene contains a premature termination codon, which can be skipped or suppressed resulting in full-length protein expression. Alternatively, the longest putative open reading frame starting with the second in-frame start codon would encode short isoform. No unequivocal evidence of ALDH3B2 expression in healthy human tissues is available. The aim of this study was to confirm its expression in human placenta characterized by the highest ALDH3B2 mRNA abundance. ALDH3B2 DNA and mRNA were sequenced. The expression was investigated using western blot. The identity of the protein was confirmed using mass spectrometry (MS). The predicted tertiary and quaternary structures, subcellular localization, and phosphorylation sites were assessed using bioinformatic analyses. All DNA and mRNA isolates contained the premature stop codon. In western blot analyses, bands corresponding to the mass of full-length protein were detected. MS analysis led to the identifica...

Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes for its idiosyncratic behaviour across living kingdoms has proven elusive to researchers over the past 20 years. In this study, a statistical model for measuring translational selection in any given genome is developed, and the test is applied to 126 fully sequenced genomes, ranging from archaea to eukaryotes. It is shown that tRNA gene redundancy and genome size are interacting forces that ultimately determine the action of translational selection, and that an optimal genome size exists for which this kind of selection is maximal. Accordingly, genome size also presents upper and lower boundaries beyond which selection on codon usage is not possible. We propose a model where the coevolution of genome size and tRNA genes explains the observed patterns in translational selection in all living organisms. This model finally unifies our understanding of codon usage across prokaryotes and eukaryotes. Helicobacter pylori, Saccharomyces cerevisiae and Homo sapiens are codon usage paradigms that can be better understood under the proposed model.

The beef tapeworm, also known as Taenia saginata, is a zoonotic tapeworm from the genus Taenia in the order Cyclophyllidea. Taenia saginata is a food-borne zoonotic parasite with a worldwide distribution. It poses serious health risks to the host and has a considerable negative socioeconomic impact. Previous studies have explained the population structure of T. saginata within the evolutionary time scale and adaptive evolution. However, it is still unknown how synonymous codons are used by T. saginata. In this study, we used 90 T. saginata strains, applying the codon usage bias (CUB). Both base content and relative synonymous codon usage (RSCU) analysis revealed that AT-ended codons were more frequently used in the genome of T. saginata. Further low CUB was observed from the effective number of codons (ENC) value. The neutrality plot analysis suggested that the dominant factor of natural selection was involved in the structuring of CUB in T. saginata. Further analysis showed that T....

Background. The discovery of genetic code alterations and expansions in both prokaryotes and eukaryotes abolished the hypothesis of a frozen and universal genetic code and exposed unanticipated flexibility in codon and amino acid assignments. It is now clear that codon identity alterations involve sense and non-sense codons and can occur in organisms with complex genomes and proteomes. However, the biological functions, the molecular mechanisms of evolution and the diversity of genetic code alterations remain largely unknown. In various species of the genus Candida, the leucine CUG codon is decoded as serine by a unique serine tRNA that contains a leucine 59-CAG-39anticodon (tRNA CAG Ser ). We are using this codon identity redefinition as a model system to elucidate the evolution of genetic code alterations. Methodology/Principal Findings. We have reconstructed the early stages of the Candida genetic code alteration by engineering tRNAs that partially reverted the identity of serine CUG codons back to their standard leucine meaning. Such genetic code manipulation had profound cellular consequences as it exposed important morphological variation, altered gene expression, re-arranged the karyotype, increased cell-cell adhesion and secretion of hydrolytic enzymes. Conclusion/Significance. Our study provides the first experimental evidence for an important role of genetic code alterations as generators of phenotypic diversity of high selective potential and supports the hypothesis that they speed up evolution of new phenotypes.

Background: In a wide variety of organisms, synonymous codons are used with different frequencies, a phenomenon known as codon bias that plays an important role in determining expression levels. However, the importance of codon bias to facilitate the simultaneous turnover of thousands of protein-coding transcripts to bring about phenotypic changes in cellular programs such as development, has not yet been investigated in detail. Results: Here, we discover that genes with A/T-ending codon preferences are expressed coordinately and display a high codon conservation in mammals. This feature is not observed in genes enriched in G/C-ending codons. A paradigmatic case of this phenomenon is KRAS, from the RAS family, an A/T-rich gene with a high codon conservation (95%) in comparison to HRAS (76%). Also, we find that genes with similar codon composition are more likely to be part of the same protein complex, and that genes with A/T-ending codons are more prone to form protein complexes tha...

Significance In light of the genetic code, combinations of three nucleotides which are known as synonymous codons, can give rise to the same amino acid. Despite the homology at the protein level, these different codons are recognized distinctly by the translational machinery. The unequal use of synonymous codons influences protein expression. Surprisingly, we find that the coding sequences of KRAS and other frequently mutated cancer genes are adapted to be efficiently translated in proliferating cells in comparison to their family counterparts. Our work contributes to the unsolved question of why in tumors some members of cancer gene families show a higher mutation rate than their family counterparts. Thus, our results elucidate the relationship between tRNA expression, codon usage, and oncogenicity.

SummaryTumors evolve under selection for gene mutations that give a growth advantage to the cancer cell. Intriguingly, some cancer genes are more often found mutated in tumors than their closely related family members. For example, KRAS mutations are more frequently observed in cancer in comparison to HRAS and NRAS. Here, we find that for RAS and six oncogene families, the most prevalent mutated members in cancer have a codon usage characteristic of genes involved in proliferation. The codon usage of KRAS is more adapted to be efficiently translated in proliferative cells than the codon usage of HRAS. We also show that the translation efficiency of KRAS varies between cell lines in a manner related to their tRNA expression. Altogether, our study demonstrates that a dynamic translation program contributes to shaping the expression profiles of oncogenes. We propose that codon bias related to cell proliferation contributes to the prevalence of mutations in certain members of oncogene f...

Codon usage and nucleotide composition of coding sequences have profound effects on protein expression. However, while it is recognized that different tissues have distinct tRNA profiles and codon usages in their transcriptomes, the effect of tissue-specific codon optimality on protein synthesis remains elusive. Here, we leverage existing state-of-the-art transcriptomics and proteomics datasets from the GTEx project and the Human Protein Atlas to compute the protein-to-mRNA ratios of 36 human tissues. Using this as a proxy of translational efficiency, we build a machine learning model that identifies codons enriched or depleted in specific tissues. In particular, we detect two clusters of tissues with an opposite pattern of codon preferences. We then use the identified patterns for the development of CUSTOM, a codon optimizer algorithm which suggests a synonymous codon design in order to optimize protein production in a tissue-specific manner. In a human cell model, we provide evide...