Codon Usage Bias Of Genes Research Articles

Compositional Features and Codon Usage Pattern of Genes Associated with Parkinson's Disease.

Codon usage bias (CUB) is the phenomenon of non-uniform usage of synonymous codons in which some codons are more used than others and it helps in understanding the molecular organization of genome. Bioinformatic approach was used to analyze the protein-coding sequences of genes associated with Parkinson's disease (PD) to explore compositional features and codon usage pattern as no details work was reported yet. The average improved effective number of codons (Nc) and Nc prime were 42.74 and 44.26 respectively, indicated that CUB was low in these genes. In most of the genes, the overall GC content was almost 50% and GC content at the 1st codon position was the highest while GC content at the 2nd codon position was lowest. Relative synonymous codon usage (RSCU) analysis elucidated over-represented (p > 1.6) and under-represented codons (p < 0.6). The GTG (Val) is the only codon over-represented in all genes. Over-represented codons except (GTG) were A or T ending while under-represented codons (except ACT) were G or C ending. The codons namely TTA (Leu), CTA (Leu), ATC (Ile), ATA (Ile), AGT (Ser), AAC (Asn), TGT (Cys), TGC (Cys), CGC (Arg), AGA (Arg), and AGG (Arg) were absent in SNCA1 to SNCA8 genes. The codon TCG (Ser) was absent in all genes except UCHL1 and PINK1. Correspondence analysis (COA) revealed that the pattern of codon usage differs among genes associated with PD. Neutrality plot analysis indicated some of the points are diagonal distribution suggested that mutation pressure influenced the CUB in genes associated with PD.

Evolution of monkeypox virus from 2017 to 2022: In the light of point mutations.

Monkeypox virus (MPXV) causing multi-country outbreak-2022 is related to viruses caused outbreak-2017-2018 in West Africa. Still not fully understood which proteins of the MPXV discovered in Nigeria in 2017 have mutated through different lineages to the extent that it could cause a multi-country outbreak in 2022; similarly, codon usage bias, host adaptation indices, and the role of selection or mutation pressure in the mutated genes are also not fully studied. Here we report that according to the available sequence data this monkeypox virus acquires point mutations in multiple proteins in each period, and these point mutations accumulate and become a virus that can root outbreak-2022. Viruses exported from Nigeria to Singapore, Israel, and the United Kingdom in 2018-2019 were developed as evolutionary ancestors to B.1 viruses (MPXVs causing multi-country outbreak-2022) through MPXV/United States/2021/MD virus. Although these exported viruses have different amino acid mutations in different proteins, amino acid mutations in 10 proteins are common among them. The MPXV-United Kingdom-P2 virus evolved with only mutations in these 10 proteins and further evolved into MPXV/United States/2021/MD with amino acid mutations in 26 (including amino acid mutations in 10 proteins of the MPXV-United States-P2) proteins. It is noteworthy that specific amino acid mutations in these 22/26 (presence in MPXV/United States/2021/MD) proteins are present in B.1 viruses. Further, analysis of Relative Synonymous Codon Usage (RSCU), Synonymous Codon Usage Fraction (SCUF), and Effective Number of Codons (ENc) revealed codon usage bias in genes that exhibited nucleotide mutations in lineage B.1. Also, host adaptation indices analyzes such as Codon Adaptation Index (CAI), Expected-CAI (eCAI), Relative Codon Deoptimization Index (RCDI) and Expected value for the RCDI (eRCDI) analyzes reveal that the genes that demonstrated nucleotide mutations in lineage B.1 are favorable for human adaptation. Similarly, ENc-GC3s plot, Neutrality plot, and Parity Rule 2 (PR2)-bias plot analyzes suggest a major role of selection pressure than mutation pressure in the evolution of genes displaying nucleotide mutations in lineage B.1. Overall, from 2017 to 2022, MPXV's mutation and spread suggests that this virus continues to evolve through point mutation in the genes according to the available sequence data.

Protein Abundance Prediction Through Machine Learning Methods

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. In this study, we evaluated the effect of codon usage bias of genes on protein abundance. Notably, we observed differences regarding codon usage patterns between genes coding for highly abundant proteins and genes coding for less abundant proteins. Analysis of synonymous codon usage and evolutionary selection showed a clear split between the two groups. Our machine learning models predicted protein abundances from codon usage metrics with remarkable accuracy, achieving strong correlation with experimental data. Upon integration of the predicted protein abundance in enzyme-constrained genome-scale metabolic models, the simulated phenotypes closely matched experimental data, which demonstrates that our predictive models are valuable tools for systems metabolic engineering approaches.

A Crosstalk on Codon Usage in Genes Associated with Leukemia.

Leukemia is the outcome of aggregation of damaged white blood cells. Several genes were reported to be associated with the pathogenesis of leukemia. These genes were computationally analyzed to decipher their codon usage bias (CUB) and to identify the prime factors influencing the codon usage profile as no work was reported yet. The mean values of synonymous codon usage order (SCUO) parameter indicated low CUB of the genes. Significant positive association of SCUO with overall GC and positional GCs might signal the presence of mutational pressure. However, neutrality plot suggested the dominant role of natural selection across the genes. Along with natural selection, the role of mutation pressure was also prominent and that might be responsible for lower CUB (SCUO = 0.19) of genes. Low translational speed might permit accuracy in the process. A strong inverse relationship of translational rate was observed with CUB of genes and folding energy.

The codon usage pattern of genes involved in ovarian cancer.

In this study, we analyzed the compositional dynamics and codon usage pattern of genes involved in ovarian cancer (OC) using a computational method. Mutations in specific genes are associated with OC, and some genes are risk factors for progression of OC, but no work has been reported yet on the codon usage pattern of genes involved in OC. Nucleotide composition analysis of OC-related genes suggested that the overall GC content was higher than AT content; that is, the genes were GC rich. The improved effective number of codons indicated that the overall extent of codon usage bias of genes involved in OC was low. The codons AGC, CTG, ATC, ACC, GTG, and GCC were overrepresented, while the codons TCG, TTA, CTA, CCG, CAA, CGT, ATA, ACG, GTA, GTT, GCG, and GGT were underrepresented in the genes. Correspondence analysis suggested that the codon usage pattern was different in different genes. A highly significant correlation was observed between GC12 and GC3 (r = 0.587, P < 0.01) of genes, suggesting that directional mutation affected the three codon positions. Our report on the codon usage pattern of genes involved in OC includes a new perspective for elucidating the mechanisms of biased usage of synonymous codons, as well as providing useful clues for molecular genetic engineering.

An analysis of codon bias in six red yeast species.

Red yeasts, primarily species of Rhodotorula, Sporobolomyces, and other genera of Pucciniomycotina, are traditionally considered proficient systems for lipid and terpene production, and only recently have also gained consideration for the production of a wider range of molecules of biotechnological potential. Improvements of transgene delivery protocols and regulated gene expression systems have been proposed, but a dearth of information on compositional and/or structural features of genes has prevented transgene sequence optimization efforts for high expression levels. Here, the codon compositional features of genes in six red yeast species were characterized, and the impact that evolutionary forces may have played in shaping this compositional bias was dissected by using several computational approaches. Results obtained are compatible with the hypothesis that mutational bias, although playing a significant role, cannot alone explain synonymous codon usage bias of genes. Nevertheless, several lines of evidences indicated a role for translational selection in driving the synonymous codons that allow high expression efficiency. These optimal synonymous codons are identified for each of the six species analyzed. Moreover, the presence of intragenic patterns of codon usage, which are thought to facilitate polyribosome formation, was highlighted. The information presented should be taken into consideration for transgene design for optimal expression in red yeast species.

Codon usage bias and its influencing factors for Y-linked genes in human

The non-uniform usage of synonymous codons during translation of a protein is the codon usage bias and is mainly influenced by natural selection and mutation pressure. We have used bioinformatic approaches to analyze codon usage bias of human Y-linked genes. Effective number of codon (ENC) suggested that the overall extent of codon usage bias of genes was low. The relative synonymous codon usage (RSCU) analysis revealed that AGA and CTG codons were over-represented in Y-linked genes. Compositional constraint under mutation pressure influenced the codon usage pattern as revealed by the correspondence analysis (COA). Parity plot suggests that both natural selection and mutation pressure might have influenced the codon usage bias of Y-linked genes.

Selfing in Haploid Plants and Efficacy of Selection: Codon Usage Bias in the Model Moss Physcomitrella patens.

A long-term reduction in effective population size will lead to major shift in genome evolution. In particular, when effective population size is small, genetic drift becomes dominant over natural selection. The onset of self-fertilization is one evolutionary event considerably reducing effective size of populations. Theory predicts that this reduction should be more dramatic in organisms capable for haploid than for diploid selfing. Although theoretically well-grounded, this assertion received mixed experimental support. Here, we test this hypothesis by analyzing synonymous codon usage bias of genes in the model moss Physcomitrella patens frequently undergoing haploid selfing. In line with population genetic theory, we found that the effect of natural selection on synonymous codon usage bias is very weak. Our conclusion is supported by four independent lines of evidence: 1) Very weak or nonsignificant correlation between gene expression and codon usage bias, 2) no increased codon usage bias in more broadly expressed genes, 3) no evidence that codon usage bias would constrain synonymous and nonsynonymous divergence, and 4) predominant role of genetic drift on synonymous codon usage predicted by a model-based analysis. These findings show striking similarity to those observed in AT-rich genomes with weak selection for optimal codon usage and GC content overall. Our finding is in contrast to a previous study reporting adaptive codon usage bias in the moss P. patens.

Gene expression, nucleotide composition and codon usage bias of genes associated with human Y chromosome.

Analysis of codon usage pattern is important to understand the genetic and evolutionary characteristics of genomes. We have used bioinformatic approaches to analyze the codon usage bias (CUB) of the genes located in human Y chromosome. Codon bias index (CBI) indicated that the overall extent of codon usage bias was low. The relative synonymous codon usage (RSCU) analysis suggested that approximately half of the codons out of 59 synonymous codons were most frequently used, and possessed a T or G at the third codon position. The codon usage pattern was different in different genes as revealed from correspondence analysis (COA). A significant correlation between effective number of codons (ENC) and various GC contents suggests that both mutation pressure and natural selection affect the codon usage pattern of genes located in human Y chromosome. In addition, Y-linked genes have significant difference in GC contents at the second and third codon positions, expression level, and codon usage pattern of some codons like the SPANX genes in X chromosome.

Synthetic gene design—The rationale for codon optimization and implications for molecular pharming in plants

Degeneracy in the genetic code allows multiple codon sequences to encode the same protein. Codon usage bias in genes is the term given to the preferred use of particular synonymous codons. Synonymous codon substitutions had been regarded as "silent" as the primary structure of the protein was not affected; however, it is now accepted that synonymous substitutions can have a significant effect on heterologous protein expression. Codon optimization, the process of altering codons within the gene sequence to improve recombinant protein expression, has become widely practised. Multiple inter-linked factors affecting protein expression need to be taken into consideration when optimizing a gene sequence. Over the years, various computer programmes have been developed to aid in the gene sequence optimization process. However, as the rulebook for altering codon usage to affect protein expression is still not completely understood, it is difficult to predict which strategy, if any, will design the "optimal" gene sequence. In this review, codon usage bias and factors affecting codon selection will be discussed and the evidence for codon optimization impact will be reviewed for recombinant protein expression using plants as a case study. These developments will be relevant to all recombinant expression systems; however, molecular pharming in plants is an area which has consistently encountered difficulties with low levels of recombinant protein expression, and should benefit from an evidence based rational approach to synthetic gene design. Biotechnol. Bioeng. 2017;114: 492-502. © 2016 Wiley Periodicals, Inc.

GC2 Biology Dictates Gene Expressivity in &lt;i&gt;Camellia sinensis&lt;/i&gt;

The effectiveness of the gene expression is influenced by the nature of codons used throughout the gene. This is due to the fact that most genes and organisms do not use synonymous codons uniformly; certain synonymous codons are used preferentially, a phenomenon called codon usage bias (CUB). Based on the hypothesis that highly expressed genes are often characterized by strong compositional bias in terms of codon usage, there are a number of measures currently in use that quantify codon usage bias in genes, and hence provide numerical indices to predict the expression level of genes. We analyzed normalized AT and GC frequency at each codon site. We observed that correlations between gene expression as measured by CAI and GC content at any codon site are very weak. GC2s showed moderate positive correlation with gene expression. We also measured the correlations between CAI and AT content at three codon sites. AT2s showed moderate negative correlation with gene expression. We further observed a strong correlation between RCBS and protein length indicating natural selection operating in favor of shorter genes to be expressed at higher level. Our analysis revealed that the second position of synonymous codons in Camellia sinensis plays a more prominent role than the third position in determining gene expressivity as evident from CUB and correlation analysis on ten genes.

Antagonistic relationships between intron content and codon usage bias of genes in three mosquito species: functional and evolutionary implications

Genome biology of mosquitoes holds potential in developing knowledge-based control strategies against vectorborne diseases such as malaria, dengue, West Nile, and others. Although the genomes of three major vector mosquitoes have been sequenced, attempts to elucidate the relationship between intron and codon usage bias across species in phylogenetic contexts are limited. In this study, we investigated the relationship between intron content and codon bias of orthologous genes among three vector mosquito species. We found an antagonistic relationship between codon usage bias and the intron number of genes in each mosquito species. The pattern is further evident among the intronless and the intron-containing orthologous genes associated with either low or high codon bias among the three species. Furthermore, the covariance between codon bias and intron number has a directional component associated with the species phylogeny when compared with other nonmosquito insects. By applying a maximum likelihood–based continuous regression method, we show that codon bias and intron content of genes vary among the insects in a phylogeny-dependent manner, but with no evidence of adaptive radiation or species-specific adaptation. We discuss the functional and evolutionary significance of antagonistic relationships between intron content and codon bias.

Codon usage bias: causative factors, quantification methods and genome‐wide patterns: with emphasis on insect genomes

Codon usage bias refers to the phenomenon where specific codons are used more often than other synonymous codons during translation of genes, the extent of which varies within and among species. Molecular evolutionary investigations suggest that codon bias is manifested as a result of balance between mutational and translational selection of such genes and that this phenomenon is widespread across species and may contribute to genome evolution in a significant manner. With the advent of whole-genome sequencing of numerous species, both prokaryotes and eukaryotes, genome-wide patterns of codon bias are emerging in different organisms. Various factors such as expression level, GC content, recombination rates, RNA stability, codon position, gene length and others (including environmental stress and population size) can influence codon usage bias within and among species. Moreover, there has been a continuous quest towards developing new concepts and tools to measure the extent of codon usage bias of genes. In this review, we outline the fundamental concepts of evolution of the genetic code, discuss various factors that may influence biased usage of synonymous codons and then outline different principles and methods of measurement of codon usage bias. Finally, we discuss selected studies performed using whole-genome sequences of different insect species to show how codon bias patterns vary within and among genomes. We conclude with generalized remarks on specific emerging aspects of codon bias studies and highlight the recent explosion of genome-sequencing efforts on arthropods (such as twelve Drosophila species, species of ants, honeybee, Nasonia and Anopheles mosquitoes as well as the recent launch of a genome-sequencing project involving 5000 insects and other arthropods) that may help us to understand better the evolution of codon bias and its biological significance.

Analysis of the codon use frequency of peroxisome proliferator-activated receptors (PPAR) family genes from different species

In mammals, peroxisome proliferator-activated receptors (PPAR) play essential roles in the regulation of cellular differentiation, development, and metabolism (carbohydrate, lipid, protein), and tumorigenesis of higher organisms. In this paper, the relative synonymous codon use frequency of 32 PPAR family genes from seven mammal species (Homo sapiens, Mus musculus, Rattus norvegicus, Bos taurus, Macaca mulatta, Oryctolagus cuniculus, Sus scrofa) were analyzed by correspondence analysis and hierarchical cluster method. The results indicated that the gene function is the dominant factor that determines codon usage bias in PPAR family genes, while species is a minor factor that determines further difference in codon usage bias for genes with similar functions.

Selection on Synonymous Sites for Increased Accessibility around miRNA Binding Sites in Plants

Synonymous codons are widely selected for various biological mechanisms in both prokaryotes and eukaryotes. Recent evidence suggests that microRNA (miRNA) function may affect synonymous codon choices near miRNA target sites. To better understand this, we perform genome-wide analysis on synonymous codon usage around miRNA target sites in four plant genomes. We observed a general trend of increased site accessibility around miRNA target sites in plants. Guanine-cytosine (GC)-poor codons are preferred in the flank region of miRNA target sites. Within-genome analyses show significant variation among miRNA targets in species. GC content of the target gene can partly explain the variation of site accessibility among miRNA targets. miRNA targets in GC-rich genes show stronger selection signals than those in GC-poor genes. Gene's codon usage bias and the conservation level of miRNA and its target also have some effects on site accessibility, but the expression level of miRNA or its target and the mechanism of miRNA activity do not contribute to site accessibility differences among miRNA targets. We suggest that synonymous codons near miRNA targets are selected for efficient miRNA binding and proper miRNA function. Our results present a new dimension of natural selection on synonymous codons near miRNA target sites in plants, which will have important implications of coding sequence evolution.

Translation Efficiency in Upstream Region of microRNA Targets in Arabidopsis thaliana

With respect to upstream regions of microRNA (miRNA) target sites located in protein coding sequences, experimental studies have suggested rare codons, rather than frequent codons, are important for miRNA function, because they slow down the local translational process. But, whether there is a trend of reduced translation efficiency near miRNA targets is still unknown. Using Arabidopsis thaliana, we perform genome-wide analysis of synonymous codon usage in upstream regions of miRNA target sites. At the whole genome level, we find no significant selection signals for decreased translational efficiency. However, the same genome analyses do show substantial variations of translation efficiency reduction among miRNA targets. We find that miRNA conservation level, gene codon usage bias, and the mechanism of miRNA action can account for the differences in translation efficiency. But gene’s GC content, gene expression level, and miRNA target’s conservation level have no effect on local translation efficiency of miRNA targets. Although local translation efficiency in the upstream region of miRNA targets is related to miRNA function in A. thaliana, the selection signal of rare codon usage in that region is weak. We propose some other biological factors are more important than local translation efficiency in miRNA action when miRNA targets are located in protein coding sequences.

Analyzing gene expression from relative codon usage bias in Yeast genome: A statistical significance and biological relevance

Based on the hypothesis that highly expressed genes are often characterized by strong compositional bias in terms of codon usage, there are a number of measures currently in use that quantify codon usage bias in genes, and hence provide numerical indices to predict the expression levels of genes. With the recent advent of expression measure from the score of the relative codon usage bias (RCBS), we have explicitly tested the performance of this numerical measure to predict the gene expression level and illustrate this with an analysis of Yeast genomes. In contradiction with previous other studies, we observe a weak correlations between GC content and RCBS, but a selective pressure on the codon preferences in highly expressed genes. The assertion that the expression of a given gene depends on the score of relative codon usage bias (RCBS) is supported by the data. We further observe a strong correlation between RCBS and protein length indicating natural selection in favour of shorter genes to be expressed at higher level. We also attempt a statistical analysis to assess the strength of relative codon bias in genes as a guide to their likely expression level, suggesting a decrease of the informational entropy in the highly expressed genes.

Analysis of the codon use frequency of AMPK family genes from different species

In mammals, AMP-activated protein kinase (AMPK) is involved in the regulation of cellular energy homeostasis and, on the whole animal level, in regulating energy balance and food intake. In this paper, the relative synonymous codon use frequency of 40 AMPK family genes from seven mammal species (Bos taurus, Homo sapiens, Macaca mulatta, Mus musculus, Pan troglodytes, Rattus norvegicus, Sus scrofa) were analyzed using correspondence analysis and hierarchical cluster method. The result suggests that gene function is the dominant factor that determines codon usage bias in AMPK family genes, while species is a minor factor that determines further difference in codon usage bias for genes with similar functions.

Cluster analysis of the codon use frequency of MHC genes from different species

The relative synonymous codon use frequency of 135 MHC genes from four mammal species ( Homo sapiens, Pan troglodyte, Macaca mulanta and Rattus norvegicus) is analyzed using a hierarchical cluster method. The result suggests that gene function is the dominant factor that determines codon usage bias, while species is a minor factor that determines further difference in codon usage bias for genes with similar functions. The conclusion may be useful in gene classification and gene function prediction.