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In 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.

Abstract Codon usage bias (CUB), where certain codons are used more frequently than expected by chance, is a ubiquitous phenomenon and occurs across the tree of life. The dominant paradigm is that the proportion of preferred codons is set by weak selection. While experimental changes in codon usage have at times shown large phenotypic effects in contrast to this paradigm, genome-wide population genetic estimates have supported the weak selection model. Here we use deep genomic population sequencing of two Drosophila melanogaster populations to measure selection on synonymous sites in a way that allowed us to estimate the prevalence of both weak and strong purifying selection. We find that selection in favor of preferred codons ranges from weak (|Nes| ∼ 1) to strong (|Nes| > 10), with strong selection acting on 10–20% of synonymous sites in preferred codons. While previous studies indicated that selection at synonymous sites could be strong, this is the first study to detect and quantify strong selection specifically at the level of CUB. Further, we find that CUB-associated polymorphism accounts for the majority of strong selection on synonymous sites, with secondary contributions of splicing (selection on alternatively spliced genes, splice junctions, and spliceosome-bound sites) and transcription factor binding. Our findings support a new model of CUB and indicate that the functional importance of CUB, as well as synonymous sites in general, have been underestimated.

The central dogma of molecular biology entails that genetic information is transferred from nucleic acid to proteins. Notwithstanding retro-transcribing genetic elements, DNA is transcribed to RNA which in turn is translated into proteins. Recent advancements have shown that each stage is regulated to control protein abundances for a variety of essential physiological processes. In this regard, mRNA regulation is essential in fine-tuning or calibrating protein abundances. In this review, we would like to discuss one of several mRNA-intrinsic features of mRNA regulation that has been gaining traction of recent—codon bias and optimality. Specifically, we address the effects of codon bias with regard to codon optimality in several biological processes centred on translation, such as mRNA stability and protein folding among others. Finally, we examine how different organisms or cell types, through this system, are able to coordinate physiological pathways to respond to a variety of stress or growth conditions.

Background The genus Caragana , known for its adaptability and high forage value, is commonly planted to rehabilitate barren land and prevent desertification. Several Caragana species are also used for medicinal purposes. Analysis of synonymous codon usage bias and their primary influencing factors in chloroplast genomes aims to provide insights into molecular research and germplasm innovation for Caragana plants. Results The GC content of the five Caragana species ranged from 36.00% to 37.10%, showing a preference for codons ending in A/U, although the codon bias was weak. The screening identified nine to twelve optimal codons, but their frequency of use was low. Correlation analysis, neutrality plots, ENC plots and PR2 plots of the parameters identified two potential groups among the five species: Caragana arborescens and Caragana jubata , and Caragana turkestanica , Caragana opulens and Caragana tibetica . These groups showed a high level of intragroup similarity in the parameter analyses. In the RSCU cluster tree analysis, Caragana turkestanica and Caragana arborescens grouped together, while Caragana tibetica , Caragana jubata and Caragana opulens formed a separate clade in the CDS sequence and complete sequence phylogenetic tree analysis. Conclusions The codon usage bias in the chloroplast genomes of the five Caragana species showed high similarity, suggesting that natural selection has a greater influence on codon bias than mutation. Furthermore, the identified optimal codons provide valuable insights for germplasm improvement of Caragana plants.

Background Codon usage bias (CUB) analysis is an effective method for studying specificity, evolutionary relationships, and mRNA translation and discovering new genes among various species. In general, CUB analysis is mainly performed within one species or between closely related species and no such study has been applied among species with distant genetic relationships. Here, seven Rosales species with high economic value were selected to conduct CUB analysis. Results The results showed that the average GC1, GC2 and GC3 contents were 51.08, 40.52 and 43.12%, respectively, indicating that the A/T content is more abundant and the Rosales species prefer A/T as the last codon. Neutrality plot and ENc plot analysis revealed that natural selection was the main factor leading to CUB during the evolution of Rosales species. All 7 Rosales species contained three high-frequency codons, AGA, GTT and TTG, encoding Arg, Val and Leu, respectively. The 7 Rosales species differed in high-frequency codon pairs and the distribution of GC3, though the usage patterns of closely related species were more consistent. The results of the biclustering heat map among 7 Rosales species and 20 other species were basically consistent with the results of genome data, suggesting that CUB analysis is an effective method for revealing evolutionary relationships among species at the family or order level. In addition, chlorophytes prefer using G/C as ending codon, while monocotyledonous and dicotyledonous plants prefer using A/T as ending codon. Conclusions The CUB pattern among Rosales species was mainly affected by natural selection. This work is the first to highlight the CUB patterns and characteristics of Rosales species and provides a new perspective for studying genetic relationships across a wide range of species.

The present study was carried out on 62 genome sequences of members of the family Anelloviridae, as there have been no reports of genome analysis of these DNA viruses using a bioinformatics approach. The genes were found to be rich in AC content with low codon usage bias (CUB). Relative synonymous codon usage (RSCU) values identified the preferred codons for each amino acid in the family. The codon AGA was overrepresented, while the codons TCG, TTG, CGG, CGT, ACG, GCG and GAT were underrepresented in all of the genomes. A significant correlation was found between the effective number of codons (ENC) and base constraints, indicating that compositional properties might have influenced the CUB. A highly significant correlation was observed between the overall base content and the base content at the third codon position, indicating that mutations might have affected the CUB. A highly significant positive correlation was observed between GC12 and GC3 (r = 0.904, p < 0.01), which indicated that directional mutation pressure influenced all three codon positions. A neutrality plot revealed that the contribution of mutation and natural selection in determining the CUB was 58.6% and 41.4%, respectively.

The genetic code, a unifying principle in biology, ensures that all organisms, stemming from a Last Universal Common Ancestor (LUCA), share fundamental rules for translating DNA into proteins. However, codon usage varies across the tree of life, influenced not only by GC-content and proteome composition but also by complex, often less understood rules dependent on each species' evolutionary trajectory. To better understand these rules, we segregated codons into their functional parts and applied Shannon's information-theoretic measures to 1,434 species from eight diverse taxonomic groups. We provide robust evidence that the first codon base plays a central role in amino acid determination, while the third base serves an accessory function. Using conditional entropy measures, we rigorously quantified this relationship, universally confirming the greater informational variability of the third base across all sampled species for the first time at this scale. Our analysis revealed significant heterogeneity in coding strategies across different taxonomic groups. Notably, the unique variability observed in Archaea, in contrast to the more constrained patterns in Eukaryotes and Bacteria, underscores the profound influence of evolutionary pressures and distinct life histories on genetic information processing. The identification of outlier species, exhibiting distinct informational profiles, highlights specific instances where unusual lifestyles or ecological niches may have driven unique adaptations in codon usage and underlying informational dependencies. These informational patterns offer a complementary perspective to traditional phylogenetic analyses, further revealing a hierarchical organization of informational dependencies among codon components that sheds light on the intricate grammar of genetic information. We also rigorously investigated the relationship between GC-content and our informational measures, concluding that these entropy measures provide valuable insights that cannot be obtained from GC-content alone. This work not only offers a novel framework for quantifying informational properties of codon usage but also reveals previously unappreciated aspects of how genetic information is encoded and processed across life's domains.

Porcine epidemic diarrhea virus (PEDV) is an enteric pathogen belonging to the family Coronaviridae that causes the porcine epidemic diarrhea, a highly contagious disease with high mortality in piglets and symptoms that include dehydration and severe diarrhea. Considering the high frequency of genetic mutations in PEDV and its potential for interspecies transmission, as it can infect and replicate in bat and human cells, a comprehensive analysis of its codon usage bias was performed. The effective number of codons (ENC) and the relative synonymous codon usage (RSCU) were determined, revealing codon usage bias in the PEDV genome. Principal component analysis (PCA), an ENC plot, and a parity rule 2 (PR2) plot showed that mutation pressure and natural selection have influenced the codon usage bias of the PEDV genomes. Correlation analysis with GRAVY and aromaticity values and neutrality plot analysis indicated that natural selection was the main force influencing the codon usage pattern, while mutation pressure played a minor role. This study provides valuable basic data for further fundamental research on evolution of PEDV.

Mouse ( Mus musculus ) models have been heavily utilized in developmental biology research to understand mammalian embryonic development, as mice share many genetic, physiological, and developmental characteristics with humans. New explorations into the integration of temporal (stage-specific) and transcriptional (tissue-specific) data have expanded our knowledge of mouse embryo tissue-specific gene functions. To better understand the substantial impact of synonymous mutational variations in the cell-state-specific transcriptome on a tissue’s codon and codon pair usage landscape, we have established a novel resource—Mouse Embryo Codon and Codon Pair Usage Tables (Mouse Embryo CoCoPUTs). This webpage not only offers codon and codon pair usage, but also GC, dinucleotide, and junction dinucleotide usage, encompassing four strains, 15 murine embryonic tissue groups, 18 Theiler stages, and 26 embryonic days. Here, we leverage Mouse Embryo CoCoPUTs and employ the use of heatmaps to depict usage changes over time and a comparison to human usage for each strain and embryonic time point, highlighting unique differences and similarities. The usage similarities found between mouse and human central nervous system data highlight the translation for projects leveraging mouse models. Data for this analysis can be directly retrieved from Mouse Embryo CoCoPUTs. This cutting-edge resource plays a crucial role in deciphering the complex interplay between usage patterns and embryonic development, offering valuable insights into variation across diverse tissues, strains, and stages. Its applications extend across multiple domains, with notable advantages for biotherapeutic development, where optimizing codon usage can enhance protein expression; one can compare strains, tissues, and mouse embryonic stages in one query. Additionally, Mouse Embryo CoCoPUTs holds great potential in the field of tissue-specific genetic engineering, providing insights for tailoring gene expression to specific tissues for targeted interventions. Furthermore, this resource may enhance our understanding of the nuanced connections between usage biases and tissue-specific gene function, contributing to the development of more accurate predictive models for genetic disorders.

Dryas octopetala var. asiatica, a dwarf shrub belonging to the Rosaceae family and native to Asia, exhibits notable plasticity in photosynthesis in response to temperature variations. However, the codon usage patterns and factors influencing them in the chloroplast genome of this species have not yet been documented. This study sequenced and assembled the complete genome of D. octopetala var. asiatica. The annotated genes in the chloroplast genome were analyzed for codon composition through multivariate statistical methods including a neutrality plot, a parity rule 2 (PR2) bias plot, and an effective number of codons (ENC) plot using CodonW 1.4.2 software. The results indicated that the mean GC content of 53 CDSs was 38.08%, with the average GC content at the third codon base position being 27.80%, suggesting a preference for A/U(T) at the third codon position in chloroplast genes. Additionally, the chloroplast genes exhibited a weak overall codon usage bias (CUB) based on ENC values and other indicators. Correlation analysis showed a significant negative correlation between ENC value and GC2, an extremely positive correlation with GC3, but no correlation with GC1 content. These findings highlight the importance of the codon composition at the third position in influencing codon usage bias. Furthermore, our analysis indicated that the CUB of the chloroplast genome of D. octopetala var. asiatica was primarily influenced by natural selection and other factors. Finally, this study identified UCA, CCU, GCU, AAU, GAU, and GGU as the optimal codons. These results offer a foundational understanding for genetic modification and evolutionary dynamics of the chloroplast genome of D. octopetala var. asiatica.