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Ribosome profiling data report on the distribution of translating ribosomes, at steady‐state, with codon‐level resolution. We present a robust method to extract codon translation rates and protein synthesis rates from these data, and identify causal features associated with elongation and translation efficiency in physiological conditions in yeast. We show that neither elongation rate nor translational efficiency is improved by experimental manipulation of the abundance or body sequence of the rare AGG tRNA. Deletion of three of the four copies of the heavily used ACA tRNA shows a modest efficiency decrease that could be explained by other rate‐reducing signals at gene start. This suggests that correlation between codon bias and efficiency arises as selection for codons to utilize translation machinery efficiently in highly translated genes. We also show a correlation between efficiency and RNA structure calculated both computationally and from recent structure probing data, as well as the Kozak initiation motif, which may comprise a mechanism to regulate initiation. Synopsis Ribosome profiling experiments in wild‐type yeast and in mutants with altered tRNA levels illustrate that neither elongation rate nor translational efficiency is affected by tRNA abundance under physiological conditions. A novel statistical model provides robust inference of codon translation rates and protein synthesis rates and hence better measures translation efficiency. Codon translation rates have insignificant correlation with measures of codon bias. Direct experimental manipulation of tRNA abundance does not affect elongation rates on affected codons or translation efficiency of overall genes. Other sequence signals, such as mRNA structure and an initiation sequence motif, correlate to translation efficiency and may be causal determinants. Graphical Abstract Ribosome profiling experiments in wild‐type yeast and in mutants with altered tRNA levels illustrate that neither elongation rate nor translational efficiency is affected by tRNA abundance under physiological 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.

Synonymous codon bias in the viral genome affects protein translation and gene expression, suggesting that the synonymous codon mutant plays an essential role in influencing virulence and evolution. However, how the recessive mutant form contributes to virus evolvability remains elusive. In this paper, we characterize how the Senecavirus A (SVA), a picornavirus, utilizes synonymous codon mutations to influence its evolution, resulting in the adaptive evolution of the virus to adverse environments. The phylogenetic tree and Median-joining (MJ)-Network of these SVA lineages worldwide were constructed to reveal SVA three-stage genetic development clusters. Furthermore, we analyzed the codon bias of the SVA genome of selected strains and found that SVA could increase the GC content of the third base of some amino acid synonymous codons to enhance the viral RNA adaptive evolution. Our results highlight the impact of recessive mutation of virus codon bias on the evolution of the SVA and uncover a previously underappreciated evolutionary strategy for SVA. They also underline the importance of understanding the genetic evolution of SVA and how SVA adapts to the adverse effects of external stress.

The WRKY transcription factor gene family in soybean [Glycine max (L.) Merr.] (GmWRKY) is critical for the plant’s development and stress responses. This study examines the evolutionary dynamics of the GmWRKY gene family, focusing on its synonymous codon usage bias (CUB) in a comprehensive set of 179 coding sequences. CUB was analyzed using various indices, revealing a preference for A/T-ending codons and relatively low codon bias. Codon adaptation index (CAI) analysis suggested that these genes are optimized for efficient translation despite relatively low bias, reflecting a balance between codon diversity and translation efficiency. Neutrality and NC plots indicated that selective forces dominate over mutational forces in shaping codon usage, while selection signature analysis showed purifying selection being prevalent across the gene family. However, episodic positive selection was also detected in certain clades, highlighting potential adaptive diversification in response to environmental stress. Additionally, promoter binding site analysis uncovered correlations between codon usage and transcriptional regulation, indicating a context-dependent relationship between CUB and gene expression. Phylogenetic analysis identified 11 well-supported clades in the modern GmWRKY gene family and ancestral sequence reconstruction revealed more relaxed codon preferences and reduced selection constraints in modern GmWRKY genes, potentially linked to neofunctionalization and adaptation to environmental changes. These findings provide a framework for optimizing gene expression in transgenic soybean crops with resilience. Further functional validation of positively selected genes is recommended to elucidate their role in stress responses.

Synonymous codon usage (codon bias) greatly influences not only translation but also mRNA stability. In vertebrates, highly expressed genes preferentially use codons with an optimal tRNA adaptation index (tAI) that mostly end in C or G. Surprisingly, the codon usage of viruses infecting humans often deviates from optimality, showing an enrichment in A/U-ending codons, which are generally associated with slow decoding and reduced mRNA stability. This observation is particularly evident in RNA viruses causing respiratory illnesses in humans. This review analyzes the mutational and selective forces that shape nucleotide composition and codon usage drift in human RNA viruses, as well as their impact on translation, viral fitness, and evolution. It also describes how some viruses overcome suboptimal codon usage to outcompete host mRNA for translation. Finally, the roles of viral tropism and host adaptation in codon usage bias of prototypical viruses are discussed.

Biased codon usage in protein-coding genes is pervasive, whereby amino acids are largely encoded by a specific subset of possible codons. Within individual genes, codon bias is stronger at evolutionarily conserved residues, favoring codons recognized by abundant tRNAs. Although this observation suggests an overall pattern of selection for translation speed and/or accuracy, other work indicates that transcript structure or binding motifs drive codon usage. However, our understanding of codon bias evolution is constrained by limited experimental data on the fitness effects of altering codons in functional genes. To bridge this gap, we generated synonymous variants of a key enzyme-coding gene in Methylobacterium extorquens. We found that mutant gene expression, enzyme production, enzyme activity, and fitness were all significantly lower than wild-type. Surprisingly, encoding the gene using only rare codons decreased fitness by 40%, whereas an allele coded entirely by frequent codons decreased fitness by more than 90%. Increasing gene expression restored mutant fitness to varying degrees, demonstrating that the fitness disadvantage of synonymous mutants arose from a lack of beneficial protein rather than costs of protein production. Protein production was negatively correlated with the frequency of motifs with high affinity for the anti-Shine-Dalgarno sequence, suggesting ribosome pausing as the dominant cause of low mutant fitness. Together, our data support the idea that, although a particular set of codons are favored on average across a genome, in an individual gene selection can either act for or against codons depending on their local context.

This research aimed to investigate heat shock proteins in the tomato genome through the analysis of amino acids. The highest length among sequences was found in seq19 with 3534 base pairs. This seq19 was reported and contained a family of proteins known as HsfA that have a domain of transcriptional activation for tolerance to heat and other abiotic stresses. The values of the codon adaptation index (CAI) ranged from 0.80 in Seq19 to 0.65 in Seq10, based on the mRNA of heat shock proteins for tomatoes. Asparagine (AAT, AAC), aspartic acid (GAT, GAC), phenylalanine (TTT, TTC), and tyrosine (TAT, TAC) have relative synonymous codon usage (RSCU) values bigger than 0.5. In modified relative codon bias (MRCBS), the high gene expressions of the amino acids under heat stress were histidine, tryptophan, asparagine, aspartic acid, lysine, phenylalanine, isoleucine, cysteine, and threonine. RSCU values that were less than 0.5 were considered rare codons that affected the rate of translation, and thus selection could be effective by reducing the frequency of expressed genes under heat stress. The normal distribution of RSCU shows about 68% of the values drawn from the standard normal distribution were within 0.22 and −0.22 standard deviations that tend to cluster around the mean. The most critical component based on principal component analysis (PCA) was the RSCU. These findings would help plant breeders in the development of growth habits for tomatoes during breeding programs.

In this study, we perform a systematic analysis of evolutionary forces (i.e., mutational bias and natural selection) that shape the codon usage bias of human genes encoding proteins characterized by different flavors of intrinsic disorder. Well-structured proteins are expected to be more under control by purifying natural selection than intrinsically disordered proteins because one or few mutations (even synonymous) in the genes can result in a protein that no longer folds correctly. On the contrary, intrinsically disordered proteins are thought to evolve more rapidly than well-folded proteins, due to a relaxed purifying natural selection and an increased role of mutational bias. Using different bioinformatic tools, we find evidence that codon usage in IDPs is not only affected by a basic mutational bias, but it is also more selectively constrained than the rest of the human proteome. We speculate that intrinsically disordered proteins have not only a high tolerance to mutations but also a selective propensity to preserve their structural disorder under physiological conditions. Additionally, we confirm not only that intrinsically disordered proteins are preferentially encoded by GC-rich genes, but also that they are characterized by the highest fraction of CpG sites in the sequences, implying a higher susceptibility to methylation resulting in C–T transition mutations. Overall, our results corroborate the essential role of intrinsic disorder for the evolutionary adaptability and evolvability of proteins, offering new insight about protein evolution not only in terms of functional properties and roles in diseases but also in terms of evolutionary forces they are subjected to.

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an ‘effective population size’ is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species’ effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback–Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder. Evolution is the process through which populations change over time, starting with mutations in the genetic sequence of an organism. Many of these mutations harm the survival and reproduction of an organism, but only by a very small amount. Some species, especially those with large populations, can purge these slightly harmful mutations more effectively than other species. This fact has been used by the ‘drift barrier theory’ to explain various profound differences amongst species, including differences in biological complexity. In this theory, the effectiveness of eliminating slightly harmful mutations is specified by an ‘effective' population size, which depends on factors beyond just the number of individuals in the population. Effective population size is normally calculated from the amount of time a ‘neutral’ mutation (one with no effect at all) stays in the population before becoming lost or taking over. Estimating this time requires both representative data for genetic diversity and knowledge of the mutation rate. A major limitation is that these data are unavailable for most species. A second limitation is that a brief, temporary reduction in the number of individuals has an oversized impact on the metric, relative to its impact on the number of slighly harmful mutations accumulated. Weibel, Wheeler et al. developed a new metric to more directly determine how effectively a species purges slightly harmful mutations. Their approach is based on the fact that the genetic code has ‘synonymous’ sequences. These sequences code for the same amino acid building block, with one of these sequences being only slightly preferred over others. The metric by Weibel, Wheeler et al. quantifies the proportion of the genome from which less preferred synonymous sequences have been effectively purged. It judges a population to have a higher effective population size when the usage of synonymous sequences departs further from the usage predicted from mutational processes. The researchers expected that natural selection would favour ‘ordered’ proteins with robust three-dimensional structures, i.e., that species with a higher effective population size would tend to have more ordered versions of a protein. Instead, they found the opposite: species with a higher effective population size tend to have more disordered versions of the same protein. This changes our view of how natural selection acts on proteins. Why species are so different remains a fundamental question in biology. Weibel, Wheeler et al. provide a useful tool for future applications of drift barrier theory to a broad range of ways that species differ.

Main conclusionMembers of Apiales are monophyletic and radiated in the Late Cretaceous. Fruit morphologies are critical for Apiales evolution and negative selection and mutation pressure play important roles in environmental adaptation.Apiales include many foods, spices, medicinal, and ornamental plants, but the phylogenetic relationships, origin and divergence, and adaptive evolution remain poorly understood. Here, we reconstructed Apiales phylogeny based on 72 plastid genes from 280 species plastid genomes representing six of seven families of this order. Highly supported phylogenetic relationships were detected, which revealed that each family of Apiales is monophyletic and confirmed that Pennanticeae is a member of Apiales. Genera Centella and Dickinsia are members of Apiaceae, and the genus Hydrocotyle previously classified into Apiaceae is confirmed to belong to Araliaceae. Besides, coalescent phylogenetic analysis and gene trees cluster revealed ten genes that can be used for distinguishing species among families of Apiales. Molecular dating suggested that the Apiales originated during the mid-Cretaceous (109.51 Ma), with the families’ radiation occurring in the Late Cretaceous. Apiaceae species exhibit higher differentiation compared to other families. Ancestral trait reconstruction suggested that fruit morphological evolution may be related to shifts in plant types (herbaceous or woody), which in turn is related to the distribution areas and species numbers. Codon bias and positive selection analyses suggest that negative selection and mutation pressure may play important roles in environmental adaptation of Apiales members. Our results improve the phylogenetic framework of Apiales and provide insights into the origin, divergence, and adaptive evolution of this order and its members.