Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift

Natural Selection Shaped Codon Usage Patterns in Wheat Dwarf Virus in Triticale

Wheat dwarf virus (WDV) poses significant threats to gramineous crops, making it crucial to explore its codon usage patterns and evolutionary dynamics for effective disease control. This study analyzed ten WDV isolates, including two from triticale (WDVT_117 and WDVT_118), using metrics such as relative synonymous codon usage (RSCU), effective number of codons (ENC), codon adaptation index (CAI), and codon bias index (CBI). Neutrality plots, ENC-plots, and PR2-plots were employed to assess the role of mutation and selection. Results revealed weak codon preference in triticale-derived strains (CAI: 0.145-0.269; CBI: -0.042-0.111; ENC > 40), with hierarchical GC content. Neutrality analysis and ENC-plot distributions indicated natural selection as the dominant force, supported by T/C bias at the third codon position (PR2-plot). Shared optimal codons UUC and UAC in highly expressed genes may imply a potential significant role in virus adaptation. RSCU-based clustering and MP phylogenetic analysis revealed that WDVT strains form a distinct cluster with elevated genetic diversity, potentially driven by genomic recombination in the synthetic host. These findings demonstrate that WDVT balances mutational constraints and host adaptation through selective codon optimization. This study provides a foundation for codon-based antiviral research and the development of agricultural strategies to combat WDV infections.

Macroevolutionary changes in natural selection on codon usage reflects evolution of the tRNA pool across a budding yeast subphylum

Across taxonomical domains, synonymous codons of an amino acid are found to be used at unequal frequencies within genes. This codon usage bias (CUB) is highly variable across species. Genome-wide CUB reflects a balance between adaptive and non-adaptive microevolutionary processes within a species. Variation in microevolutionary processes results in across-species variation in CUB. As CUB is tightly linked to important molecular and biophysical processes, it is critical to understand how changes to these processes are linked to changes in microevolutionary processes. We employed a population genetics model to quantify natural selection and mutation biases on a per-codon basis across the Saccharomycotina budding yeast subphylum. We found that the strength of natural selection and mutation biases varied significantly between closely related yeasts. Across-species variation in natural selection reflected the evolution of tRNA gene copy number. Additionally, we found evidence that changes to tRNA modification expression can contribute to changes in natural selection across species independent of changes to tGCN. Both lines of evidence support the link between the evolution of the tRNA pool and natural selection in codon usage through changes in the translation efficiency of a codon. Furthermore, we found that changes to tGCN often reflected changes to genome-wide GC%, suggesting changes to the tRNA pool reflect changes to mutation bias. Our work establishes how changes in microevolutionary processes impact changes in molecular mechanisms, ultimately shaping the macroevolutionary variation of a trait.

Significance statement

Codon usage bias (CUB) - the non-uniform usage of synonymous codons - is a feature of all genomes and varies across closely related species. Differences in CUB imply differences in the underlying microevolutionary processes (natural selection, mutation bias) driving CUB. CUB is hypothesized to be tightly linked to key molecular processes, particularly mRNA translation. We used a population genetics model to quantify natural selection and mutation bias on a per-codon basis across 327 budding yeasts. We found high variability in the microevolution of CUB and showed that changes in natural selection were correlated with the evolution of the tRNA pool. Our work establishes how variation in molecular mechanisms relates to variation in microevolution, shaping variation in a trait across species.

Lost in translation: conserved amino acid usage despite extreme codon bias in foraminifera

Analyses of codon usage in eukaryotes suggest that amino acid usage responds to GC pressure so AT-biased substitutions drive higher usage of amino acids with AT-ending codons. Here, we combine single-cell transcriptomics and phylogenomics to explore codon usage patterns in foraminifera, a diverse and ancient clade of predominantly uncultivable microeukaryotes. We curate data from 1,044 gene families in 49 individuals representing 28 genera, generating perhaps the largest existing dataset of data from a predominantly uncultivable clade of protists, to analyze compositional bias and codon usage. We find extreme variation in composition, with a median GC content at fourfold degenerate silent sites below 3% in some species and above 75% in others. The most AT-biased species are distributed among diverse non-monophyletic lineages. Surprisingly, despite the extreme variation in compositional bias, amino acid usage is highly conserved across all foraminifera. By analyzing nucleotide, codon, and amino acid composition within this diverse clade of amoeboid eukaryotes, we expand our knowledge of patterns of genome evolution across the eukaryotic tree of life.IMPORTANCEPatterns of molecular evolution in protein-coding genes reflect trade-offs between substitution biases and selection on both codon and amino acid usage. Most analyses of these factors in microbial eukaryotes focus on model species such as Acanthamoeba, Plasmodium, and yeast, where substitution bias is a primary contributor to patterns of amino acid usage. Foraminifera, an ancient clade of single-celled eukaryotes, present a conundrum, as we find highly conserved amino acid usage underlain by divergent nucleotide composition, including extreme AT-bias at silent sites among multiple non-sister lineages. We speculate that these paradoxical patterns are enabled by the dynamic genome structure of foraminifera, whose life cycles can include genome endoreplication and chromatin extrusion.

Variation in the fitness impact of translationally optimal codons among animals

Early studies in invertebrate model organisms (fruit flies, nematodes) showed that their synonymous codon usage is under selective pressure to optimize translation efficiency in highly expressed genes (a process called translational selection). In contrast, mammals show little evidence of selection for translationally optimal codons. To understand this difference, we examined the use of synonymous codons in 223 metazoan species, covering a wide range of animal clades. For each species, we predicted the set of optimal codons based on the pool of tRNA genes present in its genome, and we analyzed how the frequency of optimal codons correlates with gene expression to quantify the intensity of translational selection (S). We observed that few metazoans show clear signs of translational selection. As predicted by the nearly neutral theory, the highest values of S are observed in species with large effective population sizes (N e). Overall, however, N e appears to be a poor predictor of the intensity of translational selection, suggesting important differences in the fitness effect of synonymous codon usage across taxa. We propose that the few animal taxa that are clearly affected by translational selection correspond to organisms with strong constraints for a very rapid growth rate.

Codon usage analysis in selected virulence genes of Staphylococcal species

The Staphylococcus genus, composed of Gram-positive bacteria, includes several pathogenic species such as Staphylococcus aureus, S. epidermidis, S. haemolyticus, and S. saprophyticus, each implicated in a range of infections. This study investigates the codon usage patterns in key virulence genes, including Autolysin (alt), Elastin Binding protein (EbpS), Lipase, Thermonuclease, Intercellular Adhesion Protein (IcaR), and V8 Protease, across four Staphylococcus species. Using metrics such as the Effective Number of Codons (ENc), Relative Synonymous Codon Usage (RSCU), Codon Adaptation Index (CAI), alongside neutrality and parity plots, we explored the codon preferences and nucleotide composition biases. Our findings revealed a pronounced AT-rich codon preference, with AT-rich genomes likely aiding in energy-efficient translation and bacterial survival in host environments. These insights provide a deeper understanding of the evolutionary adaptations and translational efficiency mechanisms that contribute to the pathogenicity of Staphylococcus species. This knowledge could pave the way for novel therapeutic interventions targeting codon usage to disrupt virulence gene expression.

Compare Analysis of Codon Usage Bias of Nuclear Genome in Eight Sapindaceae Species

Codon usage bias (CUB) refers to the different frequencies with which various codons are utilized within a genome. Examining CUB is essential for understanding genome structure, function, and evolution. However, little was known about codon usage patterns and the factors influencing the nuclear genomes of eight ecologically significant Sapindaceae species widely utilized for food and medicine. In this study, an analysis of nucleotide composition revealed a higher A/T content and showed a preference for A/T at the third codon position in the eight species of Sapindaceae. A correspondence analysis of relative synonymous codon usage explained only part of the variation, suggesting that not only natural selection but also various other factors contribute to selective constraints on codon bias in the nuclear genomes of the eight Sapindaceae species. Additionally, ENC-GC3 plot, PR2-Bias, and neutrality plot analyses indicated that natural selection exerted a greater influence than mutation pressure across these eight species. Among the eight Sapindaceae species, 16 to 26 optimal codons were identified, with two common high-frequency codons: AGA (encoding Arg) and GCU (encoding Ala). The clustering heat map, which included the 8 Sapindaceae species and 13 other species, revealed two distinct clusters corresponding to monocots and dicots. This finding suggested that CUB analysis was particularly effective in elucidating evolutionary relationships at the family level. Collectively, our results emphasized the distinct codon usage characteristics and unique evolutionary traits of the eight Sapindaceae species.

Description of mitochondrial genomes and phylogenetic analysis of Megophthalminae (Hemiptera: Cicadellidae)

To elucidate phylogenetic relationships within the leafhopper's subfamily Megophthalminae (Hemiptera: Cicadellidae), mitogenomes of 12 species of the subfamily were sequenced and assembled. These were added to the mitogenomes of the eight other species that are currently available. Mitogenome size ranged from 15,193 bp in Onukigallia onukii (Matsumura, 1912) to 15,986 bp in Multinervis guangxiensis (Li and Li, 2013), they all contained 37 genes, and gene order was similar to that in other leafhoppers. Nucleotide composition analysis showed that the AT content was higher than that of GC, and the protein-coding genes usually ended with A/T at the 3rd codon position. The Ka/Ks ratio showed that the CYTB gene has the slowest evolutionary rate, while ND4 is the gene with the fastest evolutionary rate. Relative synonymous codon usage analysis revealed the most frequently used codon was UUA (L), followed by CGA (R), and the least frequently used codon was CCG (P). Parity plot and neutrality plot analyses showed that the codon usage bias of mitochondrial genes was influenced by natural selection and mutation pressure. However, natural selection plays a major role, while the effect of mutation pressure was small. Effective number of codons values were 40.15-49.17, which represented relatively low codon bias. Phylogenetic analyses based on three datasets (AA, 13PCG, 13PCG_2rRNA) using two methods (maximum likelihood and Bayesian inference). In the obtained topology, the Megophthalminae species were clustered into a monophyletic group. In conclusion, our results clarify structural modules of the mitochondrial genes and confirm the monophyly of Megophthalminae within Cicadellidae.

Genome-wide impact of codon usage bias on translation optimization in Drosophila melanogaster

Accuracy and efficiency are fundamental to mRNA translation. Codon usage bias is widespread across species. Despite the long-standing association between optimized codon usage and improved translation, our understanding of its evolutionary basis and functional effects remains limited. Drosophila is widely used to study codon usage bias, but genome-scale experimental data are scarce. Using high-resolution mass spectrometry data from Drosophila melanogaster, we show that optimal codons have lower translation errors than nonoptimal codons after accounting for these biases. Genomic-scale analysis of ribosome profiling data shows that optimal codons are translated more rapidly than nonoptimal codons. Although we find no long-term selection favoring synonymous mutations in D. melanogaster after diverging from D. simulans, we identify signatures of positive selection driving codon optimization in the D. melanogaster population. These findings expand our understanding of the functional consequences of codon optimization and serve as a foundation for future investigations.

Chloroplast genomes of Simarouba Aubl., molecular evolution and comparative analyses within Sapindales

Simarouba, a neotropical genus in the family Simaroubaceae, currently lacks comprehensive genomic data in existing databases. This study aims to fill this gap by providing genomic resources for three Simarouba species, S. amara, S. versicolor, and S. glauca. It also aims to perform comparative molecular evolutionary analyses in relation to other species within the order Sapindales. The analysis of these three Simarouba species revealed the presence of the typical quadripartite structure expected in plastomes. However, some pseudogenization events were identified in the psbC, infA, rpl22, and ycf1 genes. In particular, the CDS of the psbC gene in S. amara was reduced from 1422 bp to 584 bp due to a premature stop codon. Nucleotide diversity data pointed to gene and intergenic regions as promising candidates for species and family discrimination within the group, specifically matK, ycf1, ndhF, rpl32, petA-psbJ, and trnS-trnG. Selection signal analyses showed strong evidence for positive selection on the rpl23 gene. Phylogenetic analyses indicated that S. versicolor and S. glauca have a closer phylogenetic relationship than S. amara. We provide chloroplast genomes of three Simaruba species and use them to elucidate plastome evolution, highlight the presence of pseudogenization, and identify potential DNA barcode regions.

Comparative genome wise analysis of codon usage of Staphylococcus Genus

The genus Staphylococcus encompasses a diverse array of bacteria with significant implications for human health, including disreputable pathogens such as Staphylococcus aureus and Staphylococcus epidermidis. Understanding the genetic composition and codon usage patterns of Staphylococcus species is crucial for unraveling their evolutionary dynamics, adaptive strategies, and pathogenic potential. In this study, we conducted a comprehensive analysis of codon usage patterns across 48 species within the Staphylococcus genus. Our findings uncovered variations in genomic G-C content across Staphylococcus species, impacting codon usage preferences, with a notable preference for A/T-rich codons observed in pathogenic strains. This preference for A/T-rich codons suggests an energy-saving strategy in pathogenic organisms. Analysis of dinucleotide pair expression patterns unveiled insights into genomic dynamics, with overrepresented codon pairs reflecting trends in dinucleotide expression across genomes. Additionally, a significant correlation between CAI and genomic G-C content underscored the intricate relationship between codon usage patterns and gene expression strategies. Amino acid usage analysis highlighted preferences for energetically cheaper amino acids, suggesting adaptive strategies promoting energy efficiency. This comprehensive analysis sheds light on the evolutionary dynamics and adaptive mechanisms employed by Staphylococcus species, providing valuable insights into their pathogenic potential and clinical implications. Understanding these genomic features is crucial for devising strategies to combat staphylococcal infections and improve public health outcomes.

Understanding the nucleotide composition and patterns of codon usage in the expression of human oral cancer genes

Oral squamous cell carcinoma (OSCC) is primarily known as oral cancer (OC) that mostly occurs in mouth, lips and tongue. Mutations in some of the genes cause OC and some genes are risk factors for progression of OC. In this study, we analyzed the compositional features and pattern of codon usage in genes involved in OC using computational method as no work was reported yet. Compositional features suggested that the overall GC content was higher i.e. genes were GC rich. Effective number of codons (ENC) values ranged from 34.6 to 55.9 with a mean value of 49.03±4.22 representing low codon usage bias (CUB). Correspondence analysis (COA) suggested that the codon usage pattern was different in different genes. In genes associated with OC, highly significant correlation was observed between GC12 and GC3 (r=0.454, p<0.01) suggesting that directional mutation affected all the three codon positions. This is the first report on pattern of codon usage pattern on genes involved in OC, which not only alludes a new perspective for elucidating the mechanisms of biased usage of synonymous codons but also provide valuable clues for molecular genetic engineering.

tRNA modification reprogramming contributes to artemisinin resistance in Plasmodium falciparum

Plasmodium falciparum artemisinin (ART) resistance is driven by mutations in kelch-like protein 13 (PfK13). Quiescence, a key aspect of resistance, may also be regulated by a yet unidentified epigenetic pathway. Transfer RNA modification reprogramming and codon bias translation is a conserved epitranscriptomic translational control mechanism that allows cells to rapidly respond to stress. We report a role for this mechanism in ART-resistant parasites by combining tRNA modification, proteomic and codon usage analyses in ring-stage ART-sensitive and ART-resistant parasites in response to drug. Post-drug, ART-resistant parasites differentially hypomodify mcm5s2U on tRNA and possess a subset of proteins, including PfK13, that are regulated by Lys codon-biased translation. Conditional knockdown of the terminal s2U thiouridylase, PfMnmA, in an ART-sensitive parasite background led to increased ART survival, suggesting that hypomodification can alter the parasite ART response. This study describes an epitranscriptomic pathway via tRNA s2U reprogramming that ART-resistant parasites may employ to survive ART-induced stress.

Re-examining Correlations Between Synonymous Codon Usage and Protein Bond Angles in Escherichia coli

Rosenberg AA, Marx A, Bronstein AM (Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. Nat Commun. 2022:13:2815) recently found a surprising correlation between synonymous codon usage and the dihedral bond angles of the resulting amino acid. However, their analysis did not account for the strongest known correlate of codon usage: gene expression. We re-examined the relationship between bond angles and codon usage by applying the approach of Rosenberg et al. to simulated protein-coding sequences that (i) have random codon usage, (ii) codon usage determined by mutation biases, and (iii) maintain the general relationship between codon usage and gene expression via the assumption of selection-mutation-drift equilibrium. We observed correlations between dihedral bond angle and codon usage when codon usage is entirely random, indicating possible conflation of noise with differences in bond angle distributions between synonymous codons. More relevant to the general analysis of codon usage patterns, we found surprisingly good agreement between the analysis of the real sequences and the analysis of sequences simulated assuming selection-mutation-drift equilibrium, with 91% of significant synonymous codon pairs detected in the former were also detected in the latter. We believe the correlation between codon usage and dihedral bond angles resulted from the variation in codon usage across genes due to the interplay between mutation bias, natural selection for translation efficiency, and gene expression, further underscoring these factors must be controlled for when looking for novel patterns related to codon usage.

Analysis of codon usage bias of exonuclease genes in invertebrate iridescent viruses

Invertebrate iridescent viruses (IIVs) are double-stranded DNA viruses that belong to the Iridoviridae family. IIVs result diseases that vary in severity from subclinical to lethal in invertebrate hosts. Codon usage bias (CUB) analysis is a versatile method for comprehending the genetic and evolutionary aspects of species. In this study, we analyzed the CUB in 10 invertebrate iridescent viruses exonuclease genes by calculating and comparing the nucleotide contents, effective number of codons (ENC), codon adaptation index (CAI), relative synonymous codon usage (RSCU), and others. The results revealed that IIVs exonuclease genes are rich in A/T. The ENC analysis displayed a low codon usage bias in IIVs exonuclease genes. ENC-plot, neutrality plot, and parity rule 2 plot demonstrated that besides mutational pressure, other factors like natural selection, dinucleotide content, and aromaticity also contributed to CUB. The findings could enhance our understanding of the evolution of IIVs exonuclease genes.

Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing

Transfer RNAs (tRNAs) play a central role in protein translation. Studying them has been difficult in part because a simple method to simultaneously quantify their abundance and chemical modifications is lacking. Here we introduce Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations that provides quantitative estimates of both tRNA abundances and modification dynamics in a single experiment. We show that default nanopore sequencing settings discard the vast majority of tRNA reads, leading to poor sequencing yields and biased representations of tRNA abundances based on their transcript length. Re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads and enables recapitulation of accurate tRNA abundances. We then apply Nano-tRNAseq to Saccharomyces cerevisiae tRNA populations, revealing crosstalks and interdependencies between different tRNA modification types within the same molecule and changes in tRNA populations in response to oxidative stress.

Systematic analysis of the codon usage patterns of African swine fever virus genome coding sequences reveals its host adaptation phenotype

African swine fever (ASF) is a severe haemorrhagic disease caused by the African swine fever virus (ASFV), transmitted by ticks, resulting in high mortality among domestic pigs and wild boars. The global spread of ASFV poses significant economic threats to the swine industry. This study employs diverse analytical methods to explore ASFV's evolution and host adaptation, focusing on codon usage patterns and associated factors. Utilizing phylogenetic analysis methods including neighbour-joining and maximum-likelihood, 64 ASFV strains were categorized into four clades. Codon usage bias (CUB) is modest in ASFV coding sequences. This research identifies multiple factors - such as nucleotide composition, mutational pressures, natural selection and geographical diversity - contributing to the formation of CUB in ASFV. Analysis of relative synonymous codon usage reveals CUB variations within clades and among ASFVs and their hosts. Both Codon Adaptation Index and Similarity Index analyses confirm that ASFV strains are highly adapted to soft ticks (Ornithodoros moubata) but less so to domestic pigs, which could be a result of the long-term co-evolution of ASFV with ticks. This study sheds light on the factors influencing ASFV's codon usage and fitness dynamics, enriching our understanding of its evolution, adaptation and host interactions.

Growth-dependent Gene Expression Variation Influences the Strength of Codon Usage Biases

The most highly expressed genes in microbial genomes tend to use a limited set of synonymous codons, often referred to as "preferred codons." The existence of preferred codons is commonly attributed to selection pressures on various aspects of protein translation including accuracy and/or speed. However, gene expression is condition-dependent and even within single-celled organisms transcript and protein abundances can vary depending on a variety of environmental and other factors. Here, we show that growth rate-dependent expression variation is an important constraint that significantly influences the evolution of gene sequences. Using large-scale transcriptomic and proteomic data sets in Escherichia coli and Saccharomyces cerevisiae, we confirm that codon usage biases are strongly associated with gene expression but highlight that this relationship is most pronounced when gene expression measurements are taken during rapid growth conditions. Specifically, genes whose relative expression increases during periods of rapid growth have stronger codon usage biases than comparably expressed genes whose expression decreases during rapid growth conditions. These findings highlight that gene expression measured in any particular condition tells only part of the story regarding the forces shaping the evolution of microbial gene sequences. More generally, our results imply that microbial physiology during rapid growth is critical for explaining long-term translational constraints.

Mega-scale experimental analysis of protein folding stability in biology and design

Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale1. However, the energetics driving folding are invisible in these structures and remain largely unknown2. The hidden thermodynamics of folding can drive disease3,4, shape protein evolution5-7 and guide protein engineering8-10, and new approaches are needed to reveal these thermodynamics for every sequence and structure. Here we present cDNA display proteolysis, a method for measuring thermodynamic folding stability for up to 900,000 protein domains in a one-week experiment. From 1.8 million measurements in total, we curated a set of around 776,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 331 natural and 148 de novo designed protein domains 40-72 amino acids in length. Using this extensive dataset, we quantified (1) environmental factors influencing amino acid fitness, (2) thermodynamic couplings (including unexpected interactions) between protein sites, and (3) the global divergence between evolutionary amino acid usage and protein folding stability. We also examined how our approach could identify stability determinants in designed proteins and evaluate design methods. The cDNA display proteolysis method is fast, accurate and uniquely scalable, and promises to reveal the quantitative rules for how amino acid sequences encode folding stability.

The genome of Candidatus phytoplasma ziziphi provides insights into their biological characteristics

Phytoplasmas are obligate cell wall-less prokaryotic bacteria that primarily multiply in plant phloem tissue. Jujube witches' broom (JWB) associated with phytoplasma is a destructive disease of jujube (Ziziphus jujuba Mill.). Here we report the complete 'Candidatus Phytoplasma ziziphi' chromosome of strain Hebei-2018, which is a circular genome of 764,108-base pairs with 735 predicted CDS. Notably, extra 19,825 bp (from 621,995 to 641,819 bp) compared to the previously reported one complements the genes involved in glycolysis, such as pdhA, pdhB, pdhC, pdhD, ackA, pduL and LDH. The synonymous codon usage bias (CUB) patterns by using comparative genomics analysis among the 9 phytoplasmas were similar for most codons. The ENc-GC3s analysis among the 9 phytoplasmas showed a greater effect under the selection on the CUBs of phytoplasmas genes than mutation and other factors. The genome exhibited a strongly reduced ability in metabolic synthesis, while the genes encoding transporter systems were well developed. The genes involved in sec-dependent protein translocation system were also identified.The expressions of nine FtsHs encoding membrane associated ATP-dependent Zn proteases and Mn-SodA with redox capacity in the Ca. P. ziziphi was positively correlated with the phytoplasma concentration. Taken together, the genome will not only expand the number of phytoplasma species and provide some new information about Ca. P. ziziphi, but also contribute to exploring its pathogenic mechanism.

Analysis of Codon Usage Bias in Xyloglucan Endotransglycosylase (XET) Genes

Xyloglucan endotransglycosylase (XET) genes are widely distributed in most plants, but the codon usage bias of XET genes has remained uncharacterized. Thus, we analyzed the codon usage bias using 4500 codons of 20 XET genes to elucidate the genetic and evolutionary patterns. Phylogenetic and hierarchical cluster analyses revealed that the 20 XET genes belonged to two groups. The closer the genetic distance, the more similar the codon usage preference. The codon usage bias of most XET genes was weak, but there was also some codon usage bias. AGA, AGG, AUC, and GUG were the top four codons (RSCU > 1.5) in the 20 XET genes. CitXET had a stronger codon usage bias, and there were eight optimal codons of CitXET (i.e., AGA, AUU, UCU, CUU, CCA, GCU, GUU, and AAA). The RSCU values underwent a correspondence analysis. The two main factors affecting codon usage bias (i.e., Axes 1 and 2) accounted for 54.8% and 17.6% of the total variation, respectively. Multiple correspondence analysis revealed that XET genes were widely distributed, with Group 1 genes being closer to Axis 1 than Group 2 genes, which were closer to Axis 2. Codons with A/U at the third codon position were distributed closer to Axis 1 than codons with G/C at the third codon position. PgXET, ZmXET, VlXET, VrXET, and PcXET were biased toward codons ending with G/C. In contrast, CitXET, DpXET, and BrpXET were strongly biased toward codons ending with A/U, indicating that these XET genes have a strong codon usage bias. Translational selection and base composition (especially A and U at the third codon position), followed by mutation pressure and natural selection, may be the most important factors affecting codon usage of 20 XET genes. These results may be useful in clarifying the codon usage bias of XET genes and the relevant evolutionary characteristics.

Codon usage bias and genetic diversity in chloroplast genomes of Elaeagnus species (Myrtiflorae: Elaeagnaceae)

Codon usage bias (CUB) reveals the characteristics of species and can be utilized to understand their evolutionary relationship, increase the target genes' expression in the heterologous receptor plants, and further provide theoretic assistance for correlative study on molecular biology and genetic breeding. The chief aim of this work was to analyze the CUB in chloroplast (cp.) genes in nine Elaeagnus species to provide references for subsequent studies. The codons of Elaeagnus cp. genes preferred to end with A/T bases rather than with G/C bases. Most of the cp. genes were prone to mutation, while the rps7 genes were identical in sequences. Natural selection was inferred to have a powerful impact on the CUB in Elaeagnus cp. genomes, and their CUB was extremely strong. In addition, the optimal codons were identified in the nine cp. genomes based on the relative synonymous codon usage (RSCU) values, and the optimal codon numbers were between 15 and 19. The clustering analyses based on RSCU were contrasted with the maximum likelihood (ML)-based phylogenetic tree derived from coding sequences, suggesting that the t-distributed Stochastic Neighbor Embedding clustering method was more appropriate for evolutionary relationship analysis than the complete linkage method. Moreover, the ML-based phylogenetic tree based on the conservative matK genes and the whole cp. genomes had visible differences, indicating that the sequences of specific cp. genes were profoundly affected by their surroundings. Following the clustering analysis, Arabidopsis thaliana was considered the optimal heterologous expression receptor plant for the Elaeagnus cp. genes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01289-6.

Chloroplast gene expression level is negatively correlated with evolutionary rates and selective pressure while positively with codon usage bias in Ophioglossum vulgatum L

BACKGROUND

Characterization of the key factors determining gene expression level has been of significant interest. Previous studies on the relationship among evolutionary rates, codon usage bias, and expression level mostly focused on either nuclear genes or unicellular/multicellular organisms but few in chloroplast (cp) genes. Ophioglossum vulgatum is a unique fern and has important scientific and medicinal values. In this study, we sequenced its cp genome and transcriptome to estimate the evolutionary rates (dN and dS), selective pressure (dN/dS), gene expression level, codon usage bias, and their correlations.

RESULTS

The correlation coefficients between dN, dS, and dN/dS, and Transcripts Per Million (TPM) average values were -0.278 (P = 0.027 < 0.05), -0.331 (P = 0.008 < 0.05), and -0.311 (P = 0.013 < 0.05), respectively. The codon adaptation index (CAI) and tRNA adaptation index (tAI) were significantly positively correlated with TPM average values (P < 0.05).

CONCLUSIONS

Our results indicated that when the gene expression level was higher, the evolutionary rates and selective pressure were lower, but the codon usage bias was stronger. We provided evidence from cp gene data which supported the E-R (E stands for gene expression level and R stands for evolutionary rate) anti-correlation.

Evolutionary dynamics of codon usages for peste des petits ruminants virus

Peste des petits ruminants virus (PPRV) is an important agent of contagious, acute and febrile viral diseases in small ruminants, while its evolutionary dynamics related to codon usage are still lacking. Herein, we adopted information entropy, the relative synonymous codon usage values and similarity indexes and codon adaptation index to analyze the viral genetic features for 45 available whole genomes of PPRV. Some universal, lineage-specific, and gene-specific genetic features presented by synonymous codon usages of the six genes of PPRV that encode N, P, M, F, H and L proteins reflected evolutionary plasticity and independence. The high adaptation of PPRV to hosts at codon usages reflected high viral gene expression, but some synonymous codons that are rare in the hosts were selected in high frequencies in the viral genes. Another obvious genetic feature was that the synonymous codons containing CpG dinucleotides had weak tendencies to be selected in viral genes. The synonymous codon usage patterns of PPRV isolated during 2007–2008 and 2013–2014 in China displayed independent evolutionary pathway, although the overall codon usage patterns of these PPRV strains matched the universal codon usage patterns of lineage IV. According to the interplay between nucleotide and synonymous codon usages of the six genes of PPRV, the evolutionary dynamics including mutation pressure and natural selection determined the viral survival and fitness to its host.

PP2C1 fine-tunes melatonin biosynthesis and phytomelatonin receptor PMTR1 binding to melatonin in cassava

Melatonin is an important molecule in both animals and plants, regulating circadian rhythms and stress responses. Therefore, the improvement of melatonin accumulation not only strengthens the function of melatonin but also improves stress resistance in crops. Although melatonin biosynthetic enzymes have been identified through reverse genetics previously, an investigation of melatonin level-related genes through forward genetics in plants has yet to be performed. In this study, a genome-wide association study using cassava natural population of 298 genetic resources identified melatonin accumulation 1 (MA1), which regulates the natural variation of melatonin levels in cassava. We found that MA1 encodes type 2C protein phosphatase 1 (PP2C1), which serves as a negative regulator of melatonin levels in cassava. MePP2C1 physically interacts with MeRAV1/2 and MeWRKY20 and dephosphorylates them at serine (S) 35 residue, S34 residue, and S176 residue, respectively, thereby hindering their transcriptional activation on downstream melatonin biosynthetic genes. Notably, MePP2C1 interacts with phytomelatonin receptor MePMTR1 and dephosphorylates it at S11 residue, repressing its binding to melatonin. In summary, this study demonstrates that MePP2C1 as MA1 plays dual roles in negatively regulating both melatonin accumulation and signaling, extending the understanding of the molecular mechanism underlying melatonin accumulation and signaling through forward genetics in plants.

Codon Usage Bias Correlates With Gene Length in Neurodegeneration Associated Genes

Codon usage analysis is a crucial part of molecular characterization and is used to determine the factors affecting the evolution of a gene. The length of a gene is an important parameter that affects the characteristics of the gene, such as codon usage, compositional parameters, and sometimes, its functions. In the present study, we investigated the association of various parameters related to codon usage with the length of genes. Gene expression is affected by nucleotide disproportion. In sixty genes related to neurodegenerative disorders, the G nucleotide was the most abundant and the T nucleotide was the least. The nucleotide T exhibited a significant association with the length of the gene at both the overall compositional level and the first and second codon positions. Codon usage bias (CUB) of these genes was affected by pyrimidine and keto skews. Gene length was found to be significantly correlated with codon bias in neurodegeneration associated genes. In gene segments with lengths below 1,200 bp and above 2,400 bp, CUB was positively associated with length. Relative synonymous CUB, which is another measure of CUB, showed that codons TTA, GTT, GTC, TCA, GGT, and GGA exhibited a positive association with length, whereas codons GTA, AGC, CGT, CGA, and GGG showed a negative association. GC-ending codons were preferred over AT-ending codons. Overall analysis indicated that the association between CUB and length varies depending on the segment size; however, CUB of 1,200–2,000 bp gene segments appeared not affected by gene length. In synopsis, analysis suggests that length of the genes correlates with various imperative molecular signatures including A/T nucleotide disproportion and codon choices. In the present study we additionally evaluated various molecular features and their correlation with different indices of codon usage, like the Codon Adaptation Index (CAI) and Relative Dynonymous Codon Usage (RSCU) of codons. We also considered the impact of gene fragment size on different molecular features in genes related to neurodegeneration. This analysis will aid our understanding of and in potentially modulating gene expression in cases of defective gene functioning in clinical settings.

Intragenomic variation in non-adaptive nucleotide biases causes underestimation of selection on synonymous codon usage

Patterns of non-uniform usage of synonymous codons vary across genes in an organism and between species across all domains of life. This codon usage bias (CUB) is due to a combination of non-adaptive (e.g. mutation biases) and adaptive (e.g. natural selection for translation efficiency/accuracy) evolutionary forces. Most models quantify the effects of mutation bias and selection on CUB assuming uniform mutational and other non-adaptive forces across the genome. However, non-adaptive nucleotide biases can vary within a genome due to processes such as biased gene conversion (BGC), potentially obfuscating signals of selection on codon usage. Moreover, genome-wide estimates of non-adaptive nucleotide biases are lacking for non-model organisms. We combine an unsupervised learning method with a population genetics model of synonymous coding sequence evolution to assess the impact of intragenomic variation in non-adaptive nucleotide bias on quantification of natural selection on synonymous codon usage across 49 Saccharomycotina yeasts. We find that in the absence of a priori information, unsupervised learning can be used to identify genes evolving under different non-adaptive nucleotide biases. We find that the impact of intragenomic variation in non-adaptive nucleotide bias varies widely, even among closely-related species. We show that the overall strength and direction of translational selection can be underestimated by failing to account for intragenomic variation in non-adaptive nucleotide biases. Interestingly, genes falling into clusters identified by machine learning are also physically clustered across chromosomes. Our results indicate the need for more nuanced models of sequence evolution that systematically incorporate the effects of variable non-adaptive nucleotide biases on codon frequencies.

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Background

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.

Results

Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.

Conclusions

Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08635-0).

The genomic basis of host and vector specificity in non-pathogenic trypanosomatids

Trypanosoma theileri, a non-pathogenic parasite of bovines, has a predicted surface protein architecture that likely aids survival in its mammalian host. Their surface proteins are encoded by genes which account for ∼10% of their genome. A non-pathogenic parasite of sheep, Trypanosoma melophagium, is transmitted by the sheep ked and is closely related to T. theileri. To explore host and vector specificity between these species, we sequenced the T. melophagium genome and transcriptome and an annotated draft genome was assembled. T. melophagium was compared to 43 kinetoplastid genomes, including T. theileri. T. melophagium and T. theileri have an AT biased genome, the greatest bias of publicly available trypanosomatids. This trend may result from selection acting to decrease the genomic nucleotide cost. The T. melophagium genome is 6.3Mb smaller than T. theileri and large families of proteins, characteristic of the predicted surface of T. theileri, were found to be absent or greatly reduced in T. melophagium. Instead, T. melophagium has modestly expanded protein families associated with the avoidance of complement-mediated lysis. We propose that the contrasting genomic features of these species is linked to their mode of transmission from their insect vector to their mammalian host. This article has an associated First Person interview with the first author of the paper.

Calculating and comparing codon usage values in rare disease genes highlights codon clustering with disease-and tissue- specific hierarchy

We designed a novel strategy to define codon usage bias (CUB) in 6 specific small cohorts of human genes. We calculated codon usage (CU) values in 29 non-disease-causing (NDC) and 31 disease-causing (DC) human genes which are highly expressed in 3 distinct tissues, kidney, muscle, and skin. We applied our strategy to the same selected genes annotated in 15 mammalian species. We obtained CUB hierarchical clusters for each gene cohort which showed tissue-specific and disease-specific CUB fingerprints. We showed that DC genes (especially those expressed in muscle) display a low CUB, well recognizable in codon hierarchical clustering. We defined the extremely biased codons as "zero codons" and found that their number is significantly higher in all DC genes, all tissues, and that this trend is conserved across mammals. Based on this calculation in different gene cohorts, we identified 5 codons which are more differentially used across genes and mammals, underlining that some genes have favorite synonymous codons in use. Since of the muscle genes clear clusters, and, among these, dystrophin gene surprisingly does not show any "zero codon" we adopted a novel approach to study CUB, we called "mapping-on-codons". We positioned 2828 dystrophin missense and nonsense pathogenic variations on their respective codon, highlighting that its frequency and occurrence is not dependent on the CU values. We conclude our strategy consents to identify a hierarchical clustering of CU values in a gene cohort-specific fingerprints, with recognizable trend across mammals. In DC muscle genes also a disease-related fingerprint can be observed, allowing discrimination between DC and NDC genes. We propose that using our strategy which studies CU in specific gene cohorts, as rare disease genes, and tissue specific genes, may provide novel information about the CUB role in human and medical genetics, with implications on synonymous variations interpretation and codon optimization algorithms.

The Codon Usage Bias Analysis of Free-Living Ciliates' Macronuclear Genomes and Clustered Regularly Interspaced Short Palindromic Repeats/Cas9 Vector Construction of Stylonychia lemnae

Ciliates represent higher unicellular animals, and several species are also important model organisms for molecular biology research. Analyses of codon usage bias (CUB) of the macronuclear (MAC) genome in ciliates can not only promote a better understanding of the genetic mode and evolution history of these organisms but also help optimize codons to improve the gene editing efficiency of model ciliates. In this study, macronuclear genome sequences of nine free-living ciliates were analyzed with CodonW software to calculate the following indices: the guanine-cytosine content (GC); the frequency of the nucleotides U, C, A, and G at the third position of codons (U3s, C3s, A3s, G3s); the effective number of codons (ENC); the correlation between GC at the first and second positions (GC12); the frequency of the nucleotides G + C at the third position of synonymous codons (GC3s); the relative synonymous codon usage (RSCU). Parity rule 2 plot analysis, neutrality plot analysis, and correlation analysis were performed to explore the factors that influence codon preference. The results showed that the GC contents in nine ciliates' MAC genomes were lower than 50% and appeared AT-rich. The base compositions of GC12 and GC3s are markedly distinct and the codon usage pattern and evolution of ciliates are affected by genetic mutation and natural selection. According to the synonymous codon analysis, the codons of most ciliates ended with A or U and eight codons were the general optimal codons of nine ciliates. A clustered regularly interspaced short palindromic repeats/Cas9 (CRISPR/Cas9) expression vector of Stylonychia lemnae was constructed by optimizing the macronuclear genome codon and was successfully used to knock out the Adss gene. This is the first such extensive investigation of the MAC genome CUB of ciliates and the initial successful application of the CRISPR/Cas9 technique in free-living ciliates.

CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern

There is a growing appreciation that synonymous codon usage, although historically regarded as phenotypically silent, can instead alter a wide range of mechanisms related to functional protein production, a term we use here to describe the net effect of transcription (mRNA synthesis), mRNA half-life, translation (protein synthesis) and the probability of a protein folding correctly to its active, functional structure. In particular, recent discoveries have highlighted the important role that sub-optimal codons can play in modifying co-translational protein folding. These results have drawn increased attention to the patterns of synonymous codon usage within coding sequences, particularly in light of the discovery that these patterns can be conserved across evolution for homologous proteins. Because synonymous codon usage differs between organisms, for heterologous gene expression it can be desirable to make synonymous codon substitutions to match the codon usage pattern from the original organism in the heterologous expression host. Here we present CHARMING (for Codon HARMonizING), a robust and versatile algorithm to design mRNA sequences for heterologous gene expression and other related codon harmonization tasks. CHARMING can be run as a downloadable Python script or via a web portal at http://www.codons.org.

Comparative Analysis of Genomic and Transcriptome Sequences Reveals Divergent Patterns of Codon Bias in Wheat and Its Ancestor Species

The synonymous codons usage shows a characteristic pattern of preference in each organism. This codon usage bias is thought to have evolved for efficient protein synthesis. Synonymous codon usage was studied in genes of the hexaploid wheat Triticum aestivum (AABBDD) and its progenitor species, Triticum urartu (AA), Aegilops tauschii (DD), and Triticum turgidum (AABB). Triticum aestivum exhibited stronger usage bias for G/C-ending codons than did the three progenitor species, and this bias was especially higher compared to T. turgidum and Ae. tauschii. High GC content is a primary factor influencing codon usage in T. aestivum. Neutrality analysis showed a significant positive correlation (p<0.001) between GC12 and GC3 in the four species with regression line slopes near zero (0.16–0.20), suggesting that the effect of mutation on codon usage was only 16–20%. The GC3s values of genes were associated with gene length and distribution density within chromosomes. tRNA abundance data indicated that codon preference corresponded to the relative abundance of isoaccepting tRNAs in the four species. Both mutation and selection have affected synonymous codon usage in hexaploid wheat and its progenitor species. GO enrichment showed that GC biased genes were commonly enriched in physiological processes such as photosynthesis and response to acid chemical. In some certain gene families with important functions, the codon usage of small parts of genes has changed during the evolution process of T. aestivum.

Targeted genome editing of plants and plant cells for biomanufacturing

Plants have provided humans with useful products since antiquity, but in the last 30 years they have also been developed as production platforms for small molecules and recombinant proteins. This initially niche area has blossomed with the growth of the global bioeconomy, and now includes chemical building blocks, polymers and renewable energy. All these applications can be described as "plant molecular farming" (PMF). Despite its potential to increase the sustainability of biologics manufacturing, PMF has yet to be embraced broadly by industry. This reflects a combination of regulatory uncertainty, limited information on process cost structures, and the absence of trained staff and suitable manufacturing capacity. However, the limited adaptation of plants and plant cells to the requirements of industry-scale manufacturing is an equally important hurdle. For example, the targeted genetic manipulation of yeast has been common practice since the 1980s, whereas reliable site-directed mutagenesis in most plants has only become available with the advent of CRISPR/Cas9 and similar genome editing technologies since around 2010. Here we summarize the applications of new genetic engineering technologies to improve plants as biomanufacturing platforms. We start by identifying current bottlenecks in manufacturing, then illustrate the progress that has already been made and discuss the potential for improvement at the molecular, cellular and organism levels. We discuss the effects of metabolic optimization, adaptation of the endomembrane system, modified glycosylation profiles, programmable growth and senescence, protease inactivation, and the expression of enzymes that promote biodegradation. We outline strategies to achieve these modifications by targeted gene modification, considering case-by-case examples of individual improvements and the combined modifications needed to generate a new general-purpose "chassis" for PMF.

Folding Stability of Pax9 Intronic G-Quadruplex Correlates with Relative Molar Size in Eutherians

Eutherian dentition has been the focus of a great deal of studies in the areas of evolution, development, and genomics. The development of molar teeth is regulated by an antero-to-posterior cascade mechanism of activators and inhibitors molecules, where the relative sizes of the second (M2) and third (M3) molars are dependent of the inhibitory influence of the first molar (M1). Higher activator/inhibitor ratios will result in higher M2/M1 or M3/M1. Pax9 has been shown to play a key role in tooth development. We have previously shown that a G-quadruplex in the first intron of Pax9 can modulate the splicing efficiency. Using a sliding window approach with we analyzed the association of the folding energy (Mfe) of the Pax9 first intron with the relative molar sizes in 42 mammalian species, representing 9 orders. The Mfe of two regions located in the first intron of Pax9 were shown to be significantly associated with the M2/M1 and M3/M1 areas and mesiodistal lengths. The first region is located at the intron beginning and can fold into a stable G4 structure, whereas the second is downstream the G4 and 265 bp from intron start. Across species, the first intron of Pax9 varied in G-quadruplex structural stability. The correlations were further increased when the Mfe of the two sequences were added. Our results indicate that this region has a role in the evolution of the mammalian dental pattern by influencing the relative size of the molars.

Host Adaptive Evolution of Avian-Origin H3N2 Canine Influenza Virus

Since its first isolation in around 2007, the avian-origin H3N2 canine influenza virus (CIV) has become established and continues to circulate in dog populations. This virus serves as a useful model for deciphering the complex evolutionary process of interspecies transmission of influenza A virus (IAV) from one species to its subsequent circulation in another mammalian host. The present investigation is a comprehensive effort to identify and characterize genetic changes that accumulated in the avian-origin H3N2 CIV during its circulation in the dog. We revealed that H3N2 CIV experiences greater selection pressure with extremely high global non-synonymous to synonymous substitution ratios per codon (dN/dS ratio) for each gene compared to the avian reservoir viruses. A total of 54 amino acid substitutions were observed to have accumulated and become fixed in the H3N2 CIV population based on our comprehensive codon-based frequency diagram analysis. Of these substitutions, 11 sites also display high prevalence in H3N8 CIV, indicating that convergent evolution has occurred on different lineages of CIV. Notably, six substitutions, including HA-G146S, M1-V15I, NS1-E227K, PA-C241Y, PB2-K251R, and PB2-G590S, have been reported to play imperative roles in facilitating the transmission and spillover of IAVs across species barriers. Most of these substitutions were found to have become fixed in around 2015, which might have been a favorable factor that facilitating the spread of these CIV lineages from South Asia to North America and subsequent further circulation in these areas. We also detected 12 sites in six viral genes with evidence for positive selection by comparing the rates of non-synonymous and synonymous substitutions at each site. Besides, our study reports trends of enhanced ongoing adaptation of H3N2 CIV to their respective host cellular systems, based on the codon adaptation index analysis, which points toward increasing fitness for efficient viral replication. In addition, a reduction in the abundance of the CpG motif, as evident from an analysis of relative dinucleotide abundance, may contribute to the successful evasion of host immune recognition. The present study provides key insights into the adaptive changes that have accumulated in the avian-origin H3N2 viral genomes during its establishment and circulation into dog populations.

Read between the lines: Diversity of non-translational selection pressures on local codon usage

Protein coding genes can contain specific motifs within their nucleotide sequence that function as a signal for various biological pathways. The presence of such sequence motifs within a gene can have beneficial or detrimental effects on the phenotype and fitness of an organism, and this can lead to the enrichment or avoidance of this sequence motif. The degeneracy of the genetic code allows for the existence of alternative synonymous sequences that exclude or include these motifs, while keeping the encoded amino acid sequence intact. This implies that locally, there can be a selective pressure for preferentially using a codon over its synonymous alternative in order to avoid or enrich a specific sequence motif. This selective pressure could -in addition to mutation, drift and selection for translation efficiency and accuracy- contribute to shape the codon usage bias. In this review, we discuss patterns of avoidance of (or enrichment for) the various biological signals contained in specific nucleotide sequence motifs: transcription and translation initiation and termination signals, mRNA maturation signals, and antiviral immune system targets. Experimental data on the phenotypic or fitness effects of synonymous mutations in these sequence motifs confirm that they can be targets of local selection pressures on codon usage. We also formulate the hypothesis that transposable elements could have a similar impact on codon usage through their preferred integration sequences. Overall, selection on codon usage appears to be a combination of a global selection pressure imposed by the translation machinery, and a patchwork of local selection pressures related to biological signals contained in specific sequence motifs.

Codon-based indices for modeling gene expression and transcript evolution

Codon usage bias (CUB) refers to the phenomena that synonymous codons are used in different frequencies in most genes and organisms. The general assumption is that codon biases reflect a balance between mutational biases and natural selection. Today we understand that the codon content is related and can affect all gene expression steps. Starting from the 1980s, codon-based indices have been used for answering different questions in all biomedical fields, including systems biology, agriculture, medicine, and biotechnology. In general, codon usage bias indices weigh each codon or a small set of codons to estimate the fitting of a certain coding sequence to a certain phenomenon (e.g., bias in codons, adaptation to the tRNA pool, frequencies of certain codons, transcription elongation speed, etc.) and are usually easy to implement. Today there are dozens of such indices; thus, this paper aims to review and compare the different codon usage bias indices, their applications, and advantages. In addition, we perform analysis that demonstrates that most indices tend to correlate even though they aim to capture different aspects. Due to the centrality of codon usage bias on different gene expression steps, it is important to keep developing new indices that can capture additional aspects that are not modeled with the current indices.

Effect of genome composition and codon bias on infectious bronchitis virus evolution and adaptation to target tissues

Background

Infectious bronchitis virus (IBV) is one of the most relevant viruses affecting the poultry industry, and several studies have investigated the factors involved in its biological cycle and evolution. However, very few of those studies focused on the effect of genome composition and the codon bias of different IBV proteins, despite the remarkable increase in available complete genomes. In the present study, all IBV complete genomes were downloaded (n = 383), and several statistics representative of genome composition and codon bias were calculated for each protein-coding sequence, including but not limited to, the nucleotide odds ratio, relative synonymous codon usage and effective number of codons. Additionally, viral codon usage was compared to host codon usage based on a collection of highly expressed genes in IBV target and nontarget tissues.

Results

The results obtained demonstrated a significant difference among structural, non-structural and accessory proteins, especially regarding dinucleotide composition, which appears under strong selective forces. In particular, some dinucleotide pairs, such as CpG, a probable target of the host innate immune response, are underrepresented in genes coding for pp1a, pp1ab, S and N. Although genome composition and dinucleotide bias appear to affect codon usage, additional selective forces may act directly on codon bias. Variability in relative synonymous codon usage and effective number of codons was found for different proteins, with structural proteins and polyproteins being more adapted to the codon bias of host target tissues. In contrast, accessory proteins had a more biased codon usage (i.e., lower number of preferred codons), which might contribute to the regulation of their expression level and timing throughout the cell cycle.

Conclusions

The present study confirms the existence of selective forces acting directly on the genome and not only indirectly through phenotype selection. This evidence might help understanding IBV biology and in developing attenuated strains without affecting the protein phenotype and therefore immunogenicity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07559-5.

OTTER, a new method quantifying absolute amounts of tRNAs

To maintain optimal proteome, both codon choice of each mRNA and supply of aminoacyl-tRNAs are two principal factors in translation. Recent reports have revealed that the amounts of tRNAs in cells are more dynamic than we had expected. High-throughput methods such as RNA-Seq and microarrays are versatile for comprehensive detection of changes in individual tRNA amounts, but they suffer from inability to assess signal production efficiencies of individual tRNA species. Thus, they are not the perfect choice to measure absolute amounts of tRNAs. Here, we introduce a novel method for this purpose, termed Oligonucleotide-directed Three-prime Terminal Extension of RNA (OTTER), which employs fluorescence-labeling at the 3'-terminus of a tRNA by optimized reverse primer extension and an assessment step of each labeling efficiency by northern blotting. Using this method, we quantified the absolute amounts of the 34 individual and 4 pairs of isoacceptor tRNAs out of the total 42 nuclear-encoded isoacceptors in the yeast Saccharomyces cerevisiae. We found that the amounts of tRNAs in log phase yeast cells grown in a rich glucose medium range from 0.030 to 0.73 pmol/µg RNA. The tRNA amounts seem to be altered at the isoacceptor level by a few folds in response to physiological growing conditions. The data obtained by OTTER are poorly correlated with those by simple RNA-Seq, marginally with those by microarrays and by microscale thermophoresis. However, the OTTER data showed good agreement with the data obtained by 2D-gel analysis of in vivo radiolabeled RNAs. Thus, OTTER is a suitable method for quantifying absolute amounts of tRNAs at the level of isoacceptor resolution.

Modification of Transfer RNA Levels Affects Cyclin Aggregation and the Correct Duplication of Yeast Cells

Codon usage bias (the preferential use of certain synonymous codons (optimal) over others is found at the organism level (intergenomic) within specific genomes (intragenomic) and even in certain genes. Whether it is the result of genetic drift due to GC/AT content and/or natural selection is a topic of intense debate. Preferential codons are mostly found in genes encoding highly-expressed proteins, while lowly-expressed proteins usually contain a high proportion of rare (lowly-represented) codons. While optimal codons are decoded by highly expressed tRNAs, rare codons are usually decoded by lowly-represented tRNAs. Whether rare codons play a role in controlling the expression of lowly- or temporarily-expressed proteins is an open question. In this work we approached this question using two strategies, either by replacing rare glycine codons with optimal counterparts in the gene that encodes the cell cycle protein Cdc13, or by overexpression the tRNA ^Gly that decodes rare codons from the fission yeast, Schizosaccharomyces pombe. While the replacement of synonymous codons severely affected cell growth, increasing tRNA levels affected the aggregation status of Cdc13 and cell division. These lead us to think that rare codons in lowly-expressed cyclin proteins are crucial for cell division, and that the overexpression of tRNA that decodes rare codons affects the expression of proteins containing these rare codons. These codons may be the result of the natural selection of codons in genes that encode lowly-expressed proteins.

Analysis of codon usage patterns in citrus based on coding sequence data

BACKGROUND

Codon usage is an important determinant of gene expression levels that can help us understand codon biology, evolution and mRNA translation of species. The majority of previous codon usage studies have focused on single species analysis, although few studies have focused on the species within the same genus. In this study, we proposed a multispecies codon usage analysis workflow to reveal the genetic features and correlation in citrus.

RESULTS

Our codon usage analysis workflow was based on the GC content, GC plot, and relative synonymous codon usage value of each codon in 8 citrus species. This approach allows for the comparison of codon usage bias of different citrus species. Next, we performed cluster analysis and obtained an overview of the relationship in citrus. However, traditional methods cannot conduct quantitative analysis of the correlation. To further estimate the correlation among the citrus species, we used the frequency profile to construct feature vectors of each species. The Pearson correlation coefficient was used to quantitatively analyze the distance among the citrus species. This result was consistent with the cluster analysis.

CONCLUSIONS

Our findings showed that the citrus species are conserved at the genetic level and demonstrated the existing genetic evolutionary relationship in citrus. This work provides new insights into codon biology and the evolution of citrus and other plant species.

Large-scale in silico mutagenesis experiments reveal optimization of genetic code and codon usage for protein mutational robustness

BACKGROUND

How, and the extent to which, evolution acts on DNA and protein sequences to ensure mutational robustness and evolvability is a long-standing open question in the field of molecular evolution. We addressed this issue through the first structurome-scale computational investigation, in which we estimated the change in folding free energy upon all possible single-site mutations introduced in more than 20,000 protein structures, as well as through available experimental stability and fitness data.

RESULTS

At the amino acid level, we found the protein surface to be more robust against random mutations than the core, this difference being stronger for small proteins. The destabilizing and neutral mutations are more numerous in the core and on the surface, respectively, whereas the stabilizing mutations are about 4% in both regions. At the genetic code level, we observed smallest destabilization for mutations that are due to substitutions of base III in the codon, followed by base I, bases I+III, base II, and other multiple base substitutions. This ranking highly anticorrelates with the codon-anticodon mispairing frequency in the translation process. This suggests that the standard genetic code is optimized to limit the impact of random mutations, but even more so to limit translation errors. At the codon level, both the codon usage and the usage bias appear to optimize mutational robustness and translation accuracy, especially for surface residues.

CONCLUSION

Our results highlight the non-universality of mutational robustness and its multiscale dependence on protein features, the structure of the genetic code, and the codon usage. Our analyses and approach are strongly supported by available experimental mutagenesis data.

Unlocking a signal of introgression from codons in Lachancea kluyveri using a mutation-selection model

Background

For decades, codon usage has been used as a measure of adaptation for translational efficiency and translation accuracy of a gene’s coding sequence. These patterns of codon usage reflect both the selective and mutational environment in which the coding sequences evolved. Over this same period, gene transfer between lineages has become widely recognized as an important biological phenomenon. Nevertheless, most studies of codon usage implicitly assume that all genes within a genome evolved under the same selective and mutational environment, an assumption violated when introgression occurs. In order to better understand the effects of introgression on codon usage patterns and vice versa, we examine the patterns of codon usage in Lachancea kluyveri, a yeast which has experienced a large introgression. We quantify the effects of mutation bias and selection for translation efficiency on the codon usage pattern of the endogenous and introgressed exogenous genes using a Bayesian mixture model, ROC SEMPPR, which is built on mechanistic assumptions about protein synthesis and grounded in population genetics.

Results

We find substantial differences in codon usage between the endogenous and exogenous genes, and show that these differences can be largely attributed to differences in mutation bias favoring A/T ending codons in the endogenous genes while favoring C/G ending codons in the exogenous genes. Recognizing the two different signatures of mutation bias and selection improves our ability to predict protein synthesis rate by 42% and allowed us to accurately assess the decaying signal of endogenous codon mutation and preferences. In addition, using our estimates of mutation bias and selection, we identify Eremothecium gossypii as the closest relative to the exogenous genes, providing an alternative hypothesis about the origin of the exogenous genes, estimate that the introgression occurred ∼6×10⁸ generation ago, and estimate its historic and current selection against mismatched codon usage.

Conclusions

Our work illustrates how mechanistic, population genetic models like ROC SEMPPR can separate the effects of mutation and selection on codon usage and provide quantitative estimates from sequence data.

SARS-CoV-2 Codon Usage Bias Downregulates Host Expressed Genes With Similar Codon Usage

Severe acute respiratory syndrome has spread quickly throughout the world and was declared a pandemic by the World Health Organization (WHO). The pathogenic agent is a new coronavirus (SARS-CoV-2) that infects pulmonary cells with great effectiveness. In this study we focus on the codon composition for the viral protein synthesis and its relationship with the protein synthesis of the host. Our analysis reveals that SARS-CoV-2 preferred codons have poor representation of G or C nucleotides in the third position, a characteristic which could result in an unbalance in the tRNAs pools of the infected cells with serious implications in host protein synthesis. By integrating this observation with proteomic data from infected cells, we observe a reduced translation rate of host proteins associated with highly expressed genes and that they share the codon usage bias of the virus. The functional analysis of these genes suggests that this mechanism of epistasis can contribute to understanding how this virus evades the immune response and the etiology of some deleterious collateral effect as a result of the viral replication. In this manner, our finding contributes to the understanding of the SARS-CoV-2 pathogeny and could be useful for the design of a vaccine based on the live attenuated strategy.

The Complete Chloroplast Genome Sequencing and Comparative Analysis of Reed Canary Grass (Phalaris arundinacea) and Hardinggrass (P. aquatica)

There are 22 species in the Phalaris genera that distribute almost all over the temperate regions of the world. Among them, reed canary grass (Phalaris arundinacea, tetraploid and hexaploid) and hardinggrass (P. aquatica, tetraploid) have been long cultivated as forage grass and have received attention as bio-energy materials in recent years. We aimed to facilitate inter-species/ploidies comparisons, and to illuminate the degree of sequence variation within existing gene pools, chloroplast (cp) genomes of three Phalaris cytotypes (P. aquatica/4x, P. arundinacea/4x and P. arundinacea/6x) were sequenced and assembled. The result indicated that certain sequence variations existed between the cp genomes of P. arundinacea and P. aquatica. Several hotspot regions (atpI~atpH, trnT-UGU~ndhJ, rbcL~psaI, and ndhF~rpl32) were found, and variable genes (infA, psaI, psbK, etc.) were detected. SNPs (single nucleotide polymorphisms) and/or indels (insertions and deletions) were confirmed by the high Ka/Ks and Pi value. Furthermore, distribution and presence of cp simple sequence repeats (cpSSRs) were identified in the three Phalaris cp genomes, although little difference was found between hexaploid and tetraploid P. arundinacea, and no rearrangement was detected among the three Phalaris cp genomes. The evolutionary relationship and divergent time among these species were discussed. The RNA-seq revealed several differentially expressed genes (DEGs), among which psaA, psaB, and psbB related to leaf color were further verified by leaf color differences.

Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods

BACKGROUND

Researchers often measure changes in gene expression across conditions to better understand the shared functional roles and regulatory mechanisms of different genes. Analogous to this is comparing gene expression across species, which can improve our understanding of the evolutionary processes shaping the evolution of both individual genes and functional pathways. One area of interest is determining genes showing signals of coevolution, which can also indicate potential functional similarity, analogous to co-expression analysis often performed across conditions for a single species. However, as with any trait, comparing gene expression across species can be confounded by the non-independence of species due to shared ancestry, making standard hypothesis testing inappropriate.

RESULTS

We compared RNA-Seq data across 18 fungal species using a multivariate Brownian Motion phylogenetic comparative method (PCM), which allowed us to quantify coevolution between protein pairs while directly accounting for the shared ancestry of the species. Our work indicates proteins which physically-interact show stronger signals of coevolution than randomly-generated pairs. Interactions with stronger empirical and computational evidence also showing stronger signals of coevolution. We examined the effects of number of protein interactions and gene expression levels on coevolution, finding both factors are overall poor predictors of the strength of coevolution between a protein pair. Simulations further demonstrate the potential issues of analyzing gene expression coevolution without accounting for shared ancestry in a standard hypothesis testing framework. Furthermore, our simulations indicate the use of a randomly-generated null distribution as a means of determining statistical significance for detecting coevolving genes with phylogenetically-uncorrected correlations, as has previously been done, is less accurate than PCMs, although is a significant improvement over standard hypothesis testing. These methods are further improved by using a phylogenetically-corrected correlation metric.

CONCLUSIONS

Our work highlights potential benefits of using PCMs to detect gene expression coevolution from high-throughput omics scale data. This framework can be built upon to investigate other evolutionary hypotheses, such as changes in transcription regulatory mechanisms across species.

Hidden patterns of codon usage bias across kingdoms

The genetic code is necessarily degenerate with 64 possible nucleotide triplets being translated into 20 amino acids. Eighteen out of the 20 amino acids are encoded by multiple synonymous codons. While synonymous codons are clearly equivalent in terms of the information they carry, it is now well established that they are used in a biased fashion. There is currently no consensus as to the origin of this bias. Drawing on ideas from stochastic thermodynamics we derive from first principles a mathematical model describing the statistics of codon usage bias. We show that the model accurately describes the distribution of codon usage bias of genomes in the fungal and bacterial kingdoms. Based on it, we derive a new computational measure of codon usage bias-the distance D capturing two aspects of codon usage bias: (i) differences in the genome-wide frequency of codons and (ii) apparent non-random distributions of codons across mRNAs. By means of large scale computational analysis of over 900 species across two kingdoms of life, we demonstrate that our measure provides novel biological insights. Specifically, we show that while codon usage bias is clearly based on heritable traits and closely related species show similar degrees of bias, there is considerable variation in the magnitude of D within taxonomic classes suggesting that the contribution of sequence-level selection to codon bias varies substantially within relatively confined taxonomic groups. Interestingly, commonly used model organisms are near the median for values of D for their taxonomic class, suggesting that they may not be good representative models for species with more extreme D, which comprise organisms of medical and agricultural interest. We also demonstrate that amino acid specific patterns of codon usage are themselves quite variable between branches of the tree of life, and that some of this variability correlates with organismal tRNA content.

Synonymous codon substitutions perturb cotranslational protein folding in vivo and impair cell fitness

In the cell, proteins are synthesized from N to C terminus and begin to fold during translation. Cotranslational folding mechanisms are therefore linked to elongation rate, which varies as a function of synonymous codon usage. However, synonymous codon substitutions can affect many distinct cellular processes, which has complicated attempts to deconvolve the extent to which synonymous codon usage can promote or frustrate proper protein folding in vivo. Although previous studies have shown that some synonymous changes can lead to different final structures, other substitutions will likely be more subtle, perturbing predominantly the protein folding pathway without radically altering the final structure. Here we show that synonymous codon substitutions encoding a single essential enzyme lead to dramatically slower cell growth. These mutations do not prevent active enzyme formation; instead, they predominantly alter the protein folding mechanism, leading to enhanced degradation in vivo. These results support a model in which synonymous codon substitutions can impair cell fitness by significantly perturbing cotranslational protein folding mechanisms, despite the chaperoning provided by the cellular protein homeostasis network.

Transcript degradation and codon usage regulate gene expression in a lytic phage

Many viral genomes are small, containing only single- or double-digit numbers of genes and relatively few regulatory elements. Yet viruses successfully execute complex regulatory programs as they take over their host cells. Here, we propose that some viruses regulate gene expression via a carefully balanced interplay between transcription, translation, and transcript degradation. As our model system, we employ bacteriophage T7, whose genome of approximately sixty genes is well annotated and for which there is a long history of computational models of gene regulation. We expand upon prior modeling work by implementing a stochastic gene expression simulator that tracks individual transcripts, polymerases, ribosomes, and ribonucleases participating in the transcription, translation, and transcript-degradation processes occurring during a T7 infection. By combining this detailed mechanistic modeling of a phage infection with high-throughput gene expression measurements of several strains of bacteriophage T7, evolved and engineered, we can show that both the dynamic interplay between transcription and transcript degradation, and between these two processes and translation, appear to be critical components of T7 gene regulation. Our results point to targeted degradation as a generic gene regulation strategy that may have evolved in many other viruses. Further, our results suggest that detailed mechanistic modeling may uncover the biological mechanisms at work in both evolved and engineered virus variants.

The history of mutational pressure changes during the evolution of adeno-associated viruses: A message to gene therapy and DNA-vaccine vectors designers

The use of virus-associated vectors for gene therapy and vaccination have emerged as safe and effective delivery system. Like all other genetic materials, these vehicles are also prone to spontaneous mutations. To understand what types of nucleotide mutations are expected in the vector, one needs to know distinct characteristics of mutational process in the corresponding virus. In this study we analyzed mutational pressure directions along the length of the genomes of all types of primate adeno-associated viruses (AAV) that are frequently used in gene therapy or DNA-vaccines. We observed clear evidences of transcription-associated mutational pressure in AAV: nucleotide usage biases are changing drastically after each of the three promoters: the higher the rate of transcription, the stronger the bias towards GC to AT mutations. Moreover, the usage of G decreased at the lower transcription rate (after P19 promoter) than the usage of C (after P40 promoter). Since nucleotide usage biases are retrospective indices, we created a scenario of changes in transcriptional map during the AAV evolution. Current mutational pressure directions are different for AAV types, while all of them demonstrate high rates of T to C transitions in the second long ORF. Since transcription rate and cell tropism are the main factors determining the preferable direction of nucleotide mutations in AAV, mutational pressure should be checked experimentally in DNA vectors before their final design with the aim to make the transferred gene more stable against those mutations.