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Codon usage bias is the preferential or non-random use of synonymous codons, a ubiquitous phenomenon observed in bacteria, plants and animals. Different species have consistent and characteristic codon biases. Codon bias varies not only with species, family or group within kingdom, but also between the genes within an organism. Codon usage bias has evolved through mutation, natural selection, and genetic drift in various organisms. Genome composition, GC content, expression level and length of genes, position and context of codons in the genes, recombination rates, mRNA folding, and tRNA abundance and interactions are some factors influencing codon bias. The factors shaping codon bias may also be involved in evolution of the universal genetic code. Codon-usage bias is critical factor determining gene expression and cellular function by influencing diverse processes such as RNA processing, protein translation and protein folding. Codon usage bias reflects the origin, mutation patterns and evolution of the species or genes. Investigations of codon bias patterns in genomes can reveal phylogenetic relationships between organisms, horizontal gene transfers, molecular evolution of genes and identify selective forces that drive their evolution. Most important application of codon bias analysis is in the design of transgenes, to increase gene expression levels through codon optimization, for development of transgenic crops. The review gives an overview of deviations of genetic code, factors influencing codon usage or bias, codon usage bias of nuclear and organellar genes, computational methods to determine codon usage and the significance as well as applications of codon usage analysis in biological research, with emphasis on plants.

All eukaryotes utilize a single termination factor, eRF1, to halt translation when the ribosome encounters one of three possible stop codons; here electron cryo-microscopy structures of ribosome–eRF1 complexes in the process of recognizing each stop codon reveal how stop codons are discriminated from sense codons. How mRNA knows when to stop Mammalian messenger RNAs utilize three stop codons, but have a single termination factor, eRF1, that can recognize all three. To understand how eRF1 can distinguish stop codons from sense codons, Alan Brown et al . determined the structures of the mammalian 80S ribosome bound to eRF1 and mRNAs containing each of the stop codons. They find that two nucleotides from the 18S rRNA are stacked with two of the stop codon nucleotides, and the next nucleotide, to compact the mRNA, a conformation that favours stop codons to the exclusion of sense codons. Termination of protein synthesis occurs when a translating ribosome encounters one of three universally conserved stop codons: UAA, UAG or UGA. Release factors recognize stop codons in the ribosomal A-site to mediate release of the nascent chain and recycling of the ribosome. Bacteria decode stop codons using two separate release factors with differing specificities for the second and third bases 1 . By contrast, eukaryotes rely on an evolutionarily unrelated omnipotent release factor (eRF1) to recognize all three stop codons 2 . The molecular basis of eRF1 discrimination for stop codons over sense codons is not known. Here we present cryo-electron microscopy (cryo-EM) structures at 3.5–3.8 Å resolution of mammalian ribosomal complexes containing eRF1 interacting with each of the three stop codons in the A-site. Binding of eRF1 flips nucleotide A1825 of 18S ribosomal RNA so that it stacks on the second and third stop codon bases. This configuration pulls the fourth position base into the A-site, where it is stabilized by stacking against G626 of 18S rRNA. Thus, eRF1 exploits two rRNA nucleotides also used during transfer RNA selection to drive messenger RNA compaction. In this compacted mRNA conformation, stop codons are favoured by a hydrogen-bonding network formed between rRNA and essential eRF1 residues that constrains the identity of the bases. These results provide a molecular framework for eukaryotic stop codon recognition and have implications for future studies on the mechanisms of canonical and premature translation termination 3 , 4 .

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.

Premature termination codons (PTCs) account for 10 to 20% of genetic diseases in humans. The gene inactivation resulting from PTCs can be counteracted by the use of drugs stimulating PTC readthrough, thereby restoring production of the full-length protein. However, a greater chemical variety of readthrough inducers is required to broaden the medical applications of this therapeutic strategy. In this study, we developed a reporter cell line and performed high-throughput screening (HTS) to identify potential readthrough inducers. After three successive assays, we isolated 2-guanidinoquinazoline (TLN468). We assessed the clinical potential of this drug as a potent readthrough inducer on the 40 PTCs most frequently responsible for Duchenne muscular dystrophy (DMD). We found that TLN468 was more efficient than gentamicin, and acted on a broader range of sequences, without inducing the readthrough of normal stop codons (TC).

Gene therapy is a potentially curative medicine for many currently untreatable diseases, and recombinant adeno-associated virus (rAAV) is the most successful gene delivery vehicle for in vivo applications 1 – 3 . However, rAAV-based gene therapy suffers from several limitations, such as constrained DNA cargo size and toxicities caused by non-physiological expression of a transgene 4 – 6 . Here we show that rAAV delivery of a suppressor tRNA (rAAV.sup-tRNA) safely and efficiently rescued a genetic disease in a mouse model carrying a nonsense mutation, and effects lasted for more than 6 months after a single treatment. Mechanistically, this was achieved through a synergistic effect of premature stop codon readthrough and inhibition of nonsense-mediated mRNA decay. rAAV.sup-tRNA had a limited effect on global readthrough at normal stop codons and did not perturb endogenous tRNA homeostasis, as determined by ribosome profiling and tRNA sequencing, respectively. By optimizing the AAV capsid and the route of administration, therapeutic efficacy in various target tissues was achieved, including liver, heart, skeletal muscle and brain. This study demonstrates the feasibility of developing a toolbox of AAV-delivered nonsense suppressor tRNAs operating on premature termination codons (AAV-NoSTOP) to rescue pathogenic nonsense mutations and restore gene function under endogenous regulation. As nonsense mutations account for 11% of pathogenic mutations, AAV-NoSTOP can benefit a large number of patients. AAV-NoSTOP obviates the need to deliver a full-length protein-coding gene that may exceed the rAAV packaging limit, elicit adverse immune responses or cause transgene-related toxicities. It therefore represents a valuable addition to gene therapeutics. The feasibility of adeno-associated-virus-delivered nonsense suppressor tRNAs operating on premature termination codons (AAV-NoSTOP) is explored to restore gene function, using a mouse model of mucopolysaccharidosis type I for proof of concept.

Abstract Bifunctional stop codons that have both translation and termination functions in the same species are important for understanding the evolution and function of genetic codes in living organisms. Considering the high frequency of bifunctional codons but limited number of available genomes in ciliates, we de novo sequenced seven representative ciliate genomes to explore the evolutionary history of stop codons. We further propose a stop codon reassignment quantification method (stopCR) that can identify bifunctional codons and measure their frequencies in various eukaryotic organisms. Using our newly developed method, we found two previously undescribed genetic codes, illustrating the prevalence of bifunctional stop codons in ciliates. Overall, evolutionary genomic analyses suggest that gain or loss of reassigned stop codons in ciliates is shaped by their living environment, the eukaryotic release factor 1, and suppressor tRNAs. This study provides novel clues about the functional diversity and evolutionary history of stop codons in eukaryotic organisms.

The advent of ribosome profiling and other tools to probe mRNA translation has revealed that codon bias -- the uneven use of synonymous codons in the transcriptome -- serves as a secondary genetic code: a code that guides the efficiency of protein production, the fidelity of translation and the metabolism of mRNAs. Recent advancements in our understanding of mRNA decay have revealed a tight coupling between ribosome dynamics and the stability of mRNA transcripts; this coupling integrates codon bias into the concept of codon optimality, or the effects that specific codons and tRNA concentrations have on the efficiency and fidelity of the translation machinery. In this Review, we first discuss the evidence for codon-dependent effects on translation, beginning with the basic mechanisms through which translation perturbation can affect translation efficiency, protein folding and transcript stability. We then discuss how codon effects are leveraged by the cell to tailor the proteome to maintain homeostasis, execute specific gene expression programmes of growth or differentiation and optimize the efficiency of protein production.

Abstract We present the Codon Statistics Database, an online database that contains codon usage statistics for all the species with reference or representative genomes in RefSeq (over 15,000). The user can search for any species and access two sets of tables. One set lists, for each codon, the frequency, the Relative Synonymous Codon Usage, and whether the codon is preferred. Another set of tables lists, for each gene, its GC content, Effective Number of Codons, Codon Adaptation Index, and frequency of optimal codons. Equivalent tables can be accessed for (1) all nuclear genes, (2) nuclear genes encoding ribosomal proteins, (3) mitochondrial genes, and (4) chloroplast genes (if available in the relevant assembly). The user can also search for any taxonomic group (e.g., “primates”) and obtain a table comparing all the species in the group. The database is free to access without registration at http://codonstatsdb.unr.edu.

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

Trypanosomatids primarily regulate protein expression at the posttranscriptional level, with codon bias playing a crucial role in controlling protein production across all life forms. This study investigated how codon usage, tRNA abundance, and codon pairing modes influence protein production in T. cruzi . Through tRNA sequencing and the integration of epigenomic and translatome data, we discovered that infective and noninfective forms of T. cruzi exhibit similar codon usage and tRNA pool preferences, despite having different proteomes. We developed pipelines applicable to any organism to measure codon adaptation to tRNA pools and pairing modes. Our analysis revealed that highly expressed genes are better aligned with more abundant tRNAs and favor Watson-Crick or inosine pairing. These findings suggest an additional layer of gene regulation based on tRNA availability and pairing modes, which impacts protein expression in the different life forms of T. cruzi .