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

   https://doi.org/10.1128/mbio.03916-24  

   Cote-L'Heureux, Auden E; Sterner, Elinor G; Maurer-Alcalá, Xyrus X; Katz, Laura A (April 2025, mBio)

   Johnson, Patricia J (Ed.)

   ABSTRACT 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 asAcanthamoeba, 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. 

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2. Genomic factors shaping codon usage across the Saccharomycotina subphylum

   https://doi.org/10.1093/g3journal/jkae207  

   Zavala, Bryan; Dineen, Lauren; Fisher, Kaitlin_J; Opulente, Dana_A; Harrison, Marie-Claire; Wolters, John_F; Shen, Xing-Xing; Zhou, Xiaofan; Groenewald, Marizeth; Hittinger, Chris_Todd; et al (August 2024, G3: Genes, Genomes, Genetics)

   Abstract Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. It has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. We characterized codon usage across 1,154 strains from 1,051 species from the fungal subphylum Saccharomycotina to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns. We found a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is distinct between the 12 orders to such a degree that yeasts can be classified with an accuracy >90% using a machine learning algorithm. We also characterized the degree to which codon usage bias is impacted by translational selection. We found it was influenced by a combination of features, including the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that avoidance of the CGN codons is associated with a decline in arginine tRNA function. Consistent with previous findings, codon usage bias within the Saccharomycotina is shaped by genomic features and GC bias. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons. 

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

   https://doi.org/10.1371/journal.pgen.1010256  

   Cope, Alexander L.; Shah, Premal (June 2022, PLOS Genetics)

   Fay, Justin C. (Ed.)

   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. 

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4. Comparative Analysis of Within-Host Mutation Patterns and Diversity of Hepatitis C Virus Subtypes 1a, 1b, and 3a

   https://doi.org/10.3390/v13030511  

   Tisthammer, Kaho H.; Dong, Weiyan; Joy, Jeffrey B.; Pennings, Pleuni S. (March 2021, Viruses)

   null (Ed.)

   Understanding within-host evolution is critical for predicting viral evolutionary outcomes, yet such studies are currently lacking due to difficulty involving human subjects. Hepatitis C virus (HCV) is an RNA virus with high mutation rates. Its complex evolutionary dynamics and extensive genetic diversity are demonstrated in over 67 known subtypes. In this study, we analyzed within-host mutation frequency patterns of three HCV subtypes, using a large number of samples obtained from treatment-naïve participants by next-generation sequencing. We report that overall mutation frequency patterns are similar among subtypes, yet subtype 3a consistently had lower mutation frequencies and nucleotide diversity, while subtype 1a had the highest. We found that about 50% of genomic sites are highly conserved across subtypes, which are likely under strong purifying selection. We also compared within-host and between-host selective pressures, which revealed that Hyper Variable Region 1 within hosts was under positive selection, but was under slightly negative selection between hosts, which indicates that many mutations created within hosts are removed during the transmission bottleneck. Examining the natural prevalence of known resistance-associated variants showed their consistent existence in the treatment-naïve participants. These results provide insights into the differences and similarities among HCV subtypes that may be used to develop and improve HCV therapies. 

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5. New insights on the evolutionary relationships between the major lineages of Amoebozoa

   https://doi.org/10.1038/s41598-022-15372-7  

   Tekle, Yonas I.; Wang, Fang; Wood, Fiona C.; Anderson, O. Roger; Smirnov, Alexey (July 2022, Scientific Reports)

   Abstract The supergroup Amoebozoa unites a wide diversity of amoeboid organisms and encompasses enigmatic lineages that have been recalcitrant to modern phylogenetics. Deep divergences, taxonomic placement of some key taxa and character evolution in the group largely remain poorly elucidated or controversial. We surveyed available Amoebozoa genomes and transcriptomes to mine conserved putative single copy genes, which were used to enrich gene sampling and generate the largest supermatrix in the group to date; encompassing 824 genes, including gene sequences not previously analyzed. We recovered a well-resolved and supported tree of Amoebozoa, revealing novel deep level relationships and resolving placement of enigmatic lineages congruent with morphological data. In our analysis the deepest branching group is Tubulinea. A recent proposed major clade Tevosa, uniting Evosea and Tubulinea, is not supported. Based on the new phylogenetic tree, paleoecological and paleontological data as well as data on the biology of presently living amoebozoans, we hypothesize that the evolution of Amoebozoa probably was driven by adaptive responses to a changing environment, where successful survival and predation resulted from a capacity to disrupt and graze on microbial mats-a dominant ecosystem of the mid-Proterozoic period of the Earth history. 

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