Patterns of Ancestral Animal Codon Usage Bias Revealed Through Holozoan Protists

Jade Southworth, Paul Armitage, Brandon Fallon, Holly Dawson, Jarek Bryk, Martin Carr

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Choanoflagellates and filastereans are the closest known single celled relatives of Metazoa within Holozoa and provide insight into how animals evolved from their unicellular ancestors. Codon usage bias has been extensively studied in metazoans, with both natural selection and mutation pressure playing important roles in different species. The disparate nature of metazoan codon usage patterns prevents the reconstruction of ancestral traits. However, traits conserved across holozoan protists highlight characteristics in the unicellular ancestors of Metazoa. Presented here are the patterns of codon usage in the choanoflagellates Monosiga brevicollis and Salpingoeca rosetta, as well as the filasterean Capsaspora owczarzaki. Codon usage is shown to be remarkably conserved. Highly biased genes preferentially use GC-ending codons, however there is limited evidence this is driven by local mutation pressure. The analyses presented provide strong evidence that natural selection, for both translational accuracy and efficiency, dominates codon usage bias in holozoan protists. In particular, the signature of selection for translational accuracy can be detected even in the most weakly biased genes. Biased codon usage is shown to have co-evolved with the tRNA species, with optimal codons showing complementary binding to the highest copy number tRNA genes. Furthermore, tRNA modification is shown to be a common feature for amino acids with higher levels of degeneracy and highly biased genes show a strong preference for using modified tRNAs in translation. The translationally optimal codons defined here will be of benefit to future transgenics work in holozoan protists, as their use should maximise protein yields from edited transgenes.
Original languageEnglish
Pages (from-to)2499-2511
Number of pages13
JournalMolecular Biology and Evolution
Volume35
Issue number10
Early online date29 Aug 2018
DOIs
Publication statusPublished - 1 Oct 2018

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