How much is Transcription-associated Mutagenesis Driving tRNA Microevolution?

Abstract

Transfer RNAs (tRNAs) are among the most highly conserved and frequently transcribed genes. Recent studies have demonstrated that tRNAs experience exceptionally high rates of transcription-associated mutagenesis (TAM) as well as strong purifying selection. How the mutational input of TAM, which induces a non-uniform distribution of nucleotide substitutions, affects the fitness of tRNA molecules is unclear. Secondary structure in tRNAs is strongly conserved over macro-evolutionary time, suggesting that mutations that disrupt paired sites may be especially deleterious, but TAM-induced mutations primarily involve nucleotide transitions, which tend to preserve base-pairing stability. To examine how TAM affects tRNA molecule fitness and shapes tRNA evolution over short timescales, we analyzed tRNA allelic variation in contemporary Caenorhabditis elegans strains. We propose a model of tRNA microevolution driven by TAM and demonstrate that the observed secondary structure characteristics align with our predicted TAM-biased patterns. Furthermore, we developed a continuous Markov substitution model that incorporates TAM-specific mutational biases. This TAM-biased model fits the C. elegans tRNA data more effectively than standard models, such as the general time-reversible (GTR) model. Based on these results, we conclude that tRNAs in natural populations carry substantial levels of structure-destabilizing mutations, which may be tolerated but nevertheless likely induce meaningful fitness costs. Our findings are consistent with recent experimental studies on tRNA fitness in yeast but challenge prior theoretical and computational analyses that emphasize RNA base-pairing as a primary determinant in genotype-phenotype systems. 1 Significance StatementTransfer RNAs (tRNAs) are ancient molecules, encoded as genes in all living systems. tRNA genes are known to experience exceptionally high rates of both mutation and purifying selection, but how these opposing evolutionary forces shape tRNA evolution is unclear. We developed a sequence substitution model specific to tRNA mutagenesis and applied it to standing variation in a natural population in order to infer how mutation and selection affect the structural stability of tRNA molecules.