The effectiveness of selection in a species affects the direction of amino acid frequency evolution.

Nearly neutral theory predicts that species with higher effective population size (N e ) are better able to purge slightly deleterious mutations. We compare evolution in high-N e vs. low-N e vertebrates to reveal which amino acid frequencies are subject to subtle selective preferences. We take three complementary approaches, two measuring flux and one measuring outcomes. First, we fit non-stationary substitution models of amino acid flux using maximum likelihood, comparing the high-N e clade of rodents and lagomorphs to its low-N e sister clade of primates and colugos. Second, we compare evolutionary outcomes across a wider range of vertebrates, via correlations between amino acid frequencies and N e . Third, we dissect the details of flux in human, chimpanzee, mouse, and rat, as scored by parsimony - this also enables comparison to a historical paper. All three methods agree on which amino acids are preferred under more effective selection. Preferred amino acids tend to be smaller, less costly to synthesize, and to promote intrinsic structural disorder. Parsimony-induced bias in the historical study produces an apparent reduction in structural disorder, perhaps driven by slightly deleterious substitutions. Within highly exchangeable pairs of amino acids, arginine is strongly preferred over lysine, and valine over isoleucine, consistent with more effective selection preferring a marginally larger free energy of folding. These two preferences match differences between thermophiles and mesophilic relatives. These results reveal the biophysical consequences of mutation-selection-drift balance, and demonstrate the utility of nearly neutral theory for understanding protein evolution.

Order of amino acid recruitment into the genetic code resolved by Last Universal Common Ancestor's protein domains.

The current "consensus" order in which amino acids were added to the genetic code is based on potentially biased criteria such as absence of sulfur-containing amino acids from the Urey-Miller experiment which lacked sulfur. Even if inferred perfectly, abiotic abundance might not reflect abundance in the organisms in which the genetic code evolved. Here, we instead exploit the fact that proteins that emerged prior to the genetic code's completion are likely enriched in early amino acids and depleted in late amino acids. We identify the most ancient protein-coding sequences born prior to the archaeal-bacterial split. Amino acid usage in protein sequences whose ancestors date back to a single homolog in the Last Universal Common Ancestor (LUCA) largely matches the consensus order. However, our findings indicate that metal-binding (cysteine and histidine) and sulfur-containing (cysteine and methionine) amino acids were added to the genetic code much earlier than previously thought. Surprisingly, even more ancient protein sequences - those that had already diversified into multiple distinct copies in LUCA - show a different pattern to single copy LUCA sequences: significantly less depleted in the late amino acids tryptophan and tyrosine, and enriched rather than depleted in phenylalanine. This is compatible with at least some of these sequences predating the current genetic code. Their distinct enrichment patterns thus provide hints about earlier, alternative genetic codes.

A comparative analysis of L1 retrotransposition activities in human genomes suggests an ongoing increase in L1 number despite an evolutionary trend towards lower activity.

BACKGROUND: LINE-1 (Long Interspersed Nuclear Elements, L1) retrotransposons are the only autonomously active transposable elements in the human genome. The evolution of L1 retrotransposition rates and its implications for L1 dynamics are poorly understood. Retrotransposition rates are commonly measured in cell culture-based assays, but it is unclear how well these measurements provide insight into L1 population dynamics. This study applied comparative methods to estimate parameters for the evolution of retrotransposition rates, and infer L1 dynamics from these estimates. RESULTS: Our results show that the rates at which new L1s emerge in the human population correlate positively to cell-culture based retrotransposition activities, that there is an evolutionary trend towards lower retrotransposition activity, and that this evolutionary trend is not sufficient to counter-balance the increase in active L1s resulting from continuing retrotransposition. CONCLUSIONS: Together, these findings support a model of the population-level L1 retrotransposition dynamics that is consistent with prior expectations and indicate the remaining gaps in the understanding of L1 dynamics in human genomes.