Data from: The fitness landscape of the codon space across environments

Fitness landscapes map the relationship between genotypes and fitness.
However, most fitness landscape studies ignore the genetic architecture
imposed by the codon table and thereby neglect the potential role of
synonymous mutations. To quantify the fitness effects of synonymous
mutations and their potential impact on adaptation on a fitness landscape,
we use a new software based on Bayesian Monte Carlo Markov Chain methods
and re-estimate selection coefficients of all possible codon mutations
across 9 amino-acid positions in Saccharomyces cerevisiae Hsp90 across 6
environments. We quantify the distribution of fitness effects of
synonymous mutations and show that it is dominated by many mutations of
small or no effect and few mutations of larger effect. We then compare the
shape of the codon fitness landscape across amino-acid positions and
environments, and quantify how the consideration of synonymous fitness
effects changes the evolutionary dynamics on these fitness landscapes.
Together these results highlight a possible role of synonymous mutations
in adaptation and indicate the potential mis-inference when they are
neglected in fitness landscape studies.