Distribution of phenotype sizes in sequence-to-structure genotype-phenotype maps

Abstract

An essential quantity to ensure evolvability of populations is the navigability of the genotype space. Navigability relies on the existence of sufficiently large genotype networks, that is ensembles of sequences with the same phenotype that guarantee an efficient random drift through sequence space. The number of sequences compatible with a given structure (e.g. the number of RNA sequences folding into a particular secondary structure, or the number of DNA sequences coding for the same protein structure) is astronomically large in all functional molecules investigated. However, an exhaustive experimental or computational study of all RNA folds or all protein structures becomes impossible even for moderately long sequences. Here, we analytically derive the distribution of phenotype sizes for a hierarchy of models which successively incorporate features of increasingly realistic sequence-to-structure genotype-phenotype maps. The main feature of these models relies on the characterization of each phenotype through a prototypical sequence whose sites admit a variable fraction of letters of the alphabet. Our models interpolate between two limit distributions: a powerlaw distribution, when the ordering of sites in the prototypical sequence is strongly constrained, and a lognormal distribution, as suggested for RNA, when different orderings of the same set of sites yield different phenotypes. Our main result is the qualitative and quantitative identification of those features of the sequence-to-structure map that lead to different distributions of phenotype sizes.

28 pages, 4 figures

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Cited by in corpus (5)

• From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics
• On the networked architecture of genotype spaces and its critical effects on molecular evolution
• Statistical theory of phenotype abundance distributions: a test through exact enumeration of genotype spaces
• Phenotypic-dependent variability and the emergence of tolerance in bacterial populations
• Entropic contribution to phenotype fitness