Entropic contribution to phenotype fitness

Abstract

All possible phenotypes are not equally accessible to evolving populations. In fact, only phenotypes of large size, i.e. those resulting from many different genotypes, are found in populations of sequences, presumably because they are easier to discover and maintain. Genotypes that map to these phenotypes usually form mostly connected genotype networks that percolate the space of sequences, thus guaranteeing access to a large set of alternative phenotypes. Within a given environment, where specific phenotypic traits become relevant for adaptation, the replicative ability of a phenotype and its overall fitness (in competition experiments with alternative phenotypes) can be estimated. Two primary questions arise: how do phenotype size, reproductive capability and topology of the genotype network affect the fitness of a phenotype? And, assuming that evolution is only able to access large phenotypes, what is the range of unattainable fitness values? In order to address these questions, we quantify the adaptive advantage of phenotypes of varying size and spectral radius in a two-peak landscape. We derive analytical relationships between the three variables (size, topology, and replicative ability) which are then tested through analysis of genotype-phenotype maps and simulations of population dynamics on such maps. Finally, we analytically show that the fraction of attainable phenotypes decreases with the length of the genotype, though its absolute number increases. The fact that most phenotypes are not visible to evolution very likely forbids the attainment of the highest peak in the landscape. Nevertheless, our results indicate that the relative fitness loss due to this limited accessibility is largely inconsequential for adaptation.

arXiv comment25 pages, 10 figures, uses iopart.cls, iopart10.clo, iopart12.clo, iopams.sty, setstack.sty

References in corpus (13)

• Why Do Proteins Look Like Proteins?
• Neutral Evolution of Mutational Robustness
• Successful strategies for competing networks
• From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics
• The arrival of the frequent: how bias in genotype-phenotype maps can steer populations to local optima
• Genetic correlations greatly increase mutational robustness and can both reduce and enhance evolvability
• On the networked architecture of genotype spaces and its critical effects on molecular evolution
• Distribution of phenotype sizes in sequence-to-structure genotype-phenotype maps
• Statistical theory of phenotype abundance distributions: a test through exact enumeration of genotype spaces
• toyLIFE: a computational framework to study the multi-level organization of the genotype-phenotype map
• Human Genome Variation and the concept of Genotype Networks
• Robustness and epistasis in mutation-selection models
• Enumerating secondary structures and structural moieties for circular RNAs