6,253 research outputs found
Neutral Evolution of Mutational Robustness
We introduce and analyze a general model of a population evolving over a
network of selectively neutral genotypes. We show that the population's limit
distribution on the neutral network is solely determined by the network
topology and given by the principal eigenvector of the network's adjacency
matrix. Moreover, the average number of neutral mutant neighbors per individual
is given by the matrix spectral radius. This quantifies the extent to which
populations evolve mutational robustness: the insensitivity of the phenotype to
mutations. Since the average neutrality is independent of evolutionary
parameters---such as, mutation rate, population size, and selective
advantage---one can infer global statistics of neutral network topology using
simple population data available from {\it in vitro} or {\it in vivo}
evolution. Populations evolving on neutral networks of RNA secondary structures
show excellent agreement with our theoretical predictions.Comment: 7 pages, 3 figure
Statistical properties of neutral evolution
Neutral evolution is the simplest model of molecular evolution and thus it is
most amenable to a comprehensive theoretical investigation. In this paper, we
characterize the statistical properties of neutral evolution of proteins under
the requirement that the native state remains thermodynamically stable, and
compare them to the ones of Kimura's model of neutral evolution. Our study is
based on the Structurally Constrained Neutral (SCN) model which we recently
proposed. We show that, in the SCN model, the substitution rate decreases as
longer time intervals are considered, and fluctuates strongly from one branch
of the evolutionary tree to another, leading to a non-Poissonian statistics for
the substitution process. Such strong fluctuations are also due to the fact
that neutral substitution rates for individual residues are strongly correlated
for most residue pairs. Interestingly, structurally conserved residues,
characterized by a much below average substitution rate, are also much less
correlated to other residues and evolve in a much more regular way. Our results
could improve methods aimed at distinguishing between neutral and adaptive
substitutions as well as methods for computing the expected number of
substitutions occurred since the divergence of two protein sequences.Comment: 17 pages, 11 figure
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