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Evolutionary suppressors: Difference between revisions
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The simplest and most extreme case of an evolutionary suppressor is given by a linear chain where the offspring of each individual consistently replaces e.g. the occupant of the vertex to its right. Thus, the leftmost vertex is a root and is never replaced whereas the offspring of the rightmost, tail vertex is lost. This generates a flux through the population from left to right such that no mutant can reach fixation unless the mutation occurs in the root vertex. This happens with the probability \(1/N\) in a chain of length \(N\) but then fixation occurs with certainty. Consequently, the fixation is simply | The simplest and most extreme case of an evolutionary suppressor is given by a linear chain where the offspring of each individual consistently replaces e.g. the occupant of the vertex to its right. Thus, the leftmost vertex is a root and is never replaced whereas the offspring of the rightmost, tail vertex is lost. This generates a flux through the population from left to right such that no mutant can reach fixation unless the mutation occurs in the root vertex. This happens with the probability \(1/N\) in a chain of length \(N\) but then fixation occurs with certainty. Consequently, the fixation is simply | ||
\begin{align} | \begin{align} | ||
\ | \rho_0 = \frac1N, | ||
\end{align} | \end{align} | ||
irrespective of the mutant’s fitness. Selection is eliminated and random drift rules. If a graph contains multiple root nodes then a single mutation can never reach fixation, \(\rho=0\). | irrespective of the mutant’s fitness. Selection is eliminated and random drift rules. If a graph contains multiple root nodes then a single mutation can never reach fixation, \(\rho=0\). | ||
