Difference between revisions of "Probability of fixation"
| Line 19: | Line 19: | ||
It may be surprising at first the the probability of fixation of a new allele that confers a fitness advantage is only approximately 2''s''. So if it gives a 3% fitness advantage the probability of fixation is only about 6%. In other words there is a 94% chance the new adaptive allele will be lost due to genetic drift. This implies that adaptive evolution of a species is very inefficient and that adaptive alleles have to occur repeatedly by mutation, to be lost by drift, before they eventually fix. | It may be surprising at first the the probability of fixation of a new allele that confers a fitness advantage is only approximately 2''s''. So if it gives a 3% fitness advantage the probability of fixation is only about 6%. In other words there is a 94% chance the new adaptive allele will be lost due to genetic drift. This implies that adaptive evolution of a species is very inefficient and that adaptive alleles have to occur repeatedly by mutation, to be lost by drift, before they eventually fix. | ||
| − | Why is this process so inefficient? When an allele is rare, such as a single copy as a new mutation, the forces of drift are typically much larger than the forces of selection. As an example work out the probability of sampling zero copies of an allele at a count of one from one generation to the next with a Poisson distribution and a mean of 1+''s''. | + | Why is this process so inefficient? When an allele is rare, such as a single copy as a new mutation, the forces of drift are typically much larger than the forces of selection. As an example work out the probability of sampling zero copies of an allele at a count of one from one generation to the next with a Poisson distribution and a mean of ''λ'' = 1+''s''. |
| + | |||
| + | <math>P(k)=\frac{\lambda^k e^{-\lambda}}{k!}</math> | ||
| + | |||
| + | If ''s'' = 0.03 ... | ||
=Notes= | =Notes= | ||
Revision as of 07:30, 23 September 2018
This was derived in Kimura 1962.
[math]u(p)=\frac{1-e^{4N_esp}}{1-e^{4N_es}}[/math]
If we are considering the initial frequency of a single new mutation in the population p=1/(2Ne),
[math]u(p)_1=\frac{1-e^{4N_es\frac{1}{2N_e}}}{1-e^{4N_es}}=\frac{1-e^{2s}}{1-e^{4N_es}}[/math].
And if 4Nes is large
[math]u(p)_2\approx\frac{1-e^{2s}}{1}=1-e^{2s}[/math].
[math]e^{2s}\approx 1+2s[/math]
[math]u(p)_2 \approx 1-e^{2s} \approx 1-1+2s = 2s[/math].
This agrees with the results of Fisher 1930 and Wright 1931.
It may be surprising at first the the probability of fixation of a new allele that confers a fitness advantage is only approximately 2s. So if it gives a 3% fitness advantage the probability of fixation is only about 6%. In other words there is a 94% chance the new adaptive allele will be lost due to genetic drift. This implies that adaptive evolution of a species is very inefficient and that adaptive alleles have to occur repeatedly by mutation, to be lost by drift, before they eventually fix.
Why is this process so inefficient? When an allele is rare, such as a single copy as a new mutation, the forces of drift are typically much larger than the forces of selection. As an example work out the probability of sampling zero copies of an allele at a count of one from one generation to the next with a Poisson distribution and a mean of λ = 1+s.
[math]P(k)=\frac{\lambda^k e^{-\lambda}}{k!}[/math]
If s = 0.03 ...
Notes
This is derived from
[math]u(p) = \frac{\int_0^p G(x)\, \mbox{d} x}{\int_0^1 G(x)\, \mbox{d} x}[/math],
equation 3 of Kimura 1962.
[math]u(p,t)[/math] is the probability of fixation of an allele at frequency p within t generations.
The change in allele frequency ([math]\delta p[/math]) over short periods of time ([math]\delta t[/math]) is
[math]u(p, t+\delta t) = \int f(p, p+\delta p; \delta t) u(p+ \delta p, t) \, \mbox{d} (\delta p)[/math],
integrating over all values of changes in allele frequency ([math]\delta p[/math]).
A mean and variance of the change in allele frequency (p) per generation are defined as
[math]M_{\delta p}=\lim_{\delta t \to 0} \frac{1}{\delta t} \int (\delta p) f(p, p+\delta p; \delta t) \, \mbox{d} (\delta p)[/math]
[math]V_{\delta p}=\lim_{\delta t \to 0} \frac{1}{\delta t} \int (\delta p)^2 f(p, p+\delta p; \delta t) \, \mbox{d} (\delta p)[/math]
The probability of fixation given sufficient time for fixation to occur is
[math]u(p)=\lim_{t \to \infty} u(p,t)[/math]
(to be continued ... I need to work through this.)
