Coalescence with purifying selection
How positive selection affects genealogies is demonstrated by the script
genealogies_with_selection.py
and discussed on page
Genealogies 1.
Here, we extend this discussion to purifying selection. Instead of an infinite sites
model, we now use a finite sites model. Recurrent mutations with are injected with rate
U. The population will settle at a state where the influx of deleterious mutations
is balanced by rare back-mutations. Hence this approximates a state where the
majority of mutations are deleterious. Mutations have effect size s.
The entire script can be viewed
genealogies_with_selection.html
or downloaded
genealogies_with_selection.py.
N = 10000 #population size
s = -1e-2 #single site effect
U = 0.1 #genome wide mutation rate
r = 0.0 #outcrossing rate
Everything is more or less the same as in the example on positive selection, only that the per site
mutation rate is set as
pop.set_mutation_rate(U/pop.L)
No sex, frequent deleterious mutations
The following shows three trees sampled from a large asexual population suffering
from many deleterious mutations.
The genealogies are strongly distorted and show long terminal branches and uneven branching.
Outcrossing reduces interference
To demonstrate how outcrossing reduces interference, the following shows the genealogy in
an obligate outcrossing population with a maplength 10. The population size was reduced to
N=1000 to speed up the simulation.
Coalescence takes much longer than in the asexual example, even though the population size
is smaller by a factor of 10.
Open the
script in your favorite
text editor, change parameters, and rerun to explore.