Other: a software to detect recent positive selection reliably in natural population
From the Evolution Directory (EvolDir) via Twitter.
Dear all,
as you may know, due to the confounding effect of demography, it is
extremely difficult to detect recent positive Darwinian selection
reliably in a natural or domestic population. Recently, we proposed a
novel method. This method has been mathematically proved that the
demographic factors, including population size expansion and bottleneck,
do not affect the test.
Notably, it's a single-locus based approach. That means, to detect
positive selection reliably, all you need is just a short piece of
nuclear DNA, say several hundred base pairs. The sample size should be
>= 21 (diploid) individuals.
The logic behind the method is: the confounding effect of varying
population size can be completely removed if we only examine tree
topology. Then two very simple sampling strategies remove the
confounding effect of hidden population structure. Those two sampling
strategies are:
1) The minimum sample size from each sampling location should be at
least 2 or 3, calculated as alph * (n - 1) / 2. Alpha is the
significance level, n the sample size.
2) Assuming your sampling locations do not cover the whole species
distribution area, and these uncovered areas are separated into several
isolated regions due to natural barriers. Then try to collect one
individual/chromosome from each isolated (and uncovered) regions. Those
individuals will be used as migrant detectors. Usually, 2 or 5 migrant
detectors should be enough.
The method has been described in: Haipeng Li (2011). A new test for
detecting recent positive selection that is free from the confounding
impacts of demography. Mol Biol Evol 28:365-375.
The software can be download freely from
http://www.picb.ac.cn/evolgen/softwares/
Yours sincerely,
Yuting Wang (wangyuting@picb.ac.cn)
&
Haipeng Li (lihaipeng@picb.ac.cn)
===============================================Haipeng Li, Dr.
Laboratory of Evolutionary Genomics
CAS-MPG Partner Institute for Computational Biology
Chinese Academy of Sciences
Yue Yang Road 320
Shanghai, 200031
China
Tel: +(86)-21-54920460
Fax: +(86)-21-54920451
E-mail: lihaipeng@picb.ac.cn
================================================