Open AccessSelection limits and strategies
Author(s) -
C. Clark Cockerham,
P. M. Burrows
Publication year - 1980
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.77.1.546
Subject(s) - selection (genetic algorithm) , limit (mathematics) , truncation (statistics) , biology , statistics , distribution (mathematics) , trait , normal distribution , disruptive selection , mathematics , evolutionary biology , genetics , computer science , natural selection , mathematical analysis , artificial intelligence , programming language
Strategies are analyzed for maximizing the ultimate limit to truncation selection for a quantitative trait in finite populations. By using a formulation of Kimura and Crow [Kimura, M. & Crow, J. F. (1978)Proc. Natl. Acad. Sci. USA 75, 6168-6171], it is shown that the limit is maximized by truncating at the mode with the highest ordinate of the phenotypic distribution. This implies 50% selection for the normal or any unimodal symmetric distribution and, for skewed distributions, selection of more than one-half if desired phenotypes are in the long tail of the distribution, less than one-half if in the short tail. For dioecious populations, the optimal procedure requires, in addition, equal numbers recorded and selected of each sex. For monoecious populations the limit can be improved by using the best individuals mated to the next-best individuals. Limitations of the results are discussed.