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Prediction of genetic gain in finite populations with heterogeneous predicted breeding values accuracies
Author(s) -
Elsen J.M.
Publication year - 2016
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/jbg.12222
Subject(s) - selection (genetic algorithm) , mathematics , homogeneous , statistics , computation , differential (mechanical device) , algebraic number , reliability (semiconductor) , genetic gain , genetic variation , biology , computer science , algorithm , genetics , mathematical analysis , combinatorics , artificial intelligence , physics , power (physics) , quantum mechanics , thermodynamics , gene
Summary The algebraic expression of the genetic selection differential (expected genetic superiority of breeders after a selection on their Predicted Breeding Values) was derived when a limited number of individuals were selected from a limited sample of candidates on the basis of their predicted genetic value, with heterogeneous reliabilities. A formula is proposed for situations in which these reliabilities can be clustered in a few classes. We show that the expected genetic selection differential increases with the number of classes, the mean reliability being constant. In the panel of cases simulated, this increase reached up to 18% of the values obtained in the homogeneous situation. We used the proposed formulae to estimate selection differentials and compared it numerically with performing simulations. In terms of speed of computation, our algebraic formulae performed better than simulations in populations of limited size.