Premium
Dominance and Genetic Drift
Author(s) -
Edwards Jode W.,
Lamkey Kendall R.
Publication year - 2003
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2003.2006
Subject(s) - inbreeding , biology , genetic variation , selection (genetic algorithm) , population , statistics , genetic diversity , genetic model , genetic variability , effective population size , variance (accounting) , genetic drift , genetics , evolutionary biology , mathematics , genotype , demography , artificial intelligence , sociology , computer science , gene , accounting , business
Many public sector maize recurrent selection programs have been designed based on additive genetic expectations. Populations have been managed as large metapopulations with the assumption that population size must be very large because inbreeding due to finite size causes a linear reduction in genetic variance; we show that in BS13(S)C0 such predictions are inaccurate and discuss some implications. The objective of this study was to predict the effects of subdividing a maize population, BS13(S)C0, into finite subpopulations with previous estimates of genotypic variance‐covariance components in the BS13(S)C0 population. Changes in variance among subpopulations, genetic variances within subpopulations, and mean values of subpopulations were predicted. Predicted variance among subpopulations increased approximately linearly with the inbreeding coefficient, in accordance with additive genetic expectations. Additive genetic theory predicts a linear decline in both total and additive genetic variance within subpopulations. Predicted total genetic variance within subpopulations initially increased, then decreased when the inbreeding coefficient was between 0.2 and 0.4 for most traits. Predicted additive genetic variance within subpopulations for grain yield decreased little at inbreeding coefficients <0.5. Predicted additive genetic variance for other traits decreased in approximate accordance with additive genetic expectations. These results provide model‐based predictions that inbreeding BS13(S)C0, that is, genetic drift, will not lead to linear reductions in total genetic variance or additive genetic variance as typically expected. Implications of these results for agricultural selection programs are discussed.