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Estimation of additive genetic variance when base populations are selected
J H van der Werf1, I J de Boer
1Dept. of Anim. Breed., Wageningen Agricultural University, The Netherlands.
Journal of Animal Science
|October 1, 1990
Summary
Genetic variance decreased over 10 generations due to selection, inbreeding, and disequilibrium. Using all data and relationships in animal models provided unbiased estimates of additive genetic variance (sigma 2a).
Area of Science:
- Quantitative Genetics
- Animal Breeding
- Population Genetics
Background:
- Understanding genetic variance changes under selection is crucial for breeding programs.
- Inbreeding and gametic disequilibrium can impact additive genetic variance (sigma 2a) over generations.
- Accurate estimation of sigma 2a is essential for genetic gain.
Purpose of the Study:
- To investigate the reduction of additive genetic variance (sigma 2a) in a simulated population under selection.
- To evaluate the impact of inbreeding and gametic disequilibrium on genetic variance.
- To assess the accuracy of sigma 2a estimates using Restricted Maximum Likelihood (REML) with an animal model.
Main Methods:
- Simulated a population of size 40 for 10 generations with specific selection intensity.
- Calculated additive genetic variance (sigma 2a) and heritability at the start and end of simulations.
- Employed Restricted Maximum Likelihood (REML) with an animal model to estimate sigma 2a, analyzing the effects of data omission and relationship information.
Main Results:
- Additive genetic variance (sigma 2a) decreased from 10 to 6.72 in the small population due to selection, covariances, inbreeding, and gametic disequilibrium.
- Variance reduction was less pronounced in a larger population (size 400) with lower selection intensity.
- REML estimates of sigma 2a were unbiased when all data and relationships were used; omitting selected ancestor data led to bias due to unaccounted gametic disequilibrium.
Conclusions:
- Selection, inbreeding, and gametic disequilibrium reduce additive genetic variance (sigma 2a) over time.
- Accurate estimation of sigma 2a requires utilizing all available data and relationship information within an animal model.
- Accounting for gametic disequilibrium and inbreeding through comprehensive relationship data improves the unbiasedness of sigma 2a estimates, particularly in smaller populations or early selection stages.