Genetics, Vol. 151, 1197-1210, March 1999, Copyright © 1999

Prediction of Genetic Contributions and Generation Intervals in Populations With Overlapping Generations Under Selection

Piter Bijmaa and John A. Woolliamsb
a Animal Breeding and Genetics Group, Wageningen Institute of Animal Sciences, Wageningen Agricultural University, 6700AH Wageningen, The Netherlands
b Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, United Kingdom

Corresponding author: Piter Bijma, Animal Breeding and Genetics Group, Department of Animal Sciences, Wageningen Agricultural University, P.O. Box 338, Marijkeweg 40, 6700AH Wageningen, The Netherlands., piter.bijma{at}alg.vf.wau.nl (E-mail)

Communicating editor: T. MACKAY

A method to predict long-term genetic contributions of ancestors to future generations is studied in detail for a population with overlapping generations under mass or sib index selection. An existing method provides insight into the mechanisms determining the flow of genes through selected populations, and takes account of selection by modeling the long-term genetic contribution as a linear regression on breeding value. Total genetic contributions of age classes are modeled using a modified gene flow approach and long-term predictions are obtained assuming equilibrium genetic parameters. Generation interval was defined as the time in which genetic contributions sum to unity, which is equal to the turnover time of genes. Accurate predictions of long-term genetic contributions of individual animals, as well as total contributions of age classes were obtained. Due to selection, offspring of young parents had an above-average breeding value. Long-term genetic contributions of youngest age classes were therefore higher than expected from the age class distribution of parents, and generation interval was shorter than the average age of parents at birth of their offspring. Due to an increased selective advantage of offspring of young parents, generation interval decreased with increasing heritability and selection intensity. The method was compared to conventional gene flow and showed more accurate predictions of long-term genetic contributions.





This article has been cited by other articles:


Home page
GeneticsHome page
D. Gianola, B. Heringstad, and J. Odegaard
On the Quantitative Genetics of Mixture Characters
Genetics, August 1, 2006; 173(4): 2247 - 2255.
[Abstract] [Full Text] [PDF]


Home page
J DAIRY SCIHome page
A. C. Sorensen, M. K. Sorensen, and P. Berg
Inbreeding in Danish Dairy Cattle Breeds
J Dairy Sci, May 1, 2005; 88(5): 1865 - 1872.
[Abstract] [Full Text] [PDF]


Home page
J ANIM SCIHome page
S. Avendano, B. Villanueva, and J. A. Woolliams
Expected increases in genetic merit from using optimized contributions in two livestock populations of beef cattle and sheep
J Anim Sci, December 1, 2003; 81(12): 2964 - 2975.
[Abstract] [Full Text] [PDF]


Home page
GeneticsHome page
J. A. Woolliams and P. Bijma
Predicting Rates of Inbreeding in Populations Undergoing Selection
Genetics, April 1, 2000; 154(4): 1851 - 1864.
[Abstract] [Full Text]


Home page
GeneticsHome page
P. Bijma, J. A. M. Van Arendonk, and J. A. Woolliams
A General Procedure for Predicting Rates of Inbreeding in Populations Undergoing Mass Selection
Genetics, April 1, 2000; 154(4): 1865 - 1877.
[Abstract] [Full Text]


Home page
GeneticsHome page
J. A. Woolliams, P. Bijma, and B. Villanueva
Expected Genetic Contributions and Their Impact on Gene Flow and Genetic Gain
Genetics, October 1, 1999; 153(2): 1009 - 1020.
[Abstract] [Full Text] [PDF]