This dissertation focuses on the prediction of long-term genetic contributions, rates of inbreeding and rates of gain in artificially selected populations. The long-term genetic contribution ( r i ) of ancestor i born at time t 1 , is defined as the proportion of genes from i that are present in individuals in generation t 2 deriving by descent from i , where ( t 2 - t 1 )→∞.
The long-term genetic contribution of an individual was predicted by linear regression on the selective advantage of the individual. With overlapping generations, long-term genetic contributions were predicted using a modified gene flow approach. A novel definition of generation interval was introduced, which states that the generation interval is the length of time in which long-term genetic contributions sum to unity. It was shown that the rate of inbreeding is proportional to the sum of squared of expected long-term genetic contributions and that the rate of genetic gain is proportional to the sum of cross products of long-term genetic contributions and Mendelian sampling terms. Accurate predictions of rates of inbreeding were obtained for populations with discrete or overlapping generations undergoing either mass selection or selection on Best Linear Unbiased Prediction of breeding values. The method was applied to crossbreeding systems, which showed that the use of crossbred information may increase the rate of genetic gain, but measures to restrict the rate of inbreeding are required.
|Qualification||Doctor of Philosophy|
|Award date||27 Jun 2000|
|Place of Publication||S.l.|
|Publication status||Published - 2000|
- animal breeding
- genetic gain
- genetic diversity
- cum laude