Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Optimization of selection response under restricted inbreeding | Genet Sei Evol 1990 22 93-107 Elsevier INRA 93 Original article Optimization of selection response under restricted inbreeding M Toro M Pérez-Enciso Universidad Complutense Facultad de Biologia Departamento de Genética 28040 Madrid Spain Received 4 January 1989 accepted 13 September 1989 Summary - A reasonable objective for selection programs in small populations is the maximization of response with a restriction on the increase of inbreeding. This restriction will be especially important when information on relatives is used for evaluation of candidates for selection. To achieve this objective different strategies have been proposed i to reduce the intensity of selection ii to lower the weight given to family information in an index below the optimal value iii to restrict the variation of family size iv to make matings between the selected animals so as to minimize the average coancestry coefficient and_ v to find a general solution using linear programing. These strategies have been illustrated by genetic simulation of a simple example. The population consisted of 8 males and 8 females selected from 32 animals evaluated in each sex. The candidates were evaluated by an index using information on the individual and its 7 sibs. Five generations of selection were practised. It was concluded that there are several alternative strategies which ensure that inbreeding is below the fixed level 5 per generation without a significant loss of response in comparison with classical strategies where inbreeding is not restricted. A substantial reduction of inbreeding was found with the use of matings having minimal coancestry. However this reduction was due principally to a delay of 1 generation in the appearance of inbreeding. Linear programing was also efficient in achieving these aims. It is in principle more flexible than the other strategies but its heavy cost of computation is a disadvantage and in practice comparable results can probably be obtained using much simpler .
