9.6.2 Example: rabbit breeding

Not only horse people like show jumping, also for rabbits there is a jumping competition. One very fanatic rabbit trainer decided to start selection on jumping capacity (measured in cm of fence size). Males and females both perform equally well in the jumping circuit. As females are capable of producing large number of offspring in a short period of time, selected proportion can be of equal size in males and females. Our breeder is selecting the 20% best jumpers for breeding, based on performance of 10 ? of their offspring. The heritability for show jumping capacity in rabbits is 0.14, with a phenotypic variance of 40. Predict the genetic gain that the breeder will achieve using this selection strategy.

A selected proportion of 20% results in a selection intensity of 1.4. The accuracy of selection can be determined using table in the chapter 8.11 on ranking the animals:

Open

If we fill in the heritability and the number of offspring, we come to an accuracy of selection of 0.266. The genetic variance can be determined from the heritability and the phenotypic variance: 0.14*40 = 5.6, so the genetic standard deviation is the square root of 5.6, which is 2.37.

Filling all that information into the formula results in a genetic gain of: ΔG = 1.4 * 0.27 * 2.37 = 0.90 cm

The prediction is that the next generation on average will jump 0.90 cm higher than the current generation.

The breeder is disappointed and wants more genetic gain. Predict how much improvement he can achieve be selecting the top 15% instead of the top 20% for breeding.

The accuracy of selection and the genetic standard deviation remain the same, but the selection intensity increases from 1.4 to 1.554. The predicted response to selection then becomes 0.99 cm.

The breeder is still not completely satisfied because he wants a genetic gain of more than 1 cm and decides to base the selection on the performance of 12 instead of 10 offspring. Predict the selection response for this new situation.

Selection based on performance of more offspring will increase the accuracy of selection. Re-calculating that results in an r_IH of 0.30. The predicted selection response now becomes 1.554*0.30*2.37 = 1.10 cm.