A desired gains approach for the prediction of genetic gain in resistance to gastrointestinal nematodes in a multi-trait breeding objective in Uruguayan Merino sheep.

Gastrointestinal nematodes (GIN) constitute a problem in many sheep production systems, including those in Uruguay, causing reduced productivity and increased expenses. The main strategy to control GIN has consisted of the use of anthelmintics. However, GINs have developed resistance to anthelmintics, reducing their effectiveness. Genetic resistance to GINs has been found in flocks of different breeds. To date, there have been no reports about GINs breaking down genetic resistance in sheep. Heritability estimates of resistance to GIN within breeds are generally moderate, so that achieving genetic gain within a flock is possible. In this study, we predicted genetic gain in worm egg count (WEC), an indirect (and generally preferred) criterion of resistance to GIN, following different strategies. A multi-trait breeding objective including wool and meat traits was assumed and genetic gain over 10 years of selection in a Merino flock was estimated. We used a desired gains approach, examining situations in which the economic contribution of genetic gain in resistance to GIN in percentage terms was 0, 25, 50, 75 or 100. Except when the level of infestation with GIN was low, a considerable amount of emphasis had to be placed on selection for low WEC in order to reach the threshold below which the administration of anthelmintics is not required. High emphasis on reducing WEC lead to a reduction in genetic gain in wool and meat traits, or to their deterioration in the extreme case of 100 per cent emphasis on WEC. Given this finding, coupled with the difficulties encountered in accurately recording and selecting for WEC, we concluded that in addition to embarking upon a programme of within flock selection, sheep breeders interested in improving genetic resistance to GIN should also consider using breeding stock identified as superior for both resistance and production traits in across flock genetic evaluations.

Indirect genetic effects and inbreeding: consequences of BLUP selection for socially affected traits on rate of inbreeding.

BACKGROUND: Social interactions often occur among living organisms, including aquatic animals. There is empirical evidence showing that social interactions may genetically affect phenotypes of individuals and their group mates. In this context, the heritable effect of an individual on the phenotype of another individual is known as an Indirect Genetic Effect (IGE). Selection for socially affected traits may increase response to artificial selection, but also affect rate of inbreeding. METHODS: A simulation study was conducted to examine the effect of Best Linear Unbiased Prediction (BLUP) selection for socially affected traits on the rate of inbreeding. A base scenario without IGE and three alternative scenarios with different magnitudes of IGE were simulated. In each generation, 25 sires and 50 dams were mated, producing eight progeny per dam. The population was selected for 20 generations using BLUP. Individuals were randomly assigned to groups of eight members in each generation, with two families per group, each contributing four individuals. "Heritabilities" (for both direct and indirect genetic effects) were equal to 0.1, 0.3 or 0.5, and direct-indirect genetic correlations were -0.8, -0.4, 0, 0.4, or 0.8. The rate of inbreeding was calculated from generation 10 to 20. RESULTS: For the base scenario, the rates of inbreeding were 4.09, 2.80 and 1.95% for "heritabilities" of 0.1, 0.3 and 0.5, respectively. Overall, rates of inbreeding for the three scenarios with IGE ranged from 2.21 to 5.76% and were greater than for the base scenarios. The results show that social interaction within groups of two families increases the resemblance between estimated breeding values of relatives, which, in turn, increases the rate of inbreeding. CONCLUSION: BLUP selection for socially affected traits increased the rate of inbreeding. To maintain inbreeding at an acceptable rate, a selection algorithm that restricts the increase in mean kinship, such as optimum contribution selection, is required.