Genetic parameters of nematode resistance in dairy sheep

Summary

Resistance of gastrointestinal nematodes (GIN) in sheep to anthelmintics is rapidly increasing. The results of several studies indicate that selection for increased nematode resistance in sheep is possible, and the trait of interest is faecal egg count (FEC). Phenotyping of FEC is rather time-consuming and often costly, auxiliary traits that are more effective and easier would be greatly appreciated. The extent of Haemonchus contortus infestation is often measured by the coloration of the conjunctiva and the so-called FAMACHA© test. In our study, we aimed to test whether FAMACHA could also be used as auxiliary trait for FEC. Additionally we aimed to provide genetic parameters for FEC, milk yield and packed cell volume (PCV). We phenotyped 1,150 naturally infected Lacaune ewes on 15 commercial Swiss farms. Phenotypic correlation between FEC and FAMACHA as well as FAMACHA and PCV resulted in 0.25 (SE 0.03) and -0.35 (SE 0.08), respectively. Subsequent genetic analysis was carried out with a multi-trait animal model in order to estimate the genetic parameters of the traits mentioned above. We found moderate heritabilities of FEC, FAMACHA, PCV and milk yield in the range of 0.30 to 0.36 (SE 0.08 for all traits). The particular focus was on the genetic correlation of FEC and FAMACHA and was estimated to be 0.03 (SE 0.22). The distribution of the FAMACHA score indicated a medium to high worm infestation, but FEC was relatively low compared to other studies. Eventually the infection pressure was not high enough to yield a good genetic correlation of FEC and FAMACHA. In general, it can be concluded that the heritability for FEC is very appealing and that a selection program could be based on them. FAMACHA as an auxiliary trait could not be confirmed in this study. Either further studies need to be designed differently to better explore the relationship between FAMACHA and FEC or other possible auxiliary traits need to be sought and developed. This study was funded by SMARTER H2020 project no. 772787.