Swiss Brown Swiss in different environments: Does GxE play an important role? Beat Bapst Qualitas AG, Switzerland
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1 Swiss Brown Swiss in different environments: Does GxE play an important role? Beat Bapst Qualitas AG, Switzerland World Brown Swiss Congress, Mende
2 Introduction/Background Brown Swiss Dairy cattle is kept in various environments worldwide: Geographic/topographic/climate Lowlands Alpine regions with alpine summer pasture Tropical/Subtropical/Temperate climate... Production systems TMR feeding systems Pasture based feeding systems Organic/conventional systems
3 Also in Switzerland: Interactions between specific environment and genotype (GxE Interactions)? Are GxE interactions in Brown Swiss Dairy Cattle in Switzerland important?
4 Introduction/Background What are GxE interactions? Breed 1 Breed 1 Breed 1 Breed 2 Breed 2 Breed 2 Environment 1 Environment 2 Environment 1 Environment 2 Environment 1 Environment 2 No GxE Same ranking and also equal differences in performance Weak GxE Decrease stronger for Breed 2, same ranking Strong GxE Ranking changed
5 Methods/Data: Concept Multiple trait models Split a trait in n different other traits according to n defined environments Estimate the genetic correlations (r a ) between the traits Trait Trait 1 Trait 2 Trait n r a 1,2 r a 2,n r a 1,n
6 Methods/Data: Concept Trait Trait 1 Trait 2 Trait n r a 1,2 r a 2,n r a 1,n r a = 1 No GxE interactions 1 > r a > 0.8 Weak GxE interactions r a < 0.8 Strong GxE interactions
7 Methods/Data: Model Multiple trait animal model with repeated measurements REMLF90 Traits: Milk kg, fat kg and protein kg Stepwise model development Effect Type Trait Environment 1 Environment 2 Herd * Year random Mkg, Fat, Prot. Mkg, Fat, Prot. Calving Year * Season fix Mkg, Fat, Prot. Mkg, Fat, Prot. Lactation fix Mkg, Fat, Prot. Mkg, Fat, Prot. additiv genet. effect of animal Permanent environment random Mkg, Fat, Prot. Mkg, Fat, Prot. random Mkg, Fat, Prot. Mkg, Fat, Prot. Residual random Mkg, Fat, Prot. Mkg, Fat, Prot.
8 Methods/Data: Concept 2 Opposed environments/farms: Scenario FA: Farm altitude Mountain area 3 and 4 Env. 2 Mountain area 2 Mountain area 1 Lowland Env. 1
9 Methods/Data: Concept 2 Opposed environments/farms: Scenario UH: Udder health (annual average somatic cell count, scc ) scc < 58 : Env. 2 scc > 170 : Env. 1
10 Methods/Data: Concept 2 Opposed environments/farms: Scenario YL : Yield level Lactation yield < 6000 kg: Env. 2 Lactation yield > 8200 kg: Env. 1
11 Methods/Data: Data 2,113,959 standard lactation records Traits: Milk kg, fat kg and protein kg 746,043 cows Original Braunvieh excluded Restrictions: Test days only on the same farm during lactation, cows from lowland with summer alpine pasture were excluded Phenotypic key figures Year n Cows Ø Milk kg Ø Fat kg Ø Protein kg , , ,
12 Results: Farm altitude Heritabilities (diagonal elements) and genetic correlations, r a : Milk kg 1 Fat kg 1 Prot. kg 1 Milk kg 2 Fat kg 2 Prot.kg 2 Milk kg Fat kg Prot. kg Milk kg Fat kg Prot. kg
13 Results: Udder health Heritabilities (diagonal elements) and genetic correlations, r a : Milk kg 1 Fat kg 1 Prot. kg 1 Milk kg 2 Fat kg 2 Prot.kg 2 Milk kg Fat kg Prot. kg Milk kg Fat kg Prot. kg
14 Results: Yield level Heritabilities (diagonal elements) and genetic correlations, r a : Milk kg 1 Fat kg 1 Prot. kg 1 Milk kg 2 Fat kg 2 Prot.kg 2 Milk kg Fat kg Prot. kg Milk kg Fat kg Prot. kg
15 Conclusion/Discussion I GxE interactions do not exist for yield traits between the defined environments for Swiss Brown Swiss dairy cattle First preliminary results could not be confirmed Confirmation of former investigations for Swiss populations: r a for yield traits in conventional and organic environments (Bapst et al., 2007 in Simianer, 2007) Foreign investigations show similar results, partly with slight stronger GxE interactions (e.g. Pfeiffer et al., 2016; Cole, 2015; Streit et al., 2012) Stronger reactions were found in environments with bigger contrasts: e.g. South Africa (Neser et al., 2014)
16 Conclusion/Discussion II No need for action for the breeding program und for genetic evaluation But: Advancement of different environment definitions Test other methods/models/breeds
17 Thanks for your attention Acknowledgements: The authors acknowledge the financial support for this project provided by transnational funding bodies, being partners of the FP7 ERA-net project, CORE Organic Plus, and the cofund from the European Commission We would like to acknowledge Braunvieh Schweiz for the permission to use their data for this study
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