title: Genotype by environment interaction for yield and somatic cell score with alternative environmental definitions.
abstract: Differential genetic expression in high and low opportunity Sicilian Holstein-Friesian and Brown Swiss herd environments was investigated using endogenous and exogenous variables in a set of three definitions. Results of genetic by environmental interaction were compared using alternative environmental definitions: within herd-year standard deviation for mature equivalent milk yield (HYSD), detectable incidence of normal vs. abnormal (peakless) lactation and herds clustered by causal relationships from high and low frequency use of nutrition, milking, health and animal handling practices. Data for genetic analysis consisted of first-lactation standardized yields of milk, fat and protein, and weighted somatic cell score for 8897 daughters of 825 Holstein-Friesian sires and 1143 daughters of 220 Brown Swiss sires. Components of covariance, heritabilities, and genetic correlations were estimated using bivariate and multivariate sire models for average and contrasting environments for each definition. Sire variances for yields were consistently smaller in the low opportunity environments of both breeds. Except for differential incidence of abnormal lactation in Friesian herds, correlated yield response in less privileged environments was 0.41 to 0.81 as much as in high opportunity environments, a substantial loss. Genetic correlations between HYSD environments for yield traits of Friesian were 0.48 to 0.66 but exceeded 0.80 for other definitions. Less correlated response in somatic cell score was also predicted for environments with low use of yield-enhancing practices (0.66 for Friesian and 0.61 for Brown Swiss), which may have resulted from less health care and poorer milking management. Therefore, unfavorable management interactions likely foster unequal gains from selection in contrasting environments defined exogenously or by incidence of peakless lactation. Conversely, greater genetic as well as phenotypic response is expected from additional inputs of nutrition, health care and milking management.
authors.affiliation: CoRFiLaC, Regione Siciliana, 97100 Ragusa, Italy. er53@cornell.edu
authors.forename: E
authors.initials: E
authors.lastname: Raffrenato
authors.forename: R W
authors.initials: RW
authors.lastname: Blake
authors.forename: P A
authors.initials: PA
authors.lastname: Oltenacu
authors.forename: J
authors.initials: J
authors.lastname: Carvalheira
authors.forename: G
authors.initials: G
authors.lastname: Licitra
mesh_terms: D000704:Analysis of Variance; D000824:Animal Nutritional Physiological Phenomena; D000818:Animals; D001947:Breeding; D002417:Cattle / Q000235:genetics*; D002452:Cell Count; D003612:Dairying / Q000379:methods; D004777:Environment; D005260:Female; D014644:Genetic Variation; D005838:Genotype; D006304:Health Status; D007774:Lactation / Q000235:genetics*; D008055:Lipids / Q000032:analysis; D008297:Male; D008892:Milk / Q000737:chemistry*; D008894:Milk Proteins / Q000032:analysis; D010641:Phenotype
chemical_list: D008055:Lipids; D008894:Milk Proteins