title: Use of genotype × environment interaction model to accommodate genetic heterogeneity for residual feed intake, dry matter intake, net energy in milk, and metabolic body weight in dairy cattle.
abstract: Feed efficiency in dairy cattle has gained much attention recently. Due to the cost-prohibitive measurement of individual feed intakes, combining data from multiple countries is often necessary to ensure an adequate reference population. It may then be essential to model genetic heterogeneity when making inferences about feed efficiency or selecting efficient cattle using genomic information. In this study, we constructed a marker × environment interaction model that decomposed marker effects into main effects and interaction components that were specific to each environment. We compared environment-specific variance component estimates and prediction accuracies from the interaction model analyses, an across-environment analyses ignoring population stratification, and a within-environment analyses using an international feed efficiency data set. Phenotypes included residual feed intake, dry matter intake, net energy in milk, and metabolic body weight from 3,656 cows measured in 3 broadly defined environments: North America (NAM), the Netherlands (NLD), and Scotland (SAC). Genotypic data included 57,574 single nucleotide polymorphisms per animal. The interaction model gave the highest prediction accuracy for metabolic body weight, which had the largest estimated heritabilities ranging from 0.37 to 0.55. The within-environment model performed the best when predicting residual feed intake, which had the lowest estimated heritabilities ranging from 0.13 to 0.41. For traits (dry matter intake and net energy in milk) with intermediate estimated heritabilities (0.21 to 0.50 and 0.17 to 0.53, respectively), performance of the 3 models was comparable. Genomic correlations between environments also were computed using variance component estimates from the interaction model. Averaged across all traits, genomic correlations were highest between NAM and NLD, and lowest between NAM and SAC. In conclusion, the interaction model provided a novel way to evaluate traits measured in multiple environments in which genetic heterogeneity may exist. This model allowed estimation of environment-specific parameters and provided genomic predictions that approached or exceeded the accuracy of competing within- or across-environment models.
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706. Electronic address: Chen.Yao225@gmail.com.
authors.forename: C
authors.initials: C
authors.lastname: Yao
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824.
authors.forename: G
authors.initials: G
authors.lastname: de Los Campos
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824.
authors.forename: M J
authors.initials: MJ
authors.lastname: VandeHaar
authors.affiliation: Department of Animal Science, Iowa State University, Ames 50011.
authors.forename: D M
authors.initials: DM
authors.lastname: Spurlock
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: L E
authors.initials: LE
authors.lastname: Armentano
authors.affiliation: Scottish Agricultural College, Easter Bush, Midlothian, EH25 9RG, United Kingdom.
authors.forename: M
authors.initials: M
authors.lastname: Coffey
authors.affiliation: Wageningen UR Livestock Research, Wageningen, 6700 AH, the Netherlands.
authors.forename: Y
authors.initials: Y
authors.lastname: de Haas
authors.affiliation: Wageningen UR Livestock Research, Wageningen, 6700 AH, the Netherlands.
authors.forename: R F
authors.initials: RF
authors.lastname: Veerkamp
authors.affiliation: Department of Animal Sciences, University of Florida, Gainesville 32611.
authors.forename: C R
authors.initials: CR
authors.lastname: Staples
authors.affiliation: Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705.
authors.forename: E E
authors.initials: EE
authors.lastname: Connor
authors.affiliation: Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
authors.forename: Z
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Department of Dairy Science, Virginia Tech, Blacksburg 24061.
authors.forename: M D
authors.initials: MD
authors.lastname: Hanigan
authors.affiliation: Department of Animal Science, Michigan State University, East Lansing 48824.
authors.forename: R J
authors.initials: RJ
authors.lastname: Tempelman
authors.affiliation: Department of Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: K A
authors.initials: KA
authors.lastname: Weigel
mesh_terms: D000818:Animals; D001835:Body Weight; D002417:Cattle; D004435:Eating / Q000235:genetics; D005260:Female; D059647:Gene-Environment Interaction; D018740:Genetic Heterogeneity; D005838:Genotype; D007774:Lactation / Q000235:genetics*; D008892:Milk
keywords: feed efficiency; genomic selection; interaction model