title: Short communication: Use of single nucleotide polymorphism genotypes and health history to predict future phenotypes for milk production, dry matter intake, body weight, and residual feed intake in dairy cattle.
abstract: As feed prices have increased, the efficiency of feed utilization in dairy cattle has attracted increasing attention. In this study, we used residual feed intake (RFI) as a measurement of feed efficiency along with its component traits, adjusted milk energy (aMilkE), adjusted dry matter intake (aDMI), and adjusted metabolic body weight (aMBW), where the adjustment was for environmental factors. These traits may also be affected by prior health problems. Therefore, the carryover effects of 3 health traits from the rearing period and 10 health traits from the lactating period (in the same lactation before phenotype measurements) on RFI, aMilkE, aDMI, and aMBW were evaluated. Cows with heavier birth weight and greater body weight at calving of this lactation had significant increases in aMilkE, aDMI, and aMBW. The only trait associated with RFI was the incidence of diarrhea early in the lactation. Mastitis and reproductive problems had negative carryover effects on aMilkE. The aMBW of cows with metabolic disorders early in the lactation was lower than that of unaffected cows. The incidence of respiratory disease during lactating period was associated with greater aMBW and higher aDMI. To examine the contribution of health traits to the accuracy of predicted phenotype, genomic predictions were computed with or without information regarding 13 health trait phenotypes using random forests (RF) and support vector machine algorithms. Adding health trait phenotypes increased prediction accuracies slightly, except for prediction of RFI using RF. In general, the accuracies were greater for support vector machine than RF, especially for RFI. The methods described herein can be used to predict future phenotypes for dairy replacement heifers, thereby facilitating culling decisions that can lead to decreased feed costs during the rearing period. For these decisions, prediction of the animal's own phenotype is of greater importance than prediction of the genetic superiority or inferiority that will transmit to its offspring.
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 Dairy Science, University of Wisconsin, Madison 53706.
authors.forename: L E
authors.initials: LE
authors.lastname: Armentano
authors.affiliation: Department of Animal Sciences, Michigan State University, East Lansing 48824.
authors.forename: M J
authors.initials: MJ
authors.lastname: VandeHaar
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 / Q000235:genetics / Q000502:physiology*; D003612:Dairying / Q000379:methods*; D004435:Eating; D002149:Energy Intake; D005247:Feeding Behavior; D005260:Female; D020641:Polymorphism, Single Nucleotide
keywords: feed efficiency; genome-health prediction; health trait