title: Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture.
abstract: Hanwoo beef is known for its marbled fat, tenderness, juiciness and characteristic flavor, as well as for its low cholesterol and high omega 3 fatty acid contents. As yet, there has been no comprehensive investigation to estimate genomic selection accuracy for carcass traits in Hanwoo cattle using dense markers. This study aimed at evaluating the accuracy of alternative statistical methods that differed in assumptions about the underlying genetic model for various carcass traits: backfat thickness (BT), carcass weight (CW), eye muscle area (EMA), and marbling score (MS).
  
  
  
  Accuracies of direct genomic breeding values (DGV) for carcass traits were estimated by applying fivefold cross-validation to a dataset including 1183 animals and approximately 34,000 single nucleotide polymorphisms (SNPs).
  
  
  
  Accuracies of BayesC, Bayesian LASSO (BayesL) and genomic best linear unbiased prediction (GBLUP) methods were similar for BT, EMA and MS. However, for CW, DGV accuracy was 7% higher with BayesC than with BayesL and GBLUP. The increased accuracy of BayesC, compared to GBLUP and BayesL, was maintained for CW, regardless of the training sample size, but not for BT, EMA, and MS. Genome-wide association studies detected consistent large effects for SNPs on chromosomes 6 and 14 for CW.
  
  
  
  The predictive performance of the models depended on the trait analyzed. For CW, the results showed a clear superiority of BayesC compared to GBLUP and BayesL. These findings indicate the importance of using a proper variable selection method for genomic selection of traits and also suggest that the genetic architecture that underlies CW differs from that of the other carcass traits analyzed. Thus, our study provides significant new insights into the carcass traits of Hanwoo cattle.
authors.affiliation: Department of Animal Science, Shahrekord University, P.O. Box 115, Shahrekord, 88186-34141, Iran.
authors.forename: Hossein
authors.initials: H
authors.lastname: Mehrban
authors.affiliation: Department of Animal Life and Environment Science, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do, 456-749, Korea. dhlee@hknu.ac.kr.
authors.forename: Deuk Hwan
authors.initials: DH
authors.lastname: Lee
authors.affiliation: Department of Animal Science, Faculty of Agriculture and Natural Resources, Arak University, Arāk, 38156-8-8349, Iran.
authors.forename: Mohammad Hossein
authors.initials: MH
authors.lastname: Moradi
authors.affiliation: Hanwoo Improvement Center, National Agricultural Cooperative Federation, Haeun-ro 691, Unsan-myeon, Seosan-si, Chungnam-do, 356-831, Korea.
authors.forename: Chung
authors.initials: C
authors.lastname: IlCho
authors.affiliation: Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, P.O. Box 4111, Karaj, 31587-11167, Iran.
authors.forename: Masoumeh
authors.initials: M
authors.lastname: Naserkheil
authors.affiliation: The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, UK.
authors.forename: Noelia
authors.initials: N
authors.lastname: Ibáñez-Escriche
mesh_terms: D000465:Algorithms; D000818:Animals; D001947:Breeding; D002417:Cattle; D055106:Genome-Wide Association Study; D023281:Genomics / Q000379:methods; D005838:Genotype; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable; D000069466:Red Meat / Q000592:standards; D015203:Reproducibility of Results; D012641:Selection, Genetic