Premium
Accuracy of predicting genomic breeding values for carcass merit traits in A ngus and C harolais beef cattle
Author(s) -
Chen L.,
Vinsky M.,
Li C.
Publication year - 2015
Publication title -
animal genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.756
H-Index - 81
eISSN - 1365-2052
pISSN - 0268-9146
DOI - 10.1111/age.12238
Subject(s) - biology , beef cattle , genomic selection , microbiology and biotechnology , genetics , quantitative trait locus , zoology , computational biology , gene , genotype , single nucleotide polymorphism
Summary Accuracy of predicting genomic breeding values for carcass merit traits including hot carcass weight, longissimus muscle area ( REA ), carcass average backfat thickness ( AFAT ), lean meat yield ( LMY ) and carcass marbling score ( CMAR ) was evaluated based on 543 Angus and 400 Charolais steers genotyped on the Illumina Bovine SNP 50 Beadchip. For the genomic prediction within Angus, the average accuracy was 0.35 with a range from 0.32 ( LMY ) to 0.37 ( CMAR ) across different training/validation data‐splitting strategies and statistical methods. The within‐breed genomic prediction for Charolais yielded an average accuracy of 0.36 with a range from 0.24 ( REA ) to 0.46 ( AFAT ). The across‐breed prediction had the lowest accuracy, which was on average near zero. When the data from the two breeds were combined to predict the breeding values of either breed, the prediction accuracy averaged 0.35 for Angus with a range from 0.33 ( REA ) to 0.39 ( CMAR ) and averaged 0.33 for Charolais with a range from 0.18 ( REA ) to 0.46 ( AFAT ). The prediction accuracy was slightly higher on average when the data were split by animal's birth year than when the data were split by sire family. These results demonstrate that the genetic relationship or relatedness of selection candidates with the training population has a great impact on the accuracy of predicting genomic breeding values under the density of the marker panel used in this study.