Genomic Prediction Accuracies for Growth and Carcass Traits in a Brangus Heifer Population
Yükleniyor...
Dosyalar
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
MDPI
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution 3.0 United States
Attribution 3.0 United States
Özet
The predictive abilities and accuracies of genomic best linear unbiased prediction (GBLUP) and the Bayesian (BayesA, BayesB, BayesC and Lasso) genomic selection (GS) methods for economically important growth (birth, weaning, and yearling weights) and carcass (depth of rib fat, apercent intramuscular fat and longissimus muscle area) traits were characterized by estimating the linkage disequilibrium (LD) structure in Brangus heifers using single nucleotide polymorphisms (SNP) markers. Sharp declines in LD were observed as distance among SNP markers increased. The application of the GBLUP and the Bayesian methods to obtain the GEBV for growth and carcass traits within k-means and random clusters showed that k-means and random clustering had quite similar heritability estimates, but the Bayesian methods resulted in the lower estimates of heritability between 0.06 and 0.21 for growth and carcass traits compared with those between 0.21 and 0.35 from the GBLUP methodologies. Although the prediction ability of the GBLUP and the Bayesian methods were quite similar for growth and carcass traits, the Bayesian methods overestimated the accuracies of GEBV because of the lower estimates of heritability of growth and carcass traits. However, GBLUP resulted in accuracy of GEBV for growth and carcass traits that parallels previous reports.
Açıklama
Anahtar Kelimeler
Accuracy, Bayesian methods, GBLUP, Genomic prediction, Growth and carcass traits, k-means clustering
Kaynak
Animals
WoS Q Değeri
Q1
Scopus Q Değeri
Cilt
13
Sayı
7
Künye
Peters, S. O., Kızılkaya, K., Sinecen, M., Mestav, B., Thiruvenkadan, A. K., & Thomas, M. G. (2023). Genomic Prediction Accuracies for Growth and Carcass Traits in a Brangus Heifer Population. Animals, 13(7). https://doi.org/10.3390/ani13071272
