206 Impact of multiple sire mating system on the accuracy of genomic breeding value prediction in a beef cattle population under selection

2017 ◽  
Vol 95 (suppl_4) ◽  
pp. 102-102
Author(s):  
R. L. Tonussi ◽  
R. M. O. Silva ◽  
A. F. B. Magalhães ◽  
E. Peripolli ◽  
B. F. Olivieri ◽  
...  
2012 ◽  
Vol 6 (S2) ◽  
Author(s):  
Jian Zeng ◽  
Marcin Pszczola ◽  
Anna Wolc ◽  
Tomasz Strabel ◽  
Rohan L Fernando ◽  
...  

2020 ◽  
Author(s):  
Iara Del Pilar Solar Diaz ◽  
Gregório Miguel Ferreira de Camargo ◽  
Valdecy Aparecida Rocha da Cruz ◽  
Isis da Costa Hermisdorff ◽  
Caio Victor Damasceno Carvalho ◽  
...  

AbstractThe aim of this study was to evaluate the efficiency of inclusion and the prediction ability of the X chromosome for reproductive (occurrence of early pregnancy – P16 and age at first calving - AFC) and andrological traits (scrotal circumference -SC) in a herd of Nellore beef cattle herd. 3,263 genotypes of females and males were used. Genomic prediction for SC, AFC and P16 was carried out considering two scenarios: 1) only autosomal markers or 2) autosomal + X chromosome markers. To evaluate the effect of inclusion of the X chromosome on selection, the responses to the selection performed were compared including or not the X chromosome in the evaluation of the traits. Higher heritability estimates were obtained for SC (0.40 and 0.31), AFC (0.11 and 0.09) and P16 (0.43 and 0.38) for the analyses including the X chromosome compared to those without. The percent reduction on mean genomic breeding values when selection was based on the results of analysis that did not include the X chromosome to 1, 5 and 10% of the top males, was for SC slightly more than 7% of the mean genomic breeding value of the selected animals. For P16, the loss can reach more than 4%, while this loss does not seem to be as important for AFC. Average predictive correlation of 0.79, 0.98 and 0.84 for SC, AFC and P16 was obtained, respectively. These estimates demonstrate that inclusion of the X chromosome in the analysis can improve the prediction of genomic breeding values, especially for SC.


2011 ◽  
Vol 5 (Suppl 3) ◽  
pp. S13 ◽  
Author(s):  
Xiaochen Sun ◽  
David Habier ◽  
Rohan L Fernando ◽  
Dorian J Garrick ◽  
Jack CM Dekkers

2014 ◽  
Vol 97 (1) ◽  
pp. 537-542 ◽  
Author(s):  
J.E. Pryce ◽  
O. Gonzalez-Recio ◽  
J.B. Thornhill ◽  
L.C. Marett ◽  
W.J. Wales ◽  
...  

2013 ◽  
Vol 55 (1) ◽  
pp. 13-18 ◽  
Author(s):  
Seung Soo Lee ◽  
Seung Hwan Lee ◽  
Tae Jeong Choi ◽  
Yun Ho Choy ◽  
Kwang Hyun Cho ◽  
...  

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