Multiple trait genetic evaluation of ewe traits in Icelandic sheep

2008 ◽  
Vol 125 (6) ◽  
pp. 390-396 ◽  
Author(s):  
T. Árnason ◽  
J.V. Jónmundsson
2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 248-248
Author(s):  
Napoleon Vargas Jurado ◽  
Bret Taylor ◽  
David R Notter ◽  
Daniel Brown ◽  
Ronald M Lewis

Abstract Given its benefits on animal performance, crossbreeding is common commercially. Genetic evaluation of sheep in the U.S. is performed within breed type (terminal, maternal wool, range, hair). While incorporating crossbred records may improve assessment of purebreds, it requires accounting for heterotic and breed effects in the evaluation. The objectives were to i) determine the generalized effects of direct and maternal heterosis on growth traits of crossbred lambs, and ii) estimate covariance components for direct and maternal additive, and uncorrelated maternal environmental, effects among those traits. Data included body weights (BW) at birth (BN; n = 14395), pre-weaning (WN; n = 9298), weaning (WW; n = 9230), and post-weaning (PW; n = 1593). Mean (SD) BW were 5.3 (1.1), 22.2 (8.7), 39.1 (7.2), and 54.2 (8.7) kg for BN, WN, WW, and PW, respectively. Estimates of heterotic effects and covariance components were obtained using a multiple trait animal model. Genetic effects based on founders’ breeds were included, being significant. Estimates of direct heterosis were 3.04 ± 0.61, 2.62 ± 0.64, 3.99 ± 0.54, and 5.97 ± 0.86%, and estimates of maternal heterosis were 1.86 ± 0.87, 4.42 ± 0.79, 3.69 ± 0.66, and 3.77 ± 0.90%, for BN, WN, WW, and PW, respectively. Direct heritability estimates were 0.17 ± 0.02, 0.13 ± 0.02, 0.18 ± 0.02, and 0.47 ± 0.04 for BN, WN, WW, and PW, respectively. Additive maternal effects defined trivial variation in PW. For BN, WN, and WW, respectively, maternal heritability estimates were 0.17 ± 0.02, 0.10 ± 0.02, and 0.07 ± 0.02. Uncorrelated maternal effects defined little variation in any trait. Direct and maternal heterosis had considerable impact on growth traits, emphasizing the value of crossbreeding and the need to account for heterosis, in addition to breed effects, if crossbred lamb information is included in genetic evaluation.


2003 ◽  
Vol 81 (4) ◽  
pp. 927-932 ◽  
Author(s):  
P. R. C. Nobre ◽  
I. Misztal ◽  
S. Tsuruta ◽  
J. K. Bertrand ◽  
L. O. C. Silva ◽  
...  

2010 ◽  
Vol 88 (3) ◽  
pp. 871-878 ◽  
Author(s):  
C. Sun ◽  
P. Madsen ◽  
M. S. Lund ◽  
Y. Zhang ◽  
U. S. Nielsen ◽  
...  

2009 ◽  
Vol 61 (4) ◽  
pp. 959-967
Author(s):  
P.R.C. Nobre ◽  
A.N. Rosa ◽  
L.O.C. Silva

Expected progeny differences (EPD) of Nellore cattle estimated by random regression model (RRM) and multiple trait model (MTM) were compared. Genetic evaluation data included 3,819,895 records of up nine sequential weights of 963,227 animals measured at ages ranging from one day (birth weight) to 733 days. Traits considered were weights at birth, ten to 110-day old, 102 to 202-day old, 193 to 293-day old, 283 to 383-day old, 376 to 476-day old, 551 to 651-day old, and 633 to 733-day old. Seven data samples were created. Because the parameters estimates biologically were better, two of them were chosen: one with 84,426 records and another with 72,040. Records preadjusted to a fixed age were analyzed by a MTM, which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were carried out by REML, with five traits at a time. The RRM included the effects of age of animal, contemporary group, age of dam class, additive direct, permanent environment, additive maternal, and maternal permanent environment. Different degree of Legendre polynomials were used to describe random effects. MTM estimated covariance components and genetic parameters for weight at birth and sequential weights and RRM for all ages. Due to the fact that correlation among the estimates EPD from MTM and all the tested RM were not equal to 1.0, it is not possible to recommend RRM to genetic evaluation to large data sets.


2008 ◽  
Vol 91 (11) ◽  
pp. 4333-4343 ◽  
Author(s):  
Z. Liu ◽  
J. Jaitner ◽  
F. Reinhardt ◽  
E. Pasman ◽  
S. Rensing ◽  
...  

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