期刊论文详细信息
Genetics Selection Evolution
Pedigree and genomic evaluation of pigs using a terminal-cross model
Research Article
Juliette Riquet1  Hélène Gilbert1  Andres Legarra1  Catherine Larzul1  Llibertat Tusell1  Marie-José Mercat2 
[1] GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet Tolosan, France;IFIP – Institut du porc, BP 35104, La Motte au Vicomte, 35651, Le Rheu Cedex, France;
关键词: Genetic Correlation;    Feed Conversion Ratio;    Additive Genetic Variance;    Additive Genetic Effect;    Best Linear Unbiased Prediction;   
DOI  :  10.1186/s12711-016-0211-3
 received in 2015-07-03, accepted in 2016-03-31,  发布年份 2016
来源: Springer
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【 摘 要 】

BackgroundIn crossbreeding schemes, within-line selection of purebreds is performed mainly to improve the performance of crossbred descendants under field conditions. The genetic correlation between purebred and crossbred performance is an important parameter to be assessed because purebred performance can be a poor predictor of the performance of crossbred offspring. With the availability of high-density markers, the feasibility of using crossbred information to evaluate purebred candidates can be reassessed. This study implements and applies a single-step terminal-cross model (GEN) to real data to estimate the genetic parameters of several production and quality traits in pigs.MethodsPiétrain sires were mated with Piétrain and Large White dams to produce purebred and crossbred male half-sib piglets; growth rate, feed conversion ratio, lean meat, pH of longissimus dorsi muscle, drip loss and intramuscular fat content were recorded on all half-sibs. Animals were genotyped using the Illumina Porcine SNP60 BeadChip. The genetic correlation between purebred and crossbred performance was estimated separately for each trait. Purebred animals were evaluated using an animal model, whereas the additive genetic effect of a crossbred individual was decomposed into the additive effects of the sire and dam and a Mendelian sampling effect that was confounded with the residual effect. Genotypes of the Piétrain animals were integrated in the genetic evaluation by using a single-step procedure. As benchmarks, we used a model that was identical to GEN but only accounted for pedigree information (PED) and also two univariate single-step models (GEN_UNI) that took either purebred or crossbred performance into account.ResultsGenetic correlations between purebred and crossbred performance were high and positive for all traits (>0.69). Accuracies of estimated breeding values of genotyped sires and purebred offspring that were obtained with the GEN model outperformed both those obtained with the PED and the GEN_UNI models. The use of genomic information increased the predictive ability of the GEN model, but it did not substantially outperform the GEN_UNI models.ConclusionsWe present a single-step terminal-cross model that integrates genomic information of purebred and crossbred performance by using available software. It improves the theoretical accuracy of genetic evaluations in breeding programs that are based on crossbreeding.

【 授权许可】

CC BY   
© Tusell et al. 2016

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【 参考文献 】
  • [1]
  • [2]
  • [3]
  • [4]
  • [5]
  • [6]
  • [7]
  • [8]
  • [9]
  • [10]
  • [11]
  • [12]
  • [13]
  • [14]
  • [15]
  • [16]
  • [17]
  • [18]
  • [19]
  • [20]
  • [21]
  • [22]
  • [23]
  • [24]
  • [25]
  • [26]
  • [27]
  • [28]
  • [29]
  • [30]
  • [31]
  • [32]
  • [33]
  • [34]
  • [35]
  • [36]
  • [37]
  • [38]
  • [39]
  • [40]
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