Efficiency of genomic prediction for boar taint reduction in Danish Landrace pigs

Abstract

SummaryGenetic selection against boar taint, which is caused by high skatole and androstenone concentrations in fat, is a more acceptable alternative than is the current practice of castration. Genomic predictors offer an opportunity to overcome the limitations of such selection caused by the phenotype being expressed only in males at slaughter, and this study evaluated different approaches to obtain such predictors. Samples from 1000 pigs were included in a design which was dominated by 421 sib pairs, each pair having one animal with high and one with low skatole concentration (≥0.3 μg/g). All samples were measured for both skatole and androstenone and genotyped using the Illumina SNP60 porcine BeadChip for 62 153 single nucleotide polymorphisms. The accuracy of predicting phenotypes was assessed by cross‐validation using six different genomic evaluation methods: genomic best linear unbiased prediction (GBLUP) and five Bayesian regression methods. In addition, this was compared to the accuracy of predictions using only QTL that showed genome‐wide significance. The range of accuracies obtained by different prediction methods was narrow for androstenone, between 0.29 (Bayes Lasso) and 0.31 (Bayes B), and wider for skatole, between 0.21 (GBLUP) and 0.26 (Bayes SSVS). Relative accuracies, corrected for h 2, were 0.54–0.56 and 0.75–0.94 for androstenone and skatole respectively. The whole‐genome evaluation methods gave greater accuracy than using only the QTL detected in the data. The results demonstrate that GBLUP for androstenone is the simplest genomic technology to implement and was also close to the most accurate method. More specialised models may be preferable for skatole.

Multi-trait single-step genomic prediction accounting for heterogeneous (co)variances over the genome

“…Moreover, it also allows all extensions of BLUP methodology, such as multiple-trait, random regression, or repeated measures to be easily implemented in genomic evaluations (Tiezzi and Maltecca 2015). The GBLUP model has been widely used to predict breeding values in animal species, such as cattle (Luan et al 2009;Su et al 2012b), pig (Lukić et al 2015), sheep (Daetwyler et al 2010a) and fish (Ødegård et al 2014;Tsai et al 2016), and accuracies from GBLUP were reported to be higher than those from traditional pedigreebased BLUP.…”

Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits

“…One pair of full sibs may share more common markers than another pair of full sibs due to multiple reasons, for example, Mendelian sampling. Studies have shown substantial variations in kinship among full sibs (Lukić et al 2015 ; Vela-Avitúa et al 2015 ). Taking a bi-parental population as an example, the proportion of alleles from a specific parent can range from 20 to 80% among full sibs.…”

Odeurs indésirables de la viande de porcs mâles non castrés : problèmes et solutions potentielles

“…Cependant, l'alternative mise en oeuvre actuellement est d'évaluer le risque à l'abattoir chez les collatéraux par le nez humain (Mathur et al, 2013) car cela permet de travailler sur de grands effectifs. Par ailleurs, il est possible d'utiliser l'information génomique pour prédire les teneurs en composés odorants dans le tissu gras (Haberland et al, 2014 ;de Campos et al, 2015 ;Lukić et al, 2015).…”