Nurse capacity, fertility, and litter size in crossbred sows and genetic correlation to purebred sow information

In pigs litter size has increased during the last decades and number of weaned piglets is an important issue. The aim of this study was to develop a new trait of nurse capacity (NC) of crossbred sows viewed as crossbred performances in the two purebred parent lines, and estimate the genetic correlation to fertility and litter size five days after birth. An experiment recording phenotypes of crossbred sows was conducted in three large production herds with 11,247 first litter Danish Landrace x Yorkshire sows. All terminal sires used were Duroc AI boars. The experiment was running from 2010 to 2013. At farrowing, the total number born (TNB) was recorded. Five days after farrowing the litter size of the biological mother (LS5) was recorded. During the first three days after farrowing the number of piglets at each nurse sow was equalized to 14 piglets and after three weeks the NC was recorded and defined as the number of piglets nursed. Additional records on TNB and LS5 from related sows in nucleus and multiplier herds were added to obtain a data set with both purebred and crossbred information. A reduced animal model including both purebred and crossbred records was used and parameters were estimated. The results show that NC recorded on crossbred first litter sows had heritabilities of 0.05 and 0.07 for crossbred performance in the purebred populations of Landrace and Yorkshire, respectively. Estimated genetic correlations between TNB in purebreds and crossbreds show that nearly 50% of genetic gain in the purebred populations was transferred to crossbreds. Unfavorable genetic correlations between TNB in purebreds and NC in crossbreds were observed. For LS5 the genetic (co)variances show that 61% of the genetic gain in the two purebred lines was transferred to the commercial pig production of crossbred first litter sows, but no statistically significant genetic correlation to NC was obtained.

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

Genetic 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 h², 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.

Identification of quantitative trait loci for production traits in commercial pig populations

The aim of this study was to investigate methods for detecting QTL in outbred commercial pig populations. Several QTL for back fat and growth rate, previously detected in experimental resource populations, were examined for segregation in 10 different populations. Two hundred trait-by-population-by-chromosome tests were performed, resulting in 20 tests being significant at the 5% level. In addition, 53 QTL tests for 11 meat quality traits were declared significant, using a subset of the populations. These results show that a considerable amount of phenotypic variance observed in these populations can be explained by major alleles segregating at several of the loci described. Thus, despite a relatively strong selection pressure for growth and back fat traits in these populations, these alleles have not yet reached fixation. The approaches used here demonstrate that it is possible to verify segregation of QTL in commercial populations by limited genotyping of a selection of informative animals. Such verified QTL may be directly exploited in marker-assisted selection (MAS) programs in commercial populations and their molecular basis may be revealed by positional candidate cloning.