This study aimed to investigate interpopulation variation due to sex, breed and age, and the intrapopulation variation in the form of genetic variance for recombination in swine. Genome‐wide recombination rate and recombination occurrences (RO) were traits studied in Landrace (LR) and Large White (LW) male and female populations. Differences were found for sex, breed, sex‐breed interaction, and age effects for genome‐wide recombination rate and RO at one or more chromosomes. Dams were found to have a higher genome‐wide recombination rate and RO at all chromosomes than sires. LW animals had higher genome‐wide recombination rate and RO at seven chromosomes but lower at two chromosomes than LR individuals. The sex‐breed interaction effect did not show any pattern not already observable by sex. Recombination increased with increasing parity in females, while in males no effect of age was observed. We estimated heritabilities and repeatabilities for both investigated traits and obtained the genetic correlation between male and female genome‐wide recombination rate within each of the two breeds studied. Estimates of heritability and repeatability were low (h2 = 0.01–0.26; r = 0.18–0.42) for both traits in all populations. Genetic correlations were high and positive, with estimates of 0.98 and 0.94 for the LR and LW breeds, respectively. We performed a GWAS for genome‐wide recombination rate independently in the four sex/breed populations. The results of the GWAS were inconsistent across the four populations with different significant genomic regions identified. The results of this study provide evidence of variability for recombination in purebred swine populations.

Simple SummaryCommercial genotyping has become accessible at a relatively low cost and nowadays it is widely used by breeders to predict production and economic traits. Many studies explored the benefits of using DNA information in breeding programs, and many methods have been established to optimize the use of such information. To date, however, very few studies have explored how prediction accuracies change across generations. Here we present a short evaluation across five generations in two pig breeds and evaluate the accuracy of the prediction of relevant production traits using different generational groups.AbstractGenomic models that incorporate dense marker information have been widely used for predicting genomic breeding values since they were first introduced, and it is known that the relationship between individuals in the reference population and selection candidates affects the prediction accuracy. When genomic evaluation is performed over generations of the same population, prediction accuracy is expected to decay if the reference population is not updated. Therefore, the reference population must be updated in each generation, but little is known about the optimal way to do it. This study presents an empirical assessment of the prediction accuracy of genomic breeding values of production traits, across five generations in two Korean pig breeds. We verified the decay in prediction accuracy over time when the reference population was not updated. Additionally we compared the prediction accuracy using only the previous generation as the reference population, as opposed to using all previous generations as the reference population. Overall, the results suggested that, although there is a clear need to continuously update the reference population, it may not be necessary to keep all ancestral genotypes. Finally, comprehending how the accuracy of genomic prediction evolves over generations within a population adds relevant information to improve the performance of genomic selection.

The identification of quantitative trait loci (QTL) within different breeds of a species is important for polygenic traits such as meat quality and reproductive traits. If different breeds are selected for the same phenotype, the genetic regions that ultimately undergo positive selection will not necessarily be the same. One of the most common ways to identify these QTL is through genome wide association studies (GWAS). Outlining differences in significant QTL of complex traits can give insights into selection in one breed by using information from another. The objective of this study was to estimate heritabilities, identify QTL within purebred Yorkshire (YK) and Landrace (LR) populations by use of GWAS and to compare significant SNP between the breeds. 8,202 animals in total (5,053 Yorkshire and 3,149 Landrace) were genotyped with a 50k Illumina SNP chip, then phased and imputed to correct for any missing SNP calls using EAGLE and MINIMAC. The R package gwaR was used to estimate variance components by using a GBLUP model with fixed effects of parity, a contemporary group and sex. The response variables considered were carcass traits, specifically, meat percent (MP), backfat average (BFA), backfat depth (BFD), daily weight (DW) and day-90 weight (DW90) and were assessed per breed. Heritability estimates of each trait can be found in Table 1 and were in-line with previous studies. Significant SNP of each trait were compared between the two breeds by estimating the p-value of each SNP using gwaR. The breeds showed similar significant signals, but differences arose within BFD with additional significant peaks in LR. This could be due to real genotypic differences or could be an effect of the difference in sample size. The comparison between these two breeds can lead to insights in other pig breeds as well guide more informed selection decisions in the future.

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