Siegfried Preuß

Genomic selection using low density marker panels with application to a sire line in pigs

BackgroundGenomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip.ResultsGenotype imputation error rates were 0.133 for a 384 marker panel, 0.079 for a 768 marker panel, and 0.022 for a 3000 marker panel. Error rates for markers with approximated positions were slightly larger. Availability of high-density genotypes for close relatives of the selection candidates reduced the imputation error rate. The estimated decrease in the accuracy of genomic breeding values due to imputation errors was 3% for the 384 marker panel and negligible for larger panels, provided that at least one parent of the selection candidates was genotyped at high-density.Genomic breeding values predicted from deregressed breeding values with low reliabilities were more strongly correlated with the estimated BLUP breeding values than with the true breeding values. This was not the case when a shortened pedigree was used to predict BLUP breeding values, in which the parents of the individuals genotyped at high-density were considered unknown.ConclusionsGenomic selection with imputation from very low- to high-density marker panels is a promising strategy for the implementation of genomic selection at acceptable costs. A panel size of 384 markers can be recommended for selection candidates of a pig breeding program if at least one parent is genotyped at high-density, but this appears to be the lower bound.

Direct determination of flavor relevant and further branched-chain fatty acids from sheep subcutaneous adipose tissue by gas chromatography with mass spectrometry

4-Methyloctanoic acid, 4-ethyloctanoic acid and 4-methylnonanoic acid are key-flavor compounds of sheep and goat. Yet, the low amounts of these volatile branched-chain fatty acids (vBCFAs) in the fat of the ruminants hampered their determination on a routine basis. In this work we developed a gas chromatography/mass spectrometry selected ion monitoring (GC/MS-SIM) method for the direct determination of the vBCFAs as methyl esters, which were obtained after transesterification of subcutaneous adipose tissue of sheep. The excellent sensitivity of the GC/MS-SIM method (limit of quantification, LOQ, 3.6-4.8μg/g; limit of detection, LOD, 1.1-1.4μg/g for 4-Me-8:0, 4-Et-8:0 and 4-Me-9:0) enabled us to determine the three vBCFAs without an enrichment step. Subcutaneous adipose sheep tissue of three different breeds contained 23-88μg/g 4-methyloctanoic acid, 13-26μg/g 4-ethyloctanoic acid and ∼2.9-18μg/g 4-methylnonanoic acid. Since all fatty acids were present in the FAME fraction, the samples could be screened for further branched-chain FAMEs. After elimination of unsaturated fatty acids by hydrogenation (the presence of some unsaturated fatty acids could be verified by this measure), additional measurements in SIM and full scan modes of methyl esters and picolinyl esters enabled the determination of further 97 saturated fatty acids in the samples with eight to 20 carbons. The method is suited for routine analysis and may be useful to investigate the reasons for the abundance/absence of 4-methyloctanoic acid, 4-ethyloctanoic acid and 4-methylnonanoic acid and further branched-chain fatty acids in sheep and goat.

Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. As more genomic data is being generated within different commercial or resource pig populations, the challenge which arises is how to collectively investigate the data with the purpose to increase sample size and implicitly the statistical power. This study performs an individual population GWAS, a joint population GWAS and a meta-analysis in three pig F2 populations. D1 is derived from European type breeds (Piétrain, Large White and Landrace), D2 is obtained from an Asian breed (Meishan) and Piétrain, and D3 stems from a European Wild Boar and Piétrain, which is the common founder breed. The traits investigated are average daily gain, backfat thickness, meat to fat ratio and carcass length. The joint and the meta-analysis did not identify additional genomic clusters besides the ones discovered via the individual population GWAS. However, the benefit was an increased mapping resolution which pinpointed to narrower clusters harboring causative variants. The joint analysis identified a higher number of clusters as compared to the meta-analysis; nevertheless, the significance levels and the number of significant variants in the meta-analysis were generally higher. Both types of analysis had similar outputs suggesting that the two strategies can complement each other and that the meta-analysis approach can be a valuable tool whenever access to raw datasets is limited. Overall, a total of 20 genomic clusters that predominantly overlapped at various extents, were identified on chromosomes 2, 7 and 17, many confirming previously identified quantitative trait loci. Several new candidate genes are being proposed and, among them, a strong candidate gene to be taken into account for subsequent analysis is BMP2 (bone morphogenetic protein 2).