Abstract
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).
Highlights
In pig breeding, the search for quantitative trait loci (QTLs) and the underlying causative mutations has been in progress for more than two decades
The first resource population (D1) considered for this study has 1,785 individuals. It was obtained from five purebred Pietrain (P) boars crossed with one Large White (LW) and six crossbred sows Landrace (L) x Large White
While the joint population Genome-wide association studies (GWAS) and the meta-analysis did not identify new associated regions besides the ones identified in the individual populations, both approaches had a positive impact on the mapping resolution which implies that causative mutations can be identified with higher accuracy
Summary
The search for quantitative trait loci (QTLs) and the underlying causative mutations has been in progress for more than two decades. In the beginning of pig QTL experiments, the mapping was carried out using crosses between outbred lines and the statistical test employed was linkage analysis. This approach has proven to be efficient for pinpointing numerous QTLs in pigs [2, 3]. Those studies had reduced mapping resolution and statistical power due to several factors as: the limited number of individuals and genetic markers, and linkage analysis usage which considers only recent recombination events
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