XV QTLMAS: simulated dataset

Background: Our aim was to simulate the data for the QTLMAS2011 workshop following a pig-type family structure under an oligogenic model, each QTL being specific. Results: The population comprised 3000 individuals issued from 20 sires and 200 dams. Within each family, 10 progenies belonged to the experimental population and were assigned phenotypes and marker genotypes and 5 belonged to the selection population, only known on their marker genotypes. A total of 10,000 SNPs carried by 5 chromosomes of 1 Morgan each were simulated. Eight QTL were created (1 quadri-allelic, 2 linked in phase, 2 linked in repulsion, 1 imprinted and 2 epistatic). Random noise was added giving an heritability of 0.30. The marker density, LD and MAF were similar to real life parameters. Background Statistical methods, and softwares, for the markerassisted genetic analysis of quantitative traits and for the Genomic Evaluation of Breeding Values are partly converging in the new context of high density SNP chip technology. Genome Wide Association Studies based on independent individuals are used on a very large scale in human genetics, whereas GEBV techniques have mostly been developed for ruminant species, in particular dairy cattle where sires have very large numbers of offspring but dams only one progeny per mating. However, both GWAS and GEBV are universal approaches which should be adapted to any family structure, for instance the medium-sized full sib families found in pigs. Similarly to the 2009 and 2008 workshops [1,2], the data sets offered to exploration during the QTLMAS 2011 workshop were organized following this pig-type structure. The architecture of analyzed traits can be highly variable. The number of QTL varies from one in the monogenic inheritance found for some disease resistances to a huge number of tiny QTLs in other cases. Moreover, the QTL may be subject to various effects including dominance, epistasis or imprinting. To appreciate the ability of methods to deal with these situations, the choice was made in our simulation to avoid polygenic noise and limit the heredity to 8 segregating QTLs, each displaying its own features.