title: Comparison of biometrical approaches for QTL detection in multiple segregating families.
abstract: Detection of QTL in multiple segregating families possesses many advantages over the classical QTL mapping in biparental populations. It has thus become increasingly popular, and different biometrical approaches are available to analyze such data sets. We empirically compared an approach based on linkage mapping methodology with an association mapping approach. To this end, we used a large population of 788 elite maize lines derived from six biparental families genotyped with 857 SNP markers. In addition, we constructed genetic maps with reduced marker densities to assess the dependency of the performance of both mapping approaches on the marker density. We used cross-validation and resample model averaging and found that while association mapping performed better under high marker densities, this was reversed under low marker densities. In addition to main effect QTL, we also detected epistatic interactions. Our results suggest that both approaches will profit from a further increase in marker density and that a cross-validation should be applied irrespective of the biometrical approach.
authors.affiliation: Crop Genetics and Breeding Department, China Agricultural University, Beijing 100193, China.
authors.forename: Wenxin
authors.initials: W
authors.lastname: Liu
authors.forename: Jochen C
authors.initials: JC
authors.lastname: Reif
authors.forename: Nicolas
authors.initials: N
authors.lastname: Ranc
authors.forename: Giovanni Della
authors.initials: GD
authors.lastname: Porta
authors.forename: Tobias
authors.initials: T
authors.lastname: Würschum
mesh_terms: D002874:Chromosome Mapping; D032461:Chromosomes, Plant / Q000235:genetics; D018744:DNA, Plant / Q000235:genetics; D017343:Genes, Plant / Q000235:genetics*; D008040:Genetic Linkage; D005819:Genetic Markers; D010641:Phenotype; D016133:Polymerase Chain Reaction; D040641:Quantitative Trait Loci / Q000235:genetics*; D003313:Zea mays / Q000235:genetics* / Q000254:growth & development
chemical_list: D018744:DNA, Plant; D005819:Genetic Markers