title: Genome-wide association mapping of agronomic traits in sugar beet.
abstract: Recent results indicate that association mapping in populations from applied plant breeding is a powerful tool to detect QTL which are of direct relevance for breeding. The focus of this study was to unravel the genetic architecture of six agronomic traits in sugar beet. To this end, we employed an association mapping approach, based on a very large population of 924 elite sugar beet lines from applied plant breeding, fingerprinted with 677 single nucleotide polymorphism (SNP) markers covering the entire genome. We show that in this population linkage disequilibrium decays within a short genetic distance and is sufficient for the detection of QTL with a large effect size. To increase the QTL detection power and the mapping resolution a much higher number of SNPs is required. We found that for QTL detection, the mixed model including only the kinship matrix performed best, even in the presence of a considerable population structure. In genome-wide scans, main effect QTL and epistatic QTL were detected for all six traits. Our full two-dimensional epistasis scan revealed that for complex traits there appear to be epistatic master regulators, loci which are involved in a large number of epistatic interactions throughout the genome.
authors.affiliation: State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany. tobias.wuerschum@uni-hohenheim.de
authors.forename: Tobias
authors.initials: T
authors.lastname: Würschum
authors.forename: Hans Peter
authors.initials: HP
authors.lastname: Maurer
authors.forename: Thomas
authors.initials: T
authors.lastname: Kraft
authors.forename: Geert
authors.initials: G
authors.lastname: Janssen
authors.forename: Carolina
authors.initials: C
authors.lastname: Nilsson
authors.forename: Jochen Christoph
authors.initials: JC
authors.lastname: Reif
mesh_terms: D027461:Beta vulgaris / Q000235:genetics*; D002874:Chromosome Mapping / Q000379:methods; D003433:Crosses, Genetic; D005819:Genetic Markers; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D025341:Principal Component Analysis; D040641:Quantitative Trait Loci; D012044:Regression Analysis
chemical_list: D005819:Genetic Markers