title: Genomic selection in sugar beet breeding populations.
abstract: BACKGROUND
  Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers.
  
  
  RESULTS
  We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families.
  
  
  CONCLUSIONS
  The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.
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: Jochen C
authors.initials: JC
authors.lastname: Reif
authors.forename: Thomas
authors.initials: T
authors.lastname: Kraft
authors.forename: Geert
authors.initials: G
authors.lastname: Janssen
authors.forename: Yusheng
authors.initials: Y
authors.lastname: Zhao
mesh_terms: D027461:Beta vulgaris / Q000235:genetics*; D001947:Breeding; D002241:Carbohydrates / Q000737:chemistry / Q000235:genetics; D018745:Genome, Plant; D005838:Genotype; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D011188:Potassium / Q000378:metabolism; D040641:Quantitative Trait Loci; D019655:Quantitative Trait, Heritable; D012641:Selection, Genetic / Q000235:genetics*; D012964:Sodium / Q000378:metabolism
chemical_list: D002241:Carbohydrates; D012964:Sodium; D011188:Potassium
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