title: Genomic estimated breeding values using genomic relationship matrices in a cloned population of loblolly pine.
abstract: Replacement of the average numerator relationship matrix derived from the pedigree with the realized genomic relationship matrix based on DNA markers might be an attractive strategy in forest tree breeding for predictions of genetic merit. We used genotypes from 3461 single-nucleotide polymorphism loci to estimate genomic relationships for a population of 165 loblolly pine (Pinus taeda L.) individuals. Phenotypes of the 165 individuals were obtained from clonally replicated field trials and were used to estimate breeding values for growth (stem volume). Two alternative methods, based on allele frequencies or regression, were used to generate the genomic relationship matrices. The accuracies of genomic estimated breeding values based on the genomic relationship matrices and breeding values estimated based on the average numerator relationship matrix were compared. On average, the accuracy of predictions based on genomic relationships ranged between 0.37 and 0.74 depending on the validation method. We did not detect differences in the accuracy of predictions based on genomic relationship matrices estimated by two different methods. Using genomic relationship matrices allowed modeling of Mendelian segregation within full-sib families, an important advantage over a traditional genetic evaluation system based on pedigree. We conclude that estimation of genomic relationships could be a powerful tool in forest tree breeding because it accurately accounts both for genetic relationships among individuals and for nuisance effects such as location and replicate effects, and makes more accurate selection possible within full-sib crosses.
authors.affiliation: Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, North Carolina 27695, USA.
authors.forename: Jaime
authors.initials: J
authors.lastname: Zapata-Valenzuela
authors.forename: Ross W
authors.initials: RW
authors.lastname: Whetten
authors.forename: David
authors.initials: D
authors.lastname: Neale
authors.forename: Steve
authors.initials: S
authors.lastname: McKeand
authors.forename: Fikret
authors.initials: F
authors.lastname: Isik
mesh_terms: D001947:Breeding; D003001:Cloning, Molecular; D005787:Gene Frequency / Q000235:genetics; D005828:Genetics, Population; D018745:Genome, Plant / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D016014:Linear Models; D041603:Pinus taeda / Q000235:genetics*; D012044:Regression Analysis; D015203:Reproducibility of Results; D014197:Trees / Q000235:genetics
keywords: GenPred; Pinus taeda; Shared data resource; best linear unbiased prediction; quantitative genetics