title: Effect of population size on the estimation of QTL: a test using resistance to barley stripe rust.
abstract: The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n = 409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods-resampling, selective genotyping, and selective phenotyping-to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping.
authors.affiliation: Department of Crop and Soil Science, Oregon State University, Corvallis, OR 97331-3002, USA. isabel.vales@oregonstate.edu
authors.forename: M I
authors.initials: MI
authors.lastname: Vales
authors.forename: C C
authors.initials: CC
authors.lastname: Schön
authors.forename: F
authors.initials: F
authors.lastname: Capettini
authors.forename: X M
authors.initials: XM
authors.lastname: Chen
authors.forename: A E
authors.initials: AE
authors.lastname: Corey
authors.forename: D E
authors.initials: DE
authors.lastname: Mather
authors.forename: C C
authors.initials: CC
authors.lastname: Mundt
authors.forename: K L
authors.initials: KL
authors.lastname: Richardson
authors.forename: J S
authors.initials: JS
authors.lastname: Sandoval-Islas
authors.forename: H F
authors.initials: HF
authors.lastname: Utz
authors.forename: P M
authors.initials: PM
authors.lastname: Hayes
mesh_terms: D000704:Analysis of Variance; D001487:Basidiomycota; D001947:Breeding / Q000379:methods; D002874:Chromosome Mapping / Q000379:methods*; D003433:Crosses, Genetic; D001467:Hordeum / Q000235:genetics*; D007113:Immunity, Innate / Q000235:genetics*; D008800:Mexico; D010935:Plant Diseases / Q000235:genetics / Q000382:microbiology*; D011156:Population Density; D040641:Quantitative Trait Loci; D014861:Washington