title: Estimating the genetic architecture of quantitative traits.
abstract: Understanding and estimating the structure and parameters associated with the genetic architecture of quantitative traits is a major research focus in quantitative genetics. With the availability of a well-saturated genetic map of molecular markers, it is possible to identify a major part of the structure of the genetic architecture of quantitative traits and to estimate the associated parameters. Multiple interval mapping, which was recently proposed for simultaneously mapping multiple quantitative trait loci (QTL), is well suited to the identification and estimation of the genetic architecture parameters, including the number, genomic positions, effects and interactions of significant QTL and their contribution to the genetic variance. With multiple traits and multiple environments involved in a QTL mapping experiment, pleiotropic effects and QTL by environment interactions can also be estimated. We review the method and discuss issues associated with multiple interval mapping, such as likelihood analysis, model selection, stopping rules and parameter estimation. The potential power and advantages of the method for mapping multiple QTL and estimating the genetic architecture are discussed. We also point out potential problems and difficulties in resolving the details of the genetic architecture as well as other areas that require further investigation. One application of the analysis is to improve genome-wide marker-assisted selection, particularly when the information about epistasis is used for selection with mating.
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh 27695, USA.
authors.forename: Z B
authors.initials: ZB
authors.lastname: Zeng
authors.forename: C H
authors.initials: CH
authors.lastname: Kao
authors.forename: C J
authors.initials: CJ
authors.lastname: Basten
mesh_terms: D000465:Algorithms; D000818:Animals; D002874:Chromosome Mapping; D005819:Genetic Markers; D005838:Genotype; D008957:Models, Genetic; D009154:Mutation; D019655:Quantitative Trait, Heritable; D012641:Selection, Genetic
chemical_list: D005819:Genetic Markers