title: Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach.
abstract: Quantitative trait locus (QTL) mapping is often conducted in line-crossing experiments where a sample of individuals is randomly selected from a pool of all potential progeny. QTLs detected from such an experiment are important for us to understand the genetic mechanisms governing a complex trait, but may not be directly relevant to plant breeding if they are not detected from the breeding population where selection is targeting for. QTLs segregating in one population may not necessarily segregate in another population. To facilitate marker-assisted selection, QTLs must be detected from the very population which the selection is targeting. However, selected breeding populations often have depleted genetic variation with small population sizes, resulting in low power in detecting useful QTLs. On the other hand, if selection is effective, loci controlling the selected trait will deviate from the expected Mendelian segregation ratio. In this study, we proposed to detect QTLs in selected breeding populations via the detection of marker segregation distortion in either a single population or multiple populations using the same selection scheme. Simulation studies showed that QTL can be detected in strong selected populations with selected population sizes as small as 25 plants. We applied the new method to detect QTLs in two breeding populations of rice selected for high grain yield. Seven QTLs were identified, four of which have been validated in advanced generations in a follow-up study. Cloned genes in the vicinity of the four QTLs were also reported in the literatures. This mapping-by-selection approach provides a new avenue for breeders to improve breeding progress. The new method can be applied to breeding programs not only in rice but also in other agricultural species including crops, trees and animals.
authors.affiliation: Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.|Department of Botany and Plant Sciences, University of California, Riverside, CA, USA.
authors.forename: Y
authors.initials: Y
authors.lastname: Cui
authors.affiliation: Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.
authors.forename: F
authors.initials: F
authors.lastname: Zhang
authors.affiliation: Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.|Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, China.
authors.forename: J
authors.initials: J
authors.lastname: Xu
authors.affiliation: Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.
authors.forename: Z
authors.initials: Z
authors.lastname: Li
authors.affiliation: Department of Botany and Plant Sciences, University of California, Riverside, CA, USA.
authors.forename: S
authors.initials: S
authors.lastname: Xu
mesh_terms: D002874:Chromosome Mapping; D003198:Computer Simulation; D018744:DNA, Plant / Q000235:genetics; D005828:Genetics, Population; D008957:Models, Genetic; D012275:Oryza / Q000235:genetics*; D000069600:Plant Breeding; D040641:Quantitative Trait Loci; D012641:Selection, Genetic; D000068618:Selective Breeding
chemical_list: D018744:DNA, Plant