title: Interacted QTL mapping in partial NCII design provides evidences for breeding by design.
abstract: The utilization of heterosis in rice, maize and rapeseed has revolutionized crop production. Although elite hybrid cultivars are mainly derived from the F1 crosses between two groups of parents, named NCII mating design, little has been known about the methodology of how interacted effects influence quantitative trait performance in the population. To bridge genetic analysis with hybrid breeding, here we integrated an interacted QTL mapping approach with breeding by design in partial NCII mating design. All the potential main and interacted effects were included in one full model. If the number of the effects is huge, bulked segregant analysis were used to test which effects were associated with the trait. All the selected effects were further shrunk by empirical Bayesian, so significant effects could be identified. A series of Monte Carlo simulations was performed to validate the new method. Furthermore, all the significant effects were used to calculate genotypic values of all the missing F1 hybrids, and all these F1 phenotypic or genotypic values were used to predict elite parents and parental combinations. Finally, the new method was adopted to dissect the genetic foundation of oil content in 441 rapeseed parents and 284 F1 hybrids. As a result, 8 main-effect QTL and 37 interacted QTL were found and used to predict 10 elite restorer lines, 10 elite sterile lines and 10 elite parental crosses. Similar results across various methods and in previous studies and a high correlation coefficient (0.76) between the predicted and observed phenotypes validated the proposed method in this study.
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement / Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, Jiangsu, China.
authors.forename: Su Hong
authors.initials: SH
authors.lastname: Bu
authors.forename: Xinwang
authors.initials: X
authors.lastname: Zhao
authors.affiliation: Statistical Genomics Lab, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
authors.forename: Zhao
authors.initials: Z
authors.lastname: Xinwang
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement / Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, Jiangsu, China.
authors.forename: Can
authors.initials: C
authors.lastname: Yi
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement / Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, Jiangsu, China.
authors.forename: Jia
authors.initials: J
authors.lastname: Wen
authors.forename: Jinxing
authors.initials: J
authors.lastname: Tu
authors.affiliation: Statistical Genomics Lab, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
authors.forename: Tu
authors.initials: T
authors.lastname: Jinxing
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement / Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, Jiangsu, China; Statistical Genomics Lab, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
authors.forename: Yuan Ming
authors.initials: YM
authors.lastname: Zhang
mesh_terms: D001499:Bayes Theorem; D029741:Brassica rapa / Q000737:chemistry / Q000235:genetics; D002874:Chromosome Mapping; D003198:Computer Simulation; D018556:Crops, Agricultural / Q000235:genetics*; D003433:Crosses, Genetic; D005828:Genetics, Population; D006823:Hybrid Vigor / Q000235:genetics*; D008957:Models, Genetic; D009010:Monte Carlo Method; D000069600:Plant Breeding / Q000379:methods*; D040641:Quantitative Trait Loci / Q000235:genetics*
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