Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular ...Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.展开更多
Recurrent selection is an important breeding method for population improvement and selecting elite inbreds or fixed lines from the improved germplasm.Recently,a computer simulation tool called QuMARS has been develope...Recurrent selection is an important breeding method for population improvement and selecting elite inbreds or fixed lines from the improved germplasm.Recently,a computer simulation tool called QuMARS has been developed,which allows the simulation and optimization of various recurrent selection strategies.Our major objective in this study was to use the QuMARS tool to compare phenotypic recurrent,marker-assisted recurrent,and genomic selections(abbreviated respectively as PS,MARS and GS)for both short-and long-termbreeding procedures.ForMARS,twomarker selection models were considered,i.e.,stepwise(Rstep)and forward regressions(Forward).For GS,three prediction models were considered,i.e.,genomic best linear unbiased predictors(GBLUP),ridge regression(Ridge),and regression by Moore-Penrose general inverse(InverseMP).To generate genotypes and phenotypes for a given individual during simulation,one additive and two epistasis genetic models were considered with three levels of heritability.Results demonstrated that selection responses from GBLUP-based GS and MARS(Forward)were consistently greater than those from PS under the additive model,particularly in early selection cycles.In contrast,selection response from PS was consistently superior over MARS and GS under epistatic models.For the two epistasis models,total genetic variance and the additive variance component were increased in some cases after selection.Through simulation,we concluded that GS and PS were effective recurrent selection methods for improved breeding of targeted traits controlled by additive and epistatic quantitative trait loci(QTL).QuMARS provides an opportunity for breeders to compare,optimize and integrate new technology into their conventional breeding programs.展开更多
文摘Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.
基金This work was financially supported by the National Key Research and Development Program of China(2015BAD02B01-2-2)the HarvestPlus Challenge Program(www.harvestplus.org).
文摘Recurrent selection is an important breeding method for population improvement and selecting elite inbreds or fixed lines from the improved germplasm.Recently,a computer simulation tool called QuMARS has been developed,which allows the simulation and optimization of various recurrent selection strategies.Our major objective in this study was to use the QuMARS tool to compare phenotypic recurrent,marker-assisted recurrent,and genomic selections(abbreviated respectively as PS,MARS and GS)for both short-and long-termbreeding procedures.ForMARS,twomarker selection models were considered,i.e.,stepwise(Rstep)and forward regressions(Forward).For GS,three prediction models were considered,i.e.,genomic best linear unbiased predictors(GBLUP),ridge regression(Ridge),and regression by Moore-Penrose general inverse(InverseMP).To generate genotypes and phenotypes for a given individual during simulation,one additive and two epistasis genetic models were considered with three levels of heritability.Results demonstrated that selection responses from GBLUP-based GS and MARS(Forward)were consistently greater than those from PS under the additive model,particularly in early selection cycles.In contrast,selection response from PS was consistently superior over MARS and GS under epistatic models.For the two epistasis models,total genetic variance and the additive variance component were increased in some cases after selection.Through simulation,we concluded that GS and PS were effective recurrent selection methods for improved breeding of targeted traits controlled by additive and epistatic quantitative trait loci(QTL).QuMARS provides an opportunity for breeders to compare,optimize and integrate new technology into their conventional breeding programs.
