title: Optimal Design for Marker-assisted Gene Pyramiding in Cross Population.
abstract: Marker-assisted gene pyramiding aims to produce individuals with superior economic traits according to the optimal breeding scheme which involves selecting a series of favorite target alleles after cross of base populations and pyramiding them into a single genotype. Inspired by the science of evolutionary computation, we used the metaphor of hill-climbing to model the dynamic behavior of gene pyramiding. In consideration of the traditional cross program of animals along with the features of animal segregating populations, four types of cross programs and two types of selection strategies for gene pyramiding are performed from a practical perspective. Two population cross for pyramiding two genes (denoted II), three population cascading cross for pyramiding three genes(denoted III), four population symmetry (denoted IIII-S) and cascading cross for pyramiding four genes (denoted IIII-C), and various schemes (denoted cross program-A-E) are designed for each cross program given different levels of initial favorite allele frequencies, base population sizes and trait heritabilities. The process of gene pyramiding breeding for various schemes are simulated and compared based on the population hamming distance, average superior genotype frequencies and average phenotypic values. By simulation, the results show that the larger base population size and the higher the initial favorite allele frequency the higher the efficiency of gene pyramiding. Parents cross order is shown to be the most important factor in a cascading cross, but has no significant influence on the symmetric cross. The results also show that genotypic selection strategy is superior to phenotypic selection in accelerating gene pyramiding. Moreover, the method and corresponding software was used to compare different cross schemes and selection strategies.
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China.
authors: L Y
authors: LY
authors: Xu
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China ; Department of Biostatistics and Bioinformatics, Tulane University, New Orleans, Louisiana 70112, USA .
authors: F P
authors: FP
authors: Zhao
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China.
authors: X H
authors: XH
authors: Sheng
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China.
authors: H X
authors: HX
authors: Ren
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China.
authors: L
authors: L
authors: Zhang
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China.
authors: C H
authors: CH
authors: Wei
authors: Institute of Animal Science, Chinese Academy of Agricultural Sciences, National Center for Molecular Genetics and Breeding of Animal, Beijing 100193, China.
authors: L X
authors: LX
authors: Du
keywords: Cross Population; Evolutionary Computation; Gene Pyramiding; Population Hamming Distance