GOVS genome optimization design model accelerates maize hybrid breeding

Recently, Professor Wang Xiangfeng from the College of Agriculture of China Agricultural University, National Corn Improvement Center and Professor Ma Chuang from Northwest A&F University published a methodology research paper in the international academic journal Briefings in Bioinformatics
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Traditional breeding simulation software mainly uses the pedigree relationship and phenotypic data of genetic materials to simulate the breeding process, and at the same time guide the selection and assembly of the future breeding process
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Because of the genetic burden effect, this virtual optimal genome is impossible to achieve in reality, but this virtual optimal genome can assist breeders to make breeding decisions in two stages of the breeding process: First, the breeders follow The inbred line selects the number of high-quality genome fragments contributed by the virtual genome, that is, the more high-quality inbred lines provided, the more inbred lines that contribute more to the target traits; second, due to different good self The crossed lines are complementary to the high-quality fragments provided by the virtual genome, which can then assist breeders to select inbred lines with complementary dominant alleles, and combine the double haploid induction technology to further aggregate the dominant alleles
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Based on the above two characteristics, the genome optimization design model can be considered as a supplement to the whole genome selection model, and it can be combined with haploid induction technology to accelerate the speed of genetic acquisition
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Related paper information: https://doi.