Abstract
Key messageOptimal cross selection increases long-term genetic gain of two-part programs with rapid recurrent genomic selection. It achieves this by optimising efficiency of converting genetic diversity into genetic gain through reducing the loss of genetic diversity and reducing the drop of genomic prediction accuracy with rapid cycling.This study evaluates optimal cross selection to balance selection and maintenance of genetic diversity in two-part plant breeding programs with rapid recurrent genomic selection. The two-part program reorganises a conventional breeding program into a population improvement component with recurrent genomic selection to increase the mean value of germplasm and a product development component with standard methods to develop new lines. Rapid recurrent genomic selection has a large potential, but is challenging due to genotyping costs or genetic drift. Here we simulate a wheat breeding program for 20 years and compare optimal cross selection against truncation selection in the population improvement component with one to six cycles per year. With truncation selection we crossed a small or a large number of parents. With optimal cross selection we jointly optimised selection, maintenance of genetic diversity, and cross allocation with AlphaMate program. The results show that the two-part program with optimal cross selection delivered the largest genetic gain that increased with the increasing number of cycles. With four cycles per year optimal cross selection had 78% (15%) higher long-term genetic gain than truncation selection with a small (large) number of parents. Higher genetic gain was achieved through higher efficiency of converting genetic diversity into genetic gain; optimal cross selection quadrupled (doubled) efficiency of truncation selection with a small (large) number of parents. Optimal cross selection also reduced the drop of genomic selection accuracy due to the drift between training and prediction populations. In conclusion optimal cross selection enables optimal management and exploitation of population improvement germplasm in two-part programs.
Highlights
In this study we evaluate optimal cross selection to balance selection and maintenance of genetic diversity in two-part plant breeding programs with rapid recurrent genomic selection
Overall the results show that the two-part program with optimal cross selection delivered the largest long-term genetic gain and that this gain increased with the increasing number of recurrent selection cycles per year
This was achieved by optimising efficiency of converting genetic diversity into genetic gain, which the two-part program with truncation selection cannot achieve
Summary
In this study we evaluate optimal cross selection to balance selection and maintenance of genetic diversity in two-part plant breeding programs with rapid recurrent genomic selection. Plant breeding programs that produce inbred lines have two concurrent goals: (1) identifying new varieties or hybrid. Parents and (2) identifying parents for subsequent breeding cycles. We recently proposed a two-part program that uses genomic selection to separately address these goals (Gaynor et al 2017; Hickey et al 2017a). The two-part program reorganises conventional program into two distinct components: a product development component that develops and screens inbred lines with established breeding methods and a population improvement component that increases the population mean with rapid cycles of recurrent genomic selection. Simulations showed that the two-part program has a potential to deliver about 2.5 times larger genetic gain compared to a conventional program for the same investment (Gaynor et al 2017)
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