Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops. (20th April 2016) - Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron
Abstract: Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. Abstract : Crop breeding: Modeling selection at the seedling stage A theoretical model provides insights into the most efficient way to select new crop varieties from a population of young plants. Selecting promising individuals from which to breed new crop varieties with desirable characteristics is a time-consuming and expensive process, particularly for slow-maturing species such as fruit trees. Selection at the seedling stage can significantly accelerate the process, but relies on a close correlation between traits in the seedling and the mature crop. An international team led by Cameron Peace, of Washington State University, USA, modelled strategies for seedling selection in asexually propagated crops. They found that strategies incorporating both observed traits and genetic markers were more efficient than those using traits or markers alone. The model could be used to maximise breeding efficiency across a range of asexually propagated crops such as potatoes, apples and roses.