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Contributions to Genetic Diversity Management in Maize Breeding Programs using Genomic Selection

Abstract : There is an increasing awareness that crop breeding programs should move from short- to long-term objectives by maintaining genetic diversity to cope with future challenges in a context of climatic changes. The advent of high density genotyping opened new avenues for breeding quantitative traits including genomic prediction of individual performances, of parental crosses usefulness, and genetic diversity management. This thesis aims at developing methodologies to further enhance the efficiency and sustainability of breeding programs. This involves the evaluation of genetic diversity in elite breeding pools, its efficient conversion into short- and long-term genetic gain and the efficient identification, improvement and introduction of extrinsic variability into breeding pools. We first investigated how temporal phenotypic and genotypic data can be used to develop indicators of the genetic diversity and the potential response to selection of a breeding population. We applied these indicators on a commercial hybrid grain maize program and discussed strategies to manage and unlock potential response to selection in breeding populations.Selection of parental crosses that generate superior progeny while maintaining sufficient diversity is a key success factor of short- and long-term breeding. We extended analytical solutions to predict the distribution of a quantitative trait in the progeny of biparental crosses to the case of multiparental crosses. We also proposed to consider a multitrait approach where agronomic trait and parental genome contributions are considered as correlated normally distributed traits. This approach, called Usefulness Criterion Parental Contribution (UCPC), enables to predict the expected mean performance and diversity in the most performing fraction of progeny. We used UCPC to extend the Optimal Cross Selection (OCS) method, which aims at maximizing the performance in progeny while maintaining diversity for long-term genetic gain. In a long-term simulated recurrent genomic selection breeding program, UCPC based OCS proved to be more efficient than OCS to convert the genetic diversity into short- and long-term genetic gains. The narrow genetic base of an elite population might compromise its long-term genetic gain in unpredictable environmental conditions. An efficient strategy to broaden the genetic base of commercial breeding programs is therefore required. Many genetic resources are accessible to breeders but cannot all be considered. We reviewed, proposed and compared different predictive criteria for selecting genetic resources that best complement elite recipients, based on genomewide marker effects estimated on a collaborative diversity panel. We also investigated which mating design should be implemented between a promising genetic resource and elite recipient(s) depending on its phenotypic and genetic distance to elites. Finally, we evaluated the interest of UCPC based OCS to improve genetic resources (pre-breeding), to bridge pre-breeding and breeding (bridging), and to manage recurrent introductions into the breeding population. In a long-term simulated commercial breeding program, we demonstrated that recurrent introductions from a pre-breeding population maximize long-term genetic gain while maintaining genetic diversity constant, with only limited short-term penalty. The results of this thesis open new perspectives to manage genetic diversity in breeding.
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Antoine Allier. Contributions to Genetic Diversity Management in Maize Breeding Programs using Genomic Selection. Agricultural sciences. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASA002⟩. ⟨tel-03499495⟩

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