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Genomic prediction with a maize collaborative panel: identification of genetic resources to enrich elite breeding programs

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Abstract

Key message

Collaborative diversity panels and genomic prediction seem relevant to identify and harness genetic resources for polygenic trait-specific enrichment of elite germplasms.

Abstract

In plant breeding, genetic diversity is important to maintain the pace of genetic gain and the ability to respond to new challenges in a context of climatic and social expectation changes. Many genetic resources are accessible to breeders but cannot all be considered for broadening the genetic diversity of elite germplasm. This study presents the use of genomic predictions trained on a collaborative diversity panel, which assembles genetic resources and elite lines, to identify resources to enrich an elite germplasm. A maize collaborative panel (386 lines) was considered to estimate genome-wide marker effects. Relevant predictive abilities (0.40–0.55) were observed on a large population of private elite materials, which supported the interest of such a collaborative panel for diversity management perspectives. Grain-yield estimated marker effects were used to select a donor that best complements an elite recipient at individual loci or haplotype segments, or that is expected to give the best-performing progeny with the elite. Among existing and new criteria that were compared, some gave more weight to the donor–elite complementarity than to the donor value, and appeared more adapted to long-term objective. We extended this approach to the selection of a set of donors complementing an elite population. We defined a crossing plan between identified donors and elite recipients. Our results illustrated how collaborative projects based on diversity panels including both public resources and elite germplasm can contribute to a better characterization of genetic resources in view of their use to enrich elite germplasm.

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Data availability

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Acknowledgements

The authors thank the experimental staff at RAGT2n for elite material data extractions and Amaizing project members for the dent collaborative panel. We thank Cyril Bauland and Carine Palaffre (INRA Saint-Martin de Hinx) for the panel assembly and the coordination of seed production, private partners of the Amaizing project for field trials. We also thank Pierre Dubreuil and Simon Rio for the assembly and the analysis of phenotypic data. We thank Valerie Combes, Delphine Madur, and Stephane Nicolas for DNA extraction, analysis, and assembly of genotypic data. AA was funded by RAGT2n and the ANRT CIFRE Grant No. 2016/1281.

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Authors and Affiliations

  1. GQE - Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, 91190, Gif-sur-Yvette, France

    Antoine Allier, Alain Charcosset & Laurence Moreau

  2. RAGT2n, Genetics and Analytics Unit, 12510, Druelle, France

    Antoine Allier, Simon Teyssèdre & Christina Lehermeier

Authors
  1. Antoine Allier
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  2. Simon Teyssèdre
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  3. Christina Lehermeier
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  4. Alain Charcosset
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  5. Laurence Moreau
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Contributions

AC, LM, CL, and ST conceived and supervised the study. AA prepared the data, performed the analysis, and wrote the early version of the manuscript. All authors reviewed and approved the manuscript.

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Correspondence to Laurence Moreau.

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Communicated by Benjamin Stich.

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Allier, A., Teyssèdre, S., Lehermeier, C. et al. Genomic prediction with a maize collaborative panel: identification of genetic resources to enrich elite breeding programs. Theor Appl Genet 133, 201–215 (2020). https://doi.org/10.1007/s00122-019-03451-9

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