Genomic prediction and landscape genomics in a large maize landraces collection using high-throughput pool genotyping identifies promising sources of diversity for prebreeding

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Galaretto, Agustin O. | Gouesnard, Brigitte | Madur, Delphine | Ben-Sadoun, Sarah | Hearne, Sarah | Combes, Valérie | Balconi, Carlotta | Butrón, Ana | Revilla, Pedro | Malvar, Rosa Ana | Zanetto, Anne | Barata, Ana Maria | Murariu, Danela | Kravic, Natalija | Schierscher-Viret, Beate | Mendes-Moreira, Pedro | Pereira, A.R. | Šarčević, Hrvoje | Menz, Monica | Melkior, Stéphane | Pétiard, Benoit | Presterl, Thomas | Kessel, Bettina | Strigens, A. | Foll, Amélie Le | Derue, Carole | Murigneux, Alain | Lohwasser, Ulrike | Bauland, Cyril | Goritschnig, Sandra | Andjelkovic, Violeta | Charcosset, Alain | Nicolas, Stéphane D.

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International audience. Maize landraces are a valuable source of genetic diversity for facing climate change due to their local adaptation. High-throughput pool genotyping (HPG) is a cost-effective approach to genotype maize landraces and identify promising sources of alleles for tolerance to abiotic stress. We applied this approach on a large world-wide collection of maize landraces to i) characterize its genetic structuration; ii) identify genomic regions involved in adaptation through environmental association studies; iii) perform genomic prediction (GP) of both adaptive and agronomic traits. Landraces were structured according to their history and environmental conditions. GP yielded high accuracy, allowing to identify promising landraces. We identified genomic regions associated with bioclimatic variables that could be putatively involved in adaptation to abiotic stress. Combining eco-genetic and genomic prediction opens an avenue for using these genetic resources for prebreeding.

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