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Charmet G, Storlie E, Oury FX, et al. Genome-wide prediction of three important traits in bread wheat. Mol Breed. 2014;34(4):1843-1852doi: 10.1007/s11032-014-0143-y.
Charmet, G., Storlie, E., Oury, F. X., Laurent, V., Beghin, D., Chevarin, L., Lapierre, A., Perretant, M. R., Rolland, B., Heumez, E., Duchalais, L., Goudemand, E., Bordes, J., & Robert, O. (2014). Genome-wide prediction of three important traits in bread wheat. Molecular breeding : new strategies in plant improvement, 34(4), 1843-1852. https://doi.org/10.1007/s11032-014-0143-y
Charmet, Gilles, et al. "Genome-wide prediction of three important traits in bread wheat." Molecular breeding : new strategies in plant improvement vol. 34,4 (2014): 1843-1852. doi: https://doi.org/10.1007/s11032-014-0143-y
Charmet G, Storlie E, Oury FX, Laurent V, Beghin D, Chevarin L, Lapierre A, Perretant MR, Rolland B, Heumez E, Duchalais L, Goudemand E, Bordes J, Robert O. Genome-wide prediction of three important traits in bread wheat. Mol Breed. 2014;34(4):1843-1852. doi: 10.1007/s11032-014-0143-y. Epub 2014 Jul 16. PMID: 26316839; PMCID: PMC4544631.
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Mol Breed. 2014;34(4):1843-1852. doi: 10.1007/s11032-014-0143-y. Epub 2014 Jul 16.

Genome-wide prediction of three important traits in bread wheat.

Molecular breeding : new strategies in plant improvement

Gilles Charmet, Eric Storlie, François Xavier Oury, Valérie Laurent, Denis Beghin, Laetitia Chevarin, Annie Lapierre, Marie Reine Perretant, Bernard Rolland, Emmanuel Heumez, Laure Duchalais, Ellen Goudemand, Jacques Bordes, Olivier Robert

Affiliations

  1. UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
  2. UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France ; Colorado State University, Fort Collins, CO 80523 USA.
  3. Bioplante-Florimond Desprez, BP41, 59242 Cappelle en Pévèle, France.
  4. INRA-APBV, Domaine de la Motte, BP 35327, 35653 Le Rheu Cedex, France.
  5. INRA UE Lille, 2 chaussée Brunehaut, Estrées-Mons, BP 50136, 80203 Peronne Cedex, France.
  6. Bioplante-R2n, 60 rue Léon Beauchamp, 59930 La Chapelle d'Armentières, France.

PMID: 26316839 PMCID: PMC4544631 DOI: 10.1007/s11032-014-0143-y

Abstract

Five genomic prediction models were applied to three wheat agronomic traits-grain yield, heading date and grain test weight-in three breeding populations, each comprising about 350 doubled haploid or recombinant inbred lines evaluated in three locations during a 3-year period. The prediction accuracy, measured as the correlation between genomic estimated breeding value and observed trait, was in the range of previously published values for yield (

Keywords: Bayesian LASSO; Genomic selection; Plant breeding; Random Forest regression; Ridge regression; Triticum aestivum L.

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