Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy

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Tayeh, Nadim; Klein, Anthony; Le Paslier, Marie-Christine; Jacquin, Françoise; Houtin, Hervé; Rond, Céline; Chabert-Martinello, Marianne; Magnin-Robert, Jean-Bernard; Marget, Pascal; Aubert, Grégoire; Burstin, Judith;
  • Publisher: Frontiers Media S.A.
  • Journal: Frontiers in Plant Science,volume 6 (issn: 1664-462X, eissn: 1664-462X)
  • Related identifiers: doi: 10.3389/fpls.2015.00941/full, doi: 10.3389/fpls.2015.00941, pmc: PMC4648083
  • Subject: training set | genomic selection | Plant culture | SB1-1110 | pea (Pisum sativum L.);GenoPea 13.2K SNP Array;genomic selection;marker density;training set;prediction accuracy | marker density | Plant Science | pea (Pisum sativum L.) | Original Research | prediction accuracy | GenoPea 13.2K SNP Array

Pea is an important food and feed crop and a valuable component of low-input farming systems. Improving resistance to biotic and abiotic stresses is a major breeding target to enhance yield potential and regularity. Genomic selection has lately emerged as a promising te... View more
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