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Identification of Ganoderma disease resistance loci using natural field infection of an oil palm multiparental population

Tisne S., Pomies V., Riou V., Syahputra I., Cochard B., Denis M.. 2017. G3 - Genes Genomes Genetics, 7 : p. 1683-1692.

Multi-parental populations are promising tools for identifying quantitative disease resistance loci. Stem rot caused by Ganoderma boninense is a major threat to palm oil production, with yield losses of up to 80% prompting premature replantation of palms. There is evidence of genetic resistance sources, but the genetic architecture of Ganoderma resistance has not yet been investigated. This study aimed to identify Ganoderma resistance loci using an oil palm multi-parental population derived from nine major founders of ongoing breeding programs. A total of 1200 palm trees of the multi-parental population was planted in plots naturally infected by Ganoderma, and their health status was assessed biannually over 25 yr. The data were treated as survival data, and modeled using the Cox regression model, including a spatial effect to take the spatial component in the spread of Ganoderma into account. Based on the genotypes of 757 palm trees out of the 1200 planted, and on pedigree information, resistance loci were identified using a random effect with identity-by-descent kinship matrices as covariance matrices in the Cox model. Four Ganoderma resistance loci were identified, two controlling the occurrence of the first Ganoderma symptoms, and two the death of palm trees, while favorable haplotypes were identified among a major gene pool for ongoing breeding programs. This study implemented an efficient and flexible QTL mapping approach, and generated unique valuable information for the selection of oil palm varieties resistant to Ganoderma disease.

Mots-clés : phénotype; elaeis guineensis; méthode statistique; variation génétique; analyse de variance; analyse quantitative; gène; héritabilité génotypique; résistance aux maladies; ganoderma; côte d'ivoire; république démocratique du congo

Thématique : Maladies des plantes; Génétique et amélioration des plantes

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