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ARS Home » Northeast Area » Kearneysville, West Virginia » Appalachian Fruit Research Laboratory » Innovative Fruit Production, Improvement, and Protection » Research » Publications at this Location » Publication #304581
Title: Identification of a QTL for postharvest disease resistance to Penicillium expansum in Malus sieversii

Author
item Norelli, John
item Wisniewski, Michael
item DROBY, SAMIR - Agricultural Research Organization, Volcani Center

Submitted to: Acta Horticulturae
Publication Type: Proceedings
Publication Acceptance Date: 5/5/2014
Publication Date: 5/10/2014
Citation: Norelli, J.L., Wisniewski, M.E., Droby, S. 2015. Identification of a QTL for postharvest disease resistance to Penicillium expansum in Malus sieversii. Acta Horticulturae. 1053:199-203.

Interpretive Summary:

Technical Abstract: Blue mold of apple caused by Penicillium expansum is one of the most important postharvest rots of apple fruit. Little attention has been devoted to postharvest disease resistance in apple breeding programs due both to a lack of sources of genetic resistance and to the time required for seedlings to produce a sufficient number of fruit to phenotype the trait. Malus sieversii PI613981 collected from the wild in Kazakhstan has previously been reported to be resistant to blue mold. The development of genetic markers for this resistance to blue mold would facilitate the marker-assisted selection of this valuable trait in breeding programs. Fruit collected from a ‘Royal Gala’ X PI613981 mapping population (GMAL4593) in 2011 (145 individuals) and 2012 (115 individuals) were inoculated with P. expansum and evaluated for decay. The response of individual progeny to P. expansum ranged from highly resistant to highly susceptible, and lesion diameters observed on 101 progeny evaluated both years were significantly correlated. A genetic framework map has been developed for the GMAL4593 population and was used to identify a QTL for blue mold resistance on linkage group (chromosome) 4 and 10. Analysis of the apple genome sequence and functional genomics are currently being used to identify genetic markers derived from putative resistance genes.