Author
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Wisniewski, Michael |
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Norelli, John |
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DROBY, SAMIR - Agricultural Research Organization, Volcani Center |
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LEVIN, ELENA - Agricultural Research Organization Of Israel |
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BALLESTER, ANA-ROSA - Instituto De Agroquimica Y Technologia De Alimentos |
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ABDELFATTAH, AHMED - University Of Reggio Calabria |
Submitted to: Acta horticulturae
Publication Type: Proceedings Publication Acceptance Date: 11/1/2015 Publication Date: 11/15/2016 Citation: Wisniewski, M.E., Norelli, J.L., Droby, S., Levin, E., Ballester, A., Abdelfattah, A. 2016. Genomic tools for developing markers for postharvest disease resistance in Rosaceae fruit crops. Acta Horticulturae. DOI 10.17660/ActaHortic.2016.1144.2. Interpretive Summary: Technical Abstract: A wealth of new plant genomic information and molecular tools have been developed over the past ten years and now the challenge is to learn how to apply this information to address critical production problems, such as disease resistance and abiotic stress tolerance. Malus sieversii, an apple species native to Kazakhstan and a progenitor of the modern domesticated apple (Malus x domestica), is considered a reservoir of genetic diversity for many economically important traits. Earlier research has demonstrated that some genotypes of M. sieversii are highly resistant to postharvest pathogens such as Penicillium expansum. One such genotype, PI613981 was crossed with ‘Royal Gala’ to create a mapping population, GMAL4593. In addition to P. expansum resistance, this population also segregates for fire blight and apple scab resistance, water use efficiency, and coddling moth and oblique banded leaf roller resistance. A genetic framework map based on 171 individuals of this population has been created and the harvested fruit has been phenotyped for resistance to P. expansum. Preliminary QTLs for blue mold resistance have been identified on LG4 and LG 10. The identification of such markers is a first step in providing new markers for use in marker-assisted-breeding. Confirmation of the QTLs is currently in progress using maps with a higher density of markers along with a more comprehensive data set for resistance (more individuals and more years). Transcriptomic analyses have also been conducted to identify genes specifically associated with a resistance response and that may represent gene-specific markers. |