A Diagnostic Toolbox for Management of Apple Postharvest Necrotic Disorders - Agrofresh
Plant, Soil and Nutrition Research
2013 Annual Report
1a.Objectives (from AD-416):
To identify gene expression patterns specific to individual disorders which can be developed into biomarkers for predicting apple fruit disorders, thus determining storage plans for fruit held in controlled atmosphere storage.
1b.Approach (from AD-416):
Facilitate RNAseq transcriptome analysis of apple tissues under conditions conducive to apple fruit postharvest disorders. We will harvest apple tissues, extract mRNA, create primer-tagged cDNA libraries, sequence said libraries via Illumina HighSeq, sort and trim sequences and process for quality, map to the public apple genome sequence and determine expression patterns via read counting. Resulting data will then feed into the larger NIFA funded apple consortium project for selection and development of biomarkers.
This project is part of a broader multi-institutional effort directed toward eventual development of diagnostic tools for predicting apple fruit storage disorders negatively impacting fruit appearance or quality so that decisions can be made regarding optimal use of specific apple storage lots. For example, apple storage lots showing markers for late term apple fruit disorders might be targeted for early fresh use or sent to the processing stream if stored for a longer period so as to recover maximal product benefit. Specific activities under this project include testing of candidate gene expression patterns that may serve as early warning markers for various storage regimes and pre-storage treatments that might impact later development of fruit storage disorders. In the current year, we have mined whole genome transcriptome profiling data of apple fruit under various storage conditions and selected a number of candidate marker genes. These were then confirmed via qPCR analysis and then tested on secondary tissue lots stored under the same conditions. The same data was used for comparative genomics with tomato to identify homologous apple genes corresponding to defined and characterized tomato genes. This project is in all respects on schedule and on budget and indeed has exceeded objectives as advances in sequencing technology has allowed us to test more varieties, treatments and durations of storage than originally proposed.