Location: Physiology and Pathology of Tree Fruits Research
Project Number: 2094-30600-001-019-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Oct 1, 2025
End Date: Sep 29, 2028
Objective:
1. Gene activity analysis (RNASeq) of samples we have in hand (3 cultivars collected over 3 years (‘Bartlett’,‘d’Anjou’, and ‘Gem’; n = 267) to test and refine our preliminary pear ripening capacity predictive model.
2. Add the new data into the modeling schema, including execution of our published testing scheme for accuracy and stability.
3. Select mRNA targets for development of a commercializable biomarker panel test.
Approach:
Following a proven approach, we are mining massive, multi-cultivar, multi-year genome scale datasets with AI to identify a panel of mRNA transcripts that can predict pome fruit storability, with a special emphasis on fruit maturity. Our published apple model can predict postharvest fruit firmness within ~0.5 lbs based on expression levels of as few as 15 genes (10.1371/journal.pone.0306187). Through a funded WTFRC project, we are now building predictive models on additional maturity-related traits using gene activity signatures at harvest in apples. Follow up validation tests show that the models are cultivar agnostic (i.e. we can estimate maturity differences in all tested cultivars, n=13).
Initial pear models have been built that estimate the future ripening capacity of pears within ~1.25 lbs of fruit firmness, but whether the model accuracy remains high across cultivars, years, and orchards needs to be tested. We have collected hundreds of transcriptome datasets across many cultivars and years in both apple and pear, but unlike apple, the pear validation samples (in cryogenic storage; n=267 from 3 cultivars across 4 years) have not been analyzed. We request funds for personnel and supplies to extract samples and analyze the new transcriptome data for pears (USDA ARS will provide funds for RNASeq analysis). Genes with predictive power from those models will constitute our pilot biomarkers panel. With sufficient development such tests could help guide the timing of harvest and subsequent storage plans.
While apples and pears are horticulturally unique, they are closely related evolutionarily. They share the same process of climacteric ripening, which means that the shared molecular process of ripening likely predates the split between the two species and also predates the creation of cultivars. Therefore, studying both pome fruits together will help account for cultivar noise leaving us with a cultivar agnostic set of molecular markers to guide the timing of harvest and subsequent storage plans. This project will enhance our pear ripening models in two ways, 1) by adding pear data from new orchards/years/cultivars, 2) by providing a synergistic dimension to the greater pome fruit project by helping discover genes that influence important postharvest pome fruit quality traits.
We hypothesize that with the addition of this data we will be able to improve and test pear ripening models that could be developed into decision aid tools and help maintain the viability of the WA pear industry. In addition to decision aid tools that reduce food waste and enhance supply chain efficiency, the increased knowledge around postharvest pome fruit quality are also important project deliverables. This knowledge may allow the development of new storage technologies and inform breeding efforts by enhancing our understanding of complex trait genetics in such an intractable tree crop species.