Transcriptome of Gala appple (Malus domestica) in long term storage

Predicting phenotypic traits is important in high value agricultural crops where knowledge of disease, physiological traits, and disorders can reduce crop loss and improve end-use quality for consumers. These phenotypic traits are caused by the interaction of the genotype of a crop with its environment. In apples, negative phenotypic outcomes are often not observable at the time of harvest, and instead develop after the fruit have been in storage. Predicting these negative outcomes prior to their development would allow producers to make marketing decisions to reduce crop loss and maximize end-use quality. One promising method for predicting phenotypic outcomes is through measurements of the transcriptome, as it responds to environmental factors before visible phenotypes occur. Prognostic Transcriptomic Biomarkers, PTBs, are transcriptomic measurements of specific genes used to predict a phenotypic trait. The following research conducts a preliminary analysis to explore methods and approaches for the development of PTBs in apples by using loss of firmness in Gala Apple Fruits. We compare Random Forest and Elastic Net ability to select PTBs from a large time-series RNA-seq data set that includes multiple postharvest treatments.