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

dataset
posted on 2024-06-11, 07:19 authored by Agricultural Research Service
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.

Funding

Washington Tree Fruit Research Commission, AP-19-103

Agricultural Research Service, 2094-43000-008-000-D

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2023-02-23

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

transcriptome; gene expression

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA938164

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA938164 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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