1a.Objectives (from AD-416):
The objective of this project is to develop transcriptome gene expression data for apple at early stages of postharvest fruit disorder development. Fruit will be provided by our collaborators at the USDA in Washington State following postharvest storage treatments that promote certain fruit development disorders that have severe negative impacts on the US apple industry. The BTI cooperator will facilitate creation of cDNA libraries from said apple tissues and secure Cornell University DNA sequencing services to generate transcript sequence data. Cooperator will then perform bioinformatics analysis and quality control to secure the most accurate gene expression data. Genes that are tightly associated with particular fruit disorders will be validated by quantitative RT-PCR. Validated genes will be passed back to our Washington State colleagues to facilitate their development of diagnostic molecular screens designed to inform practical storage and marketing decisions. Said genes will also be referred back to the USDA lab for functional analyses related to apple fruit biology.
1b.Approach (from AD-416):
The general approach of this project includes extraction of apple fruit RNA, reverse transcription to cDNA, addition of sample-specific DNA “barcode” sequences, primer adapter ligation to facilitate DNA sequencing and Illumina-based pyro-sequencing of multiplexed samples to generate large numbers of transcript reads from each tissue. Resulting transcript-related cDNA sequence data (approximately 2-4 million reads/sample) will be sorted bioinformatically by barcode sequences to allow assignment to originating tissue samples, assessed for quality and normalized against all other samples to facilitate gene expression assessment based on relative numbers of transcripts per gene. Gene identify will then be assigned based on mapping of all sequence reads to the publically available apple genome sequence. The collaborator’s group is expert in bioinformatic analysis of transcriptome data and in the creation of gene expression and other bioinformatics tools. The ARS lab does not have strong competence in these areas. Genes associated with certain fruit quality traits will be subject to gene-specific primer design for quantitative RT-PCR gene expression analysis to confirm sequence-based expression data. Genes highly correlated with apple fruit disorders will be forwarded to the lab of our ARS collaborators in Washington State for development of marker systems diagnostic for predicting fruit disorders during postharvest storage. They will also be delivered back to our ARS lab that has expertise on comparative genomcis and functional analysis of fruit development, quality and ripening genes.
Apple fruit are an important crop commodity in many northern states and provide year-round nutrition and food security due to apple’s quality retention during long-term storage. Data has been generated under other projects for identification of DNA markers useful in predicting optimal storage time as related to fruit quality. The data is in the form of extensive gene expression (transcriptome) information. This same data is available and being utilized here to explore the biology of apple fruit maturation, ripening and responses to postharvest storage. We have downloaded all data to our servers and begun to perform comparative transcript profiling among different apple cultivars during storage. To date we have characterized numerous previously characterized ripening genes (e.g. genes involved in anthocyanin, ethylene, carbohydrate and organic acid metabolism) and begun correlation analysis with transcription factors to identify candidates that may regulate these important quality processes and may serve as targets for understanding ripening biology and in breeding to enhance fruit quality and postharvest storability.