Apple fruit : towards the identification of genes showing a modulated expression during development

Fruit development is a fundamental process determining fruit quality; therefore the knowledge of the genes involved allows the deployment of more efficient selection methods. In order to detect these genes, cDNA microarrays were constructed using two subtractive cDNA libraries. About 1600 clones, derived from the two libraries have been printed in duplicate on the slides. Hybridizations were always performed comparing mRNA from fruits of the cultivar 'Prima', collected in May, with different mRNA samples isolated from the same plant at different developmental stages (June, July, August, and September). The analysis of the expression profiles suggests that about 10% of the genes present on the slides show a modulated expression during fruit development. 75% of sequences have known functions and the most represented categories are: primary metabolism (17%), stress and defense (10%), aminoacid and protein metabolism (9%). A high proportion (24%) corresponds to genes encoding proteins with unknown function. Gene Ontology annotation was employed to univocally describe the differentially expressed genes, while clustering analysis allowed grouping genes according to their expression profiles. In June and July, genes have similar expression patterns and their changes in expression level are not significant. On the contrary, August and September are characterized by a high number of genes up or down regulated. Microarray data were experimentally validated by an independent method, Quantitative RT-PCR, and about 70% of them were confirmed. Though not all the data were confirmed, microarray results are a good tool to identify candidate genes potentially correlated with fruit quality QTLs. Molecular markers are going to be generated from the most interesting transcripts and their position is going to be determined on the apple linkage map. Subsequent QTL analysis will allow associating and correlating those genes with fruit quality traits.