Transcriptional signatures associated with apple fruitlet abscission

Apple (Malus x domestica L. Borkh) represents an interesting model tree crop for studying fruit abscission. The physiological fruitlet drop occurring in this species can be easily magnified by using thinning chemicals, such as benzyladenine (BA), in order to obtain fruits with improved quality and marketability. Despite the economical importance of this process, the molecular determinants of apple fruitlet abscission are still unknown. In the present research, BA was used to obtain fruitlet populations with different abscission potentials, to be analysed by means of a 30,419 oligonucleotide microarray set up starting from about 256,000 expressed sequence tag (EST) sequences available in public database. A dedicated bioinformatic pipeline was created to cluster and assemble the available ESTs into temptative unigenes that were spotted by means of the CombiMatrix technology. RNAs were extracted from cortex and seed of apple fruitlets sampled over a 4-day timecourse, during which BA triggers fruit drop, and used for microarray hybridisation. Transcriptomic profiles of persisting and abscising fruitlets were tested for statistical association with abscission potential, allowing to identify molecular signatures strictly related to fruit destiny with P < 0.001. A hypothetical model for apple fruitlet abscission was obtained by putting together available transcriptomic and metabolomic data. According to this model, BA treatment would establish a nutritional stress within the tree that is primarily perceived by the fruitlet cortex whose growth is inhibited. In weaker fruits, this stress is soon transduced to the seed via sugar signalling and hormones, followed by a block of embryogenesis and the consequent activation of the abscission zone. The molecular markers herein discovered may be used as diagnostic tools for the early identification of the self- or chemical-thinning aptitude of apple cultivars. Moreover, the functional characterization of markers with the best statistical scores will allow to shed light on the early cellular processes triggering apple fruitlet abscission.