Computational and experimental analysis identifies Arabidopsis genes specifically expressed during early seed development.

BACKGROUND:Plant seeds are complex organs in which maternal tissues, embryo and endosperm, follow distinct but coordinated developmental programs. Some morphogenetic and metabolic processes are exclusively associated with seed development. The goal of this study was to explore the feasibility of incorporating the available online bioinformatics databases to discover Arabidopsis genes specifically expressed in certain organs, in our case immature seeds. RESULTS:A total of 11,032 EST sequences obtained from isolated immature seeds were used as the initial dataset (178 of them newly described here). A pilot study was performed using EST virtual subtraction followed by microarray data analysis, using the Genevestigator tool. These techniques led to the identification of 49 immature seed-specific genes. The findings were validated by RT-PCR analysis and in situ hybridization. CONCLUSION:We conclude that the combined in silico data analysis is an effective data mining strategy for the identification of tissue-specific gene expression.

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