ISOL@: an Italian SOLAnaceae genomics resource

Area of Science:

• Bioinformatics
• Genomics
• Systems Biology

Background:

• High-throughput '-omics' technologies generate vast datasets (genome, transcriptome, proteome, metabolome).
• Integrating diverse biological data is crucial for understanding complex biological systems.
• Comparative analysis of integrated data yields meaningful biological interpretations.

Purpose of the Study:

• To introduce ISOLA, an Italian genomics resource for Solanaceae species.
• To develop a multi-level computational environment for integrating and analyzing '-omics' data.
• To facilitate biological knowledge discovery and systems biology approaches in Solanaceae.

Main Methods:

• Development of a multi-level computational platform (ISOLA).
• Integration of Solanum lycopersicum genome draft sequences.
• Incorporation of transcriptome data, including Expressed Sequence Tags (ESTs), from various Solanaceae species.
• Implementation of data sharing and quality enhancement tools for cross-level analysis.

Main Results:

• ISOLA provides a two-level platform: genome and expression.
• The genome level is based on tomato genome sequences.
• The expression level utilizes comprehensive EST collections from Solanaceae species.
• Tools facilitate data integration, quality enhancement, and knowledge extraction.

Conclusions:

• ISOLA addresses post-genomics challenges through bioinformatics and data integration.
• The platform supports a systems biology view by exploiting '-omics' data.
• ISOLA offers preliminary tomato genome annotation and a versatile environment for Solanaceae research.