CATchUP: A Web Database for Spatiotemporally Regulated Genes.

Area of Science:

• Plant genomics
• Transcriptomics
• Bioinformatics

Background:

• Gene expression control is crucial for biological activity.
• Understanding spatiotemporally expressed genes is vital for genome-scale functional gene networks.
• Comprehensive data on plant spatiotemporally expressed genes is currently limited.

Purpose of the Study:

• To develop a method for identifying spatiotemporally expressed genes in plants.
• To create a database of these genes for eight major plant species.
• To facilitate research on gene function and regulation in plants.

Main Methods:

• Devised a novel index, Δdmax, to quantify gene expression differences.
• Analyzed large-scale RNA sequencing (RNA-Seq) data from the Sequence Read Archive.
• Evaluated transcripts from eight plant species: Arabidopsis, tomato, potato, rice, sorghum, grape, Medicago, and soybean.

Main Results:

• Identified approximately 70,000 transcripts with Δdmax values of 0.3 or higher across the eight species.
• Developed the CATchUP database, providing Δdmax values, functional annotations, conservation data, and expression conditions.
• The database enables efficient searching for genes with specific expression profiles.

Conclusions:

• The Δdmax index and CATchUP database provide a valuable resource for plant gene expression research.
• This facilitates the identification of key genes involved in specific biological processes.
• Enhances our understanding of plant genome-scale functional gene networks.