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. 2011 Jan;39(Database issue):D1156-63.
doi: 10.1093/nar/gkq991. Epub 2010 Oct 21.

Tomato Functional Genomics Database: a comprehensive resource and analysis package for tomato functional genomics

Zhangjun Fei  1 , Je-Gun Joung, Xuemei Tang, Yi Zheng, Mingyun Huang, Je Min Lee, Ryan McQuinn, Denise M Tieman, Rob Alba, Harry J Klee, James J Giovannoni
Affiliations

Tomato Functional Genomics Database: a comprehensive resource and analysis package for tomato functional genomics

Zhangjun Fei et al. Nucleic Acids Res. 2011 Jan.

Abstract

Tomato Functional Genomics Database (TFGD) provides a comprehensive resource to store, query, mine, analyze, visualize and integrate large-scale tomato functional genomics data sets. The database is functionally expanded from the previously described Tomato Expression Database by including metabolite profiles as well as large-scale tomato small RNA (sRNA) data sets. Computational pipelines have been developed to process microarray, metabolite and sRNA data sets archived in the database, respectively, and TFGD provides downloads of all the analyzed results. TFGD is also designed to enable users to easily retrieve biologically important information through a set of efficient query interfaces and analysis tools, including improved array probe annotations as well as tools to identify co-expressed genes, significantly affected biological processes and biochemical pathways from gene expression data sets and miRNA targets, and to integrate transcript and metabolite profiles, and sRNA and mRNA sequences. The suite of tools and interfaces in TFGD allow intelligent data mining of recently released and continually expanding large-scale tomato functional genomics data sets. TFGD is available at http://ted.bti.cornell.edu.

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Figures

Figure 1.
Figure 1.
Pathway analysis in the database. (A) Screenshot of an example result returned by the pathway analysis tool in TFGD which lists altered pathways identified from a gene expression data set. (B) Visualization of detailed transcript expression changes in a pathway.
Figure 2.
Figure 2.
Correlation analysis between gene expression and metabolite profiles in TFGD. (A) Interface of the correlation analysis. (B) An example of known correlations identified in the database: correlation between profiles of phytoene (green) and phytoene synthase (red) across 17 ILs (r = 0.655, P = 0.00432).
Figure 3.
Figure 3.
Tomato miRNA candidate information in TFGD. (A) Abundances of a miRNA candidate in each sample. (B) Conservation between the miRNA candidate and known miRNAs. (C) miRNA candidate precursors and their secondary structures and corresponding miRNA star sequences. (D) Predicted miRNA targets.
Figure 4.
Figure 4.
siRNA viewer in TFGD. siRNAs in red were aligned to mRNA in the forward direction while those in green were in the reverse direction.
See this image and copyright information in PMC

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