PlantExpress: A Database Integrating OryzaExpress and ArthaExpress for Single-species and Cross-species Gene Expression Network Analyses with Microarray-Based Transcriptome Data.
Publicly available microarray-based transcriptome data on plants are remarkably valuable in terms of abundance and variation of samples, particularly for Oryza sativa (rice) and Arabidopsis thaliana (Arabidopsis). Here, we introduce the web database PlantExpress (http://plantomics.mind.meiji.ac.jp/PlantExpress/) as a platform for gene expression network (GEN) analysis with the public microarray data of rice and Arabidopsis. PlantExpress has two functional modes. The single-species mode is specialized for GEN analysis within one of the species, while the cross-species mode is optimized for comparative GEN analysis between the species. The single-species mode for rice is the new version of OryzaExpress, which we have maintained since 2006. The single-species mode for Arabidopsis, named ArthaExpress, was newly developed. PlantExpress stores data obtained from three microarrays, the Affymetrix Rice Genome Array, the Agilent Rice Gene Expression 4x44K Microarray, and the Affymetrix Arabidopsis ATH1 Genome Array, with respective totals of 2,678, 1,206, and 10,940 samples. This database employs a ‘MyList’ function with which users may save lists of arbitrary genes and samples (experimental conditions) to use in analyses. In cross-species mode, the MyList function allows performing comparative GEN analysis between rice and Arabidopsis. In addition, the gene lists saved in MyList can be directly exported to the PODC database, which provides information and a platform for comparative GEN analysis based on RNA-seq data and knowledge-based functional annotation of plant genes. PlantExpress will facilitate understanding the biological functions of plant genes.
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Toru
T
Kudo
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Shin
S
Terashima
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Yuno
Y
Takaki
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Ken
K
Tomita
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Misa
M
Saito
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Maasa
M
Kanno
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Koji
K
Yokoyama
Bioinformatics Laboratory, School of Agriculture, Meiji University, Higashi-mita, Tama-ku, Kawasaki, Kanagawa, Japan.
Kentaro
K
Yano
D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics*; D057225:Data Mining; D030541:Databases, Genetic; D053263:Gene Regulatory Networks; D058977:Molecular Sequence Annotation; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012275:Oryza / Q000235:genetics*; D012689:Sequence Homology, Nucleic Acid; D013045:Species Specificity; D059467:Transcriptome / Q000235:genetics*
Arabidopsis thaliana; Gene expression network; Microarray; Oryza sativa (rice)