TENOR: Database for Comprehensive mRNA-Seq Experiments in Rice
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Updated: Mar 30, 2026

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Yoshihiro Kawahara1, Youko Oono1, Hironobu Wakimoto2
1Agrogenomics Research Center, National Institute of Agrobiological Sciences, 2-1-2 Kannondai, Tsukuba, Ibaraki, 305-8602 Japan.
Abstract:
Here we present TENOR (Transcriptome ENcyclopedia Of Rice, http://tenor.dna.affrc.go.jp), a database that encompasses large-scale mRNA sequencing (mRNA-Seq) data obtained from rice under a wide variety of conditions. Since the elucidation of the ability of plants to adapt to various growing conditions is a key issue in plant sciences, it is of great interest to understand the regulatory networks of genes responsible for environmental changes. We used mRNA-Seq and performed a time-course transcriptome analysis of rice, Oryza sativa L. (cv. Nipponbare), under 10 abiotic stress conditions (high salinity; high and low phosphate; high, low and extremely low cadmium; drought; osmotic; cold; and flood) and two plant hormone treatment conditions (ABA and jasmonic acid). A large number of genes that were responsive to abiotic stresses and plant hormones were detected by differential expression analysis. Furthermore, several responsive genes were found to encode transcription factors that could control the transcriptional network of stress responses, but the timing of the induction of these genes was not uniform across conditions. A significant number of cis-regulatory elements were enriched in the promoter regions of the responsive genes and were shared among conditions. These data suggest that some key components of gene regulation networks are shared between different stress signaling pathways. All the resources (novel genes identified from mRNA-Seq data, expression profiles, co-expressed genes and cis-regulatory elements) can be searched for and are available in TENOR.
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