What is Rice Expression Database?
Rice Expression Database (RED), a sub-project of IC4R (Information Commons for Rice; http://ic4r.org), integrates expression profiles derived entirely from NGS RNA-Seq data of Nipponbare (Oryza Sativa japonica). RED includes RNA-seq data exclusively, providing information on gene expression profiles of normal tissues as well as tissues under a wide range of treatments. It provides friendly web interfaces for querying and visualizing gene expression profiles under different tissues and treatments.
What datasets are used in RED and where I can find these original data?
RED is based entirely on RNA-Seq data derived from NCBI SRA (http://www.ncbi.nlm.nih.gov/sra/) and includes high-quality RNA-Seq data by critical criteria (e.g., sequencing reads should be longer than or equal to 50bp). As a result, a total of 24 projects were used for profiling gene expression levels and detailed information can be found at http://expression.ic4r.org/project.
What procedures are used for RNA-Seq data analysis?
Roughly speaking, raw RNA-Seq data was first converted into fastq using SRA Toolkit (v 2.4.2) and we adopted Trimmomatic (v0.35) for quality control. A sample was excluded from further analysis if low-quality-reads cover over 40% of total reads.
For sequence alignment and gene expression analysis, all high-quality samples were mapped to the latest version of rice reference genome (Os-Nipponbare-Reference-IRGSP-1.0) using Hisat (v2.0.1). Only samples with ~60% reads mapped to the genome were used for gene expression profiling. Stringtie (v1.1.2) was used to calculate the expression level for each gene and transcript based on annotation information of genes and transcripts downloaded from TIGR version 7.0 (http://rice.plantbiology.msu.edu). Moreover, gene ID conversion between RAP-DB and TIGR reference annotation systems were accomplished to facilitate database searching.
Where can I find related information of SRA projects that are used in RED?
â¢Please click "Browse" on the top navigation bar and choose RNA-seq Project, then you will find brief information on the SRA projects used for profiling gene expression levels. Any project contains multiple different experiments and you can click the number shown at the last column for details. After entering into the experiment page, you will find basic information about the tissue source, treatment method, data quality and mapping quality, etc. For detailed information on each experiment, please click on the SRA accession number which will automatically direct you to SRA.
How can I browse expression levels for multiple genes?
Please click "Browse" on the top navigation bar and choose All Annotated Genes, then you will find a complete list of rice annotated genes. Please choose genes of your interest and click "Line chart" or "Heatmap chart". There are four kinds of image formats (PNG, JPEG, PDF and SVG) available for download. For a specific gene, you can also click "Boxplot" listed at the last column to obtain its expression profiles under different tissues.
How can I browse housekeeping and tissue-specific genes?
Please click "Browse" on the top navigation bar and choose HK-TS genes, then you will find a complete list of of HK and TS genes. For each gene, its expression profiles in 9 tissues and its associated Ï value as well as a button for plotting an interactive box plot across 9 tissues are provided. Moreover, you can also download the full list of HK and TS genes with customized settings.
How can I search project information?
You can visit the Search page and then click "Project" on the sidebar. After you enter a keyword or SRA project id, all related information will be retrieved and displayed.
How can I search expression levels for genes of interest?
Please visit the Search page and then click "Gene expression" on the sidebar. After entering a gene ID list (separated with comma or space blank), all genes' expression profiles will be retrieved and visualized. In addition, you can also click "Advanced" to set more conditions. For a better experience, it is highly recommended to enter less than 50 genes for each query. After obtained the queried results, you can also narrow down the results by selecting the project name, tissue type, development stage and treatment methods. In addition, combined Line plot or Heatmap visualization of gene expression levels are available.
How can I search the transcripts expression?
Plase visit "Search" on the top navigation bar and then click "Transcript expression" on the sidebar. After eentering transcipt IDs of interest, all relevant information will be automatically retrieved and displayed.
How can I obtain expression profile for a specific region?
First, please click "Search" on the top navigation bar and then click "Location" on the sidebar. Second, determine chromosome that you are interested in. Finally, specify the start site and end site of the region of interest and then you will find all relevant information associated with this region.
How can I obtain the co-expression networks?
Please click "Tools" on the top navigation bar and then click "Co-expression" on the sidebar. After entering gene IDs of interest and a cutoff value of Pearsonâs correlation coefficient, an undirected graph is automatically and dynamically generated in RED. Moreover, you can export the co-expression network into local file with EXCEL or CSV format.
Can I download the data?
Yes. Please go to the Download page and you can find a link to download all genes' expression profiles.
RNA-Seq (RNA Sequencing), also called Whole Transcriptome Shotgun Sequencing (WTSS), is a technology that uses the capabilities of next-generation sequencing to reveal a snapshot of RNA presence and quantity from a genome at a given moment in time.
Sequence Read Archive
SRA (Sequence Read Archive) makes biological sequence data available to the research community to enhance reproducibility and allow for new discoveries by comparing data sets. SRA stores raw sequencing data and alignment information from high-throughput sequencing platforms. (Adapted from SRA Homepage) http://www.ncbi.nlm.nih.gov/sra
The number of fragments aligned per kilobases of the transcript per million mappable fragments from the total dataset.
Comments & Collaborations
We look forward to worldwide comments, suggestions and guidance from colleagues and peers with common research interests. We also invite the scientific community to submit their analysis results of RNA-Seq data to RED and to build collaborations in improving the functionalities of RED.
We would love to hearing from you for any questions or comments. Please find our contact information below.Email