We built an integrated database, Rhododendron Plant Genome Database (RPGD), which represents the first comprehensive database for the genus Rhododendrons. It covers large amounts of omics data and a lot of useful tools. RPGD should be a comprehensive and helpful platform for all Rhododendron researchers.

Send Email
Ningyawen Liu   liuningyawen@mail.kib.ac.cn
Chengjun Zhang   zhangchengjun@mail.kib.ac.cn

Phone
 0871-65230869

A series of search tools, ‘search gene’, ‘search genome’, ‘search go’, ‘search gene family’, ‘search gene expression’, ‘search transcription factor’, ‘search chloroplast genome’ and ‘search ssr’, are designed to help researchers better utilize RPGD.

i.‘Search Gene’	RPGD provides three different way, including gene ID, Interproscan ID and gene ontology, to search genes information.
ii.‘Search GO’	RPGD provieds gene id, go accession and go term to find go information of gene.
iii.‘Search SSR’	RPGD provides ssr location, ssr type, ssr sequence and ssr size to query the ssr detail information.
iv.‘Search Family’	Users find genes with gene family names by user specified.
v.‘Search Gene Expression’	provides the gene expression profiles base on FPKM which researchers desire.
vi.‘Search Transcription Factor’	search transcription factor gene by entering transcription factor names.
vii. ‘Search Chloroplast Genome’	uses gene name and product to find the gene information on the chloroplast.

The results of the above queries are presented in tabular form, and there are a number of clickable hyperlinks in the tabular results that can be used to view the details of the corresponding data.

RPGD incorporates ViroBLAST, which is a useful and user-friendly tool for online data analysis. Users can input their sequences or upload their sequence files to perform blastn, blastp, blastx or tblastx against whole genome sequence, CDS, and peptides.

JBrowse in RPGD hosts different tracks, including genome sequence and gene annotation of R.delavayi and R.williamsianum respectively.

The upstream sequences of genes often contain a wealth of information, including regulatory elements and promoters. To facilitate researchers' search for upstream sequences of genes, we develop a useful tool--Upstream Sequence Finder. Researchers can download the upstream sequence through inputting gene ID.

In this module, users can browser the genome syntenic block or search the block you want to query. The result will return a table and a graph via AJAX and JavaScript dynamically, both of which are used to display the genome syntenic relationship.

A common task in routine analysis is to look for homologous genes. User can input gene ID to find orthologous groups in R.delavayi, R.williamsianum and other three species mentioned above. The results will display in tabular form.

RPGD not only stores gene expression profiles, but also provides this module to allow users to make an expression heatmap. User enters the gene set and selects the appropriate parameters and clicks to get the heatmap.

All the data in RPGD is available, including genome assembly (FASTA), gene prediction (GFF3), gene function annotation (TSV), complete chloroplast genome (FASTA), gene family data (TXT), orthologous groups data (TXT), simple sequence repeat data (XLS), gene expression data (XLS) and other related data can be downloaded in this module.

Meanwhile, Batch Download, is provided for users to export custom data sets or bulk download data sets from RPGD. Users can batch download multiple types of sequences (gene, cds, flanking sequence and gene expression profiles) by inputting a list of genes.

#Here is org.Rdelavayi.eg.db as an example

mkdir enrichment
cd enrichment
wget http://bioinfor.kib.ac.cn/RPGD/download/org/org.Rdelavayi.eg.db.tar.gz
tar -zxvf org.Rdelavayi.eg.db

#Access to the R environment
R

#install clusterProfiler and annotation packages
BiocManager::install('clusterProfiler')
install.packages('org.Rdelavayi.eg.db/',repos = NULL, type="source")

library(org.Rdelavayi.eg.db)
library(clusterProfiler)

enrich_go <- enrichGO(gene = genelist,
                keyType="GID",
                OrgDb = org,
                ont = "ALL",
                pAdjustMethod = "BH",
                #pvalueCutoff  = 0.01,
                qvalueCutoff  = 0.05) 

barplot(enrich_go,showCategory=20)
dotplot(enrich_go,showCategory=20)
                    

mkdir enrichment
cd enrichment

#Access to the R environment
R


library(org.Rdelavayi.eg.db)
library(clusterProfiler)


pathway2gene <- AnnotationDbi::select(org.Rdelavayi.eg.db, 
                    keys = keys(org.Rdelavayi.eg.db), 
                    columns = c("Pathway","KO")) %>%
                    na.omit() %>%
                    dplyr::select(Pathway, GID)

#load TERM2NAME
load("kegg_info.RData")


enrich_kegg <- enricher(gene, 
                TERM2GENE = pathway2gene, 
                TERM2NAME = pathway2name, 
                pvalueCutoff = 1, 
                qvalueCutoff = 1,
                pAdjustMethod = "BH",
                minGSSize = 1)

barplot(enrich_kegg,showCategory=20)
dotplot(enrich_kegg, showCategory=20)
                    

We welcome all colleagues to upload Rhododendron genome and transcriptome data to our RPGD. Please contact us!

In order to make our RPGD a better integrated platform, please contact us if you find any errors in the RPGD! We would like to thank our users for their cooperation.