What's New
05 Sep 2017
RiceVarMap v2.0 has been released! With new genomic variations and GWAS results, improved annotations of missense variations, integrated chromatin accessibility data for non-coding variations. click here!
07 Oct 2015
Genome variation data (BCF format) has been uploaded into Mega Cloud Storage, users can use this link to download the data.
27 Mar 2015
Genome variation data (BCF format) can be downloaded from Data downloads page.
14 Sep 2014
Cultivars can be searched by keywords from "Cultivar Information" page.
Navigation
Tutorial of RiceVarMap
Notes and Data Evaluation
Search for SNPs by Region
Search for SNPs Within Gene
Search for Genotype With SNP IDs
Search for SNP Information With SNP ID
Search for Polymorphic Positions Between Two Cultivars
Search for INDELs by Region
Search for INDELs Within Gene
Search for Genotype With INDEL ID
Search for INDEL Information With SNP ID
Cultivar Information
Blast
Design Primer by SNP/INDEL ID
Design Primer by Region
Haplotype Network Analysis
Welcome to Rice Variation Map, a comprehensive database of rice genomic variations.
New Version of RiceVarMap!
Database contents:
RiceVarMap provides comprehensive information of 6,551,358 single nucleotide polymorphisms (SNPs) and
1,214,627 insertions/deletions (INDELs) identified from sequencing data of 1,479 rice accessions. The SNP genotypes of all accessions were
imputed and evaluated, resulting in an overall missing data rate of 0.42% and an estimated accuracy greater than 99%. The SNP/INDEL
genotypes of all accessions are available for online queries and downloading. Users can search SNPs/INDELs by identifiers of the
SNPs/INDELs, genomic regions, gene identifiers and keywords of gene annotation. Allele frequencies within various sub-populations and the
effects of the variation that may alter the protein sequence of a gene are also listed for each SNP/INDEL. The database provides a tool to
compare any two accessions and identify the polymorphisms between them. The database also provides geographical details and phenotype images for various rice accessions. In particular, the database provides tools to construct haplotype
networks and design PCR-primers by taking into account surrounding known genomic variations.
Data source:
Currently, we collected sequencing data from two sets of rice germplasms consisting of totally 1,479 accessions of cultivated rice
(Oryza sativa L.):
The first set of germplasm consisted of 529 accessions selected to represent both the usefulness in
rice improvement and the genetic diversity in the cultivated species. We sequenced the 529 accessions using the Illumina HiSeq 2000 in
the form of 90-bp paired-end reads to generate high quality sequences of more than one gigabase per accession (>2.5x per genome, total
6.7 billion reads). These raw data is available in NCBI with BioProject accession number PRJNA171289. Actually, we sequenced 533
accessions in this project. After initial analysis, three accessions (C126, W196 and W232) were found with excessive heterozygosity and one (W190) with low
mapping rate, these four accessions were excluded in further analysis.
The second set of germplasm was 950 rice accessions sequenced by Huang et al. (2012, Nat. Genet. 44:32-39) that were downloaded from the EBI European Nucleotide Archive (accession number ERP000106 and ERP000729), which consisted of 4.6 billion 73-bp paired-end reads (~1x per genome).
Together these two sets of germplasms included both landraces and improved varieties from 73 countries.
These two sets of sequences provided approximately 2400-fold coverage of the rice genome.
Data processing:
Reads were aligned to rice reference genome (Nipponbare, MSU version 6.1) using software BWA.
SNPs/INDELs were identified using SAMtools and BCFtools. Synonymous/non-synonymous SNPs and SNPs/INDELs with large-effect changes were annotated based on
gene models of the annotation version 6.1 of Nipponbare from MSU using SNP effector. We then performed imputation using an in-house
modified k nearest neighbour algorithm. The details of data processing and evaluation is described in Notes and Data
Evaluation page.
Acknowledgements:
This work was supported by grants from the National High Technology Research and Development Program of
China (863 Program: 2012AA10A304 and 2014AA10A602), the National Natural Science Foundation of China (31100962, 31123009 and J1103510), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110146120013), and the Fundamental Research Funds for the Central Universities (2011PY068).
Comments or Questions?
For any questions please contact Hu Zhao (zhaohu@webmail.hzau.edu.cn).
Recommended browsers:
The recommended browsers are Chrome, Firefox, Safari and Internet Explorer (IE8 or later, IE7 and
earlier have poorer support and may give a lesser experience).
Citations:
Researchers who wish to use RiceVarMap are encouraged to refer to our publication or more:
Zhao, H., Yao, W., Ouyang, Y., Yang, W., Wang, G., Lian, X., Xing, Y., Chen, L. and Xie, W. (2014) RiceVarMap: a comprehensive database of rice genomic variations. Nucleic Acids Research. doi: 10.1093/nar/gku894
Zhao, H., Yao, W., Ouyang, Y., Yang, W., Wang, G., Lian, X., Xing, Y., Chen, L. and Xie, W. (2014) RiceVarMap: a comprehensive database of rice genomic variations. Nucleic Acids Research. doi: 10.1093/nar/gku894