Experimental

The National Institute of Agrobiological Sciences (NIAS) supports the NIAS Genebank Project for the conservation of plant, microorganism and animal genetic resources related to food and agriculture in Japan (Okuno et al., Reference Okuno, Shirata, Niino and Kawase2005). Genetic resources are classified, evaluated, multiplied and preserved in the NIAS Genebank. Genetic resources in the public domain are distributed for research and educational purposes. The database holds passport, characteristics, evaluation and storage control data (Takeya et al., Reference Takeya, Yamasaki, Uzuhashi, Aoki, Sawada, Nagai, Tomioka, Tomooka, Sato and Kawase2011).

Rice (Oryza sativa L.) is an important crop and a model plant (e.g. International Rice Genome Sequencing Project, 2005). The NIAS Genebank currently has 20,079 rice (O. sativa L.) accessions from 128 countries that are accessible. Of the conserved rice accessions, 88% have evaluation data. To enrich the genomic information available, the database now holds data on single nucleotide polymorphisms (SNPs). We have developed a system, called NIASGBsnp, to manage the SNP data (Fig. 1). Although several open rice SNP databases exist, such as the OryzaSNP Database (http://www.oryzasnp.org/) and the GRAMENE SNP Query (http://www.gramene.org/db/diversity/snp_query), the linkage between the SNP data and pertinent accession information such as phenotypic data is restrictive in most cases. The acquisition of SNP data by genotyping bulk DNA samples from each accession supports the full integration of NIASGBsnp into the Web-based plant accessions search software. Associated diseases can be matched, and the pertinent set of host and pathogen can be accessed from the NIAS Genebank.

Fig. 1

Integration of SNP data server with Web-based plant accessions search software.

The genome-wide SNPs of 140 Asian rice accessions were surveyed to reveal the sequence diversity and population structure of the cultivars (Ebana et al., Reference Ebana, Yonemaru, Fukuoka, Iwata, Kanamori, Namiki, Nagasaki and Yano2010). Bulk total DNA was extracted from young leaves of ten plants in each accession. A total of 4357 SNPs were identified by sequencing the exons and introns of anonymous rice genes on 12 chromosomes. Seven cultivar groups, including three tropical japonica and three indica, were identified by classifying the 140 accessions on the basis of these SNPs (Ebana et al., Reference Ebana, Yonemaru, Fukuoka, Iwata, Kanamori, Namiki, Nagasaki and Yano2010). From the 4357 SNPs, 768 SNPs were selected to characterize the rice accessions. We started to characterize all the rice active accessions in the NIAS Genebank. For the genotype characterization of the accessions, 25 plants per accession were used for DNA extraction to check heterogeneity in the accessions. SNPs were detected using the Golden Gate technology (Illumina, Inc., San Diego, CA, USA) with BeadsStation 500G. To date, data on the 768 markers for 301 accessions have been registered in the genetic resources database.

The NIAS Genebank already held a lot of passport, characteristics, evaluation and storage control data with regard to many accessions with SNP data. The addition of more SNP data allows users to associate genotype with phenotype.

We have improved the Genebank search system for the return of SNP data. Under ‘Plant Search (Simple Queries)’ (http://www.gene.affrc.go.jp/databases-plant_search_en.php), target accessions are selected according to search criteria such as cultivar name, origin and collection source. Users can choose ‘Accessions with SNP data only’. When such accessions are included in the search result, a link to download an XML spreadsheet file of the SNP data is presented above the results list. The spreadsheet lists the SNPs of the selected accessions and three references (Nipponbare, Kasalath and Dee-Geo-Woo-Gen). We developed the software to create an XML spreadsheet from the SNP data in the database.

Under ‘Plant Search (Evaluation Data Queries) ’ (http://www.gene.affrc.go.jp/databases-plant_search_char_en.php?type = 1), target accessions can be selected according to morphological characteristics, resistance to stresses, yields and a variety of other criteria. The option of ‘Accessions with SNP data only’ is also provided. An MS Excel spreadsheet listing all evaluation data can be downloaded from an XLS icon above the search results list. Datasets incorporating SNP, characteristics and evaluation data can be used in genomic selection or marker-assisted selection to reveal the associations between genotype and phenotype.

Detailed information on each accession can be displayed by clicking the accession ID (‘JP No.’). SNPs can be displayed as a graphical genotype in the detailed information window (Fig. 1). The presentation of SNPs as a graphical genotype supports the intuitive understanding of users (e.g. Milne et al., Reference Milne, Shaw, Stephen, Bayer, Cardle, Thomas, Flavell and Marshall2010). We developed a program to generate SNP images from the data in the database. The latest image is always available. The reference accessions are Nipponbare (japonica) and Kasalath (indica). The markers are presented in the linear order of physical position on each chromosome. When the target accession is compared with Nipponbare, homozygous and heterozygous alleles are shown in blue and red, respectively. In contrast, when the target accession is compared with Kasalath, homozygous and heterozygous alleles are shown in red and blue, respectively. Thus, overall, japonica alleles appear blue and indica alleles appear red.

The NIAS Genebank database contains microorganism genetic resources that links to the Database of Plant Diseases in Japan (http://www.gene.affrc.go.jp/databases-micro_pl_diseases_en.php) (Takeya et al., Reference Takeya, Yamasaki, Uzuhashi, Aoki, Sawada, Nagai, Tomioka, Tomooka, Sato and Kawase2011, Reference Takeya, Yamasaki, Uzuhashi, Kumagai, Sawada, Nagai, Tomioka, Sato, Aoki and Kawase2012). The most common hosts in the database are ‘rice’ and ‘rice grain’. In the window that opens when the corresponding disease name is selected, the database is linked to the plant and microorganism accessions search software via the ‘Related hosts’ and ‘Related strains’ link, respectively. The search criteria offer the new option of ‘Having related hosts only’ and ‘Having related strains only’. The NIAS Genebank can supply pathogen and plant samples for plant pathology research. As the genetic resources database has increased genomic information such as DNA sequence data of the barcode gene regions of microorganisms (Takeya et al., Reference Takeya, Yamasaki, Uzuhashi, Kumagai, Sawada, Nagai, Tomioka, Sato, Aoki and Kawase2012), pathogen-related genotypic data will support various research purposes.