SNP-Seek II: A resource for allele mining and analysis of big genomic data in Oryza sativa

Abstract

The 3000 Rice Genomes Project generated a large dataset of genomic variation to the world’s most important crop, Oryza sativa L. Using the Burrows-Wheeler Aligner (BWA) and the Genome Analysis Toolkit (GATK) variant calling on this dataset, we identified ∼40 M single-nucleotide polymorphisms (SNPs). Five reference genomes of rice representing the major variety groups were used: Nipponbare (temperate japonica), IR 64 (indica), 93–11 (indica), DJ 123 (aus), and Kasalath (aus). The results are accessible through the Rice SNP-Seek Database (http://snp-seek.irri.org) and through web services of the application programming interface (API). We incorporated legacy phenotypic and passport data for the sequenced varieties originating from the International Rice Genebank Collection Information System (IRGCIS) and gene models from several rice annotation projects. The massive genotypic data in SNP-Seek are stored using hierarchical data format 5 (HDF5) files for quick retrieval. Germplasm, phenotypic, and genomic data are stored in a relational database management system (RDBMS) using the Chado schema, allowing the use of controlled vocabularies from biological ontologies as query constraints in SNP-Seek. In this paper, we discuss the datasets stored in SNP-Seek, architecture of the database and web application, interoperability methodologies in place, and discuss a few use cases demonstrating the utility of SNP-Seek for diversity analysis and molecular breeding.

Keywords

• Allele mining
• Oryza
• SNP
• Indel
• Genotype database
• Genetic diversity