Rice is the major food for half of the world population. The nutrition component in rice is critical for improvement of people’s health. Vitamin E serves as important antioxidant by quenching the free radical intermediates and thus protects the cell membrane. Because of the high nutritional value and the benefits of vitamin E in human health, increasing the tocochromanol content of major agricultural crops has long been in the focus of breeding programs and genetic engineering approaches. The key genes involved in tocopherol biosynthesis have been elucidated in Arabidopsis and other model organisms. Quantitative trait locus (QTL) study performed in Arabidopsis suggested that some of these key genes and a few additional loci contribute to natural tocopherol variations. Identifying such genetic variations in rice, enrich our understanding of the genetic mechanisms controlling tocopherol variation, which can be directly applied to rice breeding programs. In this study, we used genome-wide association mapping with high-resolution density SNPs of rice core set to identify natural allelic variations, which contribute to tocopherol increase in rice

As one of the most important crop, rice is not only a staple food of half world’s population but a wonderful model plant, which has been leading the evolution and functional genomics study. The next-generation sequencing technology are expediting rice genomic study, by providing a simple but powerful way. In this study, we re-sequenced a core collection of 137 rice accessions from all over the world along with 158 Korean breeding varieties. Finally, 6.3G uniquely mapped reads were obtained, and about 10 million SNPs and ~1.2 million InDels were identified with average sequencing depth of 7.5X. These will help us to maximize our germplasm utilization and assists all the deep research in population dynamics and functional studies. Here, we’d like to show the approaches applied to resequencing data mining and on-going activities.

Preharvest sprouting resistance (PHS) causes the reduction of grain yield and also affects the quality of grains, resulting significant economic losses. PHS and its related traits were evaluated and observed in wide range among the 137 diverse rice accessions. To mine the associated signals for PHS resistance, genome wide association study (GWAS) was performed using phenotype data and whole genome resequencing data of 137 diverse rice accessions. This study not only could detect the previously identified dormancy and PHS associated genes but also explore the new candidate genes associated with the PHS and related traits. An example of them is seed dormancy 4 (Sdr4) gene which was found to be associated with germination % at day 14 (D14). This study provided the potential associated candidate genes which might be very useful to improve the PHS resistance in future rice breeding.