Institute of Crop Science, NARO

Rice Genomics

Rice has played a central role in human nutrition and culture for the past 10,000 years. Rice is unique among the major cereals such as corn and wheat in that the grain is cooked and eaten directly by humans rather than being processed for flour or oil. It is estimated that world rice production must increase by 30% in the next 20 years to meet projected demands from population increase and economic development. However, world rice production has actually declined during the last ten years. Rice grown on the most productive irrigated land has achieved nearly maximum production with current strains. Environmental degradation including pollution, increase in night time temperature due to global warming, reductions in suitable arable land, water, labor, and energy-dependent fertilizer provide additional constraints. These factors make steps to maximize rice productivity especially important. Increasing yield potential and yield stability will come from a combination of biotechnology and improved conventional breeding. Both will be dependent on a high quality rice genome sequence.

In Japan, the Ministry of Agriculture, Forestry and Fisheries (MAFF) embarked on a large-scale project on rice genome analysis in 1991 via the Rice Genome Research Program (RGP) with the aim of elucidating the genetic phenomenon of rice. With the success of the first phase of the RGP, the next phase focused on rice genome sequencing through the International Rice Genome Sequencing Project (IRGSP) and functional characterization of the genome. The completion of the rice genome sequence in 2004 paved the way for a new era of research in genetics, physiology, biochemistry and other related fields. In 2005, the MAFF started anew three large-scale projects, namely, analysis of genome diversity, QTL analysis, and development of genome breeding technology aimed at maximizing the utilization of information derived from the Nipponbare genome sequence. Then in 2008, the Genomics for Agricultural Innovation Project further explored new approaches in characterization of gene function with significant impact in agricultural productivity. From 2013, the Next-generation Genome-based Project provides the platform for more innovative researches to acquire knowledge and develop technologies critical to ensuring that rice production will meet the demands in the years ahead. The following links provide an overview of major achievements in projects on rice genomics.

  • The high-quality map-based genome sequence
  • Databases and resources for rice genomics
  • Elucidating gene function and cloning of useful genes
  • Challenges in rice breeding
  • The high-quality map-based genome sequence

    The IRGSP, formally established in 1998, pooled the resources of sequencing groups in ten nations to obtain a complete finished quality sequence of the rice genome (Oryza sativa L. ssp. japonica cv. Nipponbare). Finished quality sequence is defined as follows: there is less than one error in 10,000 nucleotides, ambiguities are resolved, and all state-of-the-art attempts have been made to close gaps. The IRGSP released a high quality map-based draft sequence in December 2002. Three completely sequenced chromosomes have been published as well as two completely sequenced centromeres. As the IRGSP subscribed to an immediate release policy, high quality map-based sequence has been in the public domain for some time. This has permitted rice geneticists to identify numerous genes underlying traits and revealed very large and previously unknown segmental duplications that comprise 60% of the genome.

    The high-quality map based genome sequence of rice was completed in 1984. Annotation of the sequence revealed more than 32,000 genes in the 390 Mb sequence. The NIAS/STAFF-Institute collaboration in Japan contributed to the sequencing of 6 chromosomes corresponding to more than half of the entire genome. The results have been hailed by the international community as a major achievement that will contribute to crop improvement in the 21st century. The 10th anniversary of the completion of the rice genome sequence was celebrated with the theme The Rice Genome at Ten: Helping to sove the 9 billion people question.


    Databases and resources for rice genomics

    We have developed databases, bioinformatics tools and genomics resources to complement our efforts in structural and functional characterization of the rice genome, to provide fundamental information for understanding the biology of rice and other cereal crops, and to facilitate the development of novel strategies for crop improvement. Central to these genomics efforts is the Rice Annotation Project Database (RAP-DB) providing comprehensive information on the rice genome including functional annotation for the gene models. A wide range of resources encompassing genome sequence data, genetic maps, molecular markers, insertional mutations, gene expression profiles, proteome, and the integration of these genomics data have been developed providing various types of information that can be used for complete understanding of rice biology. Rice has a large base of genetic resources and knowledge of the sequence of specific genes will pave the way in maximizing 42,000 accessions representing natural genetic variation and germplasm of the rice species in the NIAS Genebank. We also provide access to genomics resources in the form of cDNA clones, DNA markers, cloned genomic DNAs in bacterial artificial chromosomes (BAC) and P1-artificial chromosomes (PAC).


    Elucidating gene function and cloning of useful genes

    The high quality map-based rice genome sequence is the ultimate tool for discovering all the rice genes and establishing the functionality particularly for genes involved in many agronomic traits. Gene identification and functional validation has been the focus of rice genomics since the sequence has been fully elucidated. The sequence data has become the blueprint for charting the structure of many genes, developing appropriate markers, isolating the genes, and eventually, incorporating the genes into many rice cultivars. Our efforts in rice functional genomics in collaboration with researchers from other research institutes and universities have led to identification of a wide array of genes for desirable traits and functions.


    Challenges in rice breeding

    The rice genome sequence is indispensable in breeding for improved and novel cultivars. With the completion of the rice genome sequence and development of genomics tools, research on agronomically important genes have greatly accelerated. Marker assisted selection has greatly promoted analysis of genes.

    Towards improvement of Japanese rice cultivars

    Rice blast disease caused by fungal infection is one of the most destructive disease that has caused considerable damage in rice production all over Japan. A gene that controls strong resistance to rice blast (pi21) has been identified in cultivar Okabo. However introducing the gene in commercial cultivars induces a poor eating quality in the recipient cultivar. Using the genome information, the positional relationship ofpi21 and eating quality in the chromosome has been clarified which led to the successful development of a rice strain with strong blast resistance and good eating quality.

    Towards improvement of rice cultivars around the world

    The gene which controls deep rooting in rice was successfully isolated by map-based cloning. When the gene (DRO1) was introduced in shallow rooting rice cultivar, the root system developed extensively penetrating deeply into the soil thereby allowing the plants to absorb more water. It is expected that utilization of this gene in breeding of various crops will lead to the development of cultivars with strong resistance against drought stress particularly in many Asian and African countries usually affected by severe drought during the dry season.

    Towards development of innovative strategies for crop improvement

    The expression profile of all the genes during various stages of growth and development under natural field conditions have been clarified by large-scale microarray analysis. The expressional dynamics was then analysed by statistical modeling that takes into account the age of the plant, the circadian rhythm, and environmental stimuli such as temperature, solar radiation etc. This strategy allows the prediction of how a particular genotype will behave under a pre-determined condition.

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