Skip to main content

3,000 rice genomes could help feed growing world population

3,000 rice genomes could help feed growing world population
28 May 2014

A collection of 3,000 rice genomes is published this week in the open access journal GigaScience. The genome sequences, from 89 countries, will help in understanding the rich genomic diversity in rice populations and in advancing rice breeding to help feed a growing human population. The data is the result of collaboration between international teams of scientists as part of the 3,000 Rice Genomes Project.

Rice is a staple food for half the world’s population. Current estimates suggest we will need to increase global production by 25% by 2030 while using less land and water. Breeding grains of rice that are able to cope with the effects of climate change and loss of arable land is crucial.

The entire 13 terabyte dataset published in GigaScience quadruples the genomic data on rice available to scientists. It can be cited and freely mined and analysed to identify useful traits which could allow breeding of stronger varieties to keep pace with population growth and climate changes.

Rice is known for its genetic diversity and this allows lots of avenues for improvement. The publication of this dataset is just the first stage in the ambitious plans of the 3,000 Rice Genomes Project, which was launched by the BGI, International Rice Research Institute (IRRI) and Chinese Academy of Agricultural Sciences (CAAS) to explore the diversity amongst different strains by sequencing a broad spectrum of genomes within the species. Their aim is to apply this knowledge to create better strains of rice by linking up the enormous data set about the genome sequence with important data about the traits of the rice plants. The project was funded by the Bill and Melinda Gates Foundation and Chinese Ministry of Science and Technology.

The 3,000 rice strains came from 89 countries and were carefully chosen to capture varieties grown in a range of ecosystems across Asia. The enormous raw dataset will still need to be analysed and organised before it can be applied practically.

In a commentary in GigaScience the authors say: "While the applications are clear and the opportunities nearly boundless, the analytical challenges are indeed enormous."

Dr. Jun Wang, the Director of the BGI and an author on the commentary says: “I would now like to start the ‘genomics selection’ process for rice. To do this, we require a good collection of rice strains, the whole genome sequence of each, and excellent phenotype data from each. With the completion of this stage of the 3,000 rice genomes project, we have two of these components. We now need to focus on the third.”

Dr Robert Zeigler, Director General of IRRI says: “Access to 3,000 genomes of rice sequence data will tremendously accelerate the ability of breeding programs to overcome key hurdles mankind faces in the near future. [This collaborative project] will add an immense amount of knowledge to rice genetics and enable detailed analysis by the global research community to ultimately benefit the poorest farmers who grow rice under the most difficult conditions”

- ENDS -

Media Contact
Anna Perman
Media Officer
BioMed Central
T: +44 (0)20 3192 2429

Notes to Editor

1. Datanote
The 3,000 Rice Genomes Project
The 3,000 Rice Genomes Project
GigaScience 3: 7

The 3,000 Rice Genomes Project: new opportunities and challenges for future rice research
Jia-Yang Li, Jun Wang and Robert S Zeigler GigaScience 3: 8

Please name the journal in any story you write. If you are writing for the web, please link to the article. All articles are available free of charge, according to BioMed Central's open access policy.

2. GigaScience aims to revolutionize data dissemination, organization, understanding, and use. An online open-access open-data journal, we publish 'big-data' studies from the entire spectrum of life and biomedical sciences. To achieve our goals, the journal has a novel publication format: one that links standard manuscript publication with an extensive database that hosts all associated data and provides data analysis tools and cloud-computing resources.
3. BioMed Central ( is an STM (Science, Technology and Medicine) publisher which has pioneered the open access publishing model. All peer-reviewed research articles published by BioMed Central are made immediately and freely accessible online, and are licensed to allow redistribution and reuse. BioMed Central is part of Springer Science+Business Media, a leading global publisher in the STM sector