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  • Review Article
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Towards a better bowl of rice: assigning function to tens of thousands of rice genes

Nature Reviews Genetics volume 9, pages 91–101 (2008)Cite this article

Key Points

  • Rice, one of the most important food crops for humans, is the first crop plant to have its genome sequenced.

  • This article describes the availability and application of functional genomic tools for rice, including a discussion of rice whole-genome microarrays, genome tiling arrays, genome-wide gene-indexed mutant collections, gene-silencing tools, transient assay systems, integration of gene-expression profiling, insertional mutant analyses and phylogenomics.

  • With the availability of these resources, discovery of the function of the estimated 41,000 rice genes is now within reach.

  • Such discoveries have broad practical implications for understanding the biological processes of rice and other economically important grasses such as cereals and bioenergy crops.

Abstract

Rice, one of the most important food crops for humans, is the first crop plant to have its genome sequenced. Rice whole-genome microarrays, genome tiling arrays and genome-wide gene-indexed mutant collections have recently been generated. With the availability of these resources, discovering the function of the estimated 41,000 rice genes is now within reach. Such discoveries have broad practical implications for understanding the biological processes of rice and other economically important grasses such as cereals and bioenergy crops.

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Figure 1: A combination of whole-genome transcriptome and predicted-pathway analysis can be used to efficiently determine gene function.
Figure 2: Elucidation of the function of candidate genes using publicly available transcriptomics data in combination with insertion-mutant collections.

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Acknowledgements

We thank B. C. Meyers, L. Bartley, C. Dardick, L. Comai, D. Neale, J. Schroeder, J. Leach, G. L. Wang, K. Shimamoto, V. Sundaresan and R. C. Buell for comments and discussions. We also thank S. Ouyang, Y. S. Lee and P. Cao for helping to generate tables and figures. This work was supported by National Institutes of Health grants 5R01GM055962-0 United States Department of Agriculture grant 2004-63560416640 and National Science Foundation grants DBI-0313887 to P. R., the 21st Century Frontier Program CG1111 and Biogreen 21 Program to G. A, Korea Research Foundation grant 2005-C00155 to K. H. J.

Author information

Authors and Affiliations

  1. Department of Plant Pathology, 1 Shields Avenue, UC Davis, Davis, 95616, California, USA

    Ki-Hong Jung & Pamela C. Ronald

  2. Department of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Republic of Korea

    Gynheung An

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  1. Ki-Hong Jung
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  3. Pamela C. Ronald
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Correspondence to Pamela C. Ronald.

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DATABASES

Entrez Genome Project

Arabidopsis thaliana

Oryza sativa

GRAMENE

LOC_Os03g47610

LOC_Os03g52840

Udt1

NCBI gene expression omnibus

GPL4105

GPL4106

FURTHER INFORMATION

Pamela Ronald's homepage

Agilent Rice Oligo Microarray Kit

CSIRO Ac/Ds in Australia

Current TIGR rice genome pseudomolecules release

DNA Data Bank of Japan

European Molecular Biology Laboratory

Genoplante Oryza tag lines

GRAMENE pathway module

International Rice Functional Genomics Consortium

International Rice Genome Sequencing Project

Knowledge-based Oryza Molecular Biological Encyclopedia

Magnaporthe grisea–Oryza sativa Interaction Database

NCBI Gene Expression Omnibus

NCBI map viewer

NIAS Tos17 insertion mutant database

NSF Rice Oligonucleotide Array Project

Oryza Map Alignment Project

OryGenesDB, France

POSTECH Laboratory

POSTECH rice T-DNA insertion sequence database

Rice Annotation Project database

Rice Functional Genomic Express Database

RiceGE: database sources, details and summary

Rice Kinase Database

Rice Multi-Platform Microarray Search tool

Rice Mutant Database, Huazhong Agricultural University, China

Rice MPSS

Rice Tilling Database

Shanghai T-DNA Insertion Population

Taiwan Rice Insertional Mutants Database

TIGR multiexperiment viewer 4.0

TIGR Rice Genome Annotation

University of California, Davis Rice Functional Genomics Databases

Zhejiang University, China rice T-DNA tags

Glossary

Pseudomolecules

Virtual contiguous sets of clones constructed by resolving discrepancies between overlapping F-factor-based bacterial artificial chromosome (BAC) and P1-derived artificial chromosome (PAC) clones, trimming the overlapping regions at junction points in which the phase 3 BAC–PAC sequences are preferably used, and linking the unique sequences to form a contiguous sequence.

Map-based cloning

A process of identifying the gene responsible for a mutant phenotype by defining a small physical interval through linkage analysis and then systematically testing all candidate genes residing in the interval.

Allelic series

An allele is one or more alternative forms of a DNA sequence. To create an allelic series, molecular geneticists create mutations in a gene of interest and analyse the resulting phenotypes. Such allelic series are useful for determining gene function.

Cosegregation

The tendency for closely linked genes and genetic markers to segregate together.

Protoplast

A plant cell with the cell wall removed. Transient assays using protoplasts are effective for processing large quantities of genetic data coming out of high-throughput assays.

Somaclonal variation

Describes the genetic variation sometimes observed in plants that have passed through plant tissue culture. Chromosomal rearrangements are an important source of this variation.

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Jung, KH., An, G. & Ronald, P. Towards a better bowl of rice: assigning function to tens of thousands of rice genes. Nat Rev Genet 9, 91–101 (2008). https://doi.org/10.1038/nrg2286

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