Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

The rice genome revolution: from an ancient grain to Green Super Rice

Nature Reviews Genetics volume 19, pages 505–517 (2018)Cite this article

Subjects

Abstract

Rice is a staple crop for half the world’s population, which is expected to grow by 3 billion over the next 30 years. It is also a key model for studying the genomics of agroecosystems. This dual role places rice at the centre of an enormous challenge facing agriculture: how to leverage genomics to produce enough food to feed an expanding global population. Scientists worldwide are investigating the genetic variation among domesticated rice species and their wild relatives with the aim of identifying loci that can be exploited to breed a new generation of sustainable crops known as Green Super Rice.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Genomics-based strategies for developing Green Super Rice.
Fig. 2: Phylogeny and distribution of the Oryza genus.
Fig. 3: Domestication of Oryza sativa and Oryza glaberrima.
Fig. 4: High-throughput phenotyping platforms.
Fig. 5: Characterization of the 3K rice genomes through the SNP-Seek database.
Fig. 6: Many rice genes have been characterized and classified by function.
Fig. 7: A genomic breeding scheme for precisely introducing a gene into the background of an elite cultivar.

Similar content being viewed by others

References

  1. United Nations Department of Economic and Social Affairs/Population Division. World population prospects: key findings and advance tables. ESA https://esa.un.org/unpd/wpp/publications/Files/WPP2017_KeyFindings.pdf (2017).

  2. Zhang, Q. Strategies for developing green super rice. Proc. Natl Acad. Sci. USA 104, 16402–16409 (2007). This paper introduces the concept of GSR.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Matsumoto, T. et al. The map-based sequence of the rice genome. Nature 436, 793–800 (2005). This paper describes the finished sequence of the rice genome, the first crop genome to be sequenced.

    Article  CAS  Google Scholar 

  4. Yang, C., Yang, Z., Hu, J., He, G. & Shu, L. Study on the brown planthopper resistance in introgressive lines from wild rice. Acta Phytophylac. Sin. 26, 197–202 (1999).

    Google Scholar 

  5. Buckler, E. S., Thornsberry, J. M. & Kresovich, S. Molecular diversity, structure and domestication of grasses. Genet. Res. 77, 213–218 (2001).

    Article  PubMed  CAS  Google Scholar 

  6. Caicedo, A. L. et al. Genome-wide patterns of nucleotide polymorphism in domesticated rice. PLoS Genet. 3, 1745–1756 (2007).

    Article  PubMed  CAS  Google Scholar 

  7. Civáň, P., Craig, H., Cox, C. J. & Brown, T. A. Three geographically separate domestications of Asian rice. Nat. Plants 1, 15164 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Molina, J. et al. Molecular evidence for a single evolutionary origin of domesticated rice. Proc. Natl Acad. Sci. USA 108, 8351–8356 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Huang, X. et al. A map of rice genome variation reveals the origin of cultivated rice. Nature 490, 497–501 (2012).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  10. Choi, J. Y. et al. The rice paradox: multiple origins but single domestication in Asian rice. Mol. Biol. Evol. 34, 969–979 (2017). This study uses multiple reference genomes and demographic models to support a single domestication event for japonica rice followed by introgression to produce indica and aus varieties.

    PubMed  PubMed Central  Google Scholar 

  11. Li, C., Zhou, A. & Sang, T. Rice domestication by reducing shattering. Science 311, 1936–1939 (2006).

    Article  PubMed  CAS  Google Scholar 

  12. Stevens, C. J. et al. Between China and South Asia: a middle Asian corridor of crop dispersal and agricultural innovation in the Bronze Age. Holocene 26, 1541–1555 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Sweeney, M. T. et al. Global dissemination of a single mutation conferring white pericarp in rice. PLoS Genet. 3, e133 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Tan, L. et al. Control of a key transition from prostrate to erect growth in rice domestication. Nat. Genet. 40, 1360–1364 (2008).

    Article  PubMed  CAS  Google Scholar 

  15. Wang, M. et al. The genome sequence of African rice (Oryza glaberrima) and evidence for independent domestication. Nat. Genet. 46, 982–988 (2014). This paper reports the first available reference genome for African rice and provides evidence for convergent yet independent selection of a common set of genes during two geographically and culturally distinct domestication processes.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  16. Meyer, R. S. et al. Domestication history and geographical adaptation inferred from a SNP map of African rice. Nat. Genet. 48, 1083–1088 (2016).

    Article  PubMed  CAS  Google Scholar 

  17. Olsen, K. M. & Purugganan, M. D. Molecular evidence on the origin and evolution of glutinous rice. Genetics 162, 941–950 (2002).

    PubMed  PubMed Central  CAS  Google Scholar 

  18. Olsen, K. M. et al. Selection under domestication: evidence for a sweep in the rice waxy genomic region. Genetics 173, 975–983 (2006). This study provides an early demonstration of the genomic footprint of selection associated with a culturally significant trait.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Tan, Y. F. et al. The three important traits for cooking and eating quality of rice grains are controlled by a single locus in an elite rice hybrid, Shanyou 63. Theor. Appl. Genet. 99, 642–648 (1999).

    Article  PubMed  CAS  Google Scholar 

  20. Yang, T. et al. The role of a potassium transporter OsHAK5 in potassium acquisition and transport from roots to shoots in rice at low potassium supply levels. Plant Physiol. 166, 945–959 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Ruan, S. L. et al. Proteomic identification of OsCYP2, a rice cyclophilin that confers salt tolerance in rice (Oryza sativa L.) seedlings when overexpressed. BMC Plant Biol. 11, 34 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Xie, W. et al. Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection. Proc. Natl Acad. Sci. USA 112, E5411–5419 (2015). This study identifies two major groups of indica rice, based on breeding signatures, that resulted from independent breeding activities in different regions of Asia.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  23. Wang, J. et al. Artificial selection of Gn1a plays an important role in improving rice yields across different ecological regions. Rice 8, 37 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Spielmeyer, W., Ellis, M. H. & Chandler, P. M. Semidwarf (sd-1), “green revolution” rice, contains a defective gibberellin 20-oxidase gene. Proc. Natl Acad. Sci. USA 99, 9043–9048 (2002).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  25. Hoque, M. S., Masle, J., Udvardi, M. K., Ryan, P. R. & Upadhyaya, N. M. Over-expression of the rice OsAMT1-1 gene increases ammonium uptake and content, but impairs growth and development of plants under high ammonium nutrition. Funct. Plant Biol. 33, 153–163 (2006).

    Article  CAS  PubMed  Google Scholar 

  26. Khush, G. S., Mackill, D. J. & Sidhu, G. S. in Bacterial Blight of Rice (eds Banta, S. J., Cervantes, E. & Mew, T. W.) 207–217 (International Rice Research Institute, 1989).

  27. Sun, X. et al. Xa26, a gene conferring resistance to Xanthomonas oryzae pv. oryzae in rice, encodes an LRR receptor kinase-like protein. Plant J. 37, 517–527 (2004).

    Article  PubMed  CAS  Google Scholar 

  28. Kazama, T. & Toriyama, K. A pentatricopeptide repeat-containing gene that promotes the processing of aberrant atp6 RNA of cytoplasmic male-sterile rice. FEBS Lett. 544, 99–102 (2003).

    Article  PubMed  CAS  Google Scholar 

  29. The 3000 Rice Genomes Project. The 3,000 rice genomes project. GigaScience 3, 7 (2014).

    Article  CAS  Google Scholar 

  30. Wang, W. et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature 557, 43–49 (2018). This paper describes pan-genome analyses that discovered, of 29 million SNPs, 2.4 million short indels, over 90,000 structural variants and more than 10,000 novel genes, all of which contribute to population variation in Asian cultivated rice. Additionally, detected patterns of introgression at several domestication genes support multiple independent domestications in Asian rice.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  31. Zhang, J. et al. Extensive sequence divergence between the reference genomes of two elite indica rice varieties Zhenshan 97 and Minghui 63. Proc. Natl Acad. Sci. USA 113, E5163–E5171 (2016).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  32. Du, H. et al. Sequencing and de novo assembly of a near complete indica rice genome. Nat. Commun. 8, 15324 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Goff, S. A. et al. A draft sequence of the rice genome (Oryza sativa L. ssp. japonica). Science 296, 92–100 (2002).

    Article  PubMed  CAS  Google Scholar 

  34. Yu, J. et al. A draft sequence of the rice genome (Oryza sativa L. ssp indica). Science 296, 79–92 (2002).

    Article  PubMed  CAS  Google Scholar 

  35. Kawahara, Y. et al. Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data. Rice 6, 4 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Yamamoto, T. et al. Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms. BMC Genomics 11, 267 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Takagi, H. et al. MutMap-Gap: whole-genome resequencing of mutant F2 progeny bulk combined with de novo assembly of gap regions identifies the rice blast resistance gene Pii. New Phytol. 200, 276–283 (2013).

    Article  PubMed  CAS  Google Scholar 

  38. Lu, L. et al. Tracking the genome-wide outcomes of a transposable element burst over decades of amplification. Proc. Natl Acad. Sci. USA 114, E10550–E10559 (2017).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  39. Yu, J. et al. The Genomes of Oryza sativa: a history of duplications. PLoS Biol. 3, e38 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Reddy, M. M. & Ulaganathan, K. Draft genome sequence of Oryza sativa elite indica cultivar RP Bio-226. Front. Plant Sci. 6, 896 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Mahesh, H. B. et al. Indica rice genome assembly, annotation and mining of blast disease resistance genes. BMC Genomics 17, 242 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Stein, J. C. et al. Genomes of 13 domesticated and wild rice relatives highlight genetic conservation, turnover and innovation across the genus Oryza. Nat. Genet. 50, 285–296 (2018).

    Article  PubMed  CAS  Google Scholar 

  43. Zhang, Y. et al. Genome and comparative transcriptomics of African wild rice Oryza longistaminata provide insights into molecular mechanism of rhizomatousness and self-incompatibility. Mol. Plant 8, 1683–1688 (2015).

    Article  PubMed  CAS  Google Scholar 

  44. Chen, J. F. et al. Whole-genome sequencing of Oryza brachyantha reveals mechanisms underlying Oryza genome evolution. Nat. Commun. 4, 1595 (2013).

    Article  PubMed  CAS  Google Scholar 

  45. Jacquemin, J., Bhatia, D., Singh, K. & Wing, R. A. The international Oryza map alignment project: development of a genus-wide comparative genomics platform to help solve the 9 billion-people question. Curr. Opin. Plant Biol. 16, 147–156 (2013).

    Article  PubMed  CAS  Google Scholar 

  46. Yang, W. et al. Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice. Nat. Commun. 5, 5087 (2014). This work reports a high-throughput phenotyping facility and demonstrates that the data can be used for GWAS of agronomic traits.

    Article  PubMed  CAS  Google Scholar 

  47. Tanger, P. et al. Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. Sci. Rep. 7, 42839 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Vadez, V. et al. LeasyScan: a novel concept combining 3D imaging and lysimetry for high-throughput phenotyping of traits controlling plant water budget. J. Exp. Bot. 66, 5581–5593 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Shi, Y. et al. Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PLoS ONE 11, e0159781 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Courtois, B. et al. Genome-wide association mapping of root traits in a japonica rice panel. PLoS ONE 8, e78037 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Rebolledo, M. C. et al. Phenotypic and genetic dissection of component traits for early vigour in rice using plant growth modelling, sugar content analyses and association mapping. J. Exp. Bot. 66, 5555–5566 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Qiu, X. et al. Genome-wide association study of grain appearance and milling quality in a worldwide collection of indica rice germplasm. PLoS ONE 10, e0145577 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Rebolledo, M. C. et al. Combining image analysis, genome wide association studies and different field trials to reveal stable genetic regions related to panicle architecture and the number of spikelets per panicle in rice. Front. Plant Sci. 7, 1384 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Kikuchi, S. et al. Genome-wide association mapping for phenotypic plasticity in rice. Plant Cell Environ. 40, 1565–1575 (2017).

    Article  PubMed  CAS  Google Scholar 

  55. Al-Tamimi, N. et al. Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping. Nat. Commun. 7, 13342 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Sakai, H. et al. Rice annotation project database (RAP-DB): an integrative and interactive database for rice genomics. Plant Cell Physiol. 54, e6 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Zhang, J. et al. Building two indica rice reference genomes with PacBio long-read and Illumina paired-end sequencing data. Sci. Data 3, 160076 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Song, J. M. et al. Rice information gateway: a comprehensive bioinformatics platform for Indica rice genomes. Mol. Plant 11, 505–507 (2018).

    Article  PubMed  CAS  Google Scholar 

  59. McCouch, S. R. et al. Open access resources for genome-wide association mapping in rice. Nat. Commun. 7, 10532 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Mansueto, L. et al. Rice SNP-seek database update: new SNPs, indels, and queries. Nucleic Acids Res. 45, D1075–D1081 (2017).

    Article  PubMed  CAS  Google Scholar 

  61. Yao, W., Li, G., Yu, Y. & Ouyang, Y. funRiceGenes dataset for comprehensive understanding and application of rice functional genes. Gigascience 7, 1–9 (2018).

    Article  PubMed  Google Scholar 

  62. Zhang, H. T. & Wang, S. P. Progress in functional genomic studies of rice disease resistance. Chinese Bulletin of Life Sciences. 28, 1189–1199 (2016).

    Google Scholar 

  63. Deng, Y. et al. Epigenetic regulation of antagonistic receptors confers rice blast resistance with yield balance. Science 355, 962–965 (2017).

    Article  PubMed  CAS  Google Scholar 

  64. Li, W. et al. A natural allele of a transcription factor in rice confers broad-spectrum blast resistance. Cell 170, 114–126 (2017).

    Article  PubMed  CAS  Google Scholar 

  65. Hu, K. et al. Improvement of multiple agronomic traits by a disease resistance gene via cell wall reinforcement. Nat. Plants 3, 17009 (2017).

    Article  PubMed  CAS  Google Scholar 

  66. Zhao, Y. et al. Allelic diversity in an NLR gene BPH9 enables rice to combat planthopper variation. Proc. Natl Acad. Sci. USA 8, 12850–12855 (2016).

    Article  CAS  Google Scholar 

  67. Hu, J., Xiao, C. & He, Y. Recent progress on the genetics and molecular breeding of brown planthopper resistance in rice. Rice 9, 30 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Ke, Y., Deng, H. & Wang, S. Advances in understanding broad-spectrum resistance to pathogens in rice. Plant J. 90, 738–748 (2017).

    Article  PubMed  CAS  Google Scholar 

  69. Lin, J. Y. & Shen, M. Rice production constraints in China (CAB International, 1996).

  70. Hu, H. & Xiong, L. Genetic engineering and breeding of drought-resistant crops. Annu. Rev. Plant Biol. 65, 715–741 (2014).

    Article  PubMed  CAS  Google Scholar 

  71. Uga, Y. et al. Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nat. Genet. 45, 1097–1102 (2013).

    Article  PubMed  CAS  Google Scholar 

  72. Xu, K. et al. Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442, 705–708 (2006). This paper describes the cloning and characterization of the SUB1A gene. This gene has since been introgressed into Asian mega-varieties to help withstand submergence flooding of up to 2 weeks.

    Article  PubMed  CAS  Google Scholar 

  73. Hattori, Y. et al. The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature 460, 1026–1030 (2009).

    Article  PubMed  CAS  Google Scholar 

  74. Fujino, K. et al. Molecular identification of a major quantitative trait locus, qLTG3-1, controlling low-temperature germinability in rice. Proc. Natl Acad. Sci. USA 105, 12623–12628 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Lu, G. et al. Rice LTG1 is involved in adaptive growth and fitness under low ambient temperature. Plant J. 78, 468–480 (2014).

    Article  PubMed  CAS  Google Scholar 

  76. Ma, Y. et al. COLD1 confers chilling tolerance in rice. Cell 160, 1209–1221 (2015).

    Article  PubMed  CAS  Google Scholar 

  77. Li, X. M. et al. Natural alleles of a proteasome α2 subunit gene contribute to thermotolerance and adaptation of African rice. Nat. Genet. 47, 827–833 (2015).

    Article  PubMed  CAS  Google Scholar 

  78. Liu, J. et al. The RING finger ubiquitin E3 ligase OsHTAS enhances heat tolerance by promoting H2O2-induced stomatal closure in rice. Plant Physiol. 170, 429–443 (2016).

    Article  PubMed  CAS  Google Scholar 

  79. Ren, Z. H. et al. A rice quantitative trait locus for salt tolerance encodes a sodium transporter. Nat. Genet. 37, 1141–1146 (2005).

    Article  PubMed  CAS  Google Scholar 

  80. Hu, B. et al. Variation in NRT1.1B contributes to nitrate-use divergence between rice subspecies. Nat. Genet. 47, 834–838 (2015).

    Article  PubMed  CAS  Google Scholar 

  81. Sun, H. et al. Heterotrimeric G proteins regulate nitrogen-use efficiency in rice. Nat. Genet. 46, 652–656 (2014).

    Article  PubMed  CAS  Google Scholar 

  82. Fan, X. et al. Overexpression of a pH-sensitive nitrate transporter in rice increases crop yields. Proc. Natl Acad. Sci. USA 113, 7118–7123 (2016).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  83. Gamuyao, R. et al. The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature 488, 535–539 (2012).

    Article  PubMed  CAS  Google Scholar 

  84. Yamaji, N. et al. Reducing phosphorus accumulation in rice grains with an impaired transporter in the node. Nature 541, 92–95 (2017).

    Article  PubMed  CAS  Google Scholar 

  85. Xing, Y. & Zhang, Q. Genetic and molecular bases of rice yield. Annu. Rev. Plant Biol. 61, 421–442 (2010).

    Article  PubMed  CAS  Google Scholar 

  86. Wang, Y. & Li, J. Molecular basis of plant architecture. Annu. Rev. Plant Biol. 59, 253–279 (2008).

    Article  PubMed  CAS  Google Scholar 

  87. Xue, W. et al. Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat. Genet. 40, 761–767 (2008).

    Article  PubMed  CAS  Google Scholar 

  88. Wei, X. et al. DTH8 suppresses flowering in rice, influencing plant height and yield potential simultaneously. Plant Physiol. 153, 1747–1758 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Yan, W.-H. et al. A major QTL. Ghd8, plays pleiotropic roles in regulating grain productivity, plant height, and heading date in rice. Mol. Plant 4, 319–330 (2011).

    Article  PubMed  CAS  Google Scholar 

  90. Yan, W. et al. Natural variation in Ghd7.1 plays an important role in grain yield and adaptation in rice. Cell Res. 23, 969–971 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  91. Zhang, Z.-H. et al. Pleiotropism of the photoperiod-insensitive allele of Hd1 on heading date, plant height and yield traits in rice. PLoS ONE 7, e52538 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  92. Zhang, J. et al. Combinations of the Ghd7, Ghd8 and Hd1 genes largely define the ecogeographical adaptation and yield potential of cultivated rice. New Phytol. 208, 1056–1066 (2015).

    Article  PubMed  CAS  Google Scholar 

  93. Bai, X. et al. Duplication of an upstream silencer of FZP increases grain yield in rice. Nat. Plants 3, 885–893 (2017).

    Article  PubMed  CAS  Google Scholar 

  94. Zhang, L. et al. A natural tandem array alleviates epigenetic repression of IPA1 and leads to superior yielding rice. Nat. Commun. 8, 14789 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  95. Zhang, D. & Yuan, Z. Molecular control of grass inflorescence development. Annu. Rev. Plant Biol. 65, 553–578 (2014).

    Article  PubMed  CAS  Google Scholar 

  96. Chen, J. et al. A triallelic system of S5 is a major regulator of the reproductive barrier and compatibility of indica-japonica hybrids in rice. Proc. Natl Acad. Sci. USA 105, 11436–11441 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Long, Y. et al. Hybrid male sterility in rice controlled by interaction between divergent alleles of two adjacent genes. Proc. Natl Acad. Sci. USA 105, 18871–18876 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  98. Mizuta, Y., Harushima, Y. & Kurata, N. Rice pollen hybrid incompatibility caused by reciprocal gene loss of duplicated genes. Proc. Natl Acad. Sci. USA 107, 20417–20422 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  99. Yang, J. et al. A killer-protector system regulates both hybrid sterility and segregation distortion in rice. Science 337, 1336–1340 (2012). This study characterizes the S5 locus for reproductive isolation between indica and japonica subspecies, which consists of three adjacent genes forming a killer–protector system. This gene is widely used in intersubspecific hybrid rice breeding.

    Article  PubMed  CAS  Google Scholar 

  100. Yu, Y., Wing, R. A. & Li, J. in Genetics and Genomics of Rice (eds Zhang, Q. & Wing, R. A.) 237–254 (Springer-Verlag, 2013).

  101. Gao, Z. et al. Map-based cloning of the ALK gene, which controls the gelatinization temperature of rice. Sci. China C. Life Sci. 46, 661–668 (2003).

    Article  PubMed  CAS  Google Scholar 

  102. Li, Y. et al. Chalk5 encodes a vacuolar H(+)-translocating pyrophosphatase influencing grain chalkiness in rice. Nat. Genet. 46, 398–404 (2014).

    Article  PubMed  CAS  Google Scholar 

  103. Fan, C. et al. GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor. Appl. Genet. 112, 1164–1171 (2006).

    Article  PubMed  CAS  Google Scholar 

  104. Weng, J. et al. Isolation and initial characterization of GW5, a major QTL associated with rice grain width and weight. Cell Res. 18, 1199–1209 (2008).

    Article  PubMed  CAS  Google Scholar 

  105. Shomura, A. et al. Deletion in a gene associated with grain size increased yields during rice domestication. Nat. Genet. 40, 1023–1028 (2008).

    Article  PubMed  CAS  Google Scholar 

  106. Ye, X. et al. Engineering the provitamin A (beta-carotene) biosynthetic pathway into (carotenoid-free) rice endosperm. Science 287, 303–305 (2000).

    Article  PubMed  CAS  Google Scholar 

  107. Zhu, Q. et al. Development of “Purple Endosperm Rice” by engineering anthocyanin biosynthesis in the endosperm with a high-efficiency transgene stacking system. Mol. Plant 10, 918–929 (2017).

    Article  PubMed  CAS  Google Scholar 

  108. Yu, H., Xie, W., Li, J., Zhou, F. & Zhang, Q. A whole-genome SNP array (RICE6K) for genomic breeding in rice. Plant Biotechnol. J. 12, 28–37 (2014).

    Article  PubMed  CAS  Google Scholar 

  109. Chen, H. et al. A high-density SNP genotyping array for rice biology and molecular breeding. Mol. Plant 7, 541–553 (2014).

    Article  PubMed  CAS  Google Scholar 

  110. Singh, N. et al. Single-copy gene based 50 K SNP chip for genetic studies and molecular breeding in rice. Sci. Rep. 5, 11600 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Ge, S., Sang, T., Lu, B. R. & Hong, D. Y. Phylogeny of rice genomes with emphasis on origins of allotetraploid species. Proc. Natl Acad. Sci. USA 96, 14400–14405 (1999).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  112. Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  113. Purugganan, M. D. An evolutionary genomic tale of two rice species. Nat. Genet. 46, 931–932 (2014).

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

R.A.W. was supported by the Bud Antle Endowed Chair of Excellence in Agriculture and Life Sciences, the AXA Research Fund and NIFA-HATCH ARZT-1360510-H25-230. M.D.P. was supported by grants from the US National Science Foundation Plant Genome Research Program, the Zegar Family Foundation and the New York University Abu Dhabi Research Institute. Q.Z. was supported by grants from the National 863 Program 2104AA10A604, the National Key Research and Development Program 2016YFD0100903, the Earmarked Fund for the China Agriculture Research System of China (CARS-01-05) and the Bill and Melinda Gates Foundation. The authors also thank K. McNally and S. Klassen for critically reading the manuscript prior to publication.

Author information

Authors and Affiliations

  1. University of Arizona, Tucson, AZ, USA

    Rod A. Wing

  2. International Rice Research Institute, Los Baños, Philippines

    Rod A. Wing

  3. New York University, New York, NY, USA

    Michael D. Purugganan

  4. New York University Abu Dhabi, Abu Dhabi, United Arab Emirates

    Michael D. Purugganan

  5. Huazhong Agricultural University, Wuhan, China

    Qifa Zhang

Authors
  1. Rod A. Wing
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael D. Purugganan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qifa Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to all aspects of writing this Review.

Corresponding authors

Correspondence to Rod A. Wing or Qifa Zhang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Reviewer information

Nature Reviews Genetics thanks Guo-Liang Wang, Jean Christophe Glaszmann, and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

Related links

Africa Rice: http://www.africarice.org/warda/genebank.asp

Consultative Group and International Agricultural Research (CGIAR): https://www.cgiar.org/

Ensemble Plants: http://plants.ensembl.org/index.html

funRiceGenes: http://funricegenes.ncpgr.cn/

GenBank: https://www.ncbi.nlm.nih.gov/assembly/?term=Oryza

Global Rice Phenotyping Network: http://ricephenonetwork.irri.org/

Gramene: http://oge.gramene.org/genome_browser/index.html

International Center for Tropical Agriculture (CIAT): http://ciat.cgiar.org/

International Rice Genebank: http://irri.org/our-work/research/genetic-diversity/international-rice-genebank

International Rice Informatics Consortia (IRIC): http://iric.irri.org/

International Rice Research Institute (IRRI): www.irri.org

Rice Annotation Project (RAP): http://rapdb.dna.affrc.go.jp/

Michigan State University DB (MSU-DB): http://rice.plantbiology.msu.edu/

Oryzabase: https://shigen.nig.ac.jp/rice/oryzabase/

Rice Information GateWay (RIGW): http://rice.hzau.edu.cn/cgi-bin/rice/download_ext

R498 at MBKBASE: www.mbkbase.org/R498

Rice Diversity database: http://www.ricediversity.org/data/index.cfm

SNP-Seek: http://snp-seek.irri.org/

TERRA-REF Field Scanalyzer in Arizona: www.terraref.org

Supplementary information

41576_2018_24_MOESM1_ESM.xlsx

Supplementary Table 1 | List and assembly statistics of currently available Oryza genome assemblies deposited in NCBI’s GeneBank (accessed 4/29/2018).

Glossary

Lodging resistance

The ability of plants to withstand high-velocity winds, such as those from annual typhoons in the tropics. Typically, lodging resistance occurs by breeding for stiffer stalks, short stature or both.

Heterosis

Also known as hybrid vigour. A phenomenon whereby the hybrid produced by crossing two genetically distinct breeding lines (normally inbred) agronomically outperforms each of its parents (for example, in terms of higher yield and faster growth).

Genomic breeding

Approaches that use the data, knowledge, resources, genes and technologies generated by genomic research to enhance breeding programmes.

Genome types

The Oryza genus is composed of ~27 extant species that harbour 11 distinct genome types (GTs), 6 of which are diploid (n = 12; GTs: AA, BB, CC, EE, FF and GG) and 5 of which are polyploid (n = 24; GTs: BBCC, CCDD, HHJJ, HHKK and KKLL). These GTs were defined based on cytogenetics (that is, chromosome number, size and shape), fluorescence in situ hybridization (FISH) and genetic hybridization.

Introgression

The transfer of genes and genomic segments from one species or population to another through hybridization.

Field phenotyping

The use of state-of-the-art sensor and camera systems, mounted on tractors, gantries and drones, to measure plant phenotypic traits (such as height, leaf angle, 1,000-grain weight, disease pressure and canopy temperature, among others) over the course of a growing season.

Reference genomes

Also referred to as a reference sequence (RefSeq). A genome assembly that is used to represent the full genome sequence of a given organism. Ideally, a RefSeq will be gap-free and have zero sequence errors. However, genome assemblies can potentially be missing up to 50% of the full genome sequence, primarily owing to the sequencing technology used (for example, short read sequencing) and the assembly tools available.

Green Revolution

The substantial increase in grain production that began in the late 1960s and early 1970s. It was a result of widespread adoption of high-yielding wheat and rice varieties bred to incorporate semi-dwarf genes and a more systematic use of nitrogen fertilizers and pesticides.

Hybridization

The process or outcome of performing genetic crosses between individuals from distinct species or highly divergent populations.

Selective sweep

A genomic region that appears to be under natural or artificial selection. In the context of this Review, we consider it to be a region of the genome including and surrounding a domestication trait (for example, yield or grain shattering).

Abiotic stress

A stress considered to be of non-biological origin, such as heat, salt, drought, nutrient, light and dark, among others.

Genome-wide association studies

(GWAS). A mapping approach that relies on an observed statistical correlation between individual genomic variants (such as single nucleotide polymorphisms (SNPs)) and specific phenotypes in a natural population.

Artificial selection

Selection for desirable traits that is consciously and deliberately carried out by humans.

Resequencing

A technique used to sample an individual genome without the need to generate a full genome sequence. Resequencing data typically consists of short (250 bp) sequence reads at low (0.1–10-fold) genome coverage that are mapped by sequence complementarity to a reference sequence (RefSeq) to detect genetic variation (such as single nucleotide polymorphisms (SNPs) and indels) between the resequenced individual and the RefSeq.

Quantitative trait loci

(QTL). Genetic loci that contribute (positively or negatively) to non-discrete traits, such as yield, grain quality, water and heat stress.

Xian

Also known as indica, a major group of Asian cultivated rice that is widely grown in tropical and subtropical regions of Asia and is partially reproductively isolated from the geng rice.

Geng

Also known as japonica, a major group of Asian cultivated rice that is widely grown in temperate regions of Asia and other areas and is partially reproductively isolated from xian rice.

Living voucher specimens

Single-plant accessions selected to be representative of a particular species. In the case of most wild Oryza species, vouchers can be clonally propagated indefinitely.

Biotic stress

A stress considered to be of biological origin, such as plant pathogens (bacteria, fungi and viruses) and animal pests (insects and nematodes), among others.

Nucleotide binding site and leucine-rich repeat (NBS-LRR) proteins

Members of a large class of proteins encoded by many disease-resistance or insect-resistance genes (R genes) of plants. An NBS-LRR protein contains a nucleotide binding site (NBS) domain and a leucine-rich repeat (LRR) domain, which are believed to confer the specificity of resistance.

Effector-triggered immunity

A defence response that is initiated when a pathogen effector molecule is recognized by a cytoplasmically localized host nucleotide binding site and leucine-rich repeat (NBS-LRR) protein.

Pattern-triggered immunity

A defence response that is initiated when a pathogen-associated molecular pattern is recognized by the corresponding host pattern recognition receptor.

Breeding chip

A microarray that enables high-throughput genotyping and selection of offspring in breeding programmes.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wing, R.A., Purugganan, M.D. & Zhang, Q. The rice genome revolution: from an ancient grain to Green Super Rice. Nat Rev Genet 19, 505–517 (2018). https://doi.org/10.1038/s41576-018-0024-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41576-018-0024-z

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research