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Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes

Nature Biotechnology volume 30, pages 105–111 (2012)Cite this article

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Abstract

Rice is a staple crop that has undergone substantial phenotypic and physiological changes during domestication. Here we resequenced the genomes of 40 cultivated accessions selected from the major groups of rice and 10 accessions of their wild progenitors (Oryza rufipogon and Oryza nivara) to >15 × raw data coverage. We investigated genome-wide variation patterns in rice and obtained 6.5 million high-quality single nucleotide polymorphisms (SNPs) after excluding sites with missing data in any accession. Using these population SNP data, we identified thousands of genes with significantly lower diversity in cultivated but not wild rice, which represent candidate regions selected during domestication. Some of these variants are associated with important biological features, whereas others have yet to be functionally characterized. The molecular markers we have identified should be valuable for breeding and for identifying agronomically important genes in rice.

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Figure 1: Population structure of Asian rice.
Figure 2: Linkage disequilibrium differences between wild and cultivated rice groups.
Figure 3: Significant outlier regions (genes) in ROD distribution.

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References

  1. Kovach, M.J., Sweeney, M.T. & McCouch, S.R. New insights into the history of rice domestication. Trends Genet. 23, 578–587 (2007).

    Article  CAS  PubMed  Google Scholar 

  2. Sang, T. & Ge, S. Genetics and phylogenetics of rice domestication. Curr. Opin. Genet. Dev. 17, 533–538 (2007).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  4. Sweeney, M.T., Thomson, M.J., Pfeil, B.E. & McCouch, S. Caught red-handed: Rc encodes a basic helix-loop-helix protein conditioning red pericarp in rice. Plant Cell 18, 283–294 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Jin, J. et al. Genetic control of rice plant architecture under domestication. Nat. Genet. 40, 1365–1369 (2008).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  7. Huang, X. et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat. Genet. 42, 961–967 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Hirschhorn, J.N. & Daly, M.J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6, 95–108 (2005).

    Article  CAS  PubMed  Google Scholar 

  9. He, Z. et al. Two evolutionary histories in the genome of rice: the roles of domestication genes. PLoS Genet. 7, e1002100 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Glaszmann, J.C. Isozymes and classification of Asian rice varieties. Theor. Appl. Genet. 74, 21–30 (1987).

    Article  CAS  PubMed  Google Scholar 

  11. Garris, A.J., Tai, T.H., Coburn, J., Kresovich, S. & McCouch, S. Genetic structure and diversity in Oryza sativa L. Genetics 169, 1631–1638 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. International Rice Genome Sequencing Project. The map-based sequence of the rice genome. Nature 436, 793–800 (2005).

    Article  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  14. Li, R. et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25, 1966–1967 (2009).

    Article  CAS  PubMed  Google Scholar 

  15. Zdobnov, E.M. & Apweiler, R. InterProScan—an integration platform for the signature-recognition methods in InterPro. Bioinformatics 17, 847–848 (2001).

    Article  CAS  PubMed  Google Scholar 

  16. Korbel, J.O. et al. Paired-end mapping reveals extensive structural variation in the human genome. Science 318, 420–426 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Campbell, P.J. et al. Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat. Genet. 40, 722–729 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Tuzun, E. et al. Fine-scale structural variation of the human genome. Nat. Genet. 37, 727–732 (2005).

    Article  CAS  PubMed  Google Scholar 

  19. Charlesworth, D. & Willis, J.H. The genetics of inbreeding depression. Nat. Rev. Genet. 10, 783–796 (2009).

    Article  CAS  PubMed  Google Scholar 

  20. Fu, H. & Dooner, H.K. Intraspecific violation of genetic colinearity and its implications in maize. Proc. Natl. Acad. Sci. USA 99, 9573–9578 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Springer, N.M. & Stupar, R.M. Allelic variation and heterosis in maize: how do two halves make more than a whole? Genome Res. 17, 264–275 (2007).

    Article  CAS  PubMed  Google Scholar 

  22. McNally, K.L. et al. Genomewide SNP variation reveals relationships among landraces and modern varieties of rice. Proc. Natl. Acad. Sci. USA 106, 12273–12278 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Clark, R.M. et al. Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science 317, 338–342 (2007).

    Article  CAS  PubMed  Google Scholar 

  24. Lam, H.M. et al. Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nat. Genet. 42, 1053–1059 (2010).

    Article  CAS  PubMed  Google Scholar 

  25. Tanksley, S.D. & McCouch, S.R. Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277, 1063–1066 (1997).

    Article  CAS  PubMed  Google Scholar 

  26. Tajima, F. Evolutionary relationship of DNA sequences in finite populations. Genetics 105, 437–460 (1983).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Caicedo, A.L. et al. Genome-wide patterns of nucleotide polymorphism in domesticated rice. PLoS Genet. 3, e163 (2007).

    Article  PubMed Central  Google Scholar 

  28. Second, G. Origin of the genic diversity of cultivated rice (Oryza spp.): study of the polymorphism scored at 40 isozyme loci. Jpn. J. Genet. 57, 25–57 (1982).

    Article  Google Scholar 

  29. Zhu, Q. & Ge, S. Phylogenetic relationships among A-genome species of the genus Oryza revealed by intron sequences of four nuclear genes. New Phytol. 167, 249–265 (2005).

    Article  CAS  PubMed  Google Scholar 

  30. Londo, J.P., Chiang, Y.C., Hung, K.H., Chiang, T.Y. & Schaal, B.A. Phylogeography of Asian wild rice, Oryza rufipogon, reveals multiple independent domestications of cultivated rice, Oryza sativa. Proc. Natl. Acad. Sci. USA 103, 9578–9583 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Menozzi, P., Piazza, A. & Cavalli-Sforza, L. Synthetic maps of human gene frequencies in Europeans. Science 201, 786–792 (1978).

    Article  CAS  PubMed  Google Scholar 

  32. Patterson, N., Price, A.L. & Reich, D. Population structure and eigenanalysis. PLoS Genet. 2, e190 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Saitou, N. & Nei, M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425 (1987).

    CAS  PubMed  Google Scholar 

  34. Tamura, K., Dudley, J., Nei, M. & Kumar, S. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596–1599 (2007).

    Article  CAS  PubMed  Google Scholar 

  35. Tang, H., Peng, J., Wang, P. & Risch, N.J. Estimation of individual admixture: analytical and study design considerations. Genet. Epidemiol. 28, 289–301 (2005).

    Article  PubMed  Google Scholar 

  36. Li, R. et al. SNP detection for massively parallel whole-genome resequencing. Genome Res. 19, 1124–1132 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Fuller, D.Q. et al. The domestication process and domestication rate in rice: spikelet bases from the Lower Yangtze. Science 323, 1607–1610 (2009).

    Article  CAS  PubMed  Google Scholar 

  38. Hill, W.G. & Robertson, A. Linkage disequilibrium in finite populations. TAG Theoretical and Applied Genetics 38, 226–231 (1968).

    Article  CAS  PubMed  Google Scholar 

  39. Barrett, J.C., Fry, B., Maller, J. & Daly, M.J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).

    Article  CAS  PubMed  Google Scholar 

  40. Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595 (1989).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Tenaillon, M.I., U'Ren, J., Tenaillon, O. & Gaut, B.S. Selection versus demography: a multilocus investigation of the domestication process in maize. Mol. Biol. Evol. 21, 1214–1225 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Wright, S.I. et al. The effects of artificial selection on the maize genome. Science 308, 1310–1314 (2005).

    Article  CAS  PubMed  Google Scholar 

  43. Yamasaki, M. et al. A large-scale screen for artificial selection in maize identifies candidate agronomic loci for domestication and crop improvement. Plant Cell 17, 2859–2872 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Yamasaki, M., Wright, S.I. & McMullen, M.D. Genomic screening for artificial selection during domestication and improvement in maize. Ann. Bot. 100, 967–973 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Gibbs, R.A. et al. Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science 324, 528–532 (2009).

    Article  CAS  PubMed  Google Scholar 

  46. Xia, Q. et al. Complete resequencing of 40 genomes reveals domestication events and genes in silkworm (Bombyx). Science 326, 433–436 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Rubin, C.J. et al. Whole-genome resequencing reveals loci under selection during chicken domestication. Nature 464, 587–591 (2010).

    Article  CAS  PubMed  Google Scholar 

  48. Wright, S. Evolution and the Genetics of Populations (The University of Chicago Press, Chicago, 1977).

  49. Jain, M. & Khurana, J.P. Transcript profiling reveals diverse roles of auxin-responsive genes during reproductive development and abiotic stress in rice. FEBS J. 276, 3148–3162 (2009).

    Article  CAS  PubMed  Google Scholar 

  50. Paponov, I.A. et al. The evolution of nuclear auxin signalling. BMC Evol. Biol. 9, 126 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Retief, J.D. Phylogenetic analysis using PHYLIP. Methods Mol. Biol. 132, 243–258 (2000).

    CAS  PubMed  Google Scholar 

  52. Zhu, Q., Zheng, X., Luo, J., Gaut, B.S. & Ge, S. Multilocus analysis of nucleotide variation of Oryza sativa and its wild relatives: severe bottleneck during domestication of rice. Mol. Biol. Evol. 24, 875–888 (2007).

    Article  CAS  PubMed  Google Scholar 

  53. Wang, J. et al. The diploid genome sequence of an Asian individual. Nature 456, 60–65 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Li, R., Li, Y., Kristiansen, K. & Wang, J. SOAP: short oligonucleotide alignment program. Bioinformatics 24, 713–714 (2008).

    Article  CAS  PubMed  Google Scholar 

  55. Li, R. et al. De novo assembly of human genomes with massively parallel short read sequencing. Genome Res. 20, 265–272 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Stanke, M., Schoffmann, O., Morgenstern, B. & Waack, S. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics 7, 62 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Yi, X. et al. Sequencing of 50 human exomes reveals adaptation to high altitude. Science 329, 75–78 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Li, Y. et al. Structural variation in two human genomes mapped at single-nucleotide resolution by whole genome de novo assembly. Nat. Biotech. 29, 723–730 (2011).

    Article  CAS  Google Scholar 

  59. Kent, W.J. BLAT—The BLAST-Like Alignment Tool. Genome Res. 12, 656–664 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  CAS  PubMed  Google Scholar 

  61. Watterson, G.A. On the number of segregating sites in genetical models without recombination. Theor. Popul. Biol. 7, 256–276 (1975).

    Article  CAS  PubMed  Google Scholar 

  62. Hudson, R.R., Slatkin, M. & Maddison, W.P. Estimation of levels of gene flow from DNA sequence data. Genetics 132, 583–589 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Tanaka, T. et al. The Rice Annotation Project Database (RAP-DB): 2008 update. Nucleic Acids Res. 36, D1028–D1033 (2008).

    CAS  PubMed  Google Scholar 

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Acknowledgements

We thank C.-H. Shi (Zhejiang University, China) and X.-H. Wei (China National Rice Research Institute) for assistance in growing rice materials. We are grateful to the International Rice Research Institute (Los Banos, Philippines) for providing most seed samples. This work was supported by the Chinese 973 program (2007CB815700), the National Natural Science Foundation of China (30990242), the Provincial Key Grant of Yunnan Province (2008CC017; 2008GA002), the Shenzhen Municipal Government and the Yantian District local government of Shenzhen, the Ole Rømer grant from the Danish Natural Science Research Council, and a CAS-Max Planck Society Fellowship and the 100 talent program of CAS to W.W., J.W. and S.G. We also acknowledge funding support from the Chinese Ministry of Agriculture (948 program), the Shenzhen Municipal Government of China and grants from Shenzhen Bureau of Science Technology & Information, China (ZYC200903240077A; CXB200903110066A).

Author information

Author notes

  1. Xun Xu, Xin Liu, Song Ge, Jeffrey D Jensen, Fengyi Hu, Xin Li and Yang Dong: These authors contributed equally to this work.

Authors and Affiliations

  1. CAS-Max Planck Junior Research Group on Evolutionary Genomics, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences (CAS), Kunming, China

    Xun Xu, Xin Li, Yang Dong, Guojie Zhang, Rasmus Nielsen & Wen Wang

  2. BGI-Shenzhen, Shenzhen, China

    Xun Xu, Xin Liu, Lin Fang, Jingxiang Li, Weiming He, Guojie Zhang, Yingrui Li, Chang Yu, Karsten Kristiansen, Xiuqing Zhang, Jian Wang & Jun Wang

  3. Graduate University of Chinese Academy Sciences, Beijing, China

    Xun Xu, Lei Huang, Xiaoming Zheng & Fumin Zhang

  4. State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China

    Song Ge, Lei Huang, Guojie Zhang & Xiaoming Zheng

  5. School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Jeffrey D Jensen

  6. Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China

    Fengyi Hu

  7. Department of Molecular and Cellular Biology, University of Arizona, Tucson, Arizona, USA

    Ryan N Gutenkunst

  8. South China University of Technology, Guangdong, China

    Weiming He

  9. Department of Biology, University of Copenhagen, Copenhagen, Denmark

    Karsten Kristiansen, Rasmus Nielsen & Jun Wang

  10. Department of Plant Breeding & Genetics, Cornell University, Ithaca, New York, USA

    Mark Wright & Susan McCouch

  11. Departments of Integrative Biology and Statistics, University of California, Berkeley, USA

    Rasmus Nielsen

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  1. Xun Xu
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Contributions

W.W., Jun Wang, S.G., X.X., R.N. and F.H. designed the project. X.X., X. Liu, X. Li, J.D.J., M.W., L.F., G.Z., W.H., X. Zheng., Y.L. and R.N. analyzed the data. W.W., X.X., R.N., R.N.G., X. Liu, S.M., K.K. and Jun Wang wrote the manuscript. S.G., F.H., L.H. and F.Z. prepared the samples. X. Zhang, Jian Wang, C.Y., J.L. and Y.D. conducted the experiments.

Corresponding authors

Correspondence to Rasmus Nielsen, Jun Wang or Wen Wang.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1,2,5,6,8–16, Supplmentary Notes and Supplementary Figures 1–23 (PDF 4530 kb)

Supplementary Table 3

Annotation information of novel genes identified from unmapped contigs. (XLSM 156 kb)

Supplementary Table 4

Information of lost genes. (+ means not lost in that individual, - mean lost supported by both pairs and coverage information, P means only supported by pair-end information, C means only supported by coverage information.) (XLSM 202 kb)

Supplementary Table 7

CNV regions. (XLSM 72 kb)

Supplementary Data Set 1 (ZIP 7415 kb)

Supplementary Data Set 2 (ZIP 20621 kb)

Supplementary Data Set 3 (ZIP 17633 kb)

Supplementary Data Set 4 (ZIP 25994 kb)

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Xu, X., Liu, X., Ge, S. et al. Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes. Nat Biotechnol 30, 105–111 (2012). https://doi.org/10.1038/nbt.2050

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