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.

  • Letter
  • Published:

Signatures of adaptation in the weedy rice genome

Abstract

Crop domestication provided the calories that fueled the rise of civilization1,2,3. For many crop species, domestication was accompanied by the evolution of weedy crop relatives, which aggressively outcompete crops and reduce harvests4,5,6. Understanding the genetic mechanisms that underlie the evolution of weedy crop relatives is critical for agricultural weed management and food security. Here we use whole-genome sequences to examine the origin and adaptation of the two major strains of weedy rice found in the United States. We find that de-domestication from cultivated ancestors has had a major role in their evolution, with relatively few genetic changes required for the emergence of weediness traits. Weed strains likely evolved both early and late in the history of rice cultivation and represent an under-recognized component of the domestication process. Genomic regions identified here that show evidence of selection can be considered candidates for future genetic and functional analyses for rice improvement.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Neighbor-joining tree of the 183 wild, cultivated, and weedy rice accessions.
Figure 2: Origin models for SH, BHA, and Chinese weedy rice.
Figure 3: Candidate genomic regions under selection in weedy rice.
Figure 4: Selective sweeps in the weedy rice genome.

Similar content being viewed by others

Accession codes

Primary accessions

Sequence Read Archive

References

  1. Doebley, J.F., Gaut, B.S. & Smith, B.D. The molecular genetics of crop domestication. Cell 127, 1309–1321 (2006).

    CAS  PubMed  Google Scholar 

  2. Ross-Ibarra, J., Morrell, P.L. & Gaut, B.S. Plant domestication, a unique opportunity to identify the genetic basis of adaptation. Proc. Natl. Acad. Sci. USA 104, 8641–8648 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Larson, G. et al. Current perspectives and the future of domestication studies. Proc. Natl. Acad. Sci. USA 111, 6139–6146 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Vigueira, C., Olsen, K. & Caicedo, A. The red queen in the corn: agricultural weeds as models of rapid adaptive evolution. Heredity 110, 303–311 (2013).

    CAS  PubMed  Google Scholar 

  5. De Wet, J.M. & Harlan, J.R. Weeds and domesticates: evolution in the man-made habitat. Econ. Bot. 29, 99–108 (1975).

    Google Scholar 

  6. Ellstrand, N.C. et al. Crops gone wild: evolution of weeds and invasives from domesticated ancestors. Evol. Appl. 3, 494–504 (2010).

    PubMed  PubMed Central  Google Scholar 

  7. Oerke, E.C. Crop losses to pests. J. Agric. Sci. 144, 31–43 (2006).

    Google Scholar 

  8. Estorninos, L.E. Jr., Gealy, D.R., Gbur, E.E., Talbert, R.E. & McClelland, M.R. Rice and red rice interference. II. Rice response to population densities of three red rice (Oryza sativa) ecotypes. Weed Sci. 53, 683–689 (2005).

    CAS  Google Scholar 

  9. Gealy, D.R. & Yan, W. Weed suppression potential of 'Rondo' and other indica rice germplasm lines. Weed Technol. 26, 517–524 (2012).

    Google Scholar 

  10. Chauhan, B.S. Strategies to manage weedy rice in Asia. Crop Prot. 48, 51–56 (2013).

    Google Scholar 

  11. Hill, J., Smith, R.J. & Bayer, D. Rice weed control: current technology and emerging issues in temperate rice. Anim. Prod. Sci. 34, 1021–1029 (1994).

    Google Scholar 

  12. Ziska, L.H. et al. Chapter three—weedy (red) rice: an emerging constraint to global rice production. Adv. Agron. 129, 181–228 (2015).

    Google Scholar 

  13. Basu, C., Halfhill, M.D., Mueller, T.C. & Stewart, C.N. Weed genomics: new tools to understand weed biology. Trends Plant Sci. 9, 391–398 (2004).

    CAS  PubMed  Google Scholar 

  14. Burgos, N.R., Norman, R.J., Gealy, D.R. & Black, H. Competitive N uptake between rice and weedy rice. Field Crops Res. 99, 96–105 (2006).

    Google Scholar 

  15. Gealy, D.R. in Crop Ferality and Volunteerism (ed. Gressel, J.) 323–354 (CRRC Press, 2005).

  16. Shivrain, V.K. et al. Gene flow between Clearfield™ rice and red rice. Crop Prot. 26, 349–356 (2007).

    CAS  Google Scholar 

  17. Shivrain, V.K., Burgos, N.R., Gealy, D.R., Moldenhauer, K.A. & Baquireza, C.J. Maximum outcrossing rate and genetic compatibility between red rice (Oryza sativa) biotypes and Clearfield™ rice. Weed Sci. 56, 807–813 (2008).

    CAS  Google Scholar 

  18. Burgos, N.R. et al. The impact of herbicide-resistant rice technology on phenotypic diversity and population structure of United States weedy rice. Plant Physiol. 166, 1208–1220 (2014).

    PubMed  PubMed Central  Google Scholar 

  19. Lu, B.R., Yang, X. & Ellstrand, N.C. Fitness correlates of crop transgene flow into weedy populations: a case study of weedy rice in China and other examples. Evol. Appl. 9, 857–870 (2016).

    PubMed  PubMed Central  Google Scholar 

  20. Merotto, A. et al. Evolutionary and social consequences of introgression of nontransgenic herbicide resistance from rice to weedy rice in Brazil. Evol. Appl. 9, 837–846 (2016).

    PubMed  PubMed Central  Google Scholar 

  21. Song, B.K., Chuah, T.S., Tam, S.M. & Olsen, K.M. Malaysian weedy rice shows its true stripes: wild Oryza and elite rice cultivars shape agricultural weed evolution in Southeast Asia. Mol. Ecol. 23, 5003–5017 (2014).

    CAS  PubMed  Google Scholar 

  22. Pusadee, T., Schaal, B.A., Rerkasem, B. & Jamjod, S. Population structure of the primary gene pool of Oryza sativa in Thailand. Genet. Resour. Crop Evol. 60, 335–353 (2013).

    Google Scholar 

  23. Londo, J. & Schaal, B. Origins and population genetics of weedy red rice in the USA. Mol. Ecol. 16, 4523–4535 (2007).

    CAS  PubMed  Google Scholar 

  24. Reagon, M. et al. Genomic patterns of nucleotide diversity in divergent populations of US weedy rice. BMC Evol. Biol. 10, 180 (2010).

    PubMed  PubMed Central  Google Scholar 

  25. Grimm, A., Fogliatto, S., Nick, P., Ferrero, A. & Vidotto, F. Microsatellite markers reveal multiple origins for Italian weedy rice. Ecol. Evol. 3, 4786–4798 (2013).

    PubMed  PubMed Central  Google Scholar 

  26. Thurber, C.S., Jia, M.H., Jia, Y. & Caicedo, A.L. Similar traits, different genes? Examining convergent evolution in related weedy rice populations. Mol. Ecol. 22, 685–698 (2013).

    CAS  PubMed  Google Scholar 

  27. Vigueira, C., Li, W. & Olsen, K. The role of Bh4 in parallel evolution of hull colour in domesticated and weedy rice. J. Evol. Biol. 26, 1738–1749 (2013).

    CAS  PubMed  Google Scholar 

  28. Qi, X. et al. More than one way to evolve a weed: parallel evolution of US weedy rice through independent genetic mechanisms. Mol. Ecol. 24, 3329–3344 (2015).

    PubMed  Google Scholar 

  29. Qiu, J. et al. Genome re-sequencing suggested a weedy rice origin from domesticated indica–japonica hybridization: a case study from southern China. Planta 240, 1353–1363 (2014).

    CAS  PubMed  Google Scholar 

  30. Kumar, S., Stecher, G. & Tamura, K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33, 1870–1874 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Drummond, A.J., Suchard, M.A., Xie, D. & Rambaut, A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Meyer, R.S. & Purugganan, M.D. Evolution of crop species: genetics of domestication and diversification. Nat. Rev. Genet. 14, 840–852 (2013).

    CAS  PubMed  Google Scholar 

  34. Olsen, K.M. & Wendel, J.F. A bountiful harvest: genomic insights into crop domestication phenotypes. Annu. Rev. Plant Biol. 64, 47–70 (2013).

    CAS  PubMed  Google Scholar 

  35. Olsen, K.M. & Wendel, J.F. Crop plants as models for understanding plant adaptation and diversification. Front. Plant Sci. 4, 1–16 (2013).

    Google Scholar 

  36. Cui, Y. et al. Little white lies: pericarp color provides insights into the origins and evolution of southeast Asian weedy rice. G3 6, 4105–4114 (2016).

    PubMed  PubMed Central  Google Scholar 

  37. Gu, X.Y. et al. Association between seed dormancy and pericarp color is controlled by a pleiotropic gene that regulates abscisic acid and flavonoid synthesis in weedy red rice. Genetics 189, 1515–1524 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Reagon, M., Thurber, C.S., Olsen, K.M., Jia, Y. & Caicedo, A.L. The long and the short of it: SD1 polymorphism and the evolution of growth trait divergence in US weedy rice. Mol. Ecol. 20, 3743–3756 (2011).

    PubMed  Google Scholar 

  39. Pavlidis, P., Živković, D., Stamatakis, A. & Alachiotis, N. SweeD: likelihood-based detection of selective sweeps in thousands of genomes. Mol. Biol. Evol. 30, 2224–2234 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  41. The 3,000 Rice Genomes Project Group. The 3,000 Rice Genomes Project. Gigascience 3, 7 (2014).

  42. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. McKenna, A. et al. The genome analysis toolkit: a mapreduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    PubMed  PubMed Central  Google Scholar 

  45. Xu, X. et al. Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes. Nat. Biotechnol. 30, 105–111 (2012).

    CAS  Google Scholar 

  46. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  48. Larkin, M.A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007).

    CAS  PubMed  Google Scholar 

  49. Nielsen, R. et al. Darwinian and demographic forces affecting human protein coding genes. Genome Res. 19, 838–849 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank M. Dyer and staff of the University greenhouse for assistance in growing plants and L. Small for technical laboratory assistance. We are grateful to members of the Olsen laboratory for helpful comments on this manuscript. This work is supported by the National Science Foundation Plant Genome Research Program (IOS-1032023). The USDA is an equal opportunity provider and employer.

Author information

Authors and Affiliations

Authors

Contributions

K.M.O., Y.J. and A.L.C. designed the experiments. L.-F.L. and Y.-L.L. analyzed the data. L.-F.L., K.M.O. and A.L.C. wrote the manuscript.

Corresponding authors

Correspondence to Ana L Caicedo or Kenneth M Olsen.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Neighbor-joining tree of the 183 wild, cultivated, and weedy rice accessions.

Relationships of cultivated and wild rice correspond to previously observed relationships40. Wild rice accessions (dark green) are divided into different groups. The japonica (orange) and aromatic (light green) rice varieties form a clade. The BHA (red), SH (purple), and Chinese (black) weedy rice strains cluster with indica (light blue) and aus (pink), respectively. Bootstrap values (>50) are shown on each branch.

Supplementary Figure 2 Ancestral population structures of 183 rice accessions.

(a,b) Analyses of the full data set (a) and no-missing data set (b) were performed separately. Each vertical bar represents one accession, and different colors indicate distinct ancestry states. Cross-validation error was estimated for diverse K values from two to five. K = 3 minimizes the cross-validation error.

Supplementary Figure 3 Distributions of wild- and crop-specific private SNPs in SH (orange), BHA (red), and Chinese (green) weedy rice at the whole-genome level.

The box corresponds to the 95% confidence interval, and the black bar within each box is the mean value. The blue horizontal dashed line represents the equal proportion of wild- and crop-specific private SNPs. Positive and negative values represent crop-like and wild-like, respectively.

Supplementary Figure 4 Distribution patterns of wild- and crop-specific private SNPs within each chromosome of SH (orange), BHA (red), and Chinese (green) weedy rice.

The box corresponds to the 95% confidence interval, and the black bar within each box is the mean value for each chromosome. The blue horizontal dotted line represents zero. Positive and negative values represent the presence of crop-like and wild-like SNPs, respectively.

Supplementary Figure 5 Decrease in nucleotide diversity (θ) in SH and BHA weedy rice as compared to their crop ancestors.

The y axis represents the ratio of nucleotide diversity (θ) between weedy rice and their crop ancestors. Each bar is a 100-kb window, and the red solid line corresponds to the threshold for the top 5%. The numbers on the red line are the exact thresholds for each comparison.

Supplementary Figure 6 Gene Ontology (GO) analysis of the 178 candidate genes in SH weedy rice.

Supplementary Figure 7 Gene Ontology (GO) analysis of the 307 candidate genes in BHA weedy rice.

Supplementary Figure 8 Ratio of nucleotide diversity (Ï€) between indica and SH weedy rice across the genome.

(a) The criteria MQ ≥ 10 and DP ≥ 1 were used to filter the reported variants. (b) The criteria MQ ≥ 20 and DP ≥ 3 were used to filter the reported variants. (c) The criteria MQ ≥ 10 and DP ≥ 1 were used, excluding low-frequency (<2%) heterozygosity. Each bar represents a 100-kb window.

Supplementary Figure 9 Genome-wide genetic differentiation (FST) between indica and SH weedy rice across the genome.

(a) The criteria MQ ≥ 10 and DP ≥ 1 were used to filter the reported variants. (b) The criteria MQ ≥ 20 and DP ≥ 3 were used to filter the reported variants. (c) The criteria MQ ≥ 10 and DP ≥ 1 were used, excluding low-frequency (<2%) heterozygosity. Each bar represents a 100-kb window.

Supplementary Figure 10 Ratio of nucleotide diversity (Ï€) between BHA and aus across the genome.

(a) The criteria MQ ≥ 10 and DP ≥ 1 were used to filter the reported variants. (b) The criteria MQ ≥ 20 and DP ≥ 3 were used to filter the reported variants. (c) The criteria MQ ≥ 10 and DP ≥ 1 were used, excluding low-frequency (<2%) heterozygosity. Each bar represents a 100-kb window.

Supplementary Figure 11 Genome-wide genetic differentiation (FST) between BHA and aus across the genome.

(a) The criteria MQ ≥ 10 and DP ≥ 1 were used to filter the reported variants. (b) The criteria MQ ≥ 20 and DP ≥ 3 were used to filter the reported variants. (c) The criteria MQ ≥ 10 and DP ≥ 1 were used, excluding low-frequency (<2%) heterozygosity. Each bar represents a 100-kb window.

Supplementary Figure 12 Ratio of nucleotide diversity (Ï€) between wild and cultivated rice across the genome.

(a) The criteria MQ ≥ 10 and DP ≥ 1 were used to filter the reported variants. (b) The criteria MQ ≥ 20 and DP ≥ 3 were used to filter the reported variants. (c) The criteria MQ ≥ 10 and DP ≥ 1 were used, excluding low-frequency (<2%) heterozygosity. Each bar represents a 100-kb window.

Supplementary Figure 13 Genome-wide genetic differentiation (FST) between wild and cultivated rice across the genome.

(a) The criteria MQ ≥ 10 and DP ≥ 1 were used to filter the reported variants. (b) The criteria MQ ≥ 20 and DP ≥ 3 were used to filter the reported variants. (c) The criteria MQ ≥ 10 and DP ≥ 1 were used, excluding low-frequency (<2%) heterozygosity. Each bar represents a 100-kb window.

Supplementary Figure 14 Ratio of nucleotide diversity (Ï€) between wild and cultivated rice.

The identified domestication genes are shown for each chromosome.

Supplementary Figure 15 Ratio of nucleotide diversities (θ and π) between wild, cultivated, and weedy rice.

The y and x axes are the ratio of θ and π, respectively.

Supplementary Figure 16 Neighbor-joining tree based on the 54 selected rice accessions.

Relationships of cultivated and wild rice correspond to previously observed relationships40. Wild rice accessions (dark green) are divided into different groups. The japonica (orange) and aromatic (light green) rice varieties form a clade. The BHA (red), SH (purple), and Chinese (black) weedy rice strains cluster with indica (light blue) and aus (pink), respectively. Bootstrap values (>50) are shown on each branch.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–16 and Supplementary Tables 2, 4–6 and 14 (PDF 2846 kb)

Supplementary Table 1

The list of 183 accessions of wild, cultivated, and weedy rice species sampled in the collection. (XLSX 59 kb)

Supplementary Table 3

Genetic assignments at wild, cultivated, and weedy rice accessions from two to five. (XLSX 59 kb)

Supplementary Table 7

Causative mutations of domestication genes in the three types of weedy rice. (XLSX 37 kb)

Supplementary Table 8

Genome-wide detection of regions of low nucleotide diversity in SH compared to indica. (XLSX 52 kb)

Supplementary Table 9

Genome-wide detection of regions of low nucleotide diversity in BHA compared to aus. (XLSX 53 kb)

Supplementary Table 10

Functionally characterized genes showing low nucleotide diversity in SH and high genetic differentiation between SH and indica. (XLSX 57 kb)

Supplementary Table 11

Functionally characterized genes showing low nucleotide diversity in BHA and high genetic differentiation between BHA and aus. (XLSX 70 kb)

Supplementary Table 12

Number of raw variants in wild, cultivated, and weedy rice with different filter criteria. (XLSX 42 kb)

Supplementary Table 13

Genome-wide detection and functional annotation of selective sweep regions in the full crop populations. (XLSX 54 kb)

Supplementary Data

Sequence alignment of Rc genes in wild, cultivated, and weedy rice. (TXT 2000 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, LF., Li, YL., Jia, Y. et al. Signatures of adaptation in the weedy rice genome. Nat Genet 49, 811–814 (2017). https://doi.org/10.1038/ng.3825

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3825

This article is cited by

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