The global biogeography of polyploid plants

Abstract

Deciphering the global distribution of polyploid plants is fundamental for understanding plant evolution and ecology. Many factors have been hypothesized to affect the uneven distribution of polyploid plants across the globe. Nevertheless, the lack of large comparative datasets has restricted such studies to local floras and to narrow taxonomical scopes, limiting our understanding of the underlying drivers of polyploid plant distribution. We present a map portraying the worldwide polyploid frequencies, based on extensive spatial data coupled with phylogeny-based polyploidy inference for tens of thousands of species. This allowed us to assess the potential global drivers affecting polyploid distribution. Our data reveal a clear latitudinal trend, with polyploid frequency increasing away from the equator. Climate, especially temperature, appears to be the most influential predictor of polyploid distribution. However, we find this effect to be mostly indirect, mediated predominantly by variation in plant lifeforms and, to a lesser extent, by taxonomical composition and species richness. Thus, our study presents an emerging view of polyploid distribution that highlights attributes that facilitate the establishment of new polyploid lineages by providing polyploids with sufficient time (that is, perenniality) and space (low species richness) to compete with pre-adapted diploid relatives.

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References

  1. 1.

    Jiao, Y. N. et al. Ancestral polyploidy in seed plants and angiosperms. Nature 473, 97–113 (2011).

    PubMed  CAS  Google Scholar 

  2. 2.

    Van de Peer, Y., Fawcett, J. A., Proost, S., Sterck, L. & Vandepoele, K. The flowering world: a tale of duplications. Trends. Plant. Sci. 14, 680–688 (2009).

    PubMed  Google Scholar 

  3. 3.

    Leitch, A. R. & Leitch, I. J. Genomic plasticity and the diversity of polyploid plants. Science 320, 481–483 (2008).

    PubMed  PubMed Central  CAS  Google Scholar 

  4. 4.

    Adams, K. L. & Wendel, J. F. Polyploidy and genome evolution in plants. Curr. Opin. Plant Biol. 8, 135–141 (2005).

    PubMed  CAS  Google Scholar 

  5. 5.

    Wood, T. E. et al. The frequency of polyploid speciation in vascular plants. Proc. Natl Acad. Sci. USA 106, 13875–13879 (2009).

    PubMed  CAS  Google Scholar 

  6. 6.

    Otto, S. P. & Whitton, J. Polyploid incidence and evolution. Annu. Rev. Genet. 34, 401–437 (2000).

    PubMed  CAS  Google Scholar 

  7. 7.

    Rieseberg, L. H. & Willis, J. H. Plant speciation. Science 317, 910–914 (2007).

    PubMed  PubMed Central  CAS  Google Scholar 

  8. 8.

    Ramsey, J. & Schemske, D. W. Pathways, mechanisms, and rates of polyploid formation in flowering plants. Annu. Rev. Ecol. Syst. 29, 467–501 (1998).

    Google Scholar 

  9. 9.

    Soltis, D., Soltis, P. & Schemske, D. Autopolyploidy in angiosperms: have we grossly underestimated the number of species? Taxon 56, 13–30 (2007).

    Google Scholar 

  10. 10.

    Levin, D. Minority cytotype exclusion in local plant populations. Taxon 24, 34–43 (1975).

    Google Scholar 

  11. 11.

    Barringer, B. C. Polyploidy and self-fertilization in flowering plants. Am. J. Bot. 94, 1527–1533 (2007).

    PubMed  Google Scholar 

  12. 12.

    Levin, D. Polyploidy and novelty in flowering plants. Am. Nat. 122, 1–25 (1983).

    Google Scholar 

  13. 13.

    Ramsey, J. & Schemske, D. W. Neopolyploidy in flowering plants. Annu. Rev. Ecol. Syst. 33, 589–639 (2002).

    Google Scholar 

  14. 14.

    Stebbins, G. L. Chromosomal Evolution in Higher Plants (Edward Arnold, London, 1971).

  15. 15.

    Spoelhof, J. P., Soltis, P. S. & Soltis, D. E. Pure polyploidy: closing the gaps in autopolyploid research. J. Syst. Evol. 55, 340–352 (2017).

    Google Scholar 

  16. 16.

    Ramsey, J. & Ramsey, T. S. Ecological studies of polyploidy in the 100 years following its discovery. Philos. Trans. Royal Soc. B. Biol. Sci. 369, 1–20 (2014).

    Google Scholar 

  17. 17.

    te Beest, M. et al. The more the better? The role of polyploidy in facilitating plant invasions. Ann. Bot. 109, 19–45 (2011).

    Google Scholar 

  18. 18.

    Brochmann, C. et al. Polyploidy in arctic plants. Biol. J. Linn. Soc. 82, 521–536 (2004).

    Google Scholar 

  19. 19.

    Hagerup, O. Über polyploidie in beziehung zu klima, ökologie und phylogenie. Hereditas 16, 19–40 (1931).

    Google Scholar 

  20. 20.

    Martin, S. L. & Husband, B. C. Influence of phylogeny and ploidy on species ranges of North American angiosperms. J. Ecol. 97, 913–922 (2009).

    Google Scholar 

  21. 21.

    Bretagnolle, F. & Thompson, J. D. Gametes with the somatic chromosome number: mechanisms of their formation and role in the evolution of autopolyploid plants. New Phytol. 129, 1–22 (1995).

    Google Scholar 

  22. 22.

    De Storme, N. & Geelen, D. Sexual polyploidization in plants-cytological mechanisms and molecular regulation. New Phytol. 198, 670–684 (2013).

    PubMed  PubMed Central  Google Scholar 

  23. 23.

    Van de Peer, Y., Mizrachi, E. & Marchal, K. The evolutionary significance of polyploidy. Nat. Rev. Genet. 18, 411–424 (2017).

    PubMed  Google Scholar 

  24. 24.

    Stebbins, G. L. Polyploidy, hybridization, and the invasion of new habitats. Ann. Missouri Bot. Gard. 72, 824–832 (1985).

    Google Scholar 

  25. 25.

    Parisod, C., Holderegger, R. & Brochmann, C. Evolutionary consequences of autopolyploidy. New Phytol. 186, 5–17 (2010).

    PubMed  CAS  Google Scholar 

  26. 26.

    Stebbins, G. L. Polyploidy and the distribution of the Arctic-Alpine flora - new evidence and a new approach. Bot. Helv. 94, 1–13 (1984).

    Google Scholar 

  27. 27.

    Soltis, P. S. & Soltis, D. E. The role of genetic and genomic attributes in the success of polyploids. Proc. Natl Acad. Sci. USA 97, 7051–7057 (2000).

    PubMed  CAS  Google Scholar 

  28. 28.

    Comai, L. The advantages and disadvantages of being polyploid. Nat. Rev. Genet. 6, 836–846 (2005).

    PubMed  CAS  Google Scholar 

  29. 29.

    Doyle, J. J. et al. Evolutionary genetics of genome merger and doubling in plants. Annu. Rev. Genet. 42, 443–461 (2008).

    PubMed  CAS  Google Scholar 

  30. 30.

    Guignard, M. S. et al. Genome size and ploidy influence angiosperm species’ biomass under nitrogen and phosphorus limitation. New Phytol. 210, 1195–1206 (2016).

    PubMed  PubMed Central  Google Scholar 

  31. 31.

    Šmarda, P. et al. Effect of phosphorus availability on the selection of species with different ploidy levels and genome sizes in a long-term grassland fertilization experiment. New Phytol. 200, 911–921 (2013).

    PubMed  Google Scholar 

  32. 32.

    Johnston, A. E., Poulton, P. R., Fixen, P. E. & Curtin, D. Phosphorus: its efficient use in agriculture. Adv. Agron. 123, 177–228 (2014).

    CAS  Google Scholar 

  33. 33.

    Husband, B., Baldwin, S. & Suda, J. in Plant Genome Diversity, Vol. 2 (eds Greilhuber J., Jaroslav D. & Wendel J. F.) 255–276 (Springer, Vienna, 2013).

  34. 34.

    Rice, A. et al. The Chromosome Counts Database (CCDB) – a community resource of plant chromosome numbers. New Phytol. 206, 19–26 (2015).

    PubMed  Google Scholar 

  35. 35.

    Stevens, P. Angiosperm Phylogeny Website v.13 (2012); http://www.mobot.org/MOBOT/research/APweb

  36. 36.

    Müntzing, A. The evolutionary significance of autopolyploidy. Hereditas 21, 363–378 (1936).

    Google Scholar 

  37. 37.

    Stebbins, G. L. Cytological characteristics associated with the different growth habits in the dicotyledons. Am. J. Bot. 25, 189–198 (1938).

    Google Scholar 

  38. 38.

    Engemann, K. et al. Patterns and drivers of plant functional group dominance across the Western Hemisphere: a macroecological re-assessment based on a massive botanical dataset. Bot. J. Linn. Soc. 180, 141–160 (2016).

    Google Scholar 

  39. 39.

    Ehrendorfer, F. in Polyploidy: Biological Relevance (ed. Lewis, W. H.) 45–60 (Springer, Boston, 1980).

  40. 40.

    Glick, L. & Mayrose, I. ChromEvol: assessing the pattern of chromosome number evolution and the inference of polyploidy along a phylogeny. Mol. Biol. Evol. 31, 1914–1922 (2014).

    PubMed  CAS  Google Scholar 

  41. 41.

    WWF. Montane grasslands and shrublands https://www.worldwildlife.org/biomes/montane-grasslands-and-shrublands.

  42. 42.

    Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on earth. Bioscience 51, 933–938 (2001).

    Google Scholar 

  43. 43.

    Carr, G. D. in Evolution and Speciation of Island Plants (eds Stuessy, T. F. & Ono, M.) (Cambridge Univ. Press, 2007).

  44. 44.

    Oberlander, K. C., Dreyer, L. L., Goldblatt, P., Suda, J. & Linder, H. P. Species‐rich and polyploid‐poor: Insights into the evolutionary role of whole‐genome duplication from the Cape flora biodiversity hotspot. Am. J. Bot. 103, 1336–1347 (2016).

    PubMed  Google Scholar 

  45. 45.

    Gustafsson, Å. Polyploidy, life-form and vegetative reproduction. Hereditas 34, 1–22 (1948).

    Google Scholar 

  46. 46.

    Levin, D. The Role of Chromosomal Change in Plant Evolution (Oxford Univ. Press, New York, 2002).

  47. 47.

    Grömping, U. Relative importance for linear regression in R: the package relaimpo. J. Stat. Softw. 17, 1–27 (2006).

    Google Scholar 

  48. 48.

    Currie, D. J. et al. Predictions and tests of climate‐based hypotheses of broad‐scale variation in taxonomic richness. Ecol. Lett. 7, 1121–1134 (2004).

    Google Scholar 

  49. 49.

    Kreft, H. & Jetz, W. Global patterns and determinants of vascular plant diversity. Proc. Natl Acad. Sci. USA 104, 5925–5930 (2007).

    PubMed  CAS  Google Scholar 

  50. 50.

    Donoghue, M. J. A phylogenetic perspective on the distribution of plant diversity. Proc. Natl Acad. Sci. USA 105, 11549–11555 (2008).

    PubMed  CAS  Google Scholar 

  51. 51.

    Andrew Jones, F., Sobkowiak, B., Orme, D. et al. in Early Events in Monocot Evolution (eds. Wilkin, P. & Mayo, S. J.) 99–117 (Cambridge Univ. Press, New York, 2011).

  52. 52.

    Huggett, R. J. in Fundamentals of Biogeography (ed. Gerrard, J.) 77–80 (Routledge, London, 2004).

  53. 53.

    Raunkiaer, C. The Life Forms of Plants and Statistical Plant Geography (Oxford Univ. Press, Oxford, 1934).

  54. 54.

    FitzJohn, R. G. et al. How much of the world is woody? J. Ecol. 102, 1266–1272 (2014).

    Google Scholar 

  55. 55.

    Ricklefs, R. E. & Renner, S. S. Species richness within families of flowering plants. Evolution 48, 1619–1636 (1994).

    PubMed  Google Scholar 

  56. 56.

    Soltis, D. E. et al. Phylogeny and Evolution of the Angiosperms: Revised and Updated Edition (Univ. of Chicago Press, Chicago, 2018).

  57. 57.

    Moeller, D. A. et al. Global biogeography of mating system variation in seed plants. Ecol. Lett. 20, 375–384 (2017).

    PubMed  Google Scholar 

  58. 58.

    Vamosi, J. C. & Vamosi, S. M. Key innovations within a geographical context in flowering plants: towards resolving Darwin’s abominable mystery. Ecol. Lett. 13, 1270–1279 (2010).

    PubMed  Google Scholar 

  59. 59.

    Glick, L., Sabath, N., Ashman, T. L., Goldberg, E. & Mayrose, I. Polyploidy and sexual system in angiosperms: Is there an association? Am. J. Bot. 7, 1223–1235 (2016).

    Google Scholar 

  60. 60.

    Drori, M. et al. OneTwoTree: An online tool for phylogeny reconstruction. Mol. Ecol. Resour. 18, 1492–1499 (2018).

    PubMed  Google Scholar 

  61. 61.

    Benson, D. A. et al. GenBank. Nucleic Acids Res. 41, 36–42 (2013).

    Google Scholar 

  62. 62.

    Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).

    PubMed  Google Scholar 

  63. 63.

    Bennett, M. D. & Leitch, I. J. Plant DNA C-values Database (Royal Botanic Gardens, 2012); http://www.kew.org/cvalues/

  64. 64.

    R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013); http://www.R-project.org/

  65. 65.

    Zizka, A. CoordinateCleaner: Automated Cleaning of Occurrence Records from Biological Collections (2018); https://CRAN.R-project.org/package=coordinatecleaner

  66. 66.

    Wickham, H. Tidyverse: Easily Install and Load the ‘Tidyverse’ (2017); https://CRAN.R-project.org/package=tidyverse

  67. 67.

    Chamberlain, S. and Boettiger C. R Python, and Ruby clients for GBIF species occurrence data. PeerJ PrePrints (2017); https://CRAN.R-project.org/package=rgbif

  68. 68.

    South, A. rnaturalearthdata: World Vector Map Data from Natural Earth Used in ‘rnaturalearth’ (2017); https://CRAN.R-project.org/package=rnaturalearth

  69. 69.

    Meyer, R. S., DuVal, A. E. & Jensen, H. R. Patterns and processes in crop domestication: an historical review and quantitative analysis of 203 global food crops. New Phytol. 196, 29–48 (2012).

    PubMed  Google Scholar 

  70. 70.

    Hijmans, R. J. Raster: Geographic Data Analysis and Modeling, R package v.2.2-12 (2014); http://CRAN.R-project.org/package=raster

  71. 71.

    Rowlingson, R. B. and T. K. and B. Rgdal: Bindings for the Geospatial Data Abstraction Library (2014); http://cran.r-project.org/package=rgdal

  72. 72.

    Wickham, H. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40, 1–29 (2011).

    Google Scholar 

  73. 73.

    ArcGIS Desktop: Release 10 (Environmental Systems Research Institute, 2011); http://www.esri.com

  74. 74.

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).

    Google Scholar 

  75. 75.

    Raup, B. H. et al. Global Land Ice Measurements from Space (GLIMS) Database at NSIDC. AGU Fall Meeting Abstracts 1, 837 (2003).

    Google Scholar 

  76. 76.

    Ehlers, J., Gibbard, P. & Hughes, P. in Quaternary Glaciations – Extent and Chronology, Part IV (Elsevier, Oxford, 2011).

  77. 77.

    Imhoff, M. L. et al. Global patterns in human consumption of net primary production. Nature 429, 870–873 (2004).

    PubMed  CAS  Google Scholar 

  78. 78.

    Wilson, E. O. The encyclopedia of life. Trends Ecol. Evol. 18, 77–80 (2003).

    Google Scholar 

  79. 79.

    Watanabe, K. Index to Chromosome Numbers in Asteraceae http//www.asteraceae.cla.kobe-u.ac.jp/index.html (2002).

  80. 80.

    WCSP. World Checklist of Selected Plant Families (Royal Botanic Gardens, Kew, 2016); http://apps.kew.org/wcsp/ https://doi.org/10.1163/_q3_SIM_00374

  81. 81.

    Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89–92 (2014).

    PubMed  CAS  Google Scholar 

  82. 82.

    Brach, A. R. & Song, H. eFloras: new directions for online floras exemplified by the Flora of China Project. Taxon 55, 188–192 (2006).

    Google Scholar 

  83. 83.

    Batjes, N. H. Global Distribution Of Soil Phosphorus Retention Potential http://www.isric.org/data/global-assessment-soil-phosphorus-retention-potential (2011).

  84. 84.

    Sayers, E. W. et al. Database resources of the national center for biotechnology information. Nucleic Acids Res. 37, D5 (2009).

    PubMed  CAS  Google Scholar 

  85. 85.

    Harmon, L. J, Weir, J. T, Brock, C. D, Glor, R. E. & Challenger, W. GEIGER: investigating evolutionary radiations. Bioinformatics 129–131 (2008).

  86. 86.

    Sanderson, E. W. et al. The human footprint and the last of the wild. Bioscience 52, 891 (2002).

    Google Scholar 

  87. 87.

    Kier, G. et al. Global patterns of plant diversity and floristic knowledge. J. Biogeogr. 32, 1107–1116 (2005).

    Google Scholar 

  88. 88.

    Lindeman, R., Merenda, P. & Gold, R. Introduction to Bivariate and Multivariate Analysis (Scott Foresman, London, 1980).

  89. 89.

    Rosseel, Y. lavaan: An R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2012).

    Google Scholar 

  90. 90.

    Schluter, D. Estimating the form of natural selection on a quantitative trait. Evolution 42, 849–861 (1988).

    PubMed  Google Scholar 

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Acknowledgements

We thank S. P. Otto for instructive comments and G. Berman and U. Roll for technical assistance. This work was supported by the Israel Science Foundation (grant number 961/17) to I.M., by the Czech Science Foundation (grant number P505 14–30313S) to P.S. and by a fellowship provided by the Edmond J. Safra Center for Bioinformatics at Tel-Aviv University to A.R.

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Contributions

A.R. and I.M. designed the study. A.R., M.N. and L.G. collected and processed the data. M.D. and N.S. reconstructed phylogenies and provided ploidy-level inferences. A.R. and P.S. analysed data. A.R., P.S., S.M. and J.B. analysed results. A.R. and I.M. drafted the manuscript. All authors provided comments and helped to improve the manuscript. I.M supervised the study.

Corresponding author

Correspondence to Itay Mayrose.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Texts 1–5, Supplementary Figures 1–3, and Supplementary Tables 2, 6, 8, 9 and 12

Reporting Summary

Supplementary Table 1

Lifeform database. The growth form, life cycle and lifeform of angiosperm species, including the ones analysed in this study

Supplementary Table 3

Ecoregions with polyploidy prevalence. A table describing the 827 ecoregions as defined by WWF with their relative number of species found in this research database (taxa with or without ploidy inference) as well as the percentage of polyploids in each. Ecoregions without data in the database are assigned with NA

Supplementary Table 4

The 528 ecoregions used for the analyses with their respective attributes. Occurrences denote for the number of data points in our database belonging to the respective ecoregion. Species are the number of recorded species in this ecoregions regardless of whether a ploidy inference was made or not. Diploids and polyploids are the number of species with this inference in the ecoregion. Polyploid percent is the number of polyploids out of the number of diploids and polyploids (frequency per ecoregion). The Binomial PV shows the significance of the Binomial test comparing the ecoregions frequency to its surrounding biome. This is followed by the rest of the eco-climatic attributes tested in this study

Supplementary Table 5

The results of the GLM test, together with the results of GLM over 100 bootstrap samplings. P-values are presented after multiple testing Bonferroni correction. The sample size tested for each variable is reported in the table

Supplementary Table 7

Relative importance results. Relative importance results of predictors to polyploid frequency across ecoregions (n = 528) with 100 bootstrap samplings

Supplementary Table 10

NCBI taxonomy classification into six major taxonomical groups. Each taxon in the database was classified to one of the six major taxonomical groups, based on their NCBI taxonomy

Supplementary Table 11

The set of rules used in each source for constructing the lifeform dataset. Each of the seven sources of plant lifeform obtained their own set of rules, based on which each taxon in our database was assigned with its final lifeform

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Rice, A., Šmarda, P., Novosolov, M. et al. The global biogeography of polyploid plants. Nat Ecol Evol 3, 265–273 (2019). https://doi.org/10.1038/s41559-018-0787-9

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