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.

Growth rate regulation is associated with developmental modification of source efficiency

Abstract

Plants modulate their growth rate according to seasonal and environmental cues using a suite of growth repressors known to interact directly with cellular machinery controlling cell division and growth. Mutants lacking growth repressors show increased growth rates1,2, but the mechanism by which these plants ensure source availability for faster growth is unclear. Here, we undertake a comprehensive analysis of the fast-growth phenotype of a quintuple growth-repressor mutant, using a combination of theoretical and experimental approaches to understand the physiological basis of source–sink coordination. Our results show that, in addition to the control of tissue growth rates, growth repressors also affect tissue composition and leaf thickness, modulating the efficiency of production of new photosynthetic capacity. Modelling suggests that increases in growth efficiency underlie growth-rate differences between the wild type and spatula della growth-repressor mutant, with spatula della requiring less carbon to synthesize a comparable photosynthetic capability to the wild type, and fixing more carbon per unit mass. We conclude that through control of leaf development, growth repressors regulate both source availability and sink strength to achieve growth-rate variation without risking a carbon deficit.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Detailed characterization of the enhanced growth phenotype of spt della.
Fig. 2: Constraining parameters to model Ler and spt della plant growth.
Fig. 3: Leaf and plant growth is source limited in Ler and spt della.
Fig. 4: Testing the causes of the enhanced growth of spt della using the Arabidopsis framework model.

Data availability

The data generated and analysed during this study are available from the corresponding author on reasonable request.

References

  1. 1.

    Sidaway-Lee, K. et al. SPATULA links daytime temperature and plant growth rate. Curr. Biol. 20, 1493–1497 (2010).

    CAS  Article  Google Scholar 

  2. 2.

    Achard, P. et al. Integration of plant responses to environmentally activated phytohormonal signals. Science 311, 91–94 (2006).

    CAS  Article  Google Scholar 

  3. 3.

    Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Change Biol. 9, 161–185 (2003).

    Article  Google Scholar 

  4. 4.

    Peng, J. et al. The Arabidopsis GAI gene defines a signaling pathway that negatively regulates gibberellin responses. Genes Dev. 11, 3194–3205 (1997).

    CAS  Article  Google Scholar 

  5. 5.

    Silverstone, A. L. et al. Repressing a repressor: gibberellin-induced rapid reduction of the RGA protein in Arabidopsis. Plant Cell 13, 1555–1566 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Koini, M. A. et al. High temperature-mediated adaptations in plant architecture require the bHLH transcription factor PIF4. Curr. Biol. 19, 408–413 (2009).

    CAS  Article  Google Scholar 

  7. 7.

    Ichihashi, Y., Horiguchi, G., Gleissberg, S. & Tsukaya, H. The bHLH transcription factor SPATULA controls final leaf size in Arabidopsis thaliana. Plant Cell Physiol. 51, 252–261 (2010).

    CAS  Article  Google Scholar 

  8. 8.

    Serrano-Mislata, A. et al. DELLA genes restrict inflorescence meristem function independently of plant height. Nat. Plants 3, 749–754 (2017).

    CAS  Article  Google Scholar 

  9. 9.

    White, A. C., Rogers, A., Rees, M. & Osborne, C. P. How can we make plants grow faster? A source–sink perspective on growth rate. J. Exp. Bot. 67, 31–45 (2015).

    Article  Google Scholar 

  10. 10.

    Körner, C. Paradigm shift in plant growth control. Curr. Opin. Plant Biol. 25, 107–114 (2015).

    Article  Google Scholar 

  11. 11.

    Josse, E. M. et al. A DELLA in disguise: SPATULA restrains the growth of the developing Arabidopsis seedling. Plant Cell 23, 1337–1351 (2011).

    CAS  Article  Google Scholar 

  12. 12.

    Achard, P. et al. The cold-inducible CBF1 factor-dependent signaling pathway modulates the accumulation of the growth-repressing DELLA proteins via its effect on gibberellin metabolism. Plant Cell 20, 2117–2129 (2008).

    CAS  Article  Google Scholar 

  13. 13.

    Makkena, S. & Lamb, R. S. The bHLH transcription factor SPATULA regulates root growth by controlling the size of the root meristem. BMC Plant Biol. 13, 1 (2013).

    CAS  Article  Google Scholar 

  14. 14.

    Ribeiro, D. M., Araújo, W. L., Fernie, A. R., Schippers, J. H. & Mueller-Roeber, B. Action of gibberellins on growth and metabolism of Arabidopsis plants associated with high concentration of carbon dioxide. Plant Physiol. 160, 1781–1794 (2012).

    CAS  Article  Google Scholar 

  15. 15.

    Paparelli, E. et al. Nighttime sugar starvation orchestrates gibberellin biosynthesis and plant growth in Arabidopsis. Plant Cell 25, 3760–3769 (2013).

    CAS  Article  Google Scholar 

  16. 16.

    Achard, P. et al. Gibberellin signaling controls cell proliferation rate in Arabidopsis. Curr. Biol. 19, 1188–1193 (2009).

    CAS  Article  Google Scholar 

  17. 17.

    Tyler, L. et al. DELLA proteins and gibberellin-regulated seed germination and floral development in Arabidopsis. Plant Physiol. 135, 1008–1019 (2004).

    CAS  Article  Google Scholar 

  18. 18.

    Penfield, S. et al. Cold and light control seed germination through the bHLH transcription factor SPATULA. Curr. Biol. 15, 1998–2006 (2005).

    CAS  Article  Google Scholar 

  19. 19.

    Barth, S., Busimi, A., Utz, H. F. & Melchinger, A. Heterosis for biomass yield and related traits in five hybrids of Arabidopsis thaliana L. Heynh. Heredity 91, 36–42 (2003).

    CAS  Article  Google Scholar 

  20. 20.

    Meyer, R. C., Törjék, O., Becher, M. & Altmann, T. Heterosis of biomass production in Arabidopsis. Establishment during early development. Plant Physiol. 134, 1813–1823 (2004).

    CAS  Article  Google Scholar 

  21. 21.

    Boyes, D. C. et al. Growth stage-based phenotypic analysis of Arabidopsis: a model for high throughput functional genomics in plants. Plant Cell 13, 1499–1510 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Chew, Y. H. et al. Multiscale digital Arabidopsis predicts individual organ and whole-organism growth. Proc. Natl Acad. Sci. USA 111, E4127–E4136 (2014).

    CAS  Article  Google Scholar 

  23. 23.

    Rasse, D. P. & Tocquin, P. Leaf carbohydrate controls over Arabidopsis growth and response to elevated CO2: an experimentally based model. New Phytol. 172, 500–513 (2006).

    CAS  Article  Google Scholar 

  24. 24.

    Christophe, A. et al. A model-based analysis of the dynamics of carbon balance at the whole-plant level in Arabidopsis thaliana. Funct. Plant Biol. 35, 1147–1162 (2008).

    CAS  Article  Google Scholar 

  25. 25.

    Zhou, J. et al. Leaf-GP: an open and automated software application for measuring growth phenotypes for Arabidopsis and wheat. Plant Methods 13, 117 (2017).

    Article  Google Scholar 

  26. 26.

    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS  Article  Google Scholar 

  27. 27.

    Friedland, G., Jantz, K. & Rojas, R. SIOX: simple interactive object extraction in still images. In 7th IEEE International Symposium on Multimedia 7–13 (IEEE, 2005).

  28. 28.

    Conn, S. J. et al. Protocol: optimising hydroponic growth systems for nutritional and physiological analysis of Arabidopsis thaliana and other plants. Plant Methods 9, 4 (2013).

    CAS  Article  Google Scholar 

  29. 29.

    R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016).

  30. 30.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, New York, 2016).

  31. 31.

    Eaton, J. W., Bateman, D., Hauberg, S. & Wehbring, R. GNU Octave Version 3.8.1 Manual: A High-Level Interactive Language for Numerical Computations (CreateSpace Independent Publishing Platform, 2014).

Download references

Acknowledgements

This work was supported by a Leverhulme Trust Research Project Grant.

Author information

Affiliations

Authors

Contributions

N.P. and S.P. designed the experiments. N.Z., A.D.A. and N.P. performed the experiments. N.P. analysed the data and performed the modelling. N.P. and S.P. wrote the paper.

Corresponding author

Correspondence to Steven Penfield.

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.

Supplementary information

Supplementary Information

Supplementary Figures 1–5, Supplementary Methods and Supplementary Table 1.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pullen, N., Zhang, N., Dobon Alonso, A. et al. Growth rate regulation is associated with developmental modification of source efficiency. Nature Plants 5, 148–152 (2019). https://doi.org/10.1038/s41477-018-0357-9

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing