Article | Published:

Annual transcriptome dynamics in natural environments reveals plant seasonal adaptation

Nature Plantsvolume 5pages7483 (2019) | Download Citation

Abstract

As most organisms have evolved in seasonal environments, their environmental responses should be adapted to seasonal transitions. Here we show that the combination of temperature and day length shapes the seasonal dynamics of the transcriptome and adaptation to seasonal environments in a natural habitat of a perennial plant Arabidopsis halleri subsp. gemmifera. Weekly transcriptomes for two years and bihourly diurnal transcriptomes on the four equinoxes/solstices, identified 2,879 and 7,185 seasonally- and diurnally-oscillating genes, respectively. Dominance of annual temperature changes for defining seasonal oscillations of gene expressions was indicated by controlled environment experiments manipulating the natural 1.5-month lag of temperature behind day length. We found that plants have higher fitness in ‘natural’ chambers than in ‘unnatural’ chambers simulating in-phase and anti-phase oscillations between temperature and day length. Seasonal temperature responses were disturbed in unnatural chambers. Our results demonstrate how plants use multiple types of environmental information to adapt to seasonal environments.

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Data availability

The sequence data that support the findings of this study are available in the DDBJ Short Read Archive repository, with the accession numbers DRA005871, DRA005872, DRA005873, DRA005874, DRA005875 and DRA005876. Database of detailed results of individual genes is at http://sohi.ecology.kyoto-u.ac.jp/AhgRNAseq/.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Change history

  • 08 February 2019

    In Fig. 3b of the version of this Article originally published, a number of arrows indicating repression of downstream processes were mistakenly formatted as arrows indicating activation of downstream processes. This has now been amended in all versions of the Article.

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Acknowledgements

We thank Y. Kobayashi, K. Yoneya and Y. Sato for assistance and A. Dodd and N. Nakamichi for valuable discussion. This study was supported by JSPS Grant-in Aid for Scientific Research (S) no. 26221106 and JST CREST no. JPMJCR15O1 to H.K., and JST CREST no. JPMJCR15O2 and JSPS Grant-in Aid for Scientific Research nos. JP16H06171 and JP16H01473 to A.J.N.

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Affiliations

  1. Center for Ecological Research, Kyoto University, Otsu, Japan

    • Atsushi J. Nagano
    • , Tetsuhiro Kawagoe
    • , Jiro Sugisaka
    • , Mie N. Honjo
    •  & Hiroshi Kudoh
  2. Faculty of Agriculture, Ryukoku University, Otsu, Japan

    • Atsushi J. Nagano
    •  & Koji Iwayama
  3. Center for Data Science Education and Research, Shiga University, Hikone, Japan

    • Koji Iwayama

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Contributions

H.K. designed the project collaboratively with all co-authors. T.K. and J.S. conducted field experiments. J.S. and A.J.N. conducted GC experiments. M.N.H. conducted RNA-Seq experiments. A.J.N. and K.I. analysed data. A.J.N. and H.K. wrote the manuscript with input from all co-authors.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Hiroshi Kudoh.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–7.

  2. Reporting Summary

  3. Supplementary Data

    Supplementary Tables 1–9.

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DOI

https://doi.org/10.1038/s41477-018-0338-z