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Tuning water-use efficiency and drought tolerance in wheat using abscisic acid receptors

Nature Plants volume 5, pages 153–159 (2019)Cite this article

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An Author Correction to this article was published on 24 April 2023

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Abstract

Water availability is a key determinant of terrestrial plant productivity. Many climate models predict that water stress will increasingly challenge agricultural yields and exacerbate projected food deficits. To ensure food security and increase agricultural efficiency, crop water productivity must be increased. Research over past decades has established that the phytohormone abscisic acid (ABA) is a central regulator of water use and directly regulates stomatal opening and transpiration. In this study, we investigated whether the water productivity of wheat could be improved by increasing its ABA sensitivity. We show that overexpression of a wheat ABA receptor increases wheat ABA sensitivity, which significantly lowers a plant’s lifetime water consumption. Physiological analyses demonstrated that this water-saving trait is a consequence of reduced transpiration and a concomitant increase in photosynthetic activity, which together boost grain production per litre of water and protect productivity during water deficit. Our findings provide a general strategy for increasing water productivity that should be applicable to other crops because of the high conservation of the ABA signalling pathway.

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Fig. 1: Molecular characterization of wheat ABA receptors.
Fig. 2: ABA receptor overexpression confers drought tolerance.
Fig. 3: ABA receptor overexpression improves WUE in photosynthesis.
Fig. 4: Improvement of biomass production, seed production and water conservation by ABA receptor overexpression.

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Data availability

Newly identified wheat ABA receptors (TaPYLs) were deposited in NCBI databases: TaPYL1, MG273651; TaPYL3, MG273653; TaPYL6, MG273656; TaPYL7, MG273657; TaPYL8, MG273658; and TaPYL9, MG273659. To update TaPYL2, TaPYL4 and TaPYL5 information, MG273652, MG273654 and MG273655, respectively, were also deposited. The wheat reference gene annotation and sequence (International Wheat Genome Sequencing Consortium version 1.1) are available at https://wheat-urgi.versailles.inra.fr/Seq-Repository/Annotations. The raw sequence and processed data for our RNA-Seq analysis were deposited in the NCBI Gene Expression Omnibus database under the specific accession number GSE79522.

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Acknowledgements

We thank Y. Kano, T. Shimizu and Y. Imai (Tottori University) for facility maintenance, W. Yamori (The University of Tokyo) and K. Hikosaka (Tohoku University) for advice on photosynthetic analyses, M. Inoue (Tottori University) for help with calculations of SWP from SWC, and K. Shimamoto (Nara Institute of Science and Technology) for providing the p2K-1GW plasmid. We also express our gratitude to the CIMMYT and ICARDA for providing wheat cultivar seeds, and thank the NBRP for providing TaPYL4 complementary DNA. This work was supported by grants from JST PRESTO (JPMJPR15Q5 to M.O.), KAKENHI (17H05009 to M.O.), Project Marginal Region Agriculture of Tottori University (to H.T. and M.O.), the Joint Research Program of Arid Land Research Center, Tottori University (30C2007 to M.O.), the NSF (IOS1258175 and 1656890 to S.R.C.) and the Cooperative Research Grant of the Genome Research for BioResource, NODAI Genome Research Center, Tokyo University of Agriculture.

Author information

Author notes

  1. Hisato Kobayashi

    Present address: Department of Embryology, Nara Medical University, Nara, Japan

Authors and Affiliations

  1. Arid Land Research Center, Tottori University, Tottori, Japan

    Ryosuke Mega, Hisashi Tsujimoto & Masanori Okamoto

  2. NARO Institute of Crop Science, Tsukuba, Japan

    Fumitaka Abe

  3. Gene Discovery Research Group, RIKEN Center for Sustainable Resource Science, Tsukuba, Japan

    June-Sik Kim

  4. Environmental Metabolic Analysis Research Team, RIKEN Center for Sustainable Resource Science, Yokohama, Japan

    Yuuri Tsuboi & Jun Kikuchi

  5. NODAI Genome Research Center, Tokyo University of Agriculture, Tokyo, Japan

    Keisuke Tanaka & Hisato Kobayashi

  6. Department of Bioscience, Tokyo University of Agriculture, Tokyo, Japan

    Yoichi Sakata

  7. Frontier Research Academy for Young Researchers, Kyushu Institute of Technology, Kitakyushu, Japan

    Kousuke Hanada

  8. Department of Botany and Plant Sciences, Institute of Integrative Genome Biology, University of California, Riverside, CA, USA

    Sean R. Cutler

  9. Center for Bioscience Research and Education, Utsunomiya University, Utsunomiya, Japan

    Masanori Okamoto

  10. PRESTO, Japan Science and Technology Agency, Kawaguchi, Japan

    Masanori Okamoto

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Contributions

R.M. and M.O. conceived the project and planned the experiments. F.A. generated the TaPYLox lines. K.T., H.K. and Y.S. performed the RNA-Seq experiments. J.-S.K. analysed the data. Y.T. and J.K. performed the NMR experiments and data analysis. H.T. provided wheat materials and supervised the research. J.-S.K. and K.H. searched for fragment sequences of TaPYLs in the draft wheat genome. R.M. and M.O. performed all of the other experiments. R.M., S.R.C. and M.O. wrote the manuscript. All authors commented on the manuscript.

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Correspondence to Masanori Okamoto.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Figures 1–12, Supplementary Video Legend, Supplementary Methods and Supplementary References.

Reporting Summary

Supplementary Table 1

Identified Ta PYLs and TaPP2Cs superimposed on the current wheat genome (IWGSC.v1). TPM values were derived from three biologically independent samples. FDR was calculated using LRT built-in function of Sleuth v0.44 for multiple comparison.

Supplementary Table 2

Differential gene expression between Null and L8 under well-watered, ABA-treated and water-deficient conditions (WWC, ABA and drought, respectively; n = 3 biologically independent samples). FDR was calculated using LRT built-in function of Sleuth v0.44 for multiple comparison.

Supplementary Table 3

Actual copy numbers of heatmaps shown in Fig. 1c and d. Data are mean ± s.d. (n = 3 biologically independent samples).

Supplementary Table 4

Primers used in this study.

Supplementary Video 1

A movie showing the gradual wilting of four types of cultivars.

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Mega, R., Abe, F., Kim, JS. et al. Tuning water-use efficiency and drought tolerance in wheat using abscisic acid receptors. Nat. Plants 5, 153–159 (2019). https://doi.org/10.1038/s41477-019-0361-8

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