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Integrative inference of transcriptional networks in Arabidopsis yields novel ROS signalling regulators

Nature Plants volume 7, pages 500–513 (2021)Cite this article

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Abstract

Gene regulation is a dynamic process in which transcription factors (TFs) play an important role in controlling spatiotemporal gene expression. To enhance our global understanding of regulatory interactions in Arabidopsis thaliana, different regulatory input networks capturing complementary information about DNA motifs, open chromatin, TF-binding and expression-based regulatory interactions were combined using a supervised learning approach, resulting in an integrated gene regulatory network (iGRN) covering 1,491 TFs and 31,393 target genes (1.7 million interactions). This iGRN outperforms the different input networks to predict known regulatory interactions and has a similar performance to recover functional interactions compared to state-of-the-art experimental methods. The iGRN correctly inferred known functions for 681 TFs and predicted new gene functions for hundreds of unknown TFs. For regulators predicted to be involved in reactive oxygen species (ROS) stress regulation, we confirmed in total 75% of TFs with a function in ROS and/or physiological stress responses. This includes 13 ROS regulators, previously not connected to any ROS or stress function, that were experimentally validated in our ROS-specific phenotypic assays of loss- or gain-of-function lines. In conclusion, the presented iGRN offers a high-quality starting point to enhance our understanding of gene regulation in plants by integrating different experimental data types.

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Fig. 1: Construction and evaluation of the iGRN.
Fig. 2: Overlap between iGRN interactions and different experimental data sources describing gene regulatory and functional information.
Fig. 3: Phenotypes reported after TF perturbation for TFs with different network centrality properties.
Fig. 4: Oxidative stress phenotyping results of NOVEL ROS TFs.
Fig. 5: Representative images of oxidative stress phenotypes for a selection of mutants.
Fig. 6: Expression of KNOWN and NOVEL ROS TFs during various conditions provoking cellular ROS/redox imbalances.

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Data availability

The raw data for Supplementary Fig. 3 are available as Supplementary Data. Source data are provided with this paper.

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Acknowledgements

We thank C. Bolle (SCL13), X. Chen (ARF3), Y.-F. Chen (WRKY45), D. Fernandez (AGL15), H. Frerigmann (MYB51, MYB122), M. Gaj (ERF022), T. Gigolashvili (MYB51), D. Hegedus (SCL15), L. Hennig (AGL19), I. Hwang (BME3), Z. Liu (TSO1), L. Østergaard (ARF3), J. Paz-Ares (PHL1) and O. Van Aken (WRKY45) for kindly providing the Arabidopsis mutant lines noted in parentheses. We thank Z. Joly-Lopez and O. Wilkins for providing in-depth comments on an earlier version of the manuscript, as well as C. Ferrari and I. Dissanayake for proofreading. I.D.C. is supported by the Research Foundation Flanders (postdoctoral fellowship 12N2415N and grant for a long stay abroad V400620N). J.V.d.V. is indebted to the Agency for Innovation by Science and Technology in Flanders for a predoctoral fellowship. X.L. and L.L. are supported by the China Scholarship Council for a PhD fellowship (201706910099 and 201808530499). F.V.B. is supported by the Fonds Wetenschappelijk Onderzoek—Vlaanderen (FWO) and the Fonds de la Recherche Scientifique (FNRS) under EOS project no. 30829584 and the Research Foundation Flanders (project nos. G0D7914N and G055416N).

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  1. These authors contributed equally: Inge De Clercq, Jan Van de Velde.

Authors and Affiliations

  1. Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium

    Inge De Clercq, Jan Van de Velde, Xiaopeng Luo, Li Liu, Veronique Storme, Michiel Van Bel, Robin Pottie, Dries Vaneechoutte, Frank Van Breusegem & Klaas Vandepoele

  2. VIB Center for Plant Systems Biology, Ghent, Belgium

    Inge De Clercq, Jan Van de Velde, Xiaopeng Luo, Li Liu, Veronique Storme, Michiel Van Bel, Robin Pottie, Dries Vaneechoutte, Frank Van Breusegem & Klaas Vandepoele

  3. Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium

    Jan Van de Velde, Li Liu, Dries Vaneechoutte & Klaas Vandepoele

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  1. Inge De Clercq
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Contributions

J.V.d.V., I.D.C. and K.V. designed the research. I.D.C., X.L., L.L. and R.P. performed the phenotype screening. V.S. performed statistical data analysis. D.V. generated the expression compendium. J.V.d.V. and K.V. performed network analysis and function prediction. J.V.d.V., I.D.C., F.V.B. and K.V. wrote the manuscript.

Corresponding authors

Correspondence to Inge De Clercq or Klaas Vandepoele.

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Peer review information Nature Plants thanks Oscar Lorenzo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figures 1–5.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–10.

Supplementary Data 1

Overview of generated, analysed and used iGRN TF function data for Supplementary Fig. 3.

Source data

Source Data Fig. 1

Overview of generated, analysed and used iGRN regulatory interaction data for Fig. 1.

Source Data Fig. 4

Overview of raw phenotyping measurements for Fig. 4.

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De Clercq, I., Van de Velde, J., Luo, X. et al. Integrative inference of transcriptional networks in Arabidopsis yields novel ROS signalling regulators. Nat. Plants 7, 500–513 (2021). https://doi.org/10.1038/s41477-021-00894-1

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