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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.

References

  1. Franco-Zorrilla, J. M. & Solano, R. Identification of plant transcription factor target sequences. Biochim. Biophys. Acta 1860, 21–30 (2017).

    Article  CAS  Google Scholar 

  2. Lehti-Shiu, M. D., Panchy, N., Wang, P., Uygun, S. & Shiu, S. H. Diversity, expansion, and evolutionary novelty of plant DNA-binding transcription factor families. Biochim. Biophys. Acta 1860, 3–20 (2017).

    Article  CAS  Google Scholar 

  3. Jones, D. M. & Vandepoele, K. Identification and evolution of gene regulatory networks: insights from comparative studies in plants. Curr. Opin. Plant Biol. 54, 42–48 (2020).

    Article  CAS  PubMed  Google Scholar 

  4. Rhee, S. Y. & Mutwil, M. Towards revealing the functions of all genes in plants. Trends Plant Sci. 19, 212–221 (2014).

    Article  CAS  PubMed  Google Scholar 

  5. Gaudinier, A. & Brady, S. M. Mapping transcriptional networks in plants: data-driven discovery of novel biological mechanisms. Annu Rev. Plant Biol. 67, 575–594 (2016).

    Article  CAS  PubMed  Google Scholar 

  6. Ferrier, T., Matus, J. T., Jin, J. & Riechmann, J. L. Arabidopsis paves the way: genomic and network analyses in crops. Curr. Opin. Biotechnol. 22, 260–270 (2011).

    Article  CAS  PubMed  Google Scholar 

  7. Heyndrickx, K. S., Van de Velde, J., Wang, C., Weigel, D. & Vandepoele, K. A functional and evolutionary perspective on transcription factor binding in Arabidopsis thaliana. Plant Cell 26, 3894–3910 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Lu, Z., Hofmeister, B. T., Vollmers, C., DuBois, R. M. & Schmitz, R. J. Combining ATAC-seq with nuclei sorting for discovery of cis-regulatory regions in plant genomes. Nucleic Acids Res. 45, e41 (2017).

    Article  PubMed  CAS  Google Scholar 

  9. Maher, K. A. et al. Profiling of accessible chromatin regions across multiple plant species and cell types reveals common gene regulatory principles and new control modules. Plant Cell 30, 15–36 (2018).

    Article  CAS  PubMed  Google Scholar 

  10. Sijacic, P., Bajic, M., McKinney, E. C., Meagher, R. B. & Deal, R. B. Changes in chromatin accessibility between Arabidopsis stem cells and mesophyll cells illuminate cell type-specific transcription factor networks. Plant J. 94, 215–231 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kulkarni, S. R., Jones, D. M. & Vandepoele, K. Enhanced maps of transcription factor binding sites improve regulatory networks learned from accessible chromatin data. Plant Physiol. 181, 412–425 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Pajoro, A. et al. Dynamics of chromatin accessibility and gene regulation by MADS-domain transcription factors in flower development. Genome Biol. 15, R41 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Lee, I., Ambaru, B., Thakkar, P., Marcotte, E. M. & Rhee, S. Y. Rational association of genes with traits using a genome-scale gene network for Arabidopsis thaliana. Nat. Biotechnol. 28, 149–156 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Sullivan, A. M. et al. Mapping and dynamics of regulatory DNA and transcription factor networks in A. thaliana. Cell Rep. 8, 2015–2030 (2014).

    Article  CAS  PubMed  Google Scholar 

  15. Van de Velde, J., Van Bel, M., Vaneechoutte, D. & Vandepoele, K. A collection of conserved noncoding sequences to study gene regulation in flowering plants. Plant Physiol. 171, 2586–2598 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Huynh-Thu, V. A., Irrthum, A., Wehenkel, L. & Geurts, P. Inferring regulatory networks from expression data using tree-based methods. PLoS ONE 5, e12776 (2010).

  17. Marbach, D. et al. Wisdom of crowds for robust gene network inference. Nat. Methods 9, 796–804 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Yilmaz, A. et al. AGRIS: the Arabidopsis gene regulatory information server, an update. Nucleic Acids Res. 39, D1118–D1122 (2011).

    Article  CAS  PubMed  Google Scholar 

  19. Hussey, S. G., Mizrachi, E., Creux, N. M. & Myburg, A. A. Navigating the transcriptional roadmap regulating plant secondary cell wall deposition. Front Plant Sci. 4, 325 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Jin, J. et al. An Arabidopsis transcriptional regulatory map reveals distinct functional and evolutionary features of novel transcription factors. Mol. Biol. Evol. 32, 1767–1773 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Marbach, D. et al. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks. Genome Res. 22, 1334–1349 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kheradpour, P., Stark, A., Roy, S. & Kellis, M. Reliable prediction of regulator targets using 12 Drosophila genomes. Genome Res. 17, 1919–1931 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Van de Velde, J., Heyndrickx, K. S. & Vandepoele, K. Inference of transcriptional networks in Arabidopsis through conserved noncoding sequence analysis. Plant Cell 26, 2729–2745 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Tompa, M. et al. Assessing computational tools for the discovery of transcription factor binding sites. Nat. Biotechnol. 23, 137–144 (2005).

    Article  CAS  PubMed  Google Scholar 

  25. O’Maoileidigh, D. S., Graciet, E. & Wellmer, F. Gene networks controlling Arabidopsis thaliana flower development. New Phytol. 201, 16–30 (2014).

    Article  PubMed  Google Scholar 

  26. Luscombe, N. M. et al. Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 431, 308–312 (2004).

    Article  CAS  PubMed  Google Scholar 

  27. Song, L. et al. A transcription factor hierarchy defines an environmental stress response network. Science 354, aag1550 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Akiyama, K. et al. RARGE II: an integrated phenotype database of Arabidopsis mutant traits using a controlled vocabulary. Plant Cell Physiol. 55, e4 (2014).

    Article  CAS  PubMed  Google Scholar 

  29. Cheng, C. et al. An approach for determining and measuring network hierarchy applied to comparing the phosphorylome and the regulome. Genome Biol. 16, 63 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Lee, T. et al. AraNet v2: an improved database of co-functional gene networks for the study of Arabidopsis thaliana and 27 other nonmodel plant species. Nucleic Acids Res. 43, D996–D1002 (2015).

    Article  CAS  PubMed  Google Scholar 

  31. Kamiya, T. et al. The MYB36 transcription factor orchestrates Casparian strip formation. Proc. Natl Acad. Sci. USA 112, 10533–10538 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Willems et al. The ROS wheel: refining ROS transcriptional footprints. Plant Physiol. 171, 1720–1733 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  33. D’Alessandro, S., Ksas, B. & Havaux, M. Decoding beta-cyclocitral-mediated retrograde signaling reveals the role of a detoxification response in plant tolerance to photooxidative stress. Plant Cell 30, 2495–2511 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Fichman, Y. et al. MYB30 orchestrates systemic reactive oxygen signaling and plant acclimation. Plant Physiol. 184, 666–675 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Zandalinas, S. I., Sengupta, S., Burks, D., Azad, R. K. & Mittler, R. Identification and characterization of a core set of ROS wave-associated transcripts involved in the systemic acquired acclimation response of Arabidopsis to excess light. Plant J. 98, 126–141 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Meng, X. et al. Mitochondrial signalling is critical for acclimation and adaptation to flooding in Arabidopsis thaliana. Plant J. 103, 227–247 (2020).

    Article  CAS  PubMed  Google Scholar 

  37. Ryu, T. H. et al. SOG1-dependent NAC103 modulates the DNA damage response as a transcriptional regulator in Arabidopsis. Plant J. 98, 83–96 (2019).

    Article  CAS  PubMed  Google Scholar 

  38. Yin, M. et al. The Arabidopsis Cys2/His2 zinc finger transcription factor ZAT18 is a positive regulator of plant tolerance to drought stress. J. Exp. Bot. 68, 2991–3005 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Huang, P. Y. et al. NINJA-associated ERF19 negatively regulates Arabidopsis pattern-triggered immunity. J. Exp. Bot. 70, 1033–1047 (2019).

    Article  CAS  PubMed  Google Scholar 

  40. Scarpeci, T. E., Frea, V. S., Zanor, M. I. & Valle, E. M. Overexpression of AtERF019 delays plant growth and senescence, and improves drought tolerance in Arabidopsis. J. Exp. Bot. 68, 673–685 (2017).

    CAS  PubMed  Google Scholar 

  41. Hruz, T. et al. Genevestigator v3: a reference expression database for the meta-analysis of transcriptomes. Adv. Bioinforma. 2008, 420747 (2008).

    Article  Google Scholar 

  42. Heyman, J. et al. ERF115 controls root quiescent center cell division and stem cell replenishment. Science 342, 860–863 (2013).

    Article  CAS  PubMed  Google Scholar 

  43. Kong, X. et al. PHB3 maintains root stem cell niche identity through ROS-responsive AP2/ERF transcription factors in Arabidopsis. Cell Rep. 22, 1350–1363 (2018).

    Article  CAS  PubMed  Google Scholar 

  44. Chen, L., Xiang, S., Chen, Y., Li, D. & Yu, D. Arabidopsis WRKY45 interacts with the DELLA protein RGL1 to positively regulate age-triggered leaf senescence. Mol. Plant 10, 1174–1189 (2017).

    Article  CAS  PubMed  Google Scholar 

  45. Hinckley, W. E., Keymanesh, K., Cordova, J. A. & Brusslan, J. A. The HAC1 histone acetyltransferase promotes leaf senescence and regulates the expression of ERF022. Plant Direct 3, e00159 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Wang, H. et al. Arabidopsis WRKY45 transcription factor activates PHOSPHATE TRANSPORTER1;1 expression in response to phosphate starvation. Plant Physiol. 164, 2020–2029 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bustos, R. et al. A central regulatory system largely controls transcriptional activation and repression responses to phosphate starvation in Arabidopsis. PLoS Genet. 6, e1001102 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Frerigmann, H. & Gigolashvili, T. MYB34, MYB51, and MYB122 distinctly regulate indolic glucosinolate biosynthesis in Arabidopsis thaliana. Mol. Plant 7, 814–828 (2014).

    Article  CAS  PubMed  Google Scholar 

  49. Yin, Y. et al. A new class of transcription factors mediates brassinosteroid-regulated gene expression in Arabidopsis. Cell 120, 249–259 (2005).

    Article  CAS  PubMed  Google Scholar 

  50. Torres-Galea, P., Huang, L. F., Chua, N. H. & Bolle, C. The GRAS protein SCL13 is a positive regulator of phytochrome-dependent red light signaling, but can also modulate phytochrome A responses. Mol. Genet. Genomics 276, 13–30 (2006).

    Article  CAS  PubMed  Google Scholar 

  51. Lachowiec, J., Mason, G. A., Schultz, K. & Queitsch, C. Redundancy, feedback, and robustness in the Arabidopsis thaliana BZR/BEH gene family. Front. Genet. 9, 523 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Liu, P. P., Koizuka, N., Martin, R. C. & Nonogaki, H. The BME3 (Blue Micropylar End 3) GATA zinc finger transcription factor is a positive regulator of Arabidopsis seed germination. Plant J. 44, 960–971 (2005).

    Article  CAS  PubMed  Google Scholar 

  53. Nowak, K., Wojcikowska, B. & Gaj, M. D. ERF022 impacts the induction of somatic embryogenesis in Arabidopsis through the ethylene-related pathway. Planta 241, 967–985 (2015).

    Article  CAS  PubMed  Google Scholar 

  54. Hoang, X. L. T., Nhi, D. N. H., Thu, N. B. A., Thao, N. P. & Tran, L. P. Transcription factors and their roles in signal transduction in plants under abiotic stresses. Curr. Genomics 18, 483–497 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Hirsch, S. & Oldroyd, G. E. GRAS-domain transcription factors that regulate plant development. Plant Signal Behav. 4, 698–700 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Behringer, C. & Schwechheimer, C. B-GATA transcription factors—insights into their structure, regulation, and role in plant development. Front. Plant Sci. 6, 90 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Hudson, D. et al. Rice cytokinin GATA transcription Factor1 regulates chloroplast development and plant architecture. Plant Physiol. 162, 132–144 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Zhang, C. et al. Genome-wide survey of the soybean GATA transcription factor gene family and expression analysis under low nitrogen stress. PLoS ONE 10, e0125174 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Gupta, P., Nutan, K. K., Singla-Pareek, S. L. & Pareek, A. Abiotic stresses cause differential regulation of alternative splice forms of GATA transcription factor in rice. Front. Plant Sci. 8, 1944 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Brooks, M. D. et al. Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions. Nat. Commun. 10, 1569 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Gaudinier, A. et al. Transcriptional regulation of nitrogen-associated metabolism and growth. Nature 563, 259–264 (2018).

    Article  CAS  PubMed  Google Scholar 

  62. Zander, M. et al. Integrated multi-omics framework of the plant response to jasmonic acid. Nat. Plants 6, 290–302 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Reynoso, M. A. et al. Evolutionary flexibility in flooding response circuitry in angiosperms. Science 365, 1291–1295 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Smaczniak, C., Muino, J. M., Chen, D., Angenent, G. C. & Kaufmann, K. Differences in DNA binding specificity of floral homeotic protein complexes predict organ-specific target genes. Plant Cell 29, 1822–1835 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Ransbotyn, V. et al. A combination of gene expression ranking and co-expression network analysis increases discovery rate in large-scale mutant screens for novel Arabidopsis thaliana abiotic stress genes. Plant Biotechnol. J. 13, 501–513 (2015).

    Article  CAS  PubMed  Google Scholar 

  66. Liu, J. et al. Genome-wide analysis uncovers regulation of long intergenic noncoding RNAs in Arabidopsis. Plant Cell 24, 4333–4345 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Franco-Zorrilla, J. M. et al. DNA-binding specificities of plant transcription factors and their potential to define target genes. Proc. Natl Acad. Sci. USA 111, 2367–2372 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Weirauch, M. T. et al. Determination and inference of eukaryotic transcription factor sequence specificity. Cell 158, 1431–1443 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. O’Malley, R. C. et al. Cistrome and epicistrome features shape the regulatory DNA landscape. Cell 165, 1280–1292 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Vaneechoutte, D. & Vandepoele, K. Curse: building expression atlases and co-expression networks from public RNA-seq data. Bioinformatics 35, 2880–2881 (2019).

    Article  CAS  PubMed  Google Scholar 

  71. Patro, R., Mount, S. M. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32, 462–464 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Giorgi, F. M., Del Fabbro, C. & Licausi, F. Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana. Bioinformatics 29, 717–724 (2013).

    Article  CAS  PubMed  Google Scholar 

  74. Frith, M. C., Li, M. C. & Weng, Z. Cluster-Buster: finding dense clusters of motifs in DNA sequences. Nucleic Acids Res. 31, 3666–3668 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Jin, J., Zhang, H., Kong, L., Gao, G. & Luo, J. PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors. Nucleic Acids Res. 42, D1182–D1187 (2014).

    Article  CAS  PubMed  Google Scholar 

  76. Brady, S. M. et al. A stele-enriched gene regulatory network in the Arabidopsis root. Mol. Syst. Biol. 7, 459 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Li, B. et al. Promoter-based integration in plant defense regulation. Plant Physiol. 166, 1803–1820 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Taylor-Teeples, M. et al. An Arabidopsis gene regulatory network for secondary cell wall synthesis. Nature 517, 571–575 (2015).

    Article  CAS  PubMed  Google Scholar 

  79. Tian, C. et al. An organ boundary-enriched gene regulatory network uncovers regulatory hierarchies underlying axillary meristem initiation. Mol. Syst. Biol. 10, 755 (2014).

    Article  PubMed  CAS  Google Scholar 

  80. De Bodt, S., Hollunder, J., Nelissen, H., Meulemeester, N. & Inze, D. CORNET 2.0: integrating plant coexpression, protein–protein interactions, regulatory interactions, gene associations and functional annotations. New Phytol. 195, 707–720 (2012).

    Article  PubMed  CAS  Google Scholar 

  81. Nagel, D. H. et al. Genome-wide identification of CCA1 targets uncovers an expanded clock network in Arabidopsis. Proc. Natl Acad. Sci. USA 112, E4802–E4810 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Verkest, A. et al. A generic tool for transcription factor target gene discovery in Arabidopsis cell suspension cultures based on tandem chromatin affinity purification. Plant Physiol. 164, 1122–1133 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Birkenbihl, R. P., Diezel, C. & Somssich, I. E. Arabidopsis WRKY33 is a key transcriptional regulator of hormonal and metabolic responses toward Botrytis cinerea infection. Plant Physiol. 159, 266–285 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Merelo, P. et al. Genome-wide identification of KANADI1 target genes. PLoS ONE 8, e77341 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Qureshi, M. K., Sujeeth, N., Gechev, T. S. & Hille, J. The zinc finger protein ZAT11 modulates paraquat-induced programmed cell death in Arabidopsis thaliana. Acta Physiol. Plant. 35, 1863–1871 (2013).

    Article  CAS  Google Scholar 

  86. Liu, X. M. et al. ZAT11, a zinc finger transcription factor, is a negative regulator of nickel ion tolerance in Arabidopsis. Plant Cell Rep. 33, 2015–2021 (2014).

    Article  CAS  PubMed  Google Scholar 

  87. Rizhsky, L., Davletova, S., Liang, H. & Mittler, R. The zinc finger protein Zat12 is required for cytosolic ascorbate peroxidase 1 expression during oxidative stress in Arabidopsis. J. Biol. Chem. 279, 11736–11743 (2004).

    Article  CAS  PubMed  Google Scholar 

  88. Davletova, S., Schlauch, K., Coutu, J. & Mittler, R. The zinc-finger protein Zat12 plays a central role in reactive oxygen and abiotic stress signaling in Arabidopsis. Plant Physiol. 139, 847–856 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Scarpeci, T. E., Zanor, M. I., Mueller-Roeber, B. & Valle, E. M. Overexpression of AtWRKY30 enhances abiotic stress tolerance during early growth stages in Arabidopsis thaliana. Plant Mol. Biol. 83, 265–277 (2013).

    Article  CAS  PubMed  Google Scholar 

  90. Perez-Salamo, I. et al. The heat shock factor A4A confers salt tolerance and is regulated by oxidative stress and the mitogen-activated protein kinases MPK3 and MPK6. Plant Physiol. 165, 319–334 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Vanderauwera, S. et al. AtWRKY15 perturbation abolishes the mitochondrial stress response that steers osmotic stress tolerance in Arabidopsis. Proc. Natl Acad. Sci. USA 109, 20113–20118 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Mittler, R. et al. Gain- and loss-of-function mutations in Zat10 enhance the tolerance of plants to abiotic stress. FEBS Lett. 580, 6537–6542 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Sewelam, N. et al. Ethylene response factor 6 is a regulator of reactive oxygen species signaling in Arabidopsis. PLoS ONE 8, e70289 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Moffat, C. S. et al. ERF5 and ERF6 play redundant roles as positive regulators of JA/Et-mediated defense against Botrytis cinerea in Arabidopsis. PLoS ONE 7, e35995 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Dubois, M. et al. Ethylene Response Factor6 acts as a central regulator of leaf growth under water-limiting conditions in Arabidopsis. Plant Physiol. 162, 319–332 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Mahmood, K., Xu, Z., El-Kereamy, A., Casaretto, J. A. & Rothstein, S. J. The Arabidopsis transcription factor ANAC032 represses anthocyanin biosynthesis in response to high sucrose and oxidative and abiotic stresses. Front. Plant Sci. 7, 1548 (2016).

    PubMed  PubMed Central  Google Scholar 

  97. Allu, A. D., Brotman, Y., Xue, G. P. & Balazadeh, S. Transcription factor ANAC032 modulates JA/SA signalling in response to Pseudomonas syringae infection. EMBO Rep. 17, 1578–1589 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Babitha, K. C. et al. Co-expression of AtbHLH17 and AtWRKY28 confers resistance to abiotic stress in Arabidopsis. Transgenic Res. 22, 327–341 (2013).

    Article  CAS  PubMed  Google Scholar 

  99. Chen, X. et al. Overexpression of AtWRKY28 and AtWRKY75 in Arabidopsis enhances resistance to oxalic acid and Sclerotinia sclerotiorum. Plant Cell Rep. 32, 1589–1599 (2013).

    Article  CAS  PubMed  Google Scholar 

  100. Wu, L., Zhong, G., Wang, J., Li, X. & Yang, Y. Functional analysis of an Arabidopsis transcription factor WRKY28 in resistance to Alternaria brassicicola. J. Agric. Sci. Technol. 14, 65–71 (2012).

    CAS  Google Scholar 

  101. De Clercq, I. et al. The membrane-bound NAC transcription factor ANAC013 functions in mitochondrial retrograde regulation of the oxidative stress response in Arabidopsis. Plant Cell 25, 3472–3490 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Kim, J. B., Kang, J. Y. & Kim, S. Y. Over-expression of a transcription factor regulating ABA-responsive gene expression confers multiple stress tolerance. Plant Biotechnol. J. 2, 459–466 (2004).

    Article  CAS  PubMed  Google Scholar 

  103. Van Aken, O. et al. Mitochondrial and chloroplast stress responses are modulated in distinct touch and chemical inhibition phases. Plant Physiol. 171, 2150–2165 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Ng, S. et al. A membrane-bound NAC transcription factor, ANAC017, mediates mitochondrial retrograde signaling in Arabidopsis. Plant Cell 25, 3450–3471 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Dombrecht, B. et al. MYC2 differentially modulates diverse jasmonate-dependent functions in Arabidopsis. Plant Cell 19, 2225–2245 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Verma, D., Jalmi, S. K., Bhagat, P. K., Verma, N. & Sinha, A. K. A bHLH transcription factor, MYC2, imparts salt intolerance by regulating proline biosynthesis in Arabidopsis. FEBS J. 287, 2560–2576 (2020).

    Article  CAS  PubMed  Google Scholar 

  107. Song, S. et al. Interaction between MYC2 and ETHYLENE INSENSITIVE3 modulates antagonism between jasmonate and ethylene signaling in Arabidopsis. Plant Cell 26, 263–279 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Wu, A. et al. JUNGBRUNNEN1, a reactive oxygen species-responsive NAC transcription factor, regulates longevity in Arabidopsis. Plant Cell 24, 482–506 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Shahnejat-Bushehri, S., Nobmann, B., Devi Allu, A. & Balazadeh, S. JUB1 suppresses Pseudomonas syringae-induced defense responses through accumulation of DELLA proteins. Plant Signal. Behav. 11, e1181245 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  110. Ebrahimian-Motlagh, S. et al. JUNGBRUNNEN1 confers drought tolerance downstream of the HD-Zip I transcription factor AtHB13. Front. Plant Sci. 8, 2118 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  111. Nishizawa, A. et al. Arabidopsis heat shock transcription factor A2 as a key regulator in response to several types of environmental stress. Plant J. 48, 535–547 (2006).

    Article  CAS  PubMed  Google Scholar 

  112. Nishizawa-Yokoi, A., Yabuta, Y. & Shigeoka, S. The contribution of carbohydrates including raffinose family oligosaccharides and sugar alcohols to protection of plant cells from oxidative damage. Plant Signal. Behav. 3, 1016–1018 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  113. Zhang, L., Li, Y., Xing, D. & Gao, C. Characterization of mitochondrial dynamics and subcellular localization of ROS reveal that HsfA2 alleviates oxidative damage caused by heat stress in Arabidopsis. J. Exp. Bot. 60, 2073–2091 (2009).

    Article  CAS  PubMed  Google Scholar 

  114. Olate, E., Jimenez-Gomez, J. M., Holuigue, L. & Salinas, J. NPR1 mediates a novel regulatory pathway in cold acclimation by interacting with HSFA1 factors. Nat. Plants 4, 811–823 (2018).

    Article  CAS  PubMed  Google Scholar 

  115. Enomoto, T. et al. STOP1 regulates the expression of HsfA2 and GDHs that are critical for low-oxygen tolerance in Arabidopsis. J. Exp. Bot. 70, 3297–3311 (2019).

    Article  CAS  PubMed  Google Scholar 

  116. Hsieh, T. H. et al. Heterology expression of the Arabidopsis C-repeat/dehydration response element binding factor 1 gene confers elevated tolerance to chilling and oxidative stresses in transgenic tomato. Plant Physiol. 129, 1086–1094 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Jaglo-Ottosen, K. R., Gilmour, S. J., Zarka, D. G., Schabenberger, O. & Thomashow, M. F. Arabidopsis CBF1 overexpression induces COR genes and enhances freezing tolerance. Science 280, 104–106 (1998).

    Article  CAS  PubMed  Google Scholar 

  118. Hsieh, T. H., Lee, J. T., Charng, Y. Y. & Chan, M. T. Tomato plants ectopically expressing Arabidopsis CBF1 show enhanced resistance to water deficit stress. Plant Physiol. 130, 618–626 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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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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