Skip to main content

Thank you for visiting 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.

A network of transcriptional repressors modulates auxin responses

A Publisher Correction to this article was published on 23 December 2020

This article has been updated


The regulation of signalling capacity, combined with the spatiotemporal distribution of developmental signals themselves, is pivotal in setting developmental responses in both plants and animals1. The hormone auxin is a key signal for plant growth and development that acts through the AUXIN RESPONSE FACTOR (ARF) transcription factors2,3,4. A subset of these, the conserved class A ARFs5, are transcriptional activators of auxin-responsive target genes that are essential for regulating auxin signalling throughout the plant lifecycle2,3. Although class A ARFs have tissue-specific expression patterns, how their expression is regulated is unknown. Here we show, by investigating chromatin modifications and accessibility, that loci encoding these proteins are constitutively open for transcription. Through yeast one-hybrid screening, we identify the transcriptional regulators of the genes encoding class A ARFs from Arabidopsis thaliana and demonstrate that each gene is controlled by specific sets of transcriptional regulators. Transient transformation assays and expression analyses in mutants reveal that, in planta, the majority of these regulators repress the transcription of genes encoding class A ARFs. These observations support a scenario in which the default configuration of open chromatin enables a network of transcriptional repressors to regulate expression levels of class A ARF proteins and modulate auxin signalling output throughout development.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Tissue-specific expression patterns and chromatin landscape of Arabidopsis class A ARF loci.
Fig. 2: Class A ARF transcription is regulated by repressors.
Fig. 3: Expression levels and patterns of class ARF genes are altered when upstream transcription factors are modulated.

Data availability

The data including the source data that supports the finding of this study are available within the paper, its supplementary information files or publicly available datasets. Publicly available position weight matrices were obtained from the Jaspar and CisBP databases. Publicly available chromatin marking and accessibility datasets were acquired from the GEO and ArrayExpress databases with the following accession numbers: GSE24665, GSE24658, GSE7907, GSE24507, GSE50636, GSE24657, GSE24710, GSE19654, GSM2260231, GSM2260232, GSM2260235, GSM2260236, GSM2704255, GSM2704256, GSM2719200, GSM2719201, GSM2719202, GSM2719203, GSM2719204, GSM2719205, GSM1289362, GSM1289374, E-MTAB-4680, E-MTAB-4684 and GSM1289358.

Change history

  • 23 December 2020

    A Correction to this paper has been published:


  1. 1.

    Sagner, A. & Briscoe, J. Morphogen interpretation: concentration, time, competence, and signaling dynamics. Wiley Interdiscip. Rev. Dev. Biol. 6, e271 (2017).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Leyser, O. Auxin signaling. Plant Physiol. 176, 465–479 (2018).

    CAS  Google Scholar 

  3. 3.

    Tiwari, S. B., Hagen, G. & Guilfoyle, T. The roles of auxin response factor domains in auxin-responsive transcription. Plant Cell 15, 533–543 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Petrásek, J. & Friml, J. Auxin transport routes in plant development. Development 136, 2675–2688 (2009).

    Google Scholar 

  5. 5.

    Finet, C., Berne-Dedieu, A., Scutt, C. P. & Marlétaz, F. Evolution of the ARF gene family in land plants: old domains, new tricks. Mol. Biol. Evol. 30, 45–56 (2013).

    CAS  Google Scholar 

  6. 6.

    Krogan, N. T., Marcos, D., Weiner, A. I. & Berleth, T. The auxin response factor MONOPTEROS controls meristem function and organogenesis in both the shoot and root through the direct regulation of PIN genes. New Phytol. 212, 42–50 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Berleth, T. & Jurgens, G. The role of the monopteros gene in organising the basal body region of the Arabidopsis embryo. Development 118, 575–587 (1993).

    Google Scholar 

  8. 8.

    Przemeck, G. K., Mattsson, J., Hardtke, C. S., Sung, Z. R. & Berleth, T. Studies on the role of the Arabidopsis gene MONOPTEROS in vascular development and plant cell axialization. Planta 200, 229–237 (1996).

    CAS  Google Scholar 

  9. 9.

    Schlereth, A. et al. MONOPTEROS controls embryonic root initiation by regulating a mobile transcription factor. Nature 464, 913–916 (2010).

    ADS  CAS  Google Scholar 

  10. 10.

    Nagpal, P. et al. Auxin response factors ARF6 and ARF8 promote jasmonic acid production and flower maturation. Development 132, 4107–4118 (2005).

    CAS  PubMed  Google Scholar 

  11. 11.

    Gutierrez, L. et al. Phenotypic plasticity of adventitious rooting in Arabidopsis is controlled by complex regulation of AUXIN RESPONSE FACTOR transcripts and microRNA abundance. Plant Cell 21, 3119–3132 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Okushima, Y. et al. Functional genomic analysis of the AUXIN RESPONSE FACTOR gene family members in Arabidopsis thaliana: unique and overlapping functions of ARF7 and ARF19. Plant Cell 17, 444–463 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Harper, R. M. et al. The NPH4 locus encodes the auxin response factor ARF7, a conditional regulator of differential growth in aerial Arabidopsis tissue. Plant Cell 12, 757–770 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Rademacher, E. H. et al. A cellular expression map of the Arabidopsis AUXIN RESPONSE FACTOR gene family. Plant J. 68, 597–606 (2011).

    CAS  Google Scholar 

  15. 15.

    Vernoux, T. et al. The auxin signalling network translates dynamic input into robust patterning at the shoot apex. Mol. Syst. Biol. 7, 508 (2011).

    PubMed  PubMed Central  Google Scholar 

  16. 16.

    Hardtke, C. S. & Berleth, T. The Arabidopsis gene MONOPTEROS encodes a transcription factor mediating embryo axis formation and vascular development. EMBO J. 17, 1405–1411 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Roudier, F. et al. Integrative epigenomic mapping defines four main chromatin states in Arabidopsis. EMBO J. 30, 1928–1938 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Gifford, M. L., Dean, A., Gutierrez, R. A., Coruzzi, G. M. & Birnbaum, K. D. Cell-specific nitrogen responses mediate developmental plasticity. Proc. Natl Acad. Sci. USA 105, 803–808 (2008).

    ADS  CAS  Google Scholar 

  19. 19.

    Jay, F. et al. Misregulation of AUXIN RESPONSE FACTOR 8 underlies the developmental abnormalities caused by three distinct viral silencing suppressors in Arabidopsis. PLoS Pathog. 7, e1002035 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

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

    PubMed  PubMed Central  Google Scholar 

  21. 21.

    Ma, Y. et al. WUSCHEL acts as an auxin response rheostat to maintain apical stem cells in Arabidopsis. Nat. Commun. 10, 5093 (2019).

    ADS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Zhao, Z. et al. Hormonal control of the shoot stem-cell niche. Nature 465, 1089–1092 (2010).

    ADS  CAS  Google Scholar 

  23. 23.

    Leibfried, A. et al. WUSCHEL controls meristem function by direct regulation of cytokinin-inducible response regulators. Nature 438, 1172–1175 (2005).

    ADS  CAS  Google Scholar 

  24. 24.

    Dharmasiri, N. et al. Plant development is regulated by a family of auxin receptor F box proteins. Dev. Cell 9, 109–119 (2005).

    CAS  Google Scholar 

  25. 25.

    Kim, D.-H. & Sung, S. Polycomb-mediated gene silencing in Arabidopsis thaliana. Mol. Cells 37, 841–850 (2014).

    PubMed  PubMed Central  Google Scholar 

  26. 26.

    Orosa-Puente, B. et al. Root branching toward water involves posttranslational modification of transcription factor ARF7. Science 362, 1407–1410 (2018).

    ADS  CAS  Google Scholar 

  27. 27.

    Cho, H. et al. A secreted peptide acts on BIN2-mediated phosphorylation of ARFs to potentiate auxin response during lateral root development. Nat. Cell Biol. 16, 66–76 (2014).

    CAS  Google Scholar 

  28. 28.

    Ptashne, M. Repressors. Curr. Biol. 17, R740–R741 (2007).

    CAS  Google Scholar 

  29. 29.

    Jacob, F. & Monod, J. Genetic regulatory mechanisms in the synthesis of proteins. J. Mol. Biol. 3, 318–356 (1961).

    CAS  Google Scholar 

  30. 30.

    Clough, S. J. & Bent, A. F. Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J. 16, 735–743 (1998).

    CAS  Google Scholar 

  31. 31.

    Gaudinier, A. et al. Enhanced Y1H assays for Arabidopsis. Nat. Methods 8, 1053–1055 (2011).

    CAS  Google Scholar 

  32. 32.

    Kim, J. H. et al. High cleavage efficiency of a 2A peptide derived from porcine teschovirus-1 in human cell lines, zebrafish and mice. PLoS ONE 6, e18556 (2011).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Trichas, G., Begbie, J. & Srinivas, S. Use of the viral 2A peptide for bicistronic expression in transgenic mice. BMC Biol. 6, 40 (2008).

    PubMed  PubMed Central  Google Scholar 

  34. 34.

    George, E. O. & Mudholkar, G. S. On the convolution of logistic random variables. Metrika 30, 1–13 (1983).

    MathSciNet  MATH  Google Scholar 

  35. 35.

    Paponov, I. A. et al. Comprehensive transcriptome analysis of auxin responses in Arabidopsis. Mol. Plant 1, 321–337 (2008).

    CAS  Google Scholar 

  36. 36.

    Siligato, R. et al. MultiSite Gateway-compatible cell type-specific gene-inducible system for plants. Plant Physiol. 170, 627–641 (2016).

    CAS  Google Scholar 

  37. 37.

    Smetana, O. et al. High levels of auxin signalling define the stem-cell organizer of the vascular cambium. Nature 565, 485–489 (2019).

    ADS  CAS  Google Scholar 

  38. 38.

    Brady, S. M. et al. A high-resolution root spatiotemporal map reveals dominant expression patterns. Science 318, 801–806 (2007).

    ADS  CAS  Google Scholar 

  39. 39.

    Yadav, R. K., Girke, T., Pasala, S., Xie, M. & Reddy, G. V. Gene expression map of the Arabidopsis shoot apical meristem stem cell niche. Proc. Natl Acad. Sci. USA 106, 4941–4946 (2009).

    ADS  CAS  Google Scholar 

  40. 40.

    Yadav, R. K., Tavakkoli, M., Xie, M., Girke, T. & Reddy, G. V. A high-resolution gene expression map of the Arabidopsis shoot meristem stem cell niche. Development 141, 2735–2744 (2014).

    CAS  Google Scholar 

  41. 41.

    Oh, S., Park, S. & van Nocker, S. Genic and global functions for Paf1C in chromatin modification and gene expression in Arabidopsis. PLoS Genet. 4, e1000077 (2008).

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Willing, E.-M. et al. Genome expansion of Arabis alpina linked with retrotransposition and reduced symmetric DNA methylation. Nat. Plants 1, 14023 (2015).

    CAS  Google Scholar 

  43. 43.

    Deal, R. B. & Henikoff, S. A simple method for gene expression and chromatin profiling of individual cell types within a tissue. Dev. Cell 18, 1030–1040 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    You, Y. et al. Temporal dynamics of gene expression and histone marks at the Arabidopsis shoot meristem during flowering. Nat. Commun. 8, 15120 (2017).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Lafos, M. et al. Dynamic regulation of H3K27 trimethylation during Arabidopsis differentiation. PLoS Genet. 7, e1002040 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

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

    CAS  Google Scholar 

  47. 47.

    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).

    Google Scholar 

  48. 48.

    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).

    CAS  Google Scholar 

  49. 49.

    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).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

    Google Scholar 

  51. 51.

    Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Khan, A. et al. JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework. Nucleic Acids Res. 46 (D1), D260–D266 (2018).

    CAS  Google Scholar 

  53. 53.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Berger, N., Dubreucq, B., Roudier, F., Dubos, C. & Lepiniec, L. Transcriptional regulation of Arabidopsis LEAFY COTYLEDON2 involves RLE, a cis-element that regulates trimethylation of histone H3 at lysine-27. Plant Cell 23, 4065–4078 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Yu, C.-P., Lin, J.-J. & Li, W.-H. Positional distribution of transcription factor binding sites in Arabidopsis thaliana. Sci. Rep. 6, 25164 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Goda, H. et al. The AtGenExpress hormone and chemical treatment data set: experimental design, data evaluation, model data analysis and data access. Plant J. 55, 526–542 (2008).

    CAS  Google Scholar 

Download references


We thank F. Besnard, A. Larrieu and R. Azaïs for their help with data analysis and statistics; M. Herpola for RNA in situ hybridization analysis; G. Castiglione for help with root phenotyping; A. Mathelier for help with JASPAR; and D. Weijers for ARF transcriptional reporter lines. This work was supported by a joint INRA/University of Nottingham PhD grant to J.T.; ANR-2014-CE11-0018 grant and Human Frontier Science Program organization (HFSP) grant RPG0054-2013 to T.V.; a Royal Society University Research Fellowship and enhancement award (UF110249 and RGF\EA\180308) to A.B.; a starting grant from the Programme Avenir Lyon Saint Etienne (ANR-11-IDEX-0007) to F.R.; an HHMI Faculty Scholar fellowship to S.M.B.; ANR-10-LABX-49-01 and ANR-17-EURE-0003 to F.P.; ANR-18-CE12-0014-02 to T.V., F.R. and F.P.; and Aux-ID CNRS PICS grant to T.V., A.B. and E.F.

Author information




A.B. and T.V. designed the study and supervised the work; J.T., F.P., F.R., E.F., S.M.B., A.B. and T.V. designed the experiments; J.T., A-M.B. and M.E.S. performed the eY1H screen with the help of S.P. and M.B.; J.T., J.H., E.C., C.S.G.-A., S.L. and G.B. performed all experiments in relation to TF biological activity characterization; J.L. performed the statistical analysis of the protoplast experiment and participated in all statistical analysis; O.S. and A.P.M. performed the in situ hybridization experiments; A.S. and F.P. performed TF binding site analysis; S.B. and E.F. performed the modelling analysis; J.M. and F.R. performed the epigenetic data analysis; all authors were involved in data analysis; J.T., A.B. and T.V. wrote the manuscript with inputs from all authors.

Corresponding authors

Correspondence to Anthony Bishopp or Teva Vernoux.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks the anonymous reviewer(s) for their contribution to the peer review of this work.

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

Extended data figures and tables

Extended Data Fig. 1 Analysis of class A ARF expression in the RAM and the SAM using transcriptional reporter lines and in situ hybridization.

aj, Confocal images showing expression of ARF5 (a, f), ARF6 (b, g), ARF7 (c, h), ARF8 (d, i) and ARF19 (e, j) in the RAM and the SAM using promoters that lack sequences downstream of the start codon but contain the long upstream sequences (pARF−intron::mVenus) (~3 kb for ARF6 and ARF7; 5 kb for ARF5, ARF8 and ARF19) (see Methods). For SAM images (fj) an orthogonal projection is shown below to provide information about expression in different layers. ko, For comparison, the expression of each class A ARF gene in the SAM using the previously published pARF::GFP lines with shorter (~2 kb) promoters containing sequences upstream of the start codon is shown in panels ko14. ARF5 (k), ARF6 (l), ARF7 (m), ARF8 (n) and ARF19 (o). (pr) In situ hybridizations through the RAM for ARF5 (p), ARF6 (q) and ARF8 (r). Note that expression patterns of the class A ARF reporters (aj) differ from those with shorter (2 kb) promoters (ko14) and recapitulate the patterns observed with RNA in situ hybridization (pr; ref. 16). This was particularly clear in the shoot for ARF5 and ARF6. Shorter promoters drive GFP expression mostly in flower boundaries for ARF5 and throughout the meristem for ARF6, in contrast with detection of both genes throughout the periphery of the meristem both with longer promoters (ko; also Fig. 1f–j) or using in situ hybridization15. Experiments were done three (ae) and two times (fr). Scale bars: 50 μm.

Extended Data Fig. 2 Distribution of the repressive chromatin marker H3K27me3, the active chromatin marker H3K4me3 and chromatin accessibility at class A ARF loci.

a, Chromatin landscape of class A ARF and LEC2 in whole seedlings illustrating the chromatin status of class A ARF loci. Repressive H3K27me3 marker (top row), active H3K4me3 marker (middle row) and FANS-ATAC chromatin accessibility (bottom row; see Supplementary Table 1). b, c, Chromatin landscape of class A ARF and LEC2 loci showing distribution of the repressive chromatin marker H3K27me3 (a) and the active chromatin marker H3K4me3 (b) in various tissues. Seedling, whole seedlings17; leaf, rosette leaves42; root, whole roots17; seedling 2, whole seedlings44; SAM, shoot apical meristems after 0, 1, 2 or 3 d in long-day conditions44. Gene models are shown below with arrowheads indicating direction of transcription. d, The chromatin landscape of class A ARF and LEC2 loci showing chromatin accessibility in various tissues. DNaseI-seq seedling: DNase I hypersensitive sites in whole seedling46; DNaseI-seq root: DNase I hypersensitive sites in root46; FANS-ATAC seedling: FANS-ATAC accessible regions in whole seedling47; FANS-ATAC roots: FANS-ATAC accessible regions in roots47; INTAC-ATAC root tip: INTACT-ATAC transposase hypersensitive sites in root tips48. The LEC2 locus is included as a negative control for H3K4me3 marking and chromatin accessibility, and as a positive control for H3K27me3 marking54. The y axis scales (at right) show the minimum and maximum number of reads represented in each windows of the same row, except for the data set related to ref. 17, for which the data range corresponds to the IP/INPUT value of the ChIP-chip experiments. For the x axis the window size is fixed at 8.5 kb and centred on the gene of interest (gene model in blue below each column, 5′ sequences in green), with arrowheads by the gene name showing the direction of the locus.

Extended Data Fig. 3 Characterization of the TFs and TF binding sites that regulate class A ARF expression.

a, Yeast one-hybrid promoter–transcription factor interaction network for class A ARF genes. Green boxes correspond to the class A ARF; pink boxes are transcription factors binding to the ARF promoters. TF-associated functions and expression analysis are indicated in the upper and lower small boxes and colour-coded as indicated in the key. Note that when two promoter fragments were used for the screen (see Methods), 35 out of 36 regulators bound to the more proximal fragment, supporting previous observations that the majority of transcription factor binding sites reside within a few kb of the transcriptional start site55. b, Frequency of TF gene families in the Y1H library collection (black) and in the Y1H network (white). Only families represented by at least two members in the Y1H network were analysed. The network is overrepresented with members of the WRKY and SPL TF families. Statistical analysis: hypergeometric test significant to 5% (*; P = 4e-05 for WRKY family and P = 0.044 for SPL family). Sample sizes for TFs in Y1H library in black/Y1H network in white: n = 29/8 TFs (WRKY); n = 68/6 (ZFP); n = 91/6 (AP2/ERF); n = 44/2 (NAC); n = 7/2 TFs (SPL); n = 52/2 TFs (homeobox); n = 61/2 TFs (bHLH). c, TF expression in the RAM38 and the SAM39,40. 50% of the identified TFs are expressed in both shoots and roots, whereas 24% and 14% are expressed specifically in roots or shoots respectively. d, Known functions of the TFs in the Y1H network based on a literature search (see also Supplementary Table 2). e, Boxplot representation of the distribution of class A ARF promoter ranks. For TFs with established binding models, we ranked class A ARF promoters among all Arabidopsis promoters based on the score of the predicted TF binding sites. We repeated the same operation with a set of randomly chosen TFs from different families (see Methods). The comparison of rank distributions with those of a set of randomly chosen TFs from different families revealed significantly higher ranks for eY1H-identified TFs (see also Supplementary Table 3). Statistical analysis: one-sided t-test. Sample sizes: n = 29 for eY1H-selected TFs and n = 100 for randomly selected TFs. Data are represented as boxplots where the middle line is the median, the lower and upper hinges correspond to the first and third quartiles, the upper whisker extends from the hinge to the largest value no further than 1.5× interquartile range (IQR) from the hinge and the lower whisker extends from the hinge to the smallest value at most 1.5× IQR of the hinge. All the individual values are plotted. f, Summary of the DAP-seq analysis for the 17 TFs (see also Supplementary Table 3). g, Example of DAP-seq data, here a DAP-seq peak for WRKY33 in the promoter of ARF8. DAP-seq (f, g) thus confirms experimentally inferred bindings (e) for 4 of the 17 (24%) TFs for which DAP-seq data are available (see also Supplementary Table 3). Note also that chromatin immunoprecipitation sequencing (ChIP-seq) confirms the binding of WUSCHEL to the ARF8 promoter21.

Extended Data Fig. 4 Methodology used for the transient protoplast assay.

a, Design of the standard reporter plasmid containing sequences upstream and downstream of the ARF promoter including the first intron (1), the alternative reporter plasmid containing only sequences upstream of the ARF promoter (2), the standard effector plasmid (3), and an alternative effector plasmid containing the VP16 domain fused to the TF coding sequence (4). b, Example of a nucleus of a transformed living protoplast imaged with confocal microscopy with channels for mVenus, TagBFP, mCherry and bright-field. The presence of TagBFP and mCherry specifically in the nucleus is used as a transformation control and as a test of viability of the protoplasts. Quantification: definition of the nucleus as a region of interest using ImageJ to quantify fluorescence (see also Methods). Measurements were conducted in at least 4 independent experiments for each TF (minimum of 2 experiments for TF alone and 2 experiments for TF fused to VP16 domain). Scale bars, 10 μm. c, d, Example of results using the ARF5 reporter plasmid, with (c) and without (d) the VP16 activator domain fused to the TF coding sequence (left and right). Error bars, mean ± s.d.; statistical analysis, one-sided Mann–Whitney U-test with P ≤ 0.05 (*); N of protoplasts (P values): (c) control, n = 35; DOF1.8, n = 38 (0.33); KNAT1, n = 37 (0.11), LBD3, n = 38 (6e-04); SMZ, n = 43 (3e-10); (d) control, n = 43 (1e-07); DOF1.8-VP16, n = 46; KNAT1-VP16, n = 44 (0.37); LBD3-VP16, n = 32 (1e-05); SMZ-VP16, n = 39 (0.015).

Extended Data Fig. 5 ARF transcriptional regulators mostly show complementary expression patterns to their target ARFs.

a, Plants carrying the ARF transcriptional reporters were transformed with transcriptional reporters for a subset of ARF regulators driving mCherry. For five out of seven constructs (see also Fig. 3), we saw complementary patterns of expression between transcriptional repressors and their ARFs in the root. b, To further quantify the complementarity of TF versus ARF expression, we quantified the red versus green fluorescence levels in individual nuclei from different cell types (root cap, blue diamond; columella, green triangle; epidermis, red square; vascular cells, purple cross). These values were normalized so that the brightest nucleus of each channel in each line was set to 1, and values were plotted onto scatter plots. Any value falling outside the reference lines shows a >4× bias for expression of either TF or ARF (n = 3 for pAT2G26940::mCherry and pAT2G44730::mCherry in pARF8::mVenus; n = 2 for the remaining genotypes). In some cases there was clear complementarity in some cell types but not others. For example, ZFP6 shows complementary expression patterns in the root cap, epidermis and columella but overlaps with ARF8 in the vascular tissues. c, Analysis of At2g26940 expression in the SAM, where it was found in organ primordia and weakly in the centre of the SAM; no clear expression was observed in roots. As previously observed with other developmental and hormonal regulators22,23, co-localization of repressors and their target ARF occurs in some cells as in the case of ZFP6/ARF8 in the root epidermis (a, b) and At2g26940/ARF19 in shoot organ primordia (c), suggesting potential regulatory interactions to modulate transcription levels. Scale bars, 60 μm (a) and 40 μm (c). Experiments were done twice (a, c).

Extended Data Fig. 6 Expression of class A ARF in mutants for the regulatory transcription factors.

Expression of class A ARF in 24 mutants of the regulatory TFs measured with qRT–PCR, in whole root and whole shoot tissue of 7-d-old seedlings. Green boxes indicate statistically significant upregulation of the corresponding ARF in the mutant background compared to wild-type control, and blue boxes indicate statistically significant downregulation. Statistical analysis was performed using a one-sided Mann–Whitney test and a threshold at P ≤ 0.1. For simplicity, only the interactions predicted by the Y1H are shown, with other combinations shaded with a grey box. The full data set is available in Supplementary Table 6.

Extended Data Fig. 7 Feedback regulations between the transcription factors and auxin signalling.

a, Expression of several TFs are regulated by auxin, which proves feedback regulation from auxin signalling output primarily on ARF8 expression. Expression was measured after treatment with 1 μM IAA for 30 min, 1h or 3h56. Green boxes indicate upregulation, blue boxes indicate downregulation of gene expression compared with a mock treatment. b, Schematic representation of ARF8 regulation with feedbacks. Feedback from auxin signalling on regulatory TFs is expected to induce complex nonlinear regulation of ARF8 expression (see also Supplementary Note 2). c, Diagrammatic representation of the interactions taking place for different instances of model analysed in Supplementary Note 2. The two diagrams on the right (without feedback) are identical. However, for comparison with the models with feedback the parameters used for these differ (see Supplementary Note 2). dg, left, bar chart displaying concentrations before and after knock out of transcription factor X, where Y is activated (d) or repressed (f) by ARF. Right, contour plot displaying ARF transcription rate before and after knock out of transcription factor X relative to Y and X populations, where Y is activated (f) or repressed (g) by ARF. Steady-state (SS) values corresponding to the bar plot are also reported. These results are discussed in Supplementary Note 2.

Extended Data Fig. 8 Modulating the levels of ARF transcriptional regulators regulates the expression of associated ARFs.

a–f, Comparison of ARF expression in wild-type versus mutants in roots. g, Comparison of pARF7::VENUS expression in wild-type versus wrky38 shoot. For quantification (see f), fluorescence was measured in the central zone and primordia 2 (green circles). h, Quantification of fluorescence changes shown as relative changes in mean fluorescence level in mutant compared to wild type (single value). Quantifications are shown for a–g and for Fig. 3c,d. In roots, the total pARF7/19-driven fluorescent signal was quantified within a standardized zone covering the stele meristem zone and quantified relative to the wild-type controls. In the shoot, L1 and L2 correspond to quantification in the corresponding layers in the SAM of wild-type and nf-yb13 (see also Fig. 3c, d). Quantification demonstrated a significant change in pattern in wrky38 mutant SAMs (g), with an increase of pARF7 activity in the centre and a loss of the differential expression between the SAM centre and lateral organs. Statistical analysis: unpaired two-sided t-test with P ≤ 0.01 (**). Number of samples observed and quantified: for mutant/wild type roots, 13/13 for crf10, 12/14 for wrky38, 9/9 for nf-yb13, 9/8 for At2g26940, 12/11 for myb65, 12/10 for nlp5; 7 shoots for nf-yb13 and wild-type controls; 7 shoots for wrky38 and 6 wild-type controls. P values from left to right: 0.003, 2e-05, 3e-08, 0.26, 0.57, 0.11, 0.84, 0.007, 0.009. Raw data are provided in Supplementary Table 11. i, Inducible constitutive overexpression of CRF10:mCherry and AL3:mCherry in the pARF7::VENUS line. pARF7::VENUS is shown in yellow and the transcription factors fused to mCherry in red following a 24h induction with β-oestradiol. j, Both lines shown in i show a significant reduction in pARF7::VENUS expression. Unpaired two-sided t-test: P = 4e-10 (CRF10) and 2e-10 (AL3). Number of plants: wild-type control, n = 15; CRF10, n = 21; AL3, n = 20. Error bars: mean ± s.d.. Scale bars: 45 μm for root images; 50 μm for shoot images. For each analysis, the confocal settings were identical in the compared genetic backgrounds. All experiments were done two times.

Extended Data Fig. 9 Mutations in transcriptional regulators of class A ARF genes accelerate the root gravitropic response.

a–g, Kinetics of perturbed gravitropic responses of TF mutants (dashed line) compared to wild-type (solid line) over 12 h after application of the gravitational stimulus. Mutants with statistically significant difference in gravitropic response compared to the wild-type are shown: (a) nlp5, (b) zfp6, (c) al3, (d) at2g44730, (e) wrky11, (f) myb65 and (g) wrky38. Statistical analyses: unpaired two-tailed t-test with P ≤ 0.05 (*). P values from 1 h to 12 h (left to right): (a) 0.86, 0.19, 0.37, 0.004, 0.01, 0.0008, 0.0008, 0.001, 0.007, 0.004, 0.06, 0.07; (b) 0.01, 0.02, 0.05, 0.009, 0.002, 0.007, 0.01, 0.01, 0.14, 0.1, 0.01, 0.04; (c) 0.75, 0.25, 0.85, 0.12, 0.07, 0.16, 0.02, 0.1, 0.01, 0.02, 0.1, 0.06; (d) 0.40, 0.50, 0.71, 0.95, 0.86, 0.23, 0.07, 0.36, 0.12, 0.01, 0.009, 0.04; (e) 0.058, 0.97, 0.88, 0.27, 0.81, 0.16, 0.27, 0.04, 0.03, 0.01, 0.01, 0.01; (f) 0.31, 0.07, 0.09, 0.10, 0.45, 0.26, 0.08, 0.04, 0.01, 0.24, 0.02, 0.11. (g) 0.1, 0.26, 0.003, 0.003, 0.007, 0.0003, 0.0003, 0.0004, 8e-05, 0.0002, 0.001 and 0.001. Sample sizes (WT/mutant plants): (a) n = 29/29, (b) n = 32/32, (c) n = 28/30, (d) n = 28/26, (e) n = 30/29, (f) n = 30/28, (g) 29/30. Raw data are provided in Supplementary Table 12. Error bars: mean ± s.d.

Extended Data Fig. 10 Transcriptional regulation of class A ARF genes regulates shoot development.

a, Phenotypic analysis of the shoot defects in TF mutants. Leaf nr, leaf number; rosette d., rosette diameter; C. branch nr, cauline branch number; A. branch nr, axillary branch number. Green boxes indicate statistically significant increases; blue boxes indicate statistically significant reductions in the indicated developmental parameter compared to Col-0. Statistical analyses: unpaired two-tailed t-test, P ≤ 0.05 considered as statistically significant; number of plants n = 12 per genotype. b, Examples of shoot growth phenotypes: shoot growth during vegetative stage in the at2g26940 mutant alongside the control after growth for 43 d in short-day conditions. c, The dof1.8 mutant has a shorter inflorescence than control plants.

Supplementary information

Supplementary Information

Supplementary note 1: Raw data of the statistical analysis of the transcriptional activity of candidate transcription factors regulating ARFclassA in protoplasts.

Reporting Summary

Supplementary Information

Supplementary note 2: Modelling analysis of the non-linear feedback of ARF caused by the presence of multiple transcriptional regulators.

Supplementary Table

Supplementary table 1: Chromatin status of ARFclassA loci - Analysis of presence of H3K27me3 marks, H3K4me3 marks and of chromatin accessibility in published datasets.

Supplementary Table

Supplementary table 2: Candidate TFs identified using eY1H and their biological function - List of candidate transcription factors identified using eY1H and bibliographic information on their biological functions.

Supplementary Table

Supplementary table 3: Position weight matrices (PWM) for TFs identified in the eYIH screen - Analysis of transcription factor binding sites (TF binding site analysis tab) and DAP-seq peaks presence in ARFclassA promoters (DAP-Seq analysis summary and DAP-Seq binding site list tabs).

Supplementary Table

Supplementary table 4: Analysis of transcriptional activity of candidate TF regulating ARFclassA – Results of statistical analysis and meta-analysis of the transcriptional activity of candidate transcription factors regulating ARFclassA in protoplasts.

Supplementary Table

Supplementary table 5: Characterization of mutants in genes encoding candidate TF regulating ARFclassA – Information (mutant information tab) and analysis of mutated gene expression (Gene expression in mutants tab) in T-DNA mutants for transcriptional regulators of ARFclassA.

Supplementary Table

Supplementary table 6: Analysis of ARFclassA expression in TF mutants using qRT-PCR – Determination of ARFclassA expression in T-DNA mutants for transcriptional regulators using qRT-PCR and statistical analysis.

Supplementary Table

Supplementary table 7: Root elongation of plants grown on 10 µM IAA at 15 days versus plants grown without IAA – Source data and statistical analysis.

Supplementary Table

Supplementary table 8: Expression of auxin-regulated genes in TF mutant background using qRT-PCR – Analysis of the expression of the IAA13 and 19 auxin-regulated genes in T-DNA mutants for transcriptional regulators of ARFclassA using qRT-PCR.

Supplementary Table

Supplementary table 9: Shoot phenotyping of TF mutants – Analysis of different shoot phenotypes in T-DNA mutants for transcriptional regulators of ARFclassA. The five tabs corresponds to the 5 phenotypes analyzed: Number of leaves, Rosette diameter, Main shoot length, Number of cauline leaves, Number of axillary bracnhes.

Supplementary Table

Supplementary table 10: TF added to the collection used for the eY1H screen – List of transcription factors cloned to expand the collection of Gaudinier et al Nature Methods 2011 used in this study for eYIH screening.

Supplementary Table

Supplementary table 11: Expression of ARF reporters in mutants of regulatory TF measured in the root and the shoot apical meristems using fluorescent reporter lines – Source data and statistical analysis in roots (ARF expression root tab) and shoots (ARF expression shoot tab).

Supplementary Table

Supplementary table 12: Kinetics of gravitropic responses of TF mutants over 12h after application of the gravistimulus – Raw data and statistical analysis. Each tab contains the values for one mutant and the wild-type control.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Truskina, J., Han, J., Chrysanthou, E. et al. A network of transcriptional repressors modulates auxin responses. Nature 589, 116–119 (2021).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links