Abstract
The formation of a flat and thin leaf presents a developmentally challenging problem, requiring intricate regulation of adaxial–abaxial (top–bottom) polarity. The patterning principles controlling the spatial arrangement of these domains during organ growth have remained unclear. Here we show that this regulation in Arabidopsis thaliana is achieved by an organ-autonomous Turing reaction‐diffusion system centred on mobile small RNAs. The data illustrate how Turing dynamics transiently instructed by prepatterned information is sufficient to self‐sustain properly oriented polarity in a dynamic, growing organ, presenting intriguing parallels to left–right patterning in the vertebrate embryo. Computational modelling demonstrates that this self-organizing system continuously adapts to coordinate the robust planar polarity of a flat leaf while affording flexibility to generate the tissue patterns of evolutionarily diverse organ shapes. Our findings identify a small-RNA-based Turing network as a dynamic regulator of organ polarity that accounts for leaf shape diversity at the level of the individual organ, plant or species.
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Data availability
Data for this study are available from the paper and its Supplementary Information or from the corresponding author on reasonable request.
Code availability
Supplementary Code 1–3 provides all code in PDF format compatible with the Morpheus platform52. The cellular models are also available via the Git Morpheus open source repository at https://identifiers.org/morpheus/M4283. Details concerning the specific mathematical models are defined within the Supplementary Note. Additional scripts are available upon reasonable request from the authors.
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Acknowledgements
We are grateful to C. Kuhlemeier, M. Scanlon, C. Hardtke, A. Husbands, R. Dello Ioio and L. Ragni for critical feedback on the manuscript. Support for this work came from the Alexander von Humboldt Professorship to M.C.P.T.
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E.S., G.P., K.T.N. and M.C.P.T. conceived of the research direction and experiments. E.S. with support from W.d.B. performed theoretical and computational analyses. G.P. and A.B. carried out the confocal imaging and image analysis. K.T.N. and S.M. generated genetic resources and performed ChIP and other molecular biology work. E.S. and M.C.P.T. wrote the paper, with input from all co-authors.
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Extended data
Extended Data Fig. 1 Scenarios to explain the regulation of opposing mobile small RNA gradients during primordium development.
(a) Following examples of the Bicoid and Hunchback morphogens in the Drosophila embryo, miR166 and tasiARF could have fixed sources in the abaxial (bottom) and adaxial (top) epidermal layer, respectively, that are maintained independently of each other by transcription factors outside of the polarity network and thus independent from their respective downstream targets. (b) Alternatively, similar to the example of Nodal and Lefty, the miR166 and tasiARF morphogen sources could be dynamically regulated by a closed self-organising gene regulatory network that simultaneously coordinates both morphogen sources via their respective downstream targets. Arrow, activating interaction; T-ending, repressive interaction; circle, possible activating, inhibiting, or neutral interaction.
Extended Data Fig. 2 Predicted binding sites for core polarity transcription factors in promoters of representative adaxial-abaxial determinants.
(a-d) Schematic representations of predicted HD-ZIPIII (a), LBD-AS2 (b), KAN (c), and ARF (d) binding sites in the promoters of representative members in the HD-ZIPIII family (PHB, REV), AS2, the tasiARF precursor TAS3A, as well as MIR165A, MIR166A, MIR166B, KAN1, KAN2, ARF3, and ARF4, key representatives for the MIR166, KAN, and ARF gene families, respectively. Note, MIR165A is considered a variant member within the broadly conserved MIR166 miRNA family. Fragments investigated by ChIP (Extended Data Fig. 3) are indicated. Hairpin, small RNA precursor; arrow, translation start site.
Extended Data Fig. 3 The landscape of direct transcription factor-promoter interactions reveals a highly interconnected polarity network.
(a-d) ChIP analyses show significant enrichments for PHB (a), AS2 (b), KAN1 (c) and ARF3 (d) at select sites in the promoters of representative members for the HDZIPIII (red), AStasiARF (green), and miRKANARF (blue) nodes. Values (means ± s.e.m., n = 3 biological replicates) are relative to the respective transcription factor enrichment at the negative control locus ACT2. Promoter fragments are as depicted in Extended Data Fig. 2. Two-tailed Student’s t-test: *p < 0.05; **p < 0.01. For exact p-values see Supplementary Dataset 1. Enrichments for KAN1 at AS2 and ARF3, and enrichments for AS2 at KAN1 and ARF3 are replotted from Burian et al.9.
Extended Data Fig. 4 Repressive regulatory interactions characterize the polarity GRN.
(a-d) Bar plots showing relative expression changes for representative polarity determinants following short-term induction of PHB (a), AS2 (b), KAN1 (c), and ARF3 (d) indicate most regulatory interactions in the polarity GRN are repressive, mirroring predictions from the LPM. The transcriptional activation of HD-ZIPIII expression upon AS2 induction (b) is opposite to LPM predictions. This anomaly is explained by indirect effects from AS2 on HD-ZIPIII transcript levels via miR166, as the bar plot in (e) shows relative expression levels for the transcriptional pPHB:GFP fusion decrease following short-term AS2 induction, indicating that AS2 represses transcription from the PHB promoter. Relative transcript levels for AS2 and TAS3A are shown for comparison. Expression values relative to PP2A were normalized as treatment over mock control (means ± s.e.m., n = 3 biological replicates). Two-tailed Student’s t-test: *p < 0.05; **p < 0.01. For exact p-values see Supplementary Dataset 1. Bar colours reflect the respective nodes in the LPM.
Extended Data Fig. 5 Intercellular mobility is needed for full AS2 function.
(a-d) Top views of 32 days-old plants show that contrary to the planar geometry of wild-type Col-0 leaves (a), as2 mutant leaves (b) are rumpled, asymmetric and lobed (arrowheads). The as2 phenotype is rescued by expression of a mobile AS2-Venus protein fusion (c, pAS2:AS2-Venus), but is only partially complemented upon expression of a non-mobile AS2-3xVenus protein fusion (d, pAS2:AS2-3xVenus). Scale bars, 10 mm. (e) Bar plot of relative luciferase activity, calculated as Firefly over Renilla luciferase activity (mean ± s.e.m., n = 5 biological replicates), shows AS2-Venus (p = 0,0024) and AS2-3xVenus (p = 0,0056) repress pARF3:LUC to similar extents, underscoring their functional equivalence in this context. Two-tailed Student’s t-‐test: **p < 0.01, N.S. Non-Significant (p = 0,3262). (f) Additional examples of the genotypes shown in a-d, illustrating the consistency of plant phenotypes.
Extended Data Fig. 6 Expression of MIR166A and MIR166B at sites of incipient leaf primordia predicts an early role in adaxial-abaxial patterning.
(a-i) Top views of shoot apices showing the spatiotemporal patterns of expression for transcriptional reporter fusions for all nine members of the MIR166 precursor family. Similar to KAN19, MIR166A (c) and MIR166B (d) are expressed on the abaxial side of developing leaf primordia and within a narrow ring of cells at the meristem periphery that overlaps abaxial founder cells in incipient leaf primordia (p-2 to p0). In contrast, expression of MIR165A (a), MIR165B (b), and MIR166D (f) is detected on the abaxial side of leaf primordia only after their emergence from the meristem, and the remaining family members, MIR166C (e), MIR166E (g), MIR166F (h), and MIR166G (i) show no or minimal expression at the vegetative apex. Representative images from n = 5 apices per reporter are shown. Leaf primordia are numbered successively relative to the first bulging primordium (p1), numbers <1 indicate positions of incipient primordia. Asterisks, meristem centre. Cell walls were stained by PI. Scale bars, 50 µm.
Extended Data Fig. 7 A KAN-ARF complex promotes MIR166 expression.
Bar plot showing relative expression changes for MIR165A, MIR166A, and MIR166B following short-term induction of ARF3, KAN1, or ARF3 and KAN1 together reveals that expression of these MIR166 precursors is induced only upon co-induction of both transcription factors. Transcript levels for the HD-ZIPIII genes PHB and REV, are repressed also upon induction of either KAN1 or ARF3, and are included as controls. Values (means ± s.e.m., n = 3 biological replicates) are relative to the respective mock-treated control. Two-tailed Student’s t‐test: *p < 0.05; **p < 0.01. For exact p-values see Supplementary Dataset 1.
Extended Data Fig. 8 Activation of MIR166A expression by a KAN-ARF complex is evident in p3 leaf primordia.
A reduction of KAN and/or ARF activity results in the loss of MIR166A expression on the abaxial side of the growing leaf primordium shortly following (p3 under our growth conditions), indicating KAN and ARF together control the organ-autonomous expression of MIR166A. Arrowheads, abaxial side of the p3 primordium. Scale bar, 20 µm.
Extended Data Fig. 9 tasiARF confines ARF3 expression to the abaxial side of p3 and older leaf primordia.
(a-b) Optical longitudinal sections of p1 leaf primordia shows near equivalent patterns of expression for the tasiARF sensitive pARF:ARF3-YPET (a) and tasiARF insensitive pARF:ARF3*-YPET (b) reporters. (c-d) Optical longitudinal sections of p3 leaf primordia shows that whereas pARF:ARF3-YPET (c) accumulation is limited to the abaxial side, the tasiARF insensitive pARF:ARF3*-YPET reporter (d) shows expression on both the adaxial (arrowhead) and abaxial side, indicating a role for tasiARF in polarizing ARF3 expression at this stage of primordium development. Representative images from n = 5 apices are shown. Cell walls were stained by PI. Scale bars, 20 µm.
Supplementary information
Supplementary Information
Supplementary Note; captions for Videos 1 to 6, Code 1 to 3 and Dataset 1; and Tables 1 to 3.
Supplementary Video 1
Video of the model shown in Fig. 2e. Numerical simulation of the LPM inside a template of anticlinally dividing cells with no-flux boundary conditions and an initial condition of miRKANARF activity in the most abaxial cell layer as in Supplementary Note 3.2 with Equation 10, parameters in Table 3, DmiRKANARF = 7.5, DAStasiARF = 100, and Division Time = 6,400. The video shows the system’s dynamic resolution from the initial condition (t = 0) into a linear bipolar pattern at t = 50.
Supplementary Video 2
Numerical simulation as in Supplementary Video 1 progressing to t = 5,000.
Supplementary Video 3
Video of the model shown in Fig. 6d. Simulation as in Supplementary Video 2, but with parameters k2 = −1 and k5 = −1.85. Under these parameters, the LPM generates the bipolar linear pattern.
Supplementary Video 4
Video of the model shown in Fig. 6e. Simulation as in Supplementary Video 2, but with parameters k2 = −0.4 and k5 = −1.15. Under these parameters, the LPM generates the polar shift down pattern.
Supplementary Video 5
Video of the model shown in Fig. 6f. Simulation as in Supplementary Video 2, but with parameters k2 = −0.3 and k5 = −1.8. Under these parameters, the LPM generates a labyrinthine pattern.
Supplementary Video 6
Video of the model shown in Fig. 6c. Simulation as in Supplementary Video 2, but with parameters k2 = −0.3 and k5 = −1.8. Under these parameters, the LPM generates a polar shift up pattern.
Supplementary Code 1
Morpheus 2.3.1 code for numerical simulations of the LPM on a grid of static cells with no-flux boundaries starting from random initial conditions for miRKANARF (Fig. 2c and Supplementary Note 3.1, Fig. 14A).
Supplementary Code 2
Morpheus 2.3.1 code for numerical simulations of the LPM on a grid of static cells with no-flux boundaries starting from miRKANARF in the bottom cell layer as an initial condition (Fig. 2d and Supplementary Note 3.1, Fig. 14B).
Supplementary Code 3
Morpheus 2.3.1 code for numerical simulations of the LPM on the growing cellular template with no-flux boundaries starting from miRKANARF in the bottom cell layer as an initial condition (Fig. 2e and Supplementary Note 3.2).
Supplementary Dataset 1
P values for ChIP and qRT–PCR data presented in this study.
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Scacchi, E., Paszkiewicz, G., Thi Nguyen, K. et al. A diffusible small-RNA-based Turing system dynamically coordinates organ polarity. Nat. Plants 10, 412–422 (2024). https://doi.org/10.1038/s41477-024-01634-x
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DOI: https://doi.org/10.1038/s41477-024-01634-x
