Journal of Plant Research

, Volume 132, Issue 2, pp 155–157 | Cite as

Towards a next step of the research of regulatory networks in plant growth and development

  • Kengo MorohashiEmail author
  • Eugenia Russinova
PREFACE Regulatory networks in plant growth and development

Plants properly coordinate growth and development through a complex system that fundamentally underlies thousands of genes in the plant genome. As the numbers of possible relationships between genes are almost unlimited, it is challenging to elucidate one particular regulatory mechanism, no matter how important. This complex combination of connections eventually displays an organized character, designated as a network. Networks can represent many different types of data, such as protein–protein and protein–metabolite interactions. When the network consists of genes, it is referred to as a genetic network, whereas when components interact with each other and with other cellular constituents to govern the gene expression levels of mRNA and proteins, it is labelled a gene regulatory network (GRN) (de Luis Balaguer et al. 2017; Mejia-Guerra et al. 2012).

This special issue on “Regulatory networks in plant growth and development” is based on a JPR international symposium held during the 81st Annual Meeting of the Botanical Society of Japan that took place in Tokyo (Japan), September 8–10, 2017. This conference provided an overview of cutting-edge topics that covered the broad perspectives of regulatory networks in plant growth and development. Results on various aspects of plant research were presented, namely on epidermal differentiation, hypocotyl elongation, secondary metabolism, phyllotaxis, and hormone signaling.

Plant growth requires well-coordinated cell division and expansion. These events involve a key factor, expansin, of which the function is essential for cell wall expansion. Ilias et al. (2019) presented a detail analysis of the genome-wide effects of the expansin function. Cell expansion in a dark-grown hypocotyl is initially slow, where after it is followed by a rapid hypocotyl elongation. The transition from cell wall biogenesis to structural organization has been proposed to coincide with this fast elongation phase between day 3 and day 5. Ilias et al. (2019) used transgenic Arabidopsis thaliana lines for a time-course analysis of hypocotyl growth. They obtained a gene expression dataset that will further benefit the identification of regulatory networks involved in the accelerated hypocotyl growth as well as of networks perturbed by either suppression or overexpression of the expansin gene.

Plants produce various amounts of metabolites, in particular, secondary (also called specialized) metabolites. More than 200,000 secondary metabolites have been reported to date, consisting of various types of compounds, such as terpenoids, alkaloids, and phenolics (Verpoorte and Memelink 2002; Zwenger and Basu 2008). The synthesis of secondary metabolites often requires the coordinated expression of multigene families that encode enzymes needed for different enzymatic steps. Moreover, transcription factors play a key role in the GRN of such synthetic pathway. Steroidal glycoalkaloids (SGAs) and nicotine are secondary metabolites found in some Solanaceae species. A group of jasmonate-responsive ETHYLENE RESPONSE FACTOR (ERF) transcription factors regulate the production of SGAs in this family. Shoji and Hashimoto (2019) reported on the predominant role of the JASMONANATE RESPONSE FACTOR (JRE), one of the ERF transcription factors in the SGA regulation. They demonstrated that such a regulatory system occurs in different species within the Solanaceae family and discussed the altered regulation of the downstream biosynthetic gene QUINOLINATE PHOSPHORIBOSYL TRANSFERASE2 (QPT2) due to promoter mutations.

Although the elucidation of the coordinated regulation of a metabolic pathway in fruit is interesting from a prospective applications point of view, it still remains unclear. Jamaluddin et al. (2019) analyzed the transcriptome of papaya (Carica papaya), one of the most nutritional fruits and studied the effects of DE-ETIOLATED1 (DET1) gene suppression in embryogenic callus. A transcriptomic analysis of immature zygotic embryos transformed with a constitutive expressing hairpin DET1 construct (hpDET1) to repress the DET1 gene expression revealed transcriptome-wide relationships between the light-regulated and secondary metabolite biosynthetic pathways in papaya.

Plants are exposed to various biotic and abiotic environmental factors, such as light, temperature, drought, flooding, nutrient shortage, chemicals, herbivores, and microorganisms. As plants are sessile, they can only survive by adapting to their environment. To this end, they must sense the environmental factors and coordinate their biological processes for an adequate response by, on the one hand, producing secondary metabolites and, on the other hand, regulating organ growth and development. Therefore, metabolic and developmental pathways are often coregulated. In Arabidopsis, the formation of a trichome, a hair-shaped organ that develops from epidermal cells, and the synthesis of anthocyanin that accumulates in epidermal cells coexist, suggesting that their GRNs are related. Kengo Morohashi presented a systems approach based on the inducible system of the GLABRA3 gene that is a basic helix-loop-helix (bHLH)-type transcription factor involved in both trichome formation and anthocyanin biosynthesis in Arabidopsis and found that the accountable GRN consisted of an incoherent feed forward loop. Furthermore, Arai et al. (2019) reported on a AtGL3 homolog in Marchantia polymorpha (liverwort), designated MpBHLH12. Transcriptomic analysis with transgenic M. polymorpha lines revealed that the activity of MpBHLH12 might differ from that of AtGL3, despite their high amino acid sequence similarity.

Moreover, perception of different signals and integration into appropriate responses are essential elements of the living cell and require robust, but adaptable, biochemical networks. These networks are largely composed of proteins that can interact, move to specific cellular locations, be modified or be degraded. The integration of these events often triggers activation or inactivation of transcription factors, inducing or repressing thousands of genes. To coordinate these regulatory networks, plants employ not only gene products, but also small molecules, such as plant hormones. Brassinosteroid signal transduction pathway shares signaling components with the signaling pathway that controls stomatal development in the leaf epidermis (Gudesblat et al. 2012; Khan et al. 2013; Kim et al. 2012). Eugenia Russinova reported that the incorporation of these shared components into distinct macromolecular complexes through scaffolding molecules ensures their localization to different cellular compartments and provides specificity (Houbaert et al. 2018).

In plants, the aerial organs are generated from the shoot apical meristem according to robust spatiotemporal patterns that control the shoot primary architecture, known as phyllotaxis. Results from modeling approaches and laboratory experiments have demonstrated that the auxin distribution dynamics allows reiterative organogenesis at the shoot apex. Other hormones, such cytokinins, are also implicated in the regulation of the spatiotemporal patterns of organ initiation at the shoot apical meristem. Teva Vernoux discussed recent results from both modeling and imaging approaches that provided insights into the regulation mechanism of phyllotaxis.

Thanks to the symposium and recent advances on the GRN research, we realized that a network can consist of unlimited nodes and that its structure is flexible. Therefore, nested networks, such as a network of networks, could possibly exist. Even when a GRN appears in a particular biological event, it still just starts a next endeavor of building high-ordered GRNs. Considering the quick development of artificial intelligence in the computational biology field, computational analysis becomes a more powerful approach to infer a meta-GRN with such complicated structures (Haque et al. 2019). However, when the meta-GRN can be implied by experimental and/or computational approaches, it remains static, in contrast to a living organism, in which the GRN should be “alive”. A next step in this research should be to integrate time into a dynamic GRN that would more plausibly reflect genuine biological processes. In the future, we should predict outcomes (phenotypes) based on dynamic meta-GRNs of plants and eventually develop beneficial crops for agriculture and human well-being.



  1. Arai H, Yanagiura K, Toyama Y, Morohashi K (2019) Genome-wide analysis of MpBHLH12, a IIIf basic helix-loop-helix transcription factor of Marchantia polymorpha. J Plant Res. Google Scholar
  2. de Luis Balaguer MA, Fisher AP, Clark NM, Fernandez-Espinosa MG, Möller BK, Weijers D, Lohmann JU, Williams C, Lorenzo O, Sozzani R (2017) Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells. Proc Natl Acad Sci USA 114:E7632–E7640CrossRefGoogle Scholar
  3. Gudesblat GE, Schneider-Pizoń J, Betti C, Mayerhofer J, Vanhoutte I, van Dongen W, Boeren S, Zhiponova M, de Vries S, Jonak C, Russinova E (2012) SPEECHLESS integrates brassinosteroid and stomata signalling pathways. Nat Cell Biol 14:548–554CrossRefGoogle Scholar
  4. Haque S, Ahmad JS, Clark NM, Williams CM, Sozzani R (2019) Computational prediction of gene regulatory networks in plant growth and development. Curr Opin Plant Biol 47:96–105CrossRefGoogle Scholar
  5. Houbaert A, Zhang C, Tiwari M, Wang K, de Marcos Serrano A, Savatin DV, Urs MJ, Zhiponova MK, Gudesblat GE, Vanhoutte I, Eeckhout D, Boeren S, Karimi M, Betti C, Jacobs T, Fenoll C, Mena M, de Vries S, De Jaeger G, Russinova E (2018) POLAR-guided signalling complex assembly and localization drive asymmetric cell division. Nature 563:574–578CrossRefGoogle Scholar
  6. Ilias IA, Negishi K, Yasue K, Jomura N, Morohashi K, Baharum SN, Goh H-H (2019) Transcriptome-wide effects of expansin gene manipulation in etiolated Arabidopsis seedlings. J Plant Res. Google Scholar
  7. Jamaluddin ND, Rohani ER, Mohd Noor N, Goh H-H (2019) Transcriptome-wide effect of DE-ETIOLATED1 (DET1) suppression in embryogenic callus of Carica papaya. J Plant Res. Google Scholar
  8. Khan M, Rozhon W, Bigeard J, Pflieger D, Husar S, Pitzschke A, Teige M, Jonak C, Hirt H, Poppenberger B (2013) Brassinosteroid-regulated GSK3/Shaggy-like kinases phosphorylate mitogen-activated protein (MAP) kinase kinases, which control stomata development in Arabidopsis thaliana. J Biol Chem 288:7519–7527CrossRefGoogle Scholar
  9. Kim T-W, Michniewicz M, Bergmann DC, Wang Z-Y (2012) Brassinosteroid regulates stomatal development by GSK3-mediated inhibition of a MAPK pathway. Nature 482:419–422CrossRefGoogle Scholar
  10. Mejia-Guerra MK, Pomeranz M, Morohashi K, Grotewold E (2012) From plant gene regulatory grids to network dynamics. Biochim Biophys Acta 1819:454–465CrossRefGoogle Scholar
  11. Shoji T, Hashimoto T (2019) Expression of a tobacco nicotine biosynthesis gene depends on the JRE4 transcription factor in heterogenous tomato. J Plant Res. Google Scholar
  12. Verpoorte R, Memelink J (2002) Engineering secondary metabolite production in plants. Curr Opin Biotechnol 13:181–187CrossRefGoogle Scholar
  13. Zwenger S, Basu C (2008) Plant terpenoids: applications and future potentials. Biotechnol Mol Biol Rev 3:001–007Google Scholar

Copyright information

© The Botanical Society of Japan and Springer Japan KK, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Applied Biological Science, Faculty of Science and TechnologyTokyo University of ScienceNodaJapan
  2. 2.Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
  3. 3.Center for Plant Systems Biology, VIBGhentBelgium

Personalised recommendations