ArticlePlant physiology2022
Identification of growth regulators using cross-species network analysis in plants.
Article in Plant physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- Cross-species transcriptomics uncovers shared responses to water deficiency in plants.The plant genome · 2026Article
- Co-option of transcription factors drives evolution of quantitative disease resistance against a necrotrophic pathogen.The Plant cell · 2025Article
- Challenges of translating Arabidopsis insights into crops.The Plant cell · 2025Review
- Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency.The Plant cell · 2025Article
- Investigating the Mechanisms of Adventitious Root Formation in Semi-Tender Cuttings ofInternational journal of molecular sciences · 2025Article
- Cross-species transcriptomics reveals differential regulation of essential photosynthesis genes in Hirschfeldia incana.G3 (Bethesda, Md.) · 2024Article
- Genome-Wide Analysis of MYB Genes inInternational journal of molecular sciences · 2023Article
- A Survey of the Transcriptomic Resources in Durum Wheat: Stress Responses, Data Integration and Exploitation.Plants (Basel, Switzerland) · 2023Review
- A common language: Cross-species network analysis reveals growth regulators.Plant physiology · 2022Article
Corrections and comments
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Authors and funding
15 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the need to increase plant productivity, one of the challenges plant scientists are facing is to identify genes that play a role in beneficial plant traits. Moreover, even when such genes are found, it is generally not trivial to transfer this knowledge about gene function across species to identify functional orthologs. Here, we focused on the leaf to study plant growth. First, we built leaf growth transcriptional networks in Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and aspen (Populus tremula). Next, known growth regulators, here defined as genes that when mutated or ectopically expressed alter plant growth, together with cross-species conserved networks, were used as guides to predict novel Arabidopsis growth regulators. Using an in-depth literature screening, 34 out of 100 top predicted growth regulators were confirmed to affect leaf phenotype when mutated or overexpressed and thus represent novel potential growth regulators. Globally, these growth regulators were involved in cell cycle, plant defense responses, gibberellin, auxin, and brassinosteroid signaling. Phenotypic characterization of loss-of-function lines confirmed two predicted growth regulators to be involved in leaf growth (NPF6.4 and LATE MERISTEM IDENTITY2). In conclusion, the presented network approach offers an integrative cross-species strategy to identify genes involved in plant growth and development.
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Registered trials
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