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Identification of growth regulators using cross-species network analysis in plants
Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, Belgium; VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, Belgium; Institute of Biosciences and Bioresources, National Research Council (CNR), Via Amendola 165/A, Bari, Italy.
Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, Belgium; VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, Belgium.
Umeå University, Faculty of Science and Technology, Department of Plant Physiology. Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).ORCID iD: 0000-0003-2673-9113
Umeå University, Faculty of Science and Technology, Department of Plant Physiology. Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC). Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, Belgium; VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, Belgium.ORCID iD: 0000-0002-8962-3778
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2022 (English)In: Plant Physiology, ISSN 0032-0889, E-ISSN 1532-2548, Vol. 190, no 4, p. 2350-2365Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Oxford University Press, 2022. Vol. 190, no 4, p. 2350-2365
National Category
Botany Plant Biotechnology
Identifiers
URN: urn:nbn:se:umu:diva-201619DOI: 10.1093/plphys/kiac374ISI: 000844537500001PubMedID: 35984294Scopus ID: 2-s2.0-85143141934OAI: oai:DiVA.org:umu-201619DiVA, id: diva2:1718931
Funder
The Research Council of Norway, 287465Available from: 2022-12-14 Created: 2022-12-14 Last updated: 2022-12-14Bibliographically approved

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Mähler, NiklasSeyfferth, CarolinMannapperuma, ChanakaStreet, NathanielHvidsten, Torgeir R.Nilsson, Ove

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Mähler, NiklasSeyfferth, CarolinMannapperuma, ChanakaStreet, NathanielHvidsten, Torgeir R.Nilsson, Ove
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