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      THESEUS1 modulates cell wall stiffness and abscisic acid production in Arabidopsis thaliana

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          Plants need to constantly adapt to a changing environment. Adaptation includes responses to biotic and abiotic stress. Key elements determining the response to abiotic stress are the cell walls surrounding all plant cells and the phytohormone abscisic acid, which influence turgor pressure in plants. Turgor pressure in plant cells is much higher than in animal cells and a key driver of plant growth and development. Here, we investigate the mechanism regulating cell wall stiffness and coordinating changes in stiffness and turgor with abscisic acid production. We characterize key elements of the mechanism and dissect its mode of action. This knowledge will enable us to improve plant resistance to drought stress, which is necessary due to our changing environment.

          Abstract

          Plant cells can be distinguished from animal cells by their cell walls and high-turgor pressure. Although changes in turgor and the stiffness of cell walls seem coordinated, we know little about the mechanism responsible for coordination. Evidence has accumulated that plants, like yeast, have a dedicated cell wall integrity maintenance mechanism. It monitors the functional integrity of the wall and maintains integrity through adaptive responses induced by cell wall damage arising during growth, development, and interactions with the environment. These adaptive responses include osmosensitive induction of phytohormone production, defense responses, as well as changes in cell wall composition and structure. Here, we investigate how the cell wall integrity maintenance mechanism coordinates changes in cell wall stiffness and turgor in Arabidopsis thaliana. We show that the production of abscisic acid (ABA), the phytohormone-modulating turgor pressure, and responses to drought depend on the presence of a functional cell wall. We find that the cell wall integrity sensor THESEUS1 modulates mechanical properties of walls, turgor loss point, ABA biosynthesis, and ABA-controlled processes. We identify RECEPTOR-LIKE PROTEIN 12 as a component of cell wall integrity maintenance–controlling, cell wall damage–induced jasmonic acid (JA) production. We propose that THE1 is responsible for coordinating changes in turgor pressure and cell wall stiffness.

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          A new mathematical model for relative quantification in real-time RT-PCR.

          M. Pfaffl (2001)
          Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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              Simultaneous inference in general parametric models.

              Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                23 December 2021
                4 January 2022
                23 December 2021
                : 119
                : 1
                : e2119258119
                Affiliations
                [1] aInstitute for Biology, Faculty of Natural Sciences, Norwegian University of Science and Technology , 7491 Trondheim, Norway;
                [2] bDivision of Plant Physiology, Department of Biology, Philipps University of Marburg , 35043 Marburg, Germany;
                [3] cInstitut Lumière Matière, UMR5306, Université Lyon, 1-CNRS 69622 Villeurbanne, France;
                [4] dInstitute of Technology, University of Tartu , 50411 Tartu, Estonia;
                [5] eDepartment of Botany and Plant Pathology, Purdue University , West Lafayette, IN 47907
                Author notes
                3To whom correspondence may be addressed. Email: thorsten.hamann@ 123456ntnu.no .

                Edited by Sean Cutler, Department of Botany and Plant Sciences, University of California, Riverside, CA; received October 27, 2021; accepted November 14, 2021

                Author contributions: L.B., J.S., T.E., L.V., G.Y., J.M.G., J.M., T.D., S.A.M.M., and T.H. designed research; L.B., J.S., T.E., Z.B., L.V., G.Y., J.M.G., T.T., C.Ø., N.G.-B., S.J.-S., J.M., S.A.M.M., and T.H. performed research; L.B., J.S., T.E., L.V., G.Y., J.M.G., T.T., J.M., H.K., T.D., S.A.M.M., and T.H. analyzed data; and L.B., J.S., T.E., L.V., N.G.-B., H.K., T.D., S.A.M.M., and T.H. wrote the paper.

                1Present address: Research Center for Non-Destructive Testing GmbH, A 4040 Linz, Austria.

                2Present address: Laboratory of Plant Physiology, Wageningen University, 6708 PB Wageningen, The Netherlands.

                Author information
                https://orcid.org/0000-0003-3171-8181
                https://orcid.org/0000-0001-5285-0099
                https://orcid.org/0000-0002-2169-0536
                https://orcid.org/0000-0002-5029-2609
                https://orcid.org/0000-0003-0808-4037
                https://orcid.org/0000-0001-8460-5151
                Article
                202119258
                10.1073/pnas.2119258119
                8740707
                34949719
                9677dace-e566-40a1-a625-df16884decb0
                Copyright © 2021 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                : 14 November 2021
                Page count
                Pages: 10
                Funding
                Funded by: Australian Research Council (ARC) 501100000923
                Award ID: DE140100946
                Award Recipient : Scott A M McAdam
                Funded by: U.S. Department of Agriculture (USDA) 100000199
                Award ID: Hatch Project 1014908
                Award Recipient : Scott A M McAdam
                Funded by: EEA Grants (European Economic Area Grants) 501100007048
                Award ID: 7F14155 CYTOWALL
                Award Recipient : Nora Gigli-Bisceglia Award Recipient : Thorsten Hamann
                Funded by: Eesti Teadusagentuur (Estonian Research Council) 501100002301
                Award ID: PRG433
                Award Recipient : Joachim Matthias Gerhold Award Recipient : Hannes Kollist
                Funded by: EC | European Regional Development Fund (ERDF) 501100008530
                Award ID: NA
                Award Recipient : Joachim Matthias Gerhold Award Recipient : Hannes Kollist
                Funded by: Norges Teknisk-Naturvitenskapelige Universitet (NTNU) 100009123
                Award ID: NA
                Award Recipient : Laura Bacete Award Recipient : Julia Schulz
                Categories
                428
                Biological Sciences
                Plant Biology

                plant cell wall,cell wall integrity,abscisic acid,the1
                plant cell wall, cell wall integrity, abscisic acid, the1

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