A Sizer model for cell differentiation in Arabidopsis thaliana root growth |
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Authors: | Irina Pavelescu Josep Vilarrasa‐Blasi Ainoa Planas‐Riverola Mary‐Paz González‐García Ana I Caño‐Delgado Marta Ibañes |
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Affiliation: | 1. Department of Molecular Genetics, Center for Research in Agricultural Genomics (CRAG), CSIC‐IRTA‐UAB‐UB, Campus UAB, Bellaterra (Cerdanyola del Vallès), Barcelona, Spain;2. Departament de Física de la Matèria Condensada, Universitat de Barcelona, Barcelona, Spain;3. Department of Molecular Genetics, Center for Research in Agricultural Genomics (CRAG), CSIC‐IRTA‐UAB‐UB, Campus UAB, Bellaterra (Cerdanyola del Vallès), Barcelona, SpainThese authors contributed equally to this work;4. Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Barcelona, SpainThese authors contributed equally to this work |
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Abstract: | ![]() Plant roots grow due to cell division in the meristem and subsequent cell elongation and differentiation, a tightly coordinated process that ensures growth and adaptation to the changing environment. How the newly formed cells decide to stop elongating becoming fully differentiated is not yet understood. To address this question, we established a novel approach that combines the quantitative phenotypic variability of wild‐type Arabidopsis roots with computational data from mathematical models. Our analyses reveal that primary root growth is consistent with a Sizer mechanism, in which cells sense their length and stop elongating when reaching a threshold value. The local expression of brassinosteroid receptors only in the meristem is sufficient to set this value. Analysis of roots insensitive to BR signaling and of roots with gibberellin biosynthesis inhibited suggests distinct roles of these hormones on cell expansion termination. Overall, our study underscores the value of using computational modeling together with quantitative data to understand root growth. |
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Keywords: | Arabidopsis root zonation brassinosteroids cell differentiation computational analysis phenotypic variability |
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