4.6 Article

A Sizer model for cell differentiation in Arabidopsis thaliana root growth

期刊

MOLECULAR SYSTEMS BIOLOGY
卷 14, 期 1, 页码 -

出版社

WILEY
DOI: 10.15252/msb.20177687

关键词

Arabidopsis root zonation; brassinosteroids; cell differentiation; computational analysis; phenotypic variability

资金

  1. Ministerio de Economia y Competitividad (Spain)
  2. Fondo Europeo de Desarrollo Regional FEDER (EU) [FIS2015-66503-C3-3-P]
  3. MINECO [FIS2012-37655-C02-02, FIS2009-13360-C03-01]
  4. Generalitat de Catalunya through Grup de Recerca Consolidat [2014 SGR 878]
  5. Spanish Ministry of Economy and Competitiveness (MINECO) [BIO2016-78955, BIO2013-43873]
  6. Developing an European American NGS Network (DEANN) from FP7-PEOPLE-IRSES
  7. Spanish Ministry of Economy and Competitiveness [BIO2010-16673]
  8. FI PhD fellowship from Generalitat de Catalunya
  9. JAE-CSIC PhD fellowship in A. I.C.-D. laboratory
  10. Severo Ochoa Programme for Centers of Excellence in R&D in A.I.C-D. laboratory [SEV-2015-0533]
  11. ERC Consolidator Grant from the European Research Council [ERC-2015-CoG-683163]

向作者/读者索取更多资源

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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