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The peri-cell-cycle in Arabidopsis

Open access
Beeckman, T., Burssens, S., Inze, D.·2001·Journal of Experimental Botany

Abstract

The root systems of plants proliferate via de novo formed meristems originating from differentiated pericycle cells. The identity of putative signals responsible for triggering some of the pericycle cells to re-enter the cell cycle remains unknown. Here, the cell cycle regulation in the pericycle of seedling roots of Arabidopsis thaliana (L.) HEYNH: is studied shortly after germination using various strategies. Based on the detailed analysis of the promoter-beta-glucuronidase activity of four key cell cycle regulatory genes, combined with cell length measurements, microdensitometry of DNA content, and experiments with a cell cycle-blocking agent, a model is proposed for cell cycle regulation in the pericycle at the onset of lateral root initiation. The results clearly show that before the first lateral root is initiated, the pericycle consists of dissimilar cell files in respect of their cell division history. Depending on the distance behind the root tip and on position in relation to the vascular tissue, particular pericycle cells remain in the G(2) phase of the cell cycle and are apparently more susceptible to lateral root initiation than others.

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Metadata

Authors
Beeckman, T., Burssens, S., & Inze, D.
Venue
Journal of Experimental Botany
Published
2001-03-01
Volume
52
Issue
suppl 1
Pages
403-411
ISSN
  • 0022-0957 (ISSN-L)
  • 1460-2431
OpenAlex
W2022707068
Cited by
231
References
0
FWCI
14.57
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The peri-cell-cycle in Arabidopsis. https://app.cochat.ai/papers/10.1093/jexbot/52.suppl_1.403
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Beeckman, T., Burssens, S., & Inze, D. (2001). The peri-cell-cycle in Arabidopsis. Journal of Experimental Botany. https://doi.org/10.1093/jexbot/52.suppl_1.403

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.