Quantitative Analyses of Cell Division in Plants

Quantitative Analyses of Cell Division in Plants At the molecular level regulatory interactions between cell cycle genes are being uncovered rapidly, but less progress is made in unravelling how these molecular events regulate growth processes at the level of cells and of the whole organism. The main obstacle is the absence of a set of analytical tools that are powerful enough to determine pertinent parameters and, at the same time, relatively easy to use by non-specialized laboratories. Appropriate methodology to obtain this type of data has been pioneered in the first half of the last century and is now commonly defined as ‘kinematic analysis’. Unfortunately, the laborious nature of these analyses and the relatively complex numerical methods used, have limited their use to only a handful of specialized research groups. In this article we attempt to present an accessible entry to this methodology, particularly in terms of the mathematical framework. We start describing the simplest possible system, i.e., a virtually homogenous cell suspension culture. Then, we outline the analysis of dicotyledonous leaves, root tips, monocotyledonous leaves, and finally shoot apical meristems. For each of these systems we discuss the details of the calculation of cell division parameters such as cell cycle duration, size of the meristem and number of cells contained in it, which enables answering fundamental questions about the relative contribution of differences in cell production and cell size to variation in growth. In addition, we discuss the assumptions and limitations of these and alternative methodologies with the aim to facilitate the choice of appropriate analyses depending on the specific research question. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant Molecular Biology Springer Journals

Quantitative Analyses of Cell Division in Plants

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Kluwer Academic Publishers
Copyright © 2006 by Springer
Life Sciences; Biochemistry, general; Plant Sciences; Plant Pathology
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