Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 560918
Title From stained plant tissues to quantitative cell segmentation analysis with MorphoGraphX
Author(s) Kerstens, Merijn; Strauss, Soeren; Smith, Richard; Willemsen, Viola
Source In: Plant Embryogenesis / Bayer, M., New York : Humana Press Inc. (Methods in Molecular Biology ) - ISBN 9781071603413 - p. 63 - 83.
DOI https://doi.org/10.1007/978-1-0716-0342-0_6
Department(s) Laboratory of Molecular Biology
Publication type Peer reviewed book chapter
Publication year 2020
Keyword(s) 3D imaging - 3D segmentation - Cell volume - Embryos - Lateral roots - MorphoGraphX - Roots - SCRI Renaissance
Abstract

Development and growth of plant organs is determined by a myriad of molecular processes that occur in each individual cell. As a direct consequence of these processes, cells alter in size and shape. They therefore serve as excellent parameters to thoroughly understand gene function. However, conventional single-plane analyses fail to accurately capture cell metrics. Here, we present a comprehensive illustrated guide that demonstrates how SCRI Renaissance 2200 staining of Arabidopsis thaliana embryos and roots can be combined with the open-source application MorphoGraphX to quantify cell parameters in 3D. We compare this staining method with other common staining techniques and provide examples of embryo and root tissue segmentation. With our novel approach, subtle single-cell phenotypes can be identified in their native context, providing new possibilities to dissect gene networks.

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