Abstract
A comprehensive understanding of plant growth and development requires the integration of the spatial and temporal dynamics of gene regulatory networks with changes in cellular geometry during 3D organ growth. 3DCellAtlas is an integrative computational pipeline that semi-automatically identifies cell type and position within radially symmetric plant organs, and simultaneously quantifies 3D cell anisotropy and reporter abundance at single-cell resolution. It is a powerful tool that generates digital single-cell cellular atlases of plant organs and enables 3D cell geometry and reporter abundance (gene/protein/biosensor) from multiple samples to be integrated at single-cell resolution across whole organs. Here we describe how to use 3DCellAtlas to process and analyze radially symmetric organs, and to identify cell types and extract geometric cell data within these 3D cellular datasets. We detail how to use two statistical tools in 3DCellAtlas to compare cellular geometries, and to analyze reporter abundance at single-cell resolution.
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Acknowledgments
G.W.B. was funded by Biotechnology and Biological Sciences Research Council (BBSRC) Grant BB/L010232/1 and a Birmingham Research Fellowship. P.S. was funded by BBSRC grant BB/J017604/1. T.D.M.J. is supported by a Royal Commission for the Exhibition of 1851 Fellowship. R.S.S. was funded by Swiss National Science Foundation Interdisciplinary Project Grant number CR32I3_143833 and the Max Planck Society.
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Stamm, P., Strauss, S., Montenegro-Johnson, T.D., Smith, R., Bassel, G.W. (2017). In Silico Methods for Cell Annotation, Quantification of Gene Expression, and Cell Geometry at Single-Cell Resolution Using 3DCellAtlas. In: Kleine-Vehn, J., Sauer, M. (eds) Plant Hormones. Methods in Molecular Biology, vol 1497. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6469-7_11
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DOI: https://doi.org/10.1007/978-1-4939-6469-7_11
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