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Morphometrics of complex cell shapes: lobe contribution elliptic Fourier analysis (LOCO-EFA)

Sánchez-Corrales, Yara E., Hartley, Matthew, van Rooij, Jop, Maree, Athanasius F. M. ORCID: and Grieneisen, Verônica A. ORCID: 2018. Morphometrics of complex cell shapes: lobe contribution elliptic Fourier analysis (LOCO-EFA). Development 145 (6) , dev156778. 10.1242/dev.156778

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Quantifying cell morphology is fundamental to the statistical study of cell populations, and can help unravel mechanisms underlying cell and tissue morphogenesis. Current methods, however, require extensive human intervention, are highly parameter sensitive, or produce metrics that are difficult to interpret biologically. We therefore developed a method, lobe contribution elliptical Fourier analysis (LOCO-EFA), which generates from digitalised two-dimensional cell outlines meaningful descriptors that can be directly matched to morphological features. This is shown by studying well-defined geometric shapes as well as actual biological cells from plant and animal tissues. LOCO-EFA provides a tool to phenotype efficiently and objectively populations of cells, here demonstrated by applying it to the complex shaped pavement cells of Arabidopsis thaliana wild-type and speechless leaves, and Drosophila amnioserosa cells. To validate our method's applicability to large populations, we analysed computer-generated tissues. By controlling in silico cell shape, we explored the potential impact of cell packing on individual cell shape, quantifying through LOCO-EFA deviations between the specified shape of single cells in isolation and the resultant shape when they interact within a confluent tissue.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Biosciences
Additional Information: This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
Publisher: Company of Biologists
ISSN: 0950-1991
Date of First Compliant Deposit: 11 March 2019
Date of Acceptance: 2 February 2018
Last Modified: 25 Oct 2022 13:41

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