| Literature DB >> 33404501 |
Athul Vijayan1, Rachele Tofanelli1, Sören Strauss2, Lorenzo Cerrone3, Adrian Wolny3,4, Joanna Strohmeier1, Anna Kreshuk4, Fred A Hamprecht3, Richard S Smith2, Kay Schneitz1.
Abstract
A fundamental question in biology is how morphogenesis integrates the multitude of processes that act at different scales, ranging from the molecular control of gene expression to cellular coordination in a tissue. Using machine-learning-based digital image analysis, we generated a three-dimensional atlas of ovule development in Arabidopsis thaliana, enabling the quantitative spatio-temporal analysis of cellular and gene expression patterns with cell and tissue resolution. We discovered novel morphological manifestations of ovule polarity, a new mode of cell layer formation, and previously unrecognized subepidermal cell populations that initiate ovule curvature. The data suggest an irregular cellular build-up of WUSCHEL expression in the primordium and new functions for INNER NO OUTER in restricting nucellar cell proliferation and the organization of the interior chalaza. Our work demonstrates the analytical power of a three-dimensional digital representation when studying the morphogenesis of an organ of complex architecture that eventually consists of 1900 cells.Entities:
Keywords: 3D digital atlas; A. thaliana; developmental biology; image analysis; machine learning; ovule; plant biology; plants; segmentation
Mesh:
Year: 2021 PMID: 33404501 PMCID: PMC7787667 DOI: 10.7554/eLife.63262
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140