A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule

• Main Authors: Athul Vijayan, Rachele Tofanelli, Sören Strauss, Lorenzo Cerrone, Adrian Wolny, Joanna Strohmeier, Anna Kreshuk, Fred A Hamprecht, Richard S Smith, Kay Schneitz
• Format: Article
• Language: English
• Published: eLife Sciences Publications Ltd 2021-01-01
• Series: eLife
• Subjects: 3D digital atlas; image analysis; ovule; machine learning; segmentation; plants
• Online Access: https://elifesciences.org/articles/63262

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.