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

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.

Organ geometry channels reproductive cell fate in the Arabidopsis ovule primordium

“…Altogether, our work proposes a conceptual framework linking organ geometry, cell shape, and cell fate acquisition in the ovule primordium, which is potentially of broader relevance in plant patterning. In addition, the image resource published in this study is complementary to others capturing ovule development at later stages ( Lora et al, 2017 ; Vijayan et al, 2021 ). It also populates a growing number of 3D-segmented images of plant tissues and organs ( Wolny et al, 2020 ), which collectively build the fundament of a developmental atlas integrating morphogenesis with gene expression ( Hartmann et al, 2020 ).…”

“…It is described in discrete developmental stages capturing classes of primordia by their global shape and SMC appearance until meiosis and by the presence of integument layers and ovule curvature later on ( Grossniklaus and Schneitz, 1998 ). In addition, a 3D analysis of average cell volumes during primordium growth was recently provided ( Lora et al, 2017 ), and extensive 3D analysis was carried on for late ovule stages ( Vijayan et al, 2021 ). Yet, we lack a view of the patterning processes regulating early ovule primordium formation and how the dynamics of cell proliferation contributes to the cellular organization during primordium growth.…”

A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

“…3D reconstruction of A. thaliana ovule coupled with transcriptome sequencing provides incredibly detailed data about developmental processes of this organ (Vijayan et al, 2021), which can serve as a set of reference points for further integration of future single-cell data on this organ. Simultaneously, the methods of visualization and analysis of images also allow working with plants with larger organs, for example, with Nicotiana tabacum roots (Pasternak et al, 2017).…”

Deep learning-based high-throughput phenotyping can drive future discoveries in plant reproductive biology

“…Preliminary applications of deep learning in such instances have focused on identifying cells from images of plant tissues using segmentation (Wolny et al 2020 ). These methods have been used to describe ovule development (Vijayan et al 2021 ).…”