Abstract
Modern imaging approaches enable the acquisition of 3D and 4D datasets capturing plant organ development at cellular resolution. Computational analyses of these data enable the digitization and analysis of individual cells. In order to fully harness the information encoded within these datasets, annotation of the cell types within organs may be performed. This enables data points to be placed within the context of their position and identity, and for equivalent cell types to be compared between samples. The shoot apical meristem (SAM) in plants is the apical stem cell niche from which all above ground organs are derived. We developed 3DCellAtlas Meristem which enables the complete cellular annotation of all cells within the SAM with up to 96% accuracy across all cell types in Arabidopsis and 99% accuracy in tomato SAMs. Successive layers of cells are identified along with the central stem cells, boundary regions, and layers within developing primordia. Geometric analyses provide insight into the morphogenetic process that occurs during these developmental processes. Coupling these digital analyses with reporter expression will enable multidimensional analyses to be performed at single cell resolution. This provides a rapid and robust means to perform comprehensive cellular annotation of plant SAMs and digital single cell analyses, including cell geometry and gene expression. This fills a key gap in our ability to analyse and understand complex multicellular biology in the apical plant stem cell niche and paves the way for digital cellular atlases and analyses.
Highlights
The ability to accurately capture, quantify and compare phenotypes across scales is central to understanding genome function, and establishing genotype–phenotype relationships
The inability to perform cellular annotation represents an obstacle in the ability to analyse these quantitative image datasets, to extract their key biologically significant features through the functional annotation of data points, and to identify equivalent data points between different samples
We followed this procedure using Arabidopsis floral meristems and tomato vegetative meristems to test the accuracy with which cell types can be identified
Summary
The ability to accurately capture, quantify and compare phenotypes across scales is central to understanding genome function, and establishing genotype–phenotype relationships In plants this has been largely examined at macroscopic levels [12, 15]. The inability to perform cellular annotation represents an obstacle in the ability to analyse these quantitative image datasets, to extract their key biologically significant features through the functional annotation of data points (cells), and to identify equivalent data points between different samples. In this instance, individual cells and their properties can be treated as quantitative data points within the complex structure of a plant
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