Imaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolution.
Quantitative information on growing organs is required to better understand morphogenesis in both plants and animals. However, detailed analyses of growth patterns at cellular resolution have remained elusive. We developed an approach, multiangle image acquisition, three-dimensional reconstruction and cell segmentation-automated lineage tracking (MARS-ALT), in which we imaged whole organs from multiple angles, computationally merged and segmented these images to provide accurate cell identification in three dimensions and automatically tracked cell lineages through multiple rounds of cell division during development. Using these methods, we quantitatively analyzed Arabidopsis thaliana flower development at cell resolution, which revealed differential growth patterns of key regions during early stages of floral morphogenesis. Lastly, using rice roots, we demonstrated that this approach is both generic and scalable.
Fernandez
Romain
R
Equipe-projet Virtual Plants, Institut National de la Recherche en Informatique et en Automatique, Sophia Antipolis, France and Unité Mixte de Recherche Développement et Adaptation des Plantes, Montpellier, France.
Das
Pradeep
P
Mirabet
Vincent
V
Moscardi
Eric
E
Traas
Jan
J
Verdeil
Jean-Luc
JL
Malandain
Grégoire
G
Godin
Christophe
C
D000465:Algorithms; D017360:Arabidopsis / Q000166:cytology*; D002455:Cell Division / Q000502:physiology; D019070:Cell Lineage / Q000502:physiology*; D035264:Flowers / Q000166:cytology* / Q000254:growth & development*; D049452:Green Fluorescent Proteins; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D018519:Meristem / Q000166:cytology* / Q000254:growth & development; D010940:Plant Proteins / Q000378:metabolism; D015203:Reproducibility of Results; D013997:Time Factors
D010940:Plant Proteins; D049452:Green Fluorescent Proteins