title: Integrated genetic and computation methods for in planta cytometry.
abstract: We present the coupled use of specifically localized fluorescent gene markers and image processing for automated quantitative analysis of cell growth and genetic activity across living plant tissues. We used fluorescent protein markers to identify cells, create seeds and boundaries for the automatic segmentation of cell geometries and ratiometrically measure gene expression cell by cell in Arabidopsis thaliana.
authors.affiliation: Department of Plant Sciences, University of Cambridge, Cambridge, UK.
authors.forename: Fernán
authors.initials: F
authors.lastname: Federici
authors.forename: Lionel
authors.initials: L
authors.lastname: Dupuy
authors.forename: Laurent
authors.initials: L
authors.lastname: Laplaze
authors.forename: Marcus
authors.initials: M
authors.lastname: Heisler
authors.forename: Jim
authors.initials: J
authors.lastname: Haseloff
mesh_terms: D017360:Arabidopsis / Q000166:cytology / Q000235:genetics*; D002462:Cell Membrane / Q000235:genetics / Q000502:physiology; D019295:Computational Biology; D003583:Cytokinins / Q000494:pharmacology; D018507:Gene Expression Regulation, Developmental; D018506:Gene Expression Regulation, Plant; D018613:Microscopy, Confocal; D008856:Microscopy, Fluorescence; D030821:Plants, Genetically Modified / Q000166:cytology / Q000235:genetics*; D012639:Seeds / Q000166:cytology / Q000235:genetics* / Q000648:ultrastructure
chemical_list: D003583:Cytokinins