2020 article
BioVision Tracker: A semi-automated image analysis software for spatiotemporal gene expression tracking in Arabidopsis thaliana
PLANT CELL BIOLOGY, Vol. 160, pp. 419–436.
MeSH headings : Arabidopsis / genetics; Automation; Gene Expression Regulation, Plant; Image Processing, Computer-Assisted; Plant Roots / anatomy & histology; Software; Time Factors
TL;DR:
A procedure for analyzing 3D microscopy images to track spatiotemporal gene expression signals using the MATLAB-based BioVision Tracker software, which requires either a fluorescence image or a brightfield image to analyze root geometry and afluorescence image to capture and track temporal changes in gene expression.
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Added: February 22, 2021
Fluorescence microscopy can produce large quantities of data that reveal the spatiotemporal behavior of gene expression at the cellular level in plants. Automated or semi-automated image analysis methods are required to extract data from these images. These data are helpful in revealing spatial and/or temporal-dependent processes that influence development in the meristematic region of plant roots. Tracking spatiotemporal gene expression in the meristem requires the processing of multiple microscopy imaging channels (one channel used to image root geometry which serves as a reference for relating locations within the root, and one or more channels used to image fluorescent gene expression signals). Many automated image analysis methods rely on the staining of cell walls with fluorescent dyes to capture cellular geometry and overall root geometry. However, in long time-course imaging experiments, dyes may fade which hinders spatial assessment in image analysis. Here, we describe a procedure for analyzing 3D microscopy images to track spatiotemporal gene expression signals using the MATLAB-based BioVision Tracker software. This software requires either a fluorescence image or a brightfield image to analyze root geometry and a fluorescence image to capture and track temporal changes in gene expression.