e heat map representations of the data with standardized parameters across time point comparisons and replicates (Video 4). Data analysis All data processing, analysis and plotting was performed in RStudio (2020; 2021). Scripts used to process the data and create figures are enclosed as Supplemental Information and available at https://github.com/kateharline/live_img_paper, https://github.com/kateharline/roeder_lab_proj-ects/tree/master/imagej_scripts and https://github.com/kateharline/jawd-paper.Data availability Imaging data will be deposited XXXX. Funding Kate Harline was supported by NSF Graduate Research Fellowship (DGE-1650441). This work was funded by NSF MCB-2203275 (AHKR), The Schwa
Open resource ↗kateharline/live_img_paper · pdf-raw-page:20 lines:1-63Unverified paper record
An optimized pipeline for live imaging whole Arabidopsis leaves at cellular resolution
bioRxiv · 2 Nov 2022 · 10.1101/2022.11.01.514724
Abstract
Live imaging is the gold standard for determining how cellular development gives rise to organs. However, tracking all individual cells across whole organs over large developmental time windows is extremely challenging. In this work, we provide a comparably simple method for confocal live imaging of Arabidopsis thaliana first leaves across early development. Our imaging method works for both wild-type leaves and the complex curved leaves of the jaw-1D mutant. We find that dissecting the cotyledons, affixing a coverslip above the samples and mounting samples with perfluorodecalin yields optimal imaging series for robust cellular and organ level analysis. We provide details of our complementary image processing steps in MorphGraphX software for segmenting cells, tracking the cell lineages, and measuring a suite of cellular growth properties. We also provide MorphoGraphX image processing scripts that we developed to automate analysis of segmented images and data presentation. Our imaging techniques and processing steps combine into a robust imaging pipeline. With this pipeline we are able to examine important nuances in the cellular growth and differentiation of jaw-D versus WT leaves that have not been demonstrated before. Our pipeline is a practical starting place for researchers new to live imaging plant leaves, but also to anyone interested in improving the throughput and reliability of their live imaging process.
Plant phenotyping relevance
葉全体の共焦点ライブイメージング、細胞セグメンテーション・系譜追跡・成長特性測定を統合した実用的な表現型解析パイプラインの開発であり、方法が研究の中心です。
abstractIn this work, we provide a comparably simple method for confocal live imaging of Arabidopsis thaliana first leaves across early development.
abstractWe provide details of our complementary image processing steps in MorphGraphX software for segmenting cells, tracking the cell lineages, and measuring a suite of cellular growth properties.
abstractOur imaging techniques and processing steps combine into a robust imaging pipeline.
Code and data availability
The paper's phenotyping analysis code is publicly available in authors' GitHub repositories: MorphoGraphX processing/quantification scripts (iterative_growth_and_measures.py, multi_resize.py, batch_tiff.py) in roeder_lab_projects/mgx_scripts, ImageJ scripts, and R analysis/figure scripts in live_img_paper and jawdPaper
ndardized parameters across time point comparisons and replicates (Video 4). Data analysis All data processing, analysis and plotting was performed in RStudio (2020; 2021). Scripts used to process the data and create figures are enclosed as Supplemental Information and available at https://github.com/kateharline/live_img_paper, https://github.com/kateharline/roeder_lab_proj-ects/tree/master/imagej_scripts and https://github.com/kateharline/jawd-paper.Data availability Imaging data will be deposited XXXX. Funding Kate Harline was supported by NSF Graduate Research Fellowship (DGE-1650441). This work was funded by NSF MCB-2203275 (AHKR), The Schwartz Research Fund Award (AHKR), and the Nationa
Open resource ↗kateharline/roeder_lab_proj-ects · pdf-raw-page:20 lines:1-63nalysis All data processing, analysis and plotting was performed in RStudio (2020; 2021). Scripts used to process the data and create figures are enclosed as Supplemental Information and available at https://github.com/kateharline/live_img_paper, https://github.com/kateharline/roeder_lab_proj-ects/tree/master/imagej_scripts and https://github.com/kateharline/jawd-paper.Data availability Imaging data will be deposited XXXX. Funding Kate Harline was supported by NSF Graduate Research Fellowship (DGE-1650441). This work was funded by NSF MCB-2203275 (AHKR), The Schwartz Research Fund Award (AHKR), and the National Institute Of General Medical Sciences of the National Institutes of Health under
Open resource ↗kateharline/jawd-paper · pdf-raw-page:20 lines:1-63This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.