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Automated imaging of duckweed growth and development

View ORCID ProfileKevin L. Cox Jr., Jordan Manchego, View ORCID ProfileBlake C. Meyers, View ORCID ProfileKirk J. Czymmek, View ORCID ProfileAlex Harkess
doi: https://doi.org/10.1101/2021.07.21.453240
Kevin L. Cox Jr.
1Donald Danforth Plant Science Center, St. Louis, MO 63132
2Howard Hughes Medical Institute, Chevy Chase, MD 20815
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Jordan Manchego
3HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806
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Blake C. Meyers
1Donald Danforth Plant Science Center, St. Louis, MO 63132
4Department of Biology, University of Missouri, Columbia, MO 65211
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Kirk J. Czymmek
1Donald Danforth Plant Science Center, St. Louis, MO 63132
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  • For correspondence: aharkess@hudsonalpha.org KCzymmek@danforthcenter.org
Alex Harkess
3HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806
5Department of Crop, Soil, and Environmental Sciences, Auburn University, Auburn, AL 36849
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  • For correspondence: aharkess@hudsonalpha.org KCzymmek@danforthcenter.org
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Abstract

Duckweeds are some of the smallest angiosperms, possessing a simple body architecture and high rates of biomass accumulation. They can grow near-exponentially via clonal propagation. Understanding their reproductive biology, growth, and development is essential to unlock their potential for phytoremediation, carbon capture, and nutrition. However, there is a lack of non-laborious and convenient methods for spatially and temporally imaging an array of duckweed plants and growth conditions in the same experiment. We developed an automated microscopy approach to record time-lapse images of duckweed plants growing in 12-well cell culture plates. As a proof-of-concept experiment, we grew duckweed on semi-solid media with and without sucrose and monitored its effect on their growth over 3 days. Using the PlantCV toolkit, we quantified the thallus area of individual plantlets over time, and showed that L. minor grown on sucrose had an average growth rate four times higher than without sucrose. This method will serve as a blueprint to perform automated high-throughput growth assays for studying the development patterns of duckweeds from different species, genotypes, and conditions.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted July 22, 2021.
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Automated imaging of duckweed growth and development
Kevin L. Cox Jr., Jordan Manchego, Blake C. Meyers, Kirk J. Czymmek, Alex Harkess
bioRxiv 2021.07.21.453240; doi: https://doi.org/10.1101/2021.07.21.453240
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Automated imaging of duckweed growth and development
Kevin L. Cox Jr., Jordan Manchego, Blake C. Meyers, Kirk J. Czymmek, Alex Harkess
bioRxiv 2021.07.21.453240; doi: https://doi.org/10.1101/2021.07.21.453240

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