Novel Imaging Modalities Shedding Light on Plant Biology: Start Small and Grow Big.

Natalie M Clark, Lisa Van den Broeck, Marjorie Guichard, Adam Stager, Herbert G Tanner, Ikram Blilou, Guido Grossmann, Anjali S Iyer-Pascuzzi, Alexis Maizel, Erin E Sparks, Rosangela Sozzani

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15 Scopus citations


The acquisition of quantitative information on plant development across a range of temporal and spatial scales is essential to understand the mechanisms of plant growth. Recent years have shown the emergence of imaging methodologies that enable the capture and analysis of plant growth, from the dynamics of molecules within cells to the measurement of morphometric and physiological traits in field-grown plants. In some instances, these imaging methods can be parallelized across multiple samples to increase throughput. When high throughput is combined with high temporal and spatial resolution, the resulting image-derived data sets could be combined with molecular large-scale data sets to enable unprecedented systems-level computational modeling. Such image-driven functional genomics studies may be expected to appear at an accelerating rate in the near future given the early success of the foundational efforts reviewed here. We present new imaging modalities and review how they have enabled a better understanding of plant growth from the microscopic to the macroscopic scale. Expected final online publication date for the Annual Review of Plant Biology, Volume 71 is April 29, 2020. Please see for revised estimates.
Original languageEnglish (US)
Pages (from-to)789-816
Number of pages28
JournalAnnual review of plant biology
Issue number1
StatePublished - Mar 3 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We apologize to all colleagues whose work could not be included in this review due to space limitations. We thank Lindsay Erndwein of Illustrations by LindZeaMays for illustrating the figures of this article. Research in the Sozzani lab was provided by the National Science Foundation (NSF) (CAREER MCB-1453130), NSF/Biotechnology and Biological Sciences Research Council (BBSRC) (NSF MCB 1517058), and the North Carolina Agricultural & Life Sciences Research Foundation in the College of Agriculture and Life Sciences at North Carolina State
University (to R.S.). Research in the Maizel lab is supported by DFG FOR2581, the Land BadenWürttemberg, the Chica und Heinz Schaller Stiftung, the CellNetworks cluster of excellence, and the Boehringer Ingelheim Stiftung Plus3 program. E.E.S. is supported by grants from the Delaware Biosciences Center for Advanced Technology, the University of Delaware Research Foundation, and the Thomas Jefferson Fund. A.S. is supported by a University of Delaware Graduate Student Fellowship. Research in the A.S.I.P. lab is supported by grants from the Foundation for Food and Agriculture Research (FFAR), the NSF, Purdue University start-up funds, and USDA Hatch Funds (IND011293). G.G. is supported by research group funds from the Cluster of Excellence CellNetworks and a grant from the Deutsche Forschungsgemeinschaft
(GR 4559/3-1). I.B. was supported by King Abdullah University of Science and Technology (KAUST).


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