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Morphodynamic Atlas for Drosophila Development

View ORCID ProfileNoah P Mitchell, View ORCID ProfileMatthew F Lefebvre, Vishank Jain-Sharma, View ORCID ProfileNikolas Claussen, Marion K Raich, Hannah J Gustafson, Andreas R Bausch, View ORCID ProfileSebastian J Streichan
doi: https://doi.org/10.1101/2022.05.26.493584
Noah P Mitchell
1Kavli Institute for Theoretical Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA
2Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA
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Matthew F Lefebvre
2Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA
3Department of Molecular Biology, Princeton University, Princeton, NJ, USA
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Vishank Jain-Sharma
2Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA
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Nikolas Claussen
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Marion K Raich
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Hannah J Gustafson
2Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA
4Biomolecular Science and Engineering, University of California Santa Barbara
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Andreas R Bausch
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Sebastian J Streichan
2Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA
4Biomolecular Science and Engineering, University of California Santa Barbara
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  • For correspondence: streicha@ucsb.edu
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Abstract

During morphogenesis, diverse cell-scale and tissue-scale processes couple to dynamically sculpt organs. In this coupling, genetic expression patterns and biochemical signals regulate and respond to mechanical deformations to ensure reproducible and robust changes in tissue geometry. A long-standing approach to characterize these interactions has been the construction of expression atlases, and these atlases have necessarily relied on fixed snapshots of embryogenesis. Addressing how expression profiles relate to tissue dynamics, however, requires a scheme for spatiotemporal registration across different classes of data that incorporates both live samples and fixed datasets. Here, we construct a morphodynamic atlas that unifies fixed and live datasets – from gene expression profiles to cytoskeletal components – into a single, morphological consensus timeline. This resource and our computational approach to global alignment facilitate hypothesis testing using quantitative comparison of data both within and across ensembles, with resolution in both space and time to relate genes to tissue rearrangement, cell behaviors, and out-of-plane motion. Examination of embryo kinematics reveals stages in which tissue flow patterns are quasi-stationary, arranged as a sequence of ‘morphodynamic modules’. Temperature perturbations tune the duration of one such module – during body axis elongation – according to a simple, parameter-free scaling in which the total integrated tissue deformation is achieved at a temperature-dependent rate. By extending our approach to visceral organ formation during later stages of embryogenesis, we highlight how morphodynamic atlases can incorporate complex shapes deforming in 3D. In this context, morphodynamic modules are reflected in some, but not all, measures of tissue motion. Our approach and the resulting atlas opens up the ability to quantitatively test hypotheses with resolution in both space and time, relating genes to tissue rearrangement, cell behaviors, and organ motion.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 27, 2022.
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Morphodynamic Atlas for Drosophila Development
Noah P Mitchell, Matthew F Lefebvre, Vishank Jain-Sharma, Nikolas Claussen, Marion K Raich, Hannah J Gustafson, Andreas R Bausch, Sebastian J Streichan
bioRxiv 2022.05.26.493584; doi: https://doi.org/10.1101/2022.05.26.493584
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Morphodynamic Atlas for Drosophila Development
Noah P Mitchell, Matthew F Lefebvre, Vishank Jain-Sharma, Nikolas Claussen, Marion K Raich, Hannah J Gustafson, Andreas R Bausch, Sebastian J Streichan
bioRxiv 2022.05.26.493584; doi: https://doi.org/10.1101/2022.05.26.493584

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