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Identifying a developmental transition in honey bees using gene expression data

View ORCID ProfileBryan C. Daniels, Ying Wang, Robert E. Page Jr, Gro V. Amdam
doi: https://doi.org/10.1101/2022.11.03.514986
Bryan C. Daniels
1School of Complex Adaptive Systems, Arizona State University, Tempe, Arizona, USA
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  • For correspondence: bryan.daniels.1@asu.edu
Ying Wang
2Banner Health Corporation, Phoenix, Arizona, USA
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Robert E. Page Jr
3School of Life Sciences, Arizona State University, Tempe, Arizona, USA
4Department of Entomology and Nematology, University of California Davis, Davis, California, USA
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Gro V. Amdam
3School of Life Sciences, Arizona State University, Tempe, Arizona, USA
5Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Aas, Norway
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Abstract

In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the method to data from honey bees, where a known developmental transition occurs between bees performing tasks in the nest and leaving the nest to forage. Our method, which makes use of the expected shape of the distribution of gene expression levels near a transition, successfully identifies the emergence of bistability and links it to genes that are known to be involved in the behavioral transition. This proof of concept demonstrates that going beyond correlative analysis to infer the shape of gene expression distributions might be used more generally to identify collective transitions from gene expression data.

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 4.0 International license.
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Posted November 07, 2022.
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Identifying a developmental transition in honey bees using gene expression data
Bryan C. Daniels, Ying Wang, Robert E. Page Jr, Gro V. Amdam
bioRxiv 2022.11.03.514986; doi: https://doi.org/10.1101/2022.11.03.514986
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Identifying a developmental transition in honey bees using gene expression data
Bryan C. Daniels, Ying Wang, Robert E. Page Jr, Gro V. Amdam
bioRxiv 2022.11.03.514986; doi: https://doi.org/10.1101/2022.11.03.514986

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