Mapping gene expression dynamics to developmental phenotypes with information entropy analysis
Type
Article
Abstract
The development of multicellular organisms entails a deep connection between time-dependent biochemical processes taking place at the subcellular level and the resulting macroscopic phenotypes that arise in populations of up to trillions of cells. Constructing a statistical mechanics of developmental processes would help to understand how microscopic genotypes map onto macroscopic phenotypes, a general goal across biology. Here we present an attempt in this direction in the context of the fruit fly, Drosophila melanogaster. Applying a variety of information-theoretic measures to public transcriptomics datasets of whole fly embryos during development, we show that the global temporal dynamics of gene expression can be understood as a process that probabilistically guides embryonic dynamics across macroscopic phenotypic stages. In particular, our results suggest signatures of irreversibility in the information complexity of transcriptomic dynamics, as measured mainly by the permutation entropy of indexed ensembles (PI entropy). We also show that the dynamics of PI entropy correlate strongly with developmental stages. Overall, this is a test case in applying information complexity analysis to relate the statistical mechanics of biomarkers to macroscopic developmental dynamics.
Department(s)
Physics and Astronomy
Journal or Book Title
npj Systems Biology and Applications
Publication Year
2026
DOI
https://doi.org/10.1038/s41540-026-00748-6
Publisher
Springer Nature
Rights Management
The original authors own the copyright to this work and have granted Carleton College permission to display and distribute it online through the Carleton College Library. For more information on the copyright status of this work, refer to the current copyright holder.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Pattanayak, Arjendu K., Ben Ansbacher, Malachy Guzman, and Jordi Garcia-Ojalvo., "Mapping gene expression dynamics to developmental phenotypes with information entropy analysis". npj Systems Biology and Applications, vol. , no. , 2026. Available at: https://doi.org/https://doi.org/10.1038/s41540-026-00748-6. . [Online]. Accessed via Faculty Work. Physics and Astronomy. Carleton Digital Commons. https://digitalcommons.carleton.edu/phys_faculty/19
The definitive version is available at https://doi.org/https://doi.org/10.1038/s41540-026-00748-6
