Computational Approaches to Developmental Biology
Citation
Blondel, Leo. 2021. Computational Approaches to Developmental Biology. Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.Abstract
The origin and evolution of new genes is an active topic of research, relying on the taxonomical diversity now present in sequence databases. Using those databases, we described how \textit{oskar}, a key determinant of germ cell determination, likely arose from a horizontal gene transfer and then described its evolution and conservation in insects. The number of ovarioles, the egg-producing unit of the insect ovary, is hypothesized to inform the individual’s reproductive capacity. Using network biology approaches, we analyzed the effect of signaling pathway genes on the number of ovarioles and eggs laid by Drosophila melanogaster. We found putative gene modules regulating both traits and predicted novel genes affecting both phenotypes. The specification of germ layers is a central mechanism of the embryogenesis of animals, but the underlying molecular mechanisms have only been extensively studied in model organisms. Using Parhyale hawaiensis, a crustacean amphipod, I generated preliminary methods for the generation of single cell RNA sequencing of early embryogenesis, as well as recorded with light sheet microscopy the first three days of embryogenesis. The preliminary analyses of the sequencing datasets were inconclusive, but, analyzing one of the microscopy datasets, I described new preliminary cellular dynamic results. Finally, to observe and annotate 4D microscopy datasets, I developed a tool that allows the visualization of large volumetric datasets in Virtual Reality.Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37369473
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