Abstract
How gene regulatory networks (GRNs) help produce phenotypic variation is a central question in developmental biology. A particularly well-studied class of GRNs are those performing segmentation: the subdivision of a developing organism’s body axis into repeating units. Segmentation can proceed either simultaneously, where every body segment is laid down at the same time, or sequentially, where new body segments are added one by one at the posterior of the embryo. A recent model proposes that both these modes of segmentation can be explained using one, multifunctional, GRN, the topology of which is derived from the pair rule system of the vinegar fly Drosophila melanogaster (which segments simultaneously). This GRN can be subdivided into two, modular, networks, the first of which establishes the initial pair rule prepattern, and the second of which converts this pattern into the segment polarity output. Which of these networks is active in a given tissue is controlled by the timer genes caudal, Dicheate, and odd-paired.
I use Nasonia vitripennis to investigate how this multifunctional segmentation GRN can produce different types of segmentation. Nasonia are scientifically interesting because they combine multiple methods of segmentation, so provide an ideal system to investigate how GRNs produce multiple phenotypes. In the anterior, Nasonia perform progressive segmentation: temporal segment specification along the anterior-posterior axis, from a pair-rule prepattern. In the posterior, they undergo sequential segmentation. I investigated the conservation of the Nasonia GRN using HCR, a method to visualize gene expression within whole, fixed tissue. I used tools from philosophy of science (the notion of activity-function, or function that does not describe how a trait is used) to argue that modelling can be used to define the intrinsic function of a GRN. These intrinsic functions can then be used as a definition of GRN homology. I then used these concepts to argue that the early network of Nasonia is homologous to that of Drosophila, but that the structure of the late network is not conserved. Because most of the unique segmentation dynamics in Nasonia occur during the early network, my data is unable to explain these unique dynamics using GRN topology alone. On the other hand, providing the Drosophila GRN model with the Nasonia timer gene expression patterns was able to produce Nasonia’s progressive segmentation. This demonstrates two things. Firstly, changes to GRN topology cannot explain Nasonia’s progressive segmentation, but dynamic modelling of GRNs can. This fits with previous work showing that a GRN structure is not a biological explanation, and that GRNs can exhibit different behaviours from the same topology. Secondly, I showed that progressive segmentation is an intermediate between simultaneous and sequential segmentation. Sequential and simultaneous segmentation are therefore a continuum, not a binary, and a remarkable variety of phenotypes could be produced by simply varying expression of the timer genes.