On the role of cell rearrangements in pattern formation

Session

Microscopy to Modelling

Authors

Dr Berta Verd (4), Dr Tim Fulton (1, 3), Kay Speiss (3), Dr Brooks Paige (2), Dr Benjamin Steventon (3)

Affiliations

1. Queen Mary University
2. University College London
3. University of Cambridge
4. University of Oxford

Keywords

data-driven mathematical modelling

Abstract text

During development, molecular patterns are often established in tissues undergoing morphogenesis and where extensive cell rearrangements are taking place. In order to understand the formation of molecular patterns and their evolvability, it is important we take the role of cell movements explicitly into account. Data-driven mathematical modelling of gene regulatory networks (GRNs) has been very successful at uncovering the mechanisms underlying the formation of complex dynamic molecular patterns in development. However, our efforts have often centred around systems where the timescales of gene expression and morphogenesis could be separated and hence, where pattern could be understood as a function of GRN dynamics alone. While useful, this has greatly restricted the types of developmental patterning systems that could be studied.

We have developed a methodology for reverse-engineering the GRNs driving pattern formation that allows us to take cell movements explicitly into account. We can now fit dynamical models to approximated gene expression trajectories (AGETs) constructed by combining quantitative spatial gene expression data with cell tracking data from live-imaging the developing tissue. The resulting models recapitulate pattern formation on a growing tissue when simulated directly on cell tracks (Live-modelling). By taking this approach to study Tbox patterning in the elongating zebrafish tailbud we have addressed how cell rearrangements and specific modes of cell movements drive patterning as a function of temporal morphogen exposure. We are now applying this framework to axial elongation in cichlid fishes to investigate how developmental patterns evolve.