Decoding Tissue Patterning: Gene Regulatory Networks and Morphogen Dynamics

At the heart of tissue patterning are gene regulatory networks (GRN). This is the case in the neural tube where the expression of groups of transcription factors (TFs) determines the pattern of cell type generation. Selective repressive and inductive interactions between pairs of transcription factors establish discrete changes in gene expression. This produces a transcriptional code that defines distinct progenitor domains and controls the subtype identity of neurons generated from each domain. Our goal is to identify the components and connections in this network and understand their function.

We are taking a systematic approach to identify the TFs that comprise the neural tube GRN by profiling the transcriptional responses of neural progenitors exposed to different levels and durations of Shh signalling. Although many players are known, components and mechanisms remain to be discovered. To do this we take advantage of new technology such as single cell transcriptome profiling approaches and we develop new experimental and computational methods to profile gene expression.

To obtain information about the network and to test function, genetic perturbation assays are crucial. To this end we use and develop methods to disrupt gene expression, including developing multiplexed in vivo CRISPR screening methods. Together these analyses allow us to understand the mechanism and underlying logic of gene regulation and to test these we construct and test mathematical models of the transcriptional network.

Morphogen signalling

In many developing tissues, gene regulatory networks are controlled by gradients of extracellular signalling molecules – often termed morphogens – that act as patterning cues. This is the case in the neural tube where gradients of signals directs the pattern of gene expression. We found that the duration and integration of signals, as well as the level, is important for patterning. This has led to a revision of the morphogen concept in which the dynamics of the morphogen drive patterning.

We hypothesize that the wiring of the intracellular transduction pathway generates the dynamics. To investigate this, we are developing reagents that provide quantitative, dynamic measures of pathway activity. High resolution, quantitative data of the kinetics of signalling are the starting point for testable dynamical systems models of Shh signal transduction.

SELECTED PUBLICATIONS

  • Ashley RG Libby, Tiago Rito, Arthur Radley, James Briscoe. (2024)
    An in vivo CRISPR screen in chick embryos reveals a role for MLLT3 in specification of neural cells from the caudal epiblast.
    bioRxiv 2024.05.16.594506
  • Maizels RJ, Snell DM, Briscoe J. (2024)
    Reconstructing developmental trajectories using latent dynamical systems and time-resolved transcriptomics.
    Cell Systems. 15:411-424
  • Rayon T, Maizels RJ, Barrington C, Briscoe J. (2021)
    Single-cell transcriptome profiling of the human developing spinal cord reveals a conserved genetic programme with human-specific features.
    Development 148:dev199711
  • Delile J, Rayon T, Melchionda M, Edwards A, Briscoe J, Sagner A. (2019)
    Single cell transcriptomics reveals spatial and temporal dynamics of gene expression in the developing mouse spinal cord.
    Development. 146: pii: dev173807
  • Zagorski, M; Tabata, Y; Brandenberg, N; Lutolf, MP; Tkačik, G; Bollenbach, T; Briscoe, J and Kicheva, A (2017)
    Decoding of position in the developing neural tube from antiparallel morphogen gradients.
    Science 356, 1379-1383