Briscoe LabDevelopmental Dynamics of Tissue Formation
Composite showing a three-dimensional reconstruction of the neural tube alongside the raw imaging data and a fitted model curve, with progenitor domains in orange, red and green

Research

How do complex tissues develop in a precise and reproducible way from initially indistinguishable cells?

In most tissues, signals termed morphogens act as positional cues that control cell fate by regulating the transcriptional programme of responding cells. How do cells receive and interpret these signals? How is the growth, patterning and morphological elaboration of the spinal cord coordinated?

To address these questions we take an interdisciplinary approach involving biologists, physicists and computer scientists. Increasingly we also work in the other direction, building the components and the tissue to see whether our account of them is right.

For experimental work we use mouse, chick and human embryos, mouse and human stem cells, and organoid models of the neural tube and trunk.

Research areas

Gene regulatory networks

Groups of transcription factors, wired into a network, decide which type of cell each neural progenitor becomes. We are mapping the network and asking how gradients of signals such as Sonic Hedgehog control it over time.

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Gene regulation

Cis-regulatory elements are the stretches of DNA that determine when and where genes switch on and off. We are working out the rules they follow and testing those rules by building new elements from scratch.

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Tempo, growth and lineage

Development runs to a schedule and the schedule differs between species. We study what sets the pace, how the time of neuronal generation affects cell type and how lineage determines what each progenitor can make.

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Stem cells and bioengineering

We build spinal cord tissue outside the embryo, from stem cells, then control the signals it receives. Reconstructing a tissue from its parts is the strongest test of whether we understand how embryos form.

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Computational approaches

Embryos are dynamical systems. We build models that explain how cells choose fates, and methods that recover those dynamics from the data single-cell experiments produce.

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Selected papers

Twelve papers spanning the questions above, each with a note on what it contributed.

Maizels RJ, Briscoe J
Gene regulatory networks: from correlative models to causal explanations
Nature Reviews Genetics 27(6):485-498 (2026)
Argues that gene regulatory networks have become statistical descriptions rather than mechanistic explanations, and sets out three principles for building models that recover causation.
PubMed DOI
Rito T, Libby ARG, Demuth M, Domart MC, Cornwall-Scoones J, Briscoe J
Timely TGFβ signalling inhibition induces notochord
Nature 637(8046):673-682 (2025)
Built a three-dimensional in vitro model of human trunk development containing a notochord, by inhibiting TGFβ signalling at the right moment. It supplies a component missing from earlier stem cell models.
PubMed DOI
Delás MJ, Kalaitzis CM, Fawzi T, Demuth M, Zhang I, Stuart HT, Costantini E, Ivanovitch K, Tanaka EM, Briscoe J
Developmental cell fate choice in neural tube progenitors employs two distinct cis-regulatory strategies
Developmental Cell 58(1):3-17.e8 (2023)
Identified two distinct cis-regulatory strategies used by neural progenitors during fate choice, one based on differential binding and one on differential chromatin accessibility.
PubMed
Sáez M, Blassberg R, Camacho-Aguilar E, Siggia ED, Rand DA, Briscoe J
Statistically derived geometrical landscapes capture principles of decision-making dynamics during cell fate transitions
Cell Systems 13(1):12-28.e3 (2022)
Fitted geometric landscape models directly to single-cell data, showing that cell fate decisions can be described by a small number of decision structures. It made Waddington's metaphor quantitative.
PubMed DOI
Rayon T, Stamataki D, Perez-Carrasco R, Garcia-Perez L, Barrington C, Melchionda M, Exelby K, Lazaro J, Tybulewicz VLJ, Fisher EMC, Briscoe J
Species-specific pace of development is associated with differences in protein stability
Science 369(6510):eaba7667 (2020)
Traced the two- to three-fold difference in developmental tempo between human and mouse to differences in protein stability, offering a concrete molecular handle on a long-standing puzzle.
PubMed
Delile J, Rayon T, Melchionda M, Edwards A, Briscoe J, Sagner A
Single cell transcriptomics reveals spatial and temporal dynamics of gene expression in the developing mouse spinal cord
Development 146(12):dev173807 (2019)
A single-cell atlas of the developing mouse spinal cord that resolved progenitor domains and their neuronal output in space and time. It remains a widely used reference dataset.
PubMed
Metzis V, Steinhauser S, Pakanavicius E, Gouti M, Stamataki D, Ivanovitch K, Watson T, Rayon T, Mousavy Gharavy SN, Lovell-Badge R, Luscombe NM, Briscoe J
Nervous system regionalization entails axial allocation before neural differentiation
Cell 175(4):1105-1118.e17 (2018)
Demonstrated that cells are assigned an axial identity before they commit to a neural fate, reversing the assumed order of regionalisation and differentiation in the nervous system.
PubMed
Zagorski M, Tabata Y, Brandenberg N, Lutolf MP, Tkacik G, Bollenbach T, Briscoe J, Kicheva A
Decoding of position in the developing neural tube from antiparallel morphogen gradients
Science 356(6345):1379-1383 (2017)
Showed that opposing morphogen gradients allow cells to determine position with far greater precision than either gradient alone. It quantified how much positional information a tissue actually carries.
PubMed
Kutejova E, Sasai N, Shah A, Gouti M, Briscoe J
Neural progenitors adopt specific identities by directly repressing all alternative progenitor transcriptional programs
Developmental Cell 36(6):639-653 (2016)
Found that neural progenitors acquire identity by repressing every alternative programme, not by activating their own. It inverted the standard reading of how transcription factors specify cell type.
PubMed
Gouti M, Tsakiridis A, Wymeersch FJ, Huang Y, Kleinjung J, Wilson V, Briscoe J
In vitro generation of neuromesodermal progenitors reveals distinct roles for Wnt signalling in the specification of spinal cord and paraxial mesoderm identity
PLoS Biology 12(8):e1001937 (2014)
Generated neuromesodermal progenitors from pluripotent stem cells and showed how Wnt signalling steers the choice between spinal cord and paraxial mesoderm. This is the basis of the lab's in vitro spinal cord work.
PubMed
Kicheva A, Bollenbach T, Ribeiro A, Valle HP, Lovell-Badge R, Episkopou V, Briscoe J
Coordination of progenitor specification and growth in mouse and chick spinal cord
Science 345(6204):1254927 (2014)
Measured growth and patterning together in mouse and chick, and showed the two are coordinated rather than independent. It made tissue size and proportion a quantitative problem rather than a descriptive one.
PubMed
Balaskas N, Ribeiro A, Panovska J, Dessaud E, Sasai N, Page KM, Briscoe J, Ribes V
Gene regulatory logic for reading the Sonic Hedgehog signaling gradient in the vertebrate neural tube
Cell 148(1-2):273-284 (2012)
Showed that the response to the Sonic Hedgehog gradient is produced by a gene regulatory network of cross-repressive transcription factors, not by cells reading concentration directly. This established the network as the unit of explanation for neural tube patterning.
PubMed

All 121 publications →