Regulatory networks driving cell fate decisions: dissecting the logic
Figure 1: Enhancers can function by highly cooperative transcription factor occupancy using very flexible motif content and organisation (Junion, Spivakov, et al., Cell 2012)
Figure 2: Chromatin state and RNA polymerase II occupancy on enhancers (yellow) is highly predictive of enhancers’ activity and is very dynamic, mirroring that of dynamic enhancer usage during development (Bonn, Zinzen, Girardot, et al., Nature Genetics 2012)
The Furlong group aims to understand fundamental principles of transcription, focusing on the processes that determine what a cell becomes during embryonic development.
Previous and current research
Development is driven by the establishment of complex patterns of gene expression at precise times and spatial locations. Although a number of mechanisms fine-tune expression states, it is initially established through the integration of signalling and transcriptional networks converging on enhancer elements, or cis-regulatory modules (CRMs). Understanding how CRMs function is therefore central to understanding metazoan development and evolutionary change. Although there has been extensive progress in deciphering the function of individual regulatory elements, how these modules are integrated to regulate more global cis-regulatory networks remains a key challenge. Even in the extensively studied model organism Drosophila, there are no predictive models for a transcriptional network leading to cell fate specification.
Our research includes studies of the mechanism of enhancer function (figure 1) and the interplay of transcription factors and chromatin state (figure 2), as well as studies of how gene regulatory networks control development and how network perturbations lead to specific phenotypes. To address this we integrate functional genomic, genetic and computational approaches to make predictive models of transcription and developmental progression. We use Drosophila mesoderm specification into different muscle primordia as a model system. The relative simplicity of the fly mesoderm, in addition to the number of essential and conserved transcription factors already identified, make it an ideal model to understand cell fate decisions at a systems level.
Future projects and goals
Chromatin remodelling during cell fate decisions: We have developed a very accurate and sensitive method to investigate cell type-specific changes in chromatin status and chromatin binding protein occupancy in the context of a multicellular embryo’s development (figure 2). We are currently using this method to examine the interplay between changes in chromatin remodelling with dynamic changes in transcription factor occupancy and developmental transitions.
Variation and plasticity in cis-regulatory networks: Variation in cis-regulatory elements can affect gene expression and account for individual differences in phenotypes, like taste sensation and olfactory sensitivity. However, little is known about how much variation in gene expression or transcription factor function can be tolerated for essential developmental processes during embryonic development. We plan to investigate this by extending our current knowledge of the transcriptional network regulating cell fate choices during mesoderm development to many Drosophila individuals (isogenic Drosophila strains) whose genomes have been fully sequenced.
Predictive models of embryonic development: Our previous work demonstrated that only using information on combinatorial occupancy of transcription factors is sufficient to predict spatio-temporal cis-regulatory activity (Nature, 2009) and that information on chromatin state and RNA polymerase II occupancy on enhancers can predict the precise timing and location of active enhancer elements de novo (Nature Genetics, 2012). We plan to build on this by predicting a gene’s expression. Our ultimate goal is to use this systems-level approach to make predictive models of embryonic development and the effect of genetic perturbations. Working in Drosophila allows us to readily test the predicted outcome of network perturbations on embryonic development.