Periodic Reporting for period 4 - INTEGRAL (Signal Integration by Gene Regulatory Landscapes)
Periodo di rendicontazione: 2021-02-01 al 2022-01-31
The developing limb of tetrapods (animals with four limbs) is a paradigm to study how gene regulation impacts morphogenesis. We have shown that a self-regulatory signaling system coordinately controls limb bud outgrowth and patterning of the limb skeleton and that the BMP antagonist Gremlin1 (Grem1) is essential to propagate this signaling system and for normal limb development. The ERC-funded research identifies several CRM enhancers embedded in a large genomic landscape and establishes how their interactions orchestrate Grem1 expression during mouse limb development. This analysis provides fundamental insights into how several CRM enhancers interact and integrate signaling inputs to regulate the spatio-temporal Grem1 expression. Genetic and molecular analysis identified a novel dual enhancer mode as CRM enhancers regulate Grem1 transcript levels in an additive manner, while their synergistic interactions provide the spatial regulation of Grem1 expression and digit development with robustness. During this analysis, we discovered that the Grem1 cis-regulatory landscape is deeply conserved in all vertebrates with paired appendages including evolutionary ancient fish. Functional analysis of two of the most conserved CRM enhancers revealed that their orthologues from basal fishes (Coelacanth and sharks) are strongly active in the mouse digit forming area, which is fascinating as it reveals that the regulatory circuits existed before fins evolved into limbs. Comparing CRM enhancer activities with Grem1 expression in limb buds from different mammalian and sauropsid species reveals the amazing evolutionary plasticity in Grem1 cis-regulation and expression, which correlates well with the evolutionary diversification of the limb skeleton in these species. This analysis indicates that the inherent robustness generated by the synergistic CRMs likely provided an evolutionary playground enabling diversification of enhancer activities during evolutionary adaptation of tetrapod limbs. In a parallel study we combined experimental with computational analysis of mouse limb and chicken wing buds to provide broad insights into how genome evolution impacted the cis-regulatory interactions and the spatio-temporal gene expression dynamics during diversification mouse limb and chicken wing development.
Another main study concerns the integrative genome-wide analysis of gene regulation and expression during mouse limb and chicken wing development. This data-based computational analysis identified the synchrony between enhancer accessibility and gene expression in mouse forelimb buds, while stage-specific divergence was detected in chicken wing buds. Integration of these dataset with computational TF footprinting allowed construction of GRNs of interest. The in silico construction of TF target GRNs is of broad relevance as the necessary datasets can be generated with little material, which makes such analysis feasible for an increasing number of available non-model organisms: Jhanwar et al. 2021, Nature Commun 12, 5685 doi:10.1038/s41467-021-25935-3.
2. A second important discovery is the deep evolutionary conservation of the Grem1 cis-regulatory landscape in jawed vertebrates. The unexpected finding that CRM enhancers from basal fish are active in the mouse autopod and regulated by the same trans-regulatory inputs as their mouse orthologs points to the ancient origin of the trans/cis-regulatory circuits that control gene expression in paired appendages.
3. The comparative analysis of the temporal differences in open chromatin and gene expression at orthologous stages of mouse limb and chicken wing buds went way beyond its initial aim. In particular, ATAC-seq can be used for computational footprinting of TFs to profile their temporal interactions with DNA. Furthermore, candidate target GRN for specific TFs can be constructed in silico to identify both conserved and species-specific interactions. Finally this computational analysis provides a framework for future Evo-Devo studies.