We used CRISPR/Cas9-mediated genome editing in combination with molecular analysis to assess the functional requirement of CRM enhancers for regulating Grem1 expression during mouse limb development. Inactivation of individual CRM enhancers had no significant effects on the spatial Grem1 expression and digit development. Instead, we uncovered a CRM enhancer network that regulates Grem1 expression by a dual mode: transcript levels are regulated in an additive manner while synergistic interactions among the CRM enhancers provide the spatially dynamic Grem1 expression with cis-regulatory robustness. Two of the essential CRM enhancers are deeply conserved from fish to mammals. This provided us with a unique opportunity to access the role of spatial regulation of Grem1 during evolutionary diversification of tetrapod limbs. The comparative analysis of CRM enhancers from different tetrapod species revealed significant differences in their spatial activities, which match the variation in Grem1 expression that prefigures the alterations in future digits. Unexpectedly, the conserved CRM enhancers from basal cartilaginous fishes display robust activities in the developing mouse hand plate, which revealed that the basic cis-regulatory circuits that control Grem1 expression in tetrapod limb buds was established before the emergence of limbs. These analyses shed light on how Grem1 might have been coopted during the fin-to-limb transition and uncovers the species-specific spatial variations in CRM enhancer activities and Grem1 expression during the vast evolutionary diversification of tetrapod limbs. The entire analysis was published as one comprehensive study: Malkmus, Ramos Martins et al (2021). Nature Commun 12, 5557 doi:10.1038/s41467-021-25810-1.
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.