Gene Regulation and Evolution (Real Group)

Our research aims to understand how genomic changes translate into developmental phenotypes during evolution, with a particular focus on how the non-coding genome modulates gene expression across tissues and species. We use state-of-the-art approaches, including 3D genome analysis, single-cell technologies, and epigenetics, combined with comparative genomics, to uncover conserved and divergent regulatory mechanisms. Our findings are validated in vivo using transgenic mouse models, linking regulatory changes to phenotypic traits. Our primary model is the mole, a species with unique adaptations to subterranean life, including eye degeneration, hypoxia tolerance, and specialized limbs. Notably, female moles develop ovotestes that produce high levels of testosterone, contributing to their adaptation. We previously generated a chromosome-level genome of the Iberian mole (Talpa occidentalis) and showed that ovotestis development is associated with changes in 3D regulatory domains of sex-specific genes (Real et al., Science, 2020). Using this model, we integrate comparative genomics and functional approaches to study gene regulatory evolution in vivo.

1. Decipher how evolutionary changes in cis-regulatory elements shape developmental gene expression.
2. Reconstruct and compare gene regulatory networks at single-cell resolution across species.
3. Functionally validate regulatory evolution in vivo using transgenic models.
4. Investigate the evolution and function of large regulatory landscapes using synthetic genomics.
5. Define the principles governing the evolution of gene regulatory landscapes.

1) Evolution of species-specific gene regulatory networks through genome-wide changes.

We investigate how evolutionary changes in gene regulation shape transcriptional outputs at single-cell resolution by integrating scRNA-seq, scATAC-seq, and 3D genome data from developing mole and mouse limbs. Using computational and deep-learning approaches, we reconstruct cell-type-specific gene regulatory networks and identify species-specific regulatory changes.

2) Assessing the evolution of specific regulatory landscapes in vivo.

We investigate how the evolution of large regulatory landscapes shapes developmental traits by using synthetic genomics, combined with 3D genome analysis and advanced genome editing. By engineering and replacing extensive genomic regions between species in vivo, we directly test how changes in regulatory architecture impact gene expression and phenotype. This strategy provides a powerful framework to dissect how complex regulatory systems evolve while preserving essential functions and generating species-specific adaptations.