PIX2025 - A Framework for Disclosing Evolutionary Regulome-Phenome Associations - (PREX2023-000059)

To understand the molecular basis of species phenotypes, we must go beyond species-centric models and develop frameworks that integrate regulatory evolution across lineages. This project will build a computational framework to analyze genomic, transcriptomic, and epigenomic data in a phylogenetic context. It will model gene regulatory architectures (GRAs), their cross-species rewiring, and impacts on gene expression to uncover mechanisms of trait evolution. We will identify regulatory elements associated with the evolution of traits like cancer prevalence and longevity. Key innovations include scalable phylogenetic models, inference of directional selection on regulatory activity, and variant prioritization. The framework will be benchmarked with curated datasets and yield tools, resources, and insights applicable to evolutionary biology, biomedicine, and conservation. Eligibility We seek a motivated PhD candidate in Comparative Multiomics and Computational Biology with: • Bachelor’s and Master’s in Biomedicine, Biotechnology, Biology, or related field • Strong skills in R, Python, and Bash • Experience in computational biology, bioinformatics, or experimental omics techniques is a plus • Interest in integrating computational and experimental approaches Responsibilities • Design, implement, and apply methods to integrate multiomic data to define and compare regulatory states across species • Support generation and analy