Computational inference and analysis of ancestral genomes

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Advances in DNA sequencing technologies have resulted in the sequencing of the genomes of a large number of species from all domains of life. This represents an incredible opportunity to study the evolution of these genomes and interpret patterns of evolutionary events to help identifying functional elements in genomes. This also opens the door to the intriguing possibility that the genomes of ancestral species maybe be computationally inferred from those of extant species. In this proposal, we first aim to refine the computational tools needed to infer ancestral DNA sequences. We then propose to take advantage of these inferred ancestral sequences to better understand the origin of key regions of the human genome and of that of important crop and pathogen species. In particular, we will use these ancestral sequences to identify very ancient evolutionary events such as the insertion of transposons or pseudogenes, that have shaped the genomes of early mammals, but whose trace can no longer be recognized in extant genomes. We will also rely on our ability to infer ancestral sequences to study the genesis of new regulatory elements, in particular those that may have conferred primate-specific traits. Finally, we will train computational predictors to identify functional elements of the genome, in particular regulatory elements, on the basis of their inferred evolutionary history. Our project will bring important resources to the genomics community in the form of software and databases that will guide experimental biologists and genomicists in their analyses. It will also help shed light on the origin of key elements of our genome.