Population Genomics

The Population Genomics Group started in 2015. The Group focuses on describing and quantifying the genetic variation present in current populations in order to understand the micro-evolution of the given species and asses the phenotypic consequences of such genetic diversity. In particular, we address questions related to which is the genetic origin from a population point of view of a given individual, which are the demographic and selective factors that shaped the genetic variation present in a population and how ultimately this variation influences and allows us to detect the individual risk in complex common diseases with a genetic burden such as ADHD. Overall, all this multidisciplinary combined knowledge allows us to better understanding how (which are the genetic markers involved in the disease) and why (which is the natural history of the disease) we get sick.

In order to achieve these goals, we are actively working on developing new tools and algorithms for describing population substructure in the genome and understanding the biological implications of such structure, identifying the fingerprint of polygenic adaptation in complex phenotypes and evaluating the impact of archaic introgression in phenotypes of interest. Our Group focuses on human species but the universality of the proposed methods allows us to apply them to other model organisms.

• Development of new algorithms for spatial genetic ancestry prediction
• Identification of the fingerprint of polygenic adaptation in complex phenotypes such as attention-deficit/hyperactivity disorder (ADHD)
• Analysis of the impact of archaic introgression in the evolution of ADHD
• Development of new algorithms based on Deep Learning for statistically inferring demographic parameters and distinguishing among competing complex models
• Analysis of the genetic variants associated to attention deficit hyperactivity disorder (ADHD) phenotype
• Study of the genetic variation and medical implication in the Pyrenees

Dolgova O and Lao O.
“Evolutionary and Medical Consequences of Archaic Introgression into Modern Human Genomes.”
Genes, 9(7):358, 201. https://doi.org/10.3390/genes9070358