Evolution on epidemiologically-relevant timescales

University Of California Los Angeles, Los Angeles CA

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY Genetic variation encodes the history of our species, underlies our ability to adapt to new environments, and is the basis for individual- and population-specific disease risk. Over billions of years, evolution has transformed living organisms from simple single cells to the huge diversity around us. However, evolution is more than an ancient process of our past; it is ongoing. While a flash of evolutionary time, the last ~10,000 years have been a period of extraordinary genetic and phenotypic change: humans have adopted agriculture, pushed into new environments, and exploded in population size, increasing gene flow between populations and infectious disease exposure. Indeed, most human genetic variants arose in the last 10s to 100s of generations. Yet, many common population-genetic tools don’t work on this timescale. By leveraging the signatures of rapid evolution, we aim to tackle fundamental evolutionary questions such as how populations adapt to new environments and emerging diseases. Over the past 4 years since starting the lab and R35, we have developed and applied multiple new theoretical models and computational methods to understand demographic and selective processes in admixed populations. The flexibility of the R35 further allowed us to branch into two newer models systems for evolutionary genetics: pathogen evolution and primates as a model of human evolution. Over the next five years, we will tackle these questions across three timescales and model systems. Area 1: leveraging genetic ancestry to infer adaptation & phenotype evolution. We will develop new statistics to infer positive selection within the last tens of generations using admixed genomes both before and after admixture, and use ancestry patterns to test hypotheses about broader genetic architectures. Area 2: model-based inference of selection under complex pathogen lifecycles. Using our expertise in population- genetic and dynamical systems transmission models, we recently developed a model that bridges epidemiological and genetic change by synthesizing whole-genome simulations and dynamical systems models. We will extend our theoretical models of evolution in pathogen systems that incorporate realistic dynamics, starting with malaria as a case study, to understand how different aspects of the lifecycle shape neutral variation and our ability to detect adaptation. Finally, Area 3: using primates as a model of large-scale structural evolution. As our close phylogenetic relatives, primates are an ideal system to understand human evolution, and mechanisms generating genetic variation. Within mammals, large-scale structural variation and chromosome number evolution is generally one of the slower evolutionary processes with large conservation across phyla. However, multiple primates show surprisingly large karyotype evolution and structural changes during within-genus radiations. We will use a combination of population-level resequencing of wild primates with long-read technologies to study karyotype evolution, recombination variation, and the potential adaptive consequences of structural variation.