Molly Przeworski is a population geneticist. Her research focuses on the processes that generate genetic variation, mutation and recombination, with the aims of understanding how and why they differ among humans and across vertebrate species. Research in her lab has also clarified how natural selection operates in human populations: notably, it has helped characterize the footprints of adaptation in genetic variation data and revealed that few recent human adaptations involved the fixation of new mutations of large effect. In parallel, her group has worked on mapping trait variation to the genome, both to investigate what associations are being detected in humans and to extend the approach to non-model organisms of ecological importance.
Molly received a B.A. in Mathematics from Princeton University and a Ph.D. from the Committee on Evolutionary Biology at the University of Chicago, then conducted postdoctoral research in the Statistics Department of the University of Oxford. Before moving to Columbia University, she was a researcher at the Max Planck Institute for Evolutionary Anthropology and a faculty member at Brown University and the University of Chicago. Her work has been recognized by a Scientific Achievement Award from the American Society of Human Genetics, as well as election to the American Academy of Arts and Sciences and National Academy of Sciences.
Keynote talk
Why do germline mutation rates vary among humans?
Germline mutation is the source of all heritable differences and therefore of fundamental importance. In humans, it has long been appreciated that mutation rates are higher in fathers, particularly older fathers. The textbook view has been that these patterns reflect replication errors that accrue during spermatogenesis. I will present multiple lines of evidence that call this view into question. I will argue instead that the data are best explained by a much larger role of DNA damage in the genesis of germline mutations than previously appreciated, and draw implications for why mutation rates depend on sex and age. Finally, I will discuss our study of inter-individual variation in germline mutation rates based on trios and sibling pairs from UK Biobank and AllofUs datasets.