Population genomic methodology for analysis of ancient DNA: assessing population relationships and the temporal dynamics of natural selection

项目总结

Project Summary There are now hundreds of ancient genomes available from a wide range of species, including humans. Such data provide a direct window into the history of demography and natural selection in the recent past, and have greatly contributed to the understanding of how humans colonized the world following the out-of-Africa dispersal. Nonetheless, the statistical methods for analyzing ancient DNA have lagged behind the developments in sequencing technology. The proposed research will develop novel methods based on population genomics theory to advance the field of ancient DNA research. These methods will be applied to data from ancient humans to provide new insights into the last 50 thousand years of human evolution. Moreover, via collaboration with international ancient DNA laboratories, applications of these methods will contribute to the understanding of animal domestication, a key innovation that allowed humans to form complex societies. We will develop statistical methods to assess the relationship of ancient samples to present-day individuals in a way that explicitly accounts for the fact that alleles arose as new mutations and are thus at lower frequency in ancient samples. By working with collaborators studying pig domestication, we will test hypotheses about how movement of humans coincided with the advent of agriculture and the transportation of domesticated animals. We will also develop methodology to elucidate details of how modern humans and archaic humans, such as Neandertals interbred. By leveraging patterns of variation in Neandertal DNA sharing within and among Eurasian populations, we will determine the number of times that humans and Neandertals interbred, and determine demographic structure in the pan-continental Neandertal population. Finally, we will use ancient DNA to refine our understanding of natural selection during horse domestication and human dispersal. Working with international collaborators, we will use ancient DNA to detect genes that were critical to horse domestication, and determine whether the mutations existed before domestication or if they arose de novo following domestication. We will also examine how the distribution of fitness effects has changed over time and space in humans by comparing the distribution of fitness effects inferred for ancient samples of varying ages, in order to gain an understanding of how human adaptation has been shaped by demographic history and climate change over the last hundred thousand years.