Project description:<p>Residues from ancient artifacts can help identify which plant species were used for their psychoactive properties, providing important information regarding the deep-time co-evolutionary relationship between plants and humans. However, relying on the presence or absence of one or several biomarkers has limited the ability to confidently connect residues to particular plants. We describe a comprehensive metabolomics-based approach that can distinguish closely related species and provide greater confidence in species use determinations. An approximately 1430-year-old pipe from central Washington State not only contained nicotine, but also had strong evidence for the smoking of <em>Nicotiana quadrivalvis</em> and <em>Rhus glabra</em>, as opposed to several other species in this pre-contact pipe. Analysis of a post-contact pipe suggested use of different plants, including the introduced trade tobacco, <em>Nicotiana rustica</em>. Ancient residue metabolomics provides a new frontier in archaeo-chemistry, with greater precision to investigate the evolution of drug use and similar plant-human co-evolutionary dynamics.</p>
Project description:Ancient genome sequencing technologies now provide the opportunity to study natural selection in unprecedented detail. Rather than making inferences from indirect footprints left by selection in present-day genomes, we can directly observe whether a given allele was present or absent in a particular region of the world at almost any period of human history within the last 10,000 years. Methods for studying selection using ancient genomes often rely on partitioning individuals into discrete time periods or regions of the world. However, a complete understanding of natural selection requires more nuanced statistical methods which can explicitly model allele frequency changes in a continuum across space and time. Here we introduce a method for inferring the spread of a beneficial allele across a landscape using two-dimensional partial differential equations. Unlike previous approaches, our framework can handle time-stamped ancient samples, as well as genotype likelihoods and pseudohaploid sequences from low-coverage genomes. We apply the method to a panel of published ancient West Eurasian genomes to produce dynamic maps showcasing the inferred spread of candidate beneficial alleles over time and space. We also provide estimates for the strength of selection and diffusion rate for each of these alleles. Finally, we highlight possible avenues of improvement for accurately tracing the spread of beneficial alleles in more complex scenarios.
Project description:For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.
Project description:European population history has been shaped by migrations of people, and their subsequent admixture. Recently, ancient DNA has brought new insights into European migration events linked to the advent of agriculture, and possibly to the spread of Indo-European languages. However, little is known about the ancient population history of north-eastern Europe, in particular about populations speaking Uralic languages, such as Finns and Saami. Here we analyse ancient genomic data from 11 individuals from Finland and north-western Russia. We show that the genetic makeup of northern Europe was shaped by migrations from Siberia that began at least 3500 years ago. This Siberian ancestry was subsequently admixed into many modern populations in the region, particularly into populations speaking Uralic languages today. Additionally, we show that ancestors of modern Saami inhabited a larger territory during the Iron Age, which adds to the historical and linguistic information about the population history of Finland.