Disease and pathogens have affected human populations throughout history, something that the global pandemics of the 21^st century can attest for. With the development of methods for DNA extraction and sequencing during the last decade, it is now possible to study ancient pathogen evolution and transmission more in depth, within the field of ancient metagenomics. However, a long-standing challenge in ancient metagenomics has been high error rates and false positive identifications. In this thesis, I have aimed to initially improve the methods for analysing ancient DNA data, and further to study the presence and evolution of pathogens in populations across human prehistory. In chapter I, I present aMeta, an accurate ancient metagenomics profiling workflow that has been designed to minimize the number of false positive identifications, as well as to streamline computer memory usage. Using simulated as well as authentic ancient DNA data, aMeta was benchmarked against an existing workflow, and its superior sensitivity and specificity in both microbial detection and authentication was demonstrated. Further, we could show its substantially lower usage of computer memory. In chapter II, the aMeta workflow was applied on a dataset consisting of 38 individuals from four Mesolithic and Neolithic Scandinavian human cultural complexes. Several species of bacteria were identified in the dataset, for example the bacterium Salmonella enterica in two individuals from the Battle Axe cultural complex. Since osteological examination did not present any physical damage to the bones, this disease may have been the cause of death for the infected individuals. Several species of the bacterial genus Yersinia were identified in individuals from the Funnel Beaker culture context, and denser populations in an agricultural context may have facilitated the transmission of these pathogens. Further, in Mesolithic and Neolithic hunter-gatherers, two pathogenic species of the genus Neisseria were identified, representing the, to our knowledge, earliest findings of the species to date. In chapter III, aMeta was applied to a dataset from Mexico, consisting of 41 individuals dated between 900 – 1800 CE. In one individual, we identified DNA from the bacterium Vibrio cholerae, the causing agent of cholera. We created a phylogeny consisting of available, globally collected Vibrio genomes and concluded that our finding, the earliest of V. cholerae to date, likely belongs to a non-choleric strain and thus may not have been the cause of an epidemic. Further, the finding indicates that cholera may have arrived in the Americas decades earlier than previous research has shown. In chapter IV, we presented genomic data from 40 individuals in northeast Asia, dated between circa 16,900 and 550 years ago. Population demographics showed genetic affinity between the analysed individuals and present-day human populations in Asia and Native America. We further used the metagenomics tool Malt to identify Yersinia pestis reads in two individuals from 4,400 and 3,800 years ago respectively, representing the most northeastern ancient finding of the bacterium.

Humans have relied on animal fur for centuries, yet fur farming only began recently during the mid-19th Century. Little is known about this incipient domestication or the genomic processes involved. Domestication may involve founder effects, population bottlenecks and low population size, which, when combined with intense artificial selection, lead to inbreeding, a limited gene pool and reduced fitness. The arctic fox (Vulpes lagopus) has been farmed intensively since the early 1900s and has been artificially selected for economic phenotypes. We investigated the origin of these lineages and the genomic consequences of intensive farming by comparing the genomes of farmed and wild arctic foxes from across their range. Our research indicates recent inbreeding through long Runs of Homozygosity and reduced genomic variation in farmed foxes relative to their respective wild populations. We identified a coastal ecotype origin for all Fennoscandian farmed arctic foxes, aligning them phylogenetically with the wild Icelandic population, a geographically isolated and phenotypically distinct coastal lineage. The depleted genome-wide heterozygosity and increased recent inbreeding in farmed fox lineages is consistent with a heavy consequence of domestication, shedding light on the demographic history and genomic consequences of human manipulation. We highlight the need for increased genomic investigations into fur farm populations to understand the incipient domestication process and uncover the cost of intense farming. The genomic consequences of domestication must be considered in the management of fur farms, with actionable steps needed to prevent descendants of escaped farmed foxes from polluting the gene pool in the wild through introgression.

With the Neolithic transition, human lifestyle shifted from hunting and gathering to farming. This change altered subsistence patterns, cultural expression, and population structures as shown by the archaeological/zooarchaeological record, as well as by stable isotope and ancient DNA data. Here, we used metagenomic data to analyse if the transitions also impacted the microbiome composition in 25 Mesolithic and Neolithic hunter-gatherers and 13 Neolithic farmers from several Scandinavian Stone Age cultural contexts. Salmonella enterica, a bacterium that may have been the cause of death for the infected individuals, was found in two Neolithic samples from Battle Axe culture contexts. Several species of the bacterial genus Yersinia were found in Neolithic individuals from Funnel Beaker culture contexts as well as from later Neolithic context. Transmission of e.g. Y. enterocolitica may have been facilitated by the denser populations in agricultural contexts.

Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMeta, an accurate metagenomic profiling workflow for ancient DNA designed to minimize the amount of false discoveries and computer memory requirements. Using simulated data, we benchmark aMeta against a current state-of-the-art workflow and demonstrate its superiority in microbial detection and authentication, as well as substantially lower usage of computer memory.

We present genome-wide data from 40 individuals dating to c.16,900 to 550 years ago in northeast Asia. We describe hitherto unknown gene flow and admixture events in the region, revealing a complex population history. While populations east of Lake Baikal remained relatively stable from the Mesolithic to the Bronze Age, those from Yakutia and west of Lake Baikal witnessed major population transformations, from the Late Upper Paleolithic to the Neolithic, and during the Bronze Age, respectively. We further locate the Asian ancestors of Paleo-Inuits, using direct genetic evidence. Last, we report the most northeastern ancient occurrence of the plague-related bacterium, Yersinia pestis. Our findings indicate the highly connected and dynamic nature of northeast Asia populations throughout the Holocene.

Ancient DNA (aDNA) has played a major role in our understanding of the past. Important advances in the sequencing and analysis of aDNA from a range of organisms have enabled a detailed understanding of processes such as past demography, introgression, domestication, adaptation and speciation. However, to date and with the notable exception of microbiomes and sediments, most aDNA studies have focused on single taxa or taxonomic groups, making the study of changes at the community level challenging. This is rather surprising because current sequencing and analytical approaches allow us to obtain and analyse aDNA from multiple source materials. When combined, these data can enable the simultaneous study of multiple taxa through space and time, and could thus provide a more comprehensive understanding of ecosystem-wide changes. It is therefore timely to develop an integrative approach to aDNA studies by combining data from multiple taxa and substrates. In this review, we discuss the various applications, associated challenges and future prospects of such an approach.

Ancient DNA provides a powerful means to investigate the timing, rate and extent of population declines caused by extrinsic factors, such as past climate change and human activities. One species probably affected by both these factors is the arctic fox, which had a large distribution during the last glaciation that subsequently contracted at the start of the Holocene. More recently, the arctic fox population in Scandinavia went through a demographic bottleneck owing to human persecution. To investigate the consequences of these processes, we generated mitogenome sequences from a temporal dataset comprising Pleistocene, historical and modern arctic fox samples. We found no evidence that Pleistocene populations in mid-latitude Europe or Russia contributed to the present-day gene pool of the Scandinavian population, suggesting that postglacial climate warming led to local population extinctions. Furthermore, during the twentieth-century bottleneck in Scandinavia, at least half of the mitogenome haplotypes were lost, consistent with a 20-fold reduction in female effective population size. In conclusion, these results suggest that the arctic fox in mainland Western Europe has lost genetic diversity as a result of both past climate change and human persecution. Consequently, it might be particularly vulnerable to the future challenges posed by climate change. This article is part of a discussion meeting issue 'The past is a foreign country: how much can the fossil record actually inform conservation?'