Assessing the Relationship of Ancient and Modern Populations.
ABSTRACT: Genetic material sequenced from ancient samples is revolutionizing our understanding of the recent evolutionary past. However, ancient DNA is often degraded, resulting in low coverage, error-prone sequencing. Several solutions exist to this problem, ranging from simple approach, such as selecting a read at random for each site, to more complicated approaches involving genotype likelihoods. In this work, we present a novel method for assessing the relationship of an ancient sample with a modern population, while accounting for sequencing error and postmortem damage by analyzing raw reads from multiple ancient individuals simultaneously. We show that, when analyzing SNP data, it is better to sequence more ancient samples to low coverage: two samples sequenced to 0.5× coverage provide better resolution than a single sample sequenced to 2× coverage. We also examined the power to detect whether an ancient sample is directly ancestral to a modern population, finding that, with even a few high coverage individuals, even ancient samples that are very slightly diverged from the modern population can be detected with ease. When we applied our approach to European samples, we found that no ancient samples represent direct ancestors of modern Europeans. We also found that, as shown previously, the most ancient Europeans appear to have had the smallest effective population sizes, indicating a role for agriculture in modern population growth.
Project description:Historical genetic links among similar populations can be difficult to establish. Identity by descent (IBD) analyses find genomic blocks that represent direct genealogical relationships among individuals. However, this method has rarely been applied to ancient genomes because IBD stretches are progressively fragmented by recombination and thus not recognizable after few tens of generations. To explore such genealogical relationships, we estimated long IBD blocks among modern Europeans, generating networks to uncover the genetic structures. We found that Basques, Sardinians, Icelanders and Orcadians form, each of them, highly intraconnected sub-clusters in a European network, indicating dense genealogical links within small, isolated populations. We also exposed individual genealogical links -such as the connection between one Basque and one Icelandic individual- that cannot be uncovered with other, widely used population genetics methods such as PCA or ADMIXTURE. Moreover, using ancient DNA technology we sequenced a Late Medieval individual (Barcelona, Spain) to high genomic coverage and identified IBD blocks shared between her and modern Europeans. The Medieval IBD blocks are statistically overrepresented only in modern Spaniards, which is the geographically closest population. This approach can be used to produce a fine-scale reflection of shared ancestry across different populations of the world, offering a direct genetic link from the past to the present.
Project description:When sequencing an ancient DNA sample from a hominin fossil, DNA from present-day humans involved in excavation and extraction will be sequenced along with the endogenous material. This type of contamination is problematic for downstream analyses as it will introduce a bias towards the population of the contaminating individual(s). Quantifying the extent of contamination is a crucial step as it allows researchers to account for possible biases that may arise in downstream genetic analyses. Here, we present an MCMC algorithm to co-estimate the contamination rate, sequencing error rate and demographic parameters-including drift times and admixture rates-for an ancient nuclear genome obtained from human remains, when the putative contaminating DNA comes from present-day humans. We assume we have a large panel representing the putative contaminant population (e.g. European, East Asian or African). The method is implemented in a C++ program called 'Demographic Inference with Contamination and Error' (DICE). We applied it to simulations and genome data from ancient Neanderthals and modern humans. With reasonable levels of genome sequence coverage (>3X), we find we can recover accurate estimates of all these parameters, even when the contamination rate is as high as 50%.
Project description:Over the last few years, genome-wide data for a large number of ancient human samples have been collected. Whilst datasets of captured SNPs have been collated, high coverage shotgun genomes (which are relatively few but allow certain types of analyses not possible with ascertained captured SNPs) have to be reprocessed by individual groups from raw reads. This task is computationally intensive. Here, we release a dataset including 35 whole-genome sequenced samples, previously published and distributed worldwide, together with the genetic pipeline used to process them. The dataset contains 72,041,355 sites called across 19 ancient and 16 modern individuals and includes sequence data from four previously published ancient samples which we sequenced to higher coverage (10-18x). Such a resource will allow researchers to analyse their new samples with the same genetic pipeline and directly compare them to the reference dataset without re-processing published samples. Moreover, this dataset can be easily expanded to increase the sample distribution both across time and space.
Project description:While numerous ancient human DNA datasets from across Europe have been published till date, modern-day Poland in particular, remains uninvestigated. Besides application in the reconstruction of continent-wide human history, data from this region would also contribute towards our understanding of the history of the Slavs, whose origin is hypothesized to be in East or Central Europe. Here, we present the first population-scale ancient human DNA study from the region of modern-day Poland by establishing mitochondrial DNA profiles for 23 samples dated to 200 BC - 500 AD (Roman Iron Age) and for 20 samples dated to 1000-1400 AD (Medieval Age). Our results show that mitochondrial DNA sequences from both periods belong to haplogroups that are characteristic of contemporary West Eurasia. Haplotype sharing analysis indicates that majority of the ancient haplotypes are widespread in some modern Europeans, including Poles. Notably, the Roman Iron Age samples share more rare haplotypes with Central and Northeast Europeans, whereas the Medieval Age samples share more rare haplotypes with East-Central and South-East Europeans, primarily Slavic populations. Our data demonstrates genetic continuity of certain matrilineages (H5a1 and N1a1a2) in the area of present-day Poland from at least the Roman Iron Age until present. As such, the maternal gene pool of present-day Poles, Czechs and Slovaks, categorized as Western Slavs, is likely to have descended from inhabitants of East-Central Europe during the Roman Iron Age.
Project description:BACKGROUND: DNA sequences from ancient specimens may in fact result from undetected contamination of the ancient specimens by modern DNA, and the problem is particularly challenging in studies of human fossils. Doubts on the authenticity of the available sequences have so far hampered genetic comparisons between anatomically archaic (Neandertal) and early modern (Cro-Magnoid) Europeans. METHODOLOGY/PRINCIPAL FINDINGS: We typed the mitochondrial DNA (mtDNA) hypervariable region I in a 28,000 years old Cro-Magnoid individual from the Paglicci cave, in Italy (Paglicci 23) and in all the people who had contact with the sample since its discovery in 2003. The Paglicci 23 sequence, determined through the analysis of 152 clones, is the Cambridge reference sequence, and cannot possibly reflect contamination because it differs from all potentially contaminating modern sequences. CONCLUSIONS/SIGNIFICANCE: The Paglicci 23 individual carried a mtDNA sequence that is still common in Europe, and which radically differs from those of the almost contemporary Neandertals, demonstrating a genealogical continuity across 28,000 years, from Cro-Magnoid to modern Europeans. Because all potential sources of modern DNA contamination are known, the Paglicci 23 sample will offer a unique opportunity to get insight for the first time into the nuclear genes of early modern Europeans.
Project description:Despite the crucial role of cyanobacteria in various ecosystems, little is known about their evolutionary histories, especially microevolutionary dynamics, because of the lack of knowledge regarding their mutation rates. Here we directly estimated cyanobacterial mutation rates based on ancient DNA analyses of ice core samples collected from Kyrgyz Republic that dates back to ~12,500 cal years before present. We successfully sequenced the 16S rRNA and 16S-23S internal transcribed spacer (ITS) region. Two cyanobacterial operational taxonomic units (OTUs) were detected from the ancient ice core samples, and these OTUs are shared with those from the modern glacier surface. The mutation rate of ITS region was estimated by comparing ancient and modern populations, and were at the magnitude of 10-7substitutions/sites/year. By using a model selection framework, we also demonstrated that the ancient sequences from the ice sample were not contaminated from modern samples. Bayesian demographic analysis based on coalescent theory revealed that cyanobacterial population sizes increased over Asia regions during the Holocene. Thus, our results enhance our understanding of the enigmatic timescale of cyanobacterial microevolution, which has the potential to elucidate the environmental responses of cyanobacteria to the drastic climatic change events of the Quaternary.
Project description:Parental relatedness of present-day humans varies substantially across the globe, but little is known about the past. Here we analyze ancient DNA, leveraging that parental relatedness leaves genomic traces in the form of runs of homozygosity. We present an approach to identify such runs in low-coverage ancient DNA data aided by haplotype information from a modern phased reference panel. Simulation and experiments show that this method robustly detects runs of homozygosity longer than 4 centimorgan for ancient individuals with at least 0.3 × coverage. Analyzing genomic data from 1,785 ancient humans who lived in the last 45,000 years, we detect low rates of first cousin or closer unions across most ancient populations. Moreover, we find a marked decay in background parental relatedness co-occurring with or shortly after the advent of sedentary agriculture. We observe this signal, likely linked to increasing local population sizes, across several geographic transects worldwide.
Project description:Archaeological silk provides abundant information for studying ancient technologies and cultures. However, due to the spontaneous degradation and the damages from burial conditions, most ancient silk fibers which suffered the damages for thousands of years were turned into invisible molecular residues. For the obtained rare samples, extra care needs to be taken to accurately identify the genuine archaeological silk remains from modern contaminations. Although mass spectrometry (MS) is a powerful tool for identifying and analyzing the ancient protein residues, the traditional approach could not directly determine the dating and contamination of each sample. In this paper, a series of samples with a broad range of ages were tested by MS to find an effective and innovative approach to determine whether modern contamination exists, in order to verify the authenticity and reliability of the ancient samples. The new findings highlighted that the detected peptide types of the fibroin light chain can indicate the degradation levels of silk samples and help to distinguish contamination from ancient silk remains.
Project description:By at least 45,000 years before present, anatomically modern humans had spread across Eurasia [1-3], but it is not well known how diverse these early populations were and whether they contributed substantially to later people or represent early modern human expansions into Eurasia that left no surviving descendants today. Analyses of genome-wide data from several ancient individuals from Western Eurasia and Siberia have shown that some of these individuals have relationships to present-day Europeans [4, 5] while others did not contribute to present-day Eurasian populations [3, 6]. As contributions from Upper Paleolithic populations in Eastern Eurasia to present-day humans and their relationship to other early Eurasians is not clear, we generated genome-wide data from a 40,000-year-old individual from Tianyuan Cave, China, [1, 7] to study his relationship to ancient and present-day humans. We find that he is more related to present-day and ancient Asians than he is to Europeans, but he shares more alleles with a 35,000-year-old European individual than he shares with other ancient Europeans, indicating that the separation between early Europeans and early Asians was not a single population split. We also find that the Tianyuan individual shares more alleles with some Native American groups in South America than with Native Americans elsewhere, providing further support for population substructure in Asia  and suggesting that this persisted from 40,000 years ago until the colonization of the Americas. Our study of the Tianyuan individual highlights the complex migration and subdivision of early human populations in Eurasia.
Project description:North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across Eurasia. It contributes to the description of the spatio-temporal distribution of mitochondrial diversity and will be of significance for future reconstructions of the history of Europeans.