Toward high-resolution population genomics using archaeological samples

Advancements and Challenges in Ancient DNA Research: Bridging the Global North-South Divide

Ancient DNA (aDNA) research first began in 1984 and ever since has greatly expanded our understanding of evolution and migration. Today, aDNA analysis is used to solve various puzzles about the origin of mankind, migration patterns, and the spread of infectious diseases. The incredible findings ranging from identifying the new branches within the human family to studying the genomes of extinct flora and fauna have caught the world by surprise in recent times. However, a closer look at these published results points out a clear Global North and Global South divide. Therefore, through this research, we aim to emphasize encouraging better collaborative opportunities and technology transfer to support researchers in the Global South. Further, the present research also focuses on expanding the scope of the ongoing conversation in the field of aDNA by reporting relevant literature published around the world and discussing the advancements and challenges in the field.

Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years

Radiocarbon dating is the gold standard in archeology to estimate the age of skeletons, a key to studying their origins. Many published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. We developed the temporal population structure (TPS), a DNA-based dating method for genomes ranging from the Late Mesolithic to today, and applied it to 3,591 ancient and 1,307 modern Eurasians. TPS predictions aligned with the known dates and correctly accounted for kin relationships. TPS dating of poorly dated Eurasian samples resolved conflicting reports in the literature, as illustrated by one test case. We also demonstrated how TPS improved the ability to study phenotypic traits over time. TPS can be used when radiocarbon dating is unfeasible or uncertain or to develop alternative hypotheses for samples younger than 10,000 years ago, a limitation that may be resolved over time as ancient data accumulate.

aYChr-DB: a database of ancient human Y haplogroups

Ancient Y-Chromosomal DNA is an invaluable tool for dating and discerning the origins of migration routes and demographic processes that occurred thousands of years ago. Driven by the adoption of high-throughput sequencing and capture enrichment methods in paleogenomics, the number of published ancient genomes has nearly quadrupled within the last three years (2018-2020). Whereas ancient mtDNA haplogroup repositories are available, no similar resource exists for ancient Y-Chromosomal haplogroups. Here, we present aYChr-DB-a comprehensive collection of 1797 ancient Eurasian human Y-Chromosome haplogroups ranging from 44 930 BC to 1945 AD. We include descriptors of age, location, genomic coverage and associated archaeological cultures. We also produced a visualization of ancient Y haplogroup distribution over time. The aYChr-DB database is a valuable resource for population genomic and paleogenomic studies.

Complex spatio-temporal distribution and genomic ancestry of mitochondrial DNA haplogroups in 24,216 Danes

Mitochondrial DNA (mtDNA) haplogroups (hgs) are evolutionarily conserved sets of mtDNA SNP-haplotypes with characteristic geographical distribution. Associations of hgs with disease and physiological characteristics have been reported, but have frequently not been reproducible. Using 418 mtDNA SNPs on the PsychChip (Illumina), we assessed the spatio-temporal distribution of mtDNA hgs in Denmark from DNA isolated from 24,642 geographically un-biased dried blood spots (DBS), collected from 1981 to 2005 through the Danish National Neonatal Screening program. ADMIXTURE was used to establish the genomic ancestry of all samples using a reference of 100K+ autosomal SNPs in 2,248 individuals from nine populations. Median-joining analysis determined that the hgs were highly variable, despite being typically Northern European in origin, suggesting multiple founder events. Furthermore, considerable heterogeneity and variation in nuclear genomic ancestry was observed. Thus, individuals with hg H exhibited 95%, and U hgs 38.2% - 92.5%, Danish ancestry. Significant clines between geographical regions and rural and metropolitan populations were found. Over 25 years, macro-hg L increased from 0.2% to 1.2% (p = 1.1*E-10), and M from 1% to 2.4% (p = 3.7*E-8). Hg U increased among the R macro-hg from 14.1% to 16.5% (p = 1.9*E-3). Genomic ancestry, geographical skewedness, and sub-hg distribution suggested that the L, M and U increases are due to immigration. The complex spatio-temporal dynamics and genomic ancestry of mtDNA in the Danish population reflect repeated migratory events and, in later years, net immigration. Such complexity may explain the often contradictory and population-specific reports of mito-genomic association with disease.

Ancient Ancestry Informative Markers for Identifying Fine-Scale Ancient Population Structure in Eurasians

The rapid accumulation of ancient human genomes from various areas and time periods potentially enables the expansion of studies of biodiversity, biogeography, forensics, population history, and epidemiology into past populations. However, most ancient DNA (aDNA) data were generated through microarrays designed for modern-day populations, which are known to misrepresent the population structure. Past studies addressed these problems by using ancestry informative markers (AIMs). It is, thereby, unclear whether AIMs derived from contemporary human genomes can capture ancient population structures, and whether AIM-finding methods are applicable to aDNA, provided that the high missingness rates in ancient-and oftentimes haploid-DNA can also distort the population structure. Here, we define ancient AIMs (aAIMs) and develop a framework to evaluate established and novel AIM-finding methods in identifying the most informative markers. We show that aAIMs identified by a novel principal component analysis (PCA)-based method outperform all of the competing methods in classifying ancient individuals into populations and identifying admixed individuals. In some cases, predictions made using the aAIMs were more accurate than those made with a complete marker set. We discuss the features of the ancient Eurasian population structure and strategies to identify aAIMs. This work informs the design of single nucleotide polymorphism (SNP) microarrays and the interpretation of aDNA results, which enables a population-wide testing of primordialist theories.

ARIADNA: machine learning method for ancient DNA variant discovery

Ancient DNA (aDNA) studies often rely on standard methods of mutation calling, optimized for high-quality contemporary DNA but not for excessive contamination, time- or environment-related damage of aDNA. In the absence of validated datasets and despite showing extreme sensitivity to aDNA quality, these methods have been used in many published studies, sometimes with additions of arbitrary filters or modifications, designed to overcome aDNA degradation and contamination problems. The general lack of best practices for aDNA mutation calling may lead to inaccurate results. To address these problems, we present ARIADNA (ARtificial Intelligence for Ancient DNA), a novel approach based on machine learning techniques, using specific aDNA characteristics as features to yield improved mutation calls. In our comparisons of variant callers across several ancient genomes, ARIADNA consistently detected higher-quality genome variants with fast runtimes, while reducing the false positive rate compared with other approaches.

Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe

BACKGROUND

The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia.

RESULTS

We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts.

CONCLUSIONS

Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

Evolutionary adaptation revealed by comparative genome analysis of woolly mammoths and elephants

Comparative genomics studies typically limit their focus to single nucleotide variants (SNVs) and that was the case for previous comparisons of woolly mammoth genomes. We extended the analysis to systematically identify not only SNVs but also larger structural variants (SVs) and indels and found multiple mammoth-specific deletions and duplications affecting exons or even complete genes. The most prominent SV found was an amplification of RNase L (with different copy numbers in different mammoth genomes, up to 9-fold), involved in antiviral defense and inflammasome function. This amplification was accompanied by mutations affecting several domains of the protein including the active site and produced different sets of RNase L paralogs in four mammoth genomes likely contributing to adaptations to environmental threats. In addition to immunity and defense, we found many other unique genetic changes in woolly mammoths that suggest adaptations to life in harsh Arctic conditions, including variants involving lipid metabolism, circadian rhythms, and skeletal and body features. Together, these variants paint a complex picture of evolution of the mammoth species and may be relevant in the studies of their population history and extinction.

Museums are biobanks: unlocking the genetic potential of the three billion specimens in the world's biological collections

Museums and herbaria represent vast repositories of biological material. Until recently, working with these collections has been difficult, due to the poor condition of historical DNA. However, recent advances in next-generation sequencing technology, and subsequent development of techniques for preparing and sequencing historical DNA, have recently made working with collection specimens an attractive option. Here we describe the unique technical challenges of working with collection specimens, and innovative molecular methods developed to tackle them. We also highlight possible applications of collection specimens, for taxonomy, ecology and evolution. The application of next-generation sequencing methods to museum and herbaria collections is still in its infancy. However, by giving researchers access to billions of specimens across time and space, it holds considerable promise for generating future discoveries across many fields.