Genome-wide study of a Neolithic Wartberg grave community reveals distinct HLA variation and hunter-gatherer ancestry

Immel, Alexander; Pierini, Federica; Rinne, Christoph; Meadows, John; Barquera, Rodrigo; Szolek, András; Susat, Julian; Böhme, Lisa; Dose, Janina; Bonczarowska, Joanna H.; Drummer, Clara; Fuchs, Katharina; Ellinghaus, David; Kässens, Jan Christian; Furholt, Martin; Kohlbacher, Oliver; Schade-Lindig, Sabine; Franke, André; Schreiber, Stefan; Krause, Johannes; Müller, Johannes; Lenz, Tobias; Nebel, Almut; Krause‐Kyora, Ben

doi:10.1038/s42003-020-01627-4

Cited by 25 publications

(30 citation statements)

References 72 publications

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“…The addition of simulated DNA damage did not notably impact the typing accuracy at any coverage or read length. The typing accuracy in figure 5 and supplementary figure S5 is shown in 2-field resolution, as this resolution was used in (25).…”

Section: Resultsmentioning

confidence: 99%

“…Sequencing of ancient DNA (aDNA) is often limited by a low depth of coverage, short DNA sequence length and chemical damage to the DNA (24). However, studies of aDNA have still used modern HLA typing tools such as Optitype (25) and an adaptation of HLAssign (26) to perform HLA typing on ancient individuals. HLAssign relies on data generated using targeted HLA enrichment (27), while Optitype is designed for general, non-enriched sequencing data (17).…”

Section: Introductionmentioning

confidence: 99%

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Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

Thuesen

Klausen²,

Gopalakrishnan

et al. 2022

Preprint

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The human leukocyte antigen (HLA) system is a group of genes coding for proteins that are central to the adaptive immune system and identifying the specific HLA allele combination of a patient is relevant in organ donation, risk assessment of autoimmune and infectious diseases and cancer immunotherapy. However, due to the high genetic polymorphism in this region, HLA typing requires specialized methods. We investigated the performance of five next-generation-sequencing (NGS) based HLA typing tools with a non-restricted license namely HLA*LA, Optitype, HISAT-genotype, Kourami and STC-Seq. This evaluation was done for the five HLA loci, HLA-A, -B, -C, -DRB1 and -DQB1 using whole-exome sequencing (WES) samples from 829 individuals. The robustness of the tools to lower coverage was evaluated by subsampling and HLA typing 230 WES samples at coverages ranging from 1X to 100X. The typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions, which specifically focus on the peptide binding region. On average, across the five HLA genes, HLA*LA was found to have the highest typing accuracy. For the individual genes, HLA-A, -B and -C, Optitype's typing accuracy was highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools' robustness to lower coverage data varied widely and further depended on the specific HLA locus. For all class I loci, Optitype had a typing accuracy above 95% (according to the modification of the amino acids in the functionally relevant portion of the protein) at 50X, but increasing the depth of coverage beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA genes as well as HLA*LA's typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which often is based on lower quality sequencing data. Interestingly, we found that Optitype's typing accuracy is not notably impaired by short read length or by DNA damage, which is typical of aDNA, as long as the depth of coverage is sufficiently high.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

Thuesen

Klausen²,

Gopalakrishnan

et al. 2022

Preprint

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“…Population movements during the Neolithic can be traced in the gene pools across the European continent as farming was introduced from the Near East. Several regional studies have testified to varying degrees of reproductive interaction with local Mesolithic groups, ranging from genetic continuity 6 to gradual population admixture [7][8][9][10] to almost complete replacement 11 . However, our knowledge of the population structure in the Mesolithic period and how it was formed is limited, partly because of a paucity of data from skeletons older than 8,000 years, compromising resolution into subsequent demographic transitions.…”

Section: Introductionmentioning

confidence: 99%

Population genomics of postglacial western eurasia

Allentoft

Sikora

Refoyo-Martínez

et al. 2022

Preprint

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The transitions from foraging to farming and later to pastoralism in Stone Age Eurasia (c. 11-3 thousand years before present, BP) represent some of the most dramatic lifestyle changes in human evolution. We sequenced 317 genomes of primarily Mesolithic and Neolithic individuals from across Eurasia combined with radiocarbon dates, stable isotope data, and pollen records. Genome imputation and co-analysis with previously published shotgun sequencing data resulted in >1600 complete ancient genome sequences offering fine-grained resolution into the Stone Age populations. We observe that: 1) Hunter-gatherer groups were more genetically diverse than previously known, and deeply divergent between western and eastern Eurasia. 2) We identify hitherto genetically undescribed hunter-gatherers from the Middle Don region that contributed ancestry to the later Yamnaya steppe pastoralists; 3) The genetic impact of the Neolithic transition was highly distinct, east and west of a boundary zone extending from the Black Sea to the Baltic. Large-scale shifts in genetic ancestry occurred to the west of this "Great Divide", including an almost complete replacement of hunter-gatherers in Denmark, while no substantial ancestry shifts took place during the same period to the east. This difference is also reflected in genetic relatedness within the populations, decreasing substantially in the west but not in the east where it remained high until c. 4,000 BP; 4) The second major genetic transformation around 5,000 BP happened at a much faster pace with Steppe-related ancestry reaching most parts of Europe within 1,000-years. Local Neolithic farmers admixed with incoming pastoralists in eastern, western, and southern Europe whereas Scandinavia experienced another near-complete population replacement. Similar dramatic turnover-patterns are evident in western Siberia; 5) Extensive regional differences in the ancestry components involved in these early events remain visible to this day, even within countries. Neolithic farmer ancestry is highest in southern and eastern England while Steppe-related ancestry is highest in the Celtic populations of Scotland, Wales, and Cornwall (this research has been conducted using the UK Biobank resource); 6) Shifts in diet, lifestyle and environment introduced new selection pressures involving at least 21 genomic regions. Most such variants were not universally selected across populations but were only advantageous in particular ancestral backgrounds. Contrary to previous claims, we find that selection on the FADS regions, associated with fatty acid metabolism, began before the Neolithisation of Europe. Similarly, the lactase persistence allele started increasing in frequency before the expansion of Steppe-related groups into Europe and has continued to increase up to the present. Along the genetic cline separating Mesolithic hunter-gatherers from Neolithic farmers, we find significant correlations with trait associations related to skin disorders, diet and lifestyle and mental health status, suggesting marked phenotypic differences between these groups with very different lifestyles. This work provides new insights into major transformations in recent human evolution, elucidating the complex interplay between selection and admixture that shaped patterns of genetic variation in modern populations.

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“…Similarly, the Wartberg collective burial at Nierdertiefenbach near Koblenz (3300–3200 bc ) produced genomes with a very significant hunter-gatherer ancestry, yet the admixture of hunters and farmers was here calculated to have taken place in 3860–3550 cal. bc (Immel et al 2021, 4).…”

Section: The Problem Of Admixturementioning

confidence: 99%

Neolithization and Population Replacement in Britain: An Alternative View

Thomas¹

2022

CAJ

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Investigation of British Mesolithic and Neolithic genomes suggests discontinuity between the two and has been interpreted as indicating a significant migration of continental farmers, displacing the indigenous population. These incomers had already acquired some hunter-gatherer genetic heritage before their arrival, and this increased little in Britain. However, the proportion of hunter-gatherer genetic ancestry in British Neolithic genomes is generally greater than for most contemporary examples on the continent, particularly in emerging evidence from northern France, while the ultimate origin of British Neolithic populations in Iberia is open to question. Both the date calculated for the arrival of new people in Britain and their westerly origin are at odds with other aspects of the existing evidence. Here, a two-phase model of Neolithization is proposed. The first appearance of Neolithic things and practices significantly predated a more substantial transfer of population, creating the conditions under which new communities could be brought into being. The rather later establishment of a major migration stream coincided with an acceleration in the spread of Neolithic artefacts and activities, as well as an enrichment of the Neolithic material assemblage.

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Genome-wide study of a Neolithic Wartberg grave community reveals distinct HLA variation and hunter-gatherer ancestry

Cited by 25 publications

References 72 publications

Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

Population genomics of postglacial western eurasia

Neolithization and Population Replacement in Britain: An Alternative View

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