Neolithic genomes reveal a distinct ancient HLA allele pool and population transformation in Europe

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

doi:10.1101/851188

Cited by 6 publications

(11 citation statements)

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“…Due to the durability of the stone-built components of these monuments, this "Atlantic" complex is often referred to as the "megalithic culture," or cultures. Ancient DNA analyses of megalithic graves in Ireland, Scotland, Sweden (Sánchez-Quinto et al 2019), and northern Germany (Immel et al 2019) show that biological relatedness probably dominated kinship structures, which determined who was buried in which megalithic grave, and that such kinship was-at least in the studied samples-patrilocal and could connect several megalithic graves (Sánchez-Quinto et al 2019).…”

Section: Different Variants Of Neolithic Societies In Europementioning

confidence: 93%

Mobility and Social Change: Understanding the European Neolithic Period after the Archaeogenetic Revolution

Furholt

2021

J Archaeol Res

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This paper discusses and synthesizes the consequences of the archaeogenetic revolution to our understanding of mobility and social change during the Neolithic period in Europe (6500–2000 BC). In spite of major obstacles to a productive integration of archaeological and anthropological knowledge with ancient DNA data, larger changes in the European gene pool are detected and taken as indications for large-scale migrations during two major periods: the Early Neolithic expansion into Europe (6500–4000 BC) and the third millennium BC “steppe migration.” Rather than massive migration events, I argue that both major genetic turnovers are better understood in terms of small-scale mobility and human movement in systems of population circulation, social fission and fusion of communities, and translocal interaction, which together add up to a large-scale signal. At the same time, I argue that both upticks in mobility are initiated by the two most consequential social transformations that took place in Eurasia, namely the emergence of farming, animal husbandry, and sedentary village life during the Neolithic revolution and the emergence of systems of centralized political organization during the process of urbanization and early state formation in southwest Asia.

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Section: Different Variants Of Neolithic Societies In Europementioning

confidence: 93%

Mobility and Social Change: Understanding the European Neolithic Period after the Archaeogenetic Revolution

Furholt

2021

J Archaeol Res

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“…Based on the analysis, we report the highest allele frequencies for HLA-A to be A*24:02 (0.44) and A*02:01 (0.38), B*51:01 (0.31) and B*27:05 (0.25) for HLA-B , and C*02:02 (0.25) and C*15:02 (0.23) for HLA-C ( supplementary tables S4 and S5, Supplementary Material online). In comparison, Late Neolithic individuals from the Wartberg culture show similar distributions of the HLA class I alleles, with HLA-B*27:05 at a frequency of 23% and HLA-C*02:02 at 17% ( Immel et al 2019 ), which is higher than the modern frequencies of the two alleles in Europeans being 3.73% ( Wu et al 2021 ) and 5.6% (UK pop 3 from ( Gonzalez-Galarza et al 2021 )), respectively. Interestingly, the two highest frequency HLA-B alleles in our sample, HLA-B*51:01 and HLA-B*27:05, have been associated with Behçet’s disease susceptibility ( Verity et al 1999 ; Kirino et al 2013 ) and ankylosing spondylitis (AS) ( Cauli et al 2013 ; International Genetics of Ankylosing Spondylitis Consortium (IGAS) 2013 ; Chen et al 2017 ).…”

Section: Resultsmentioning

confidence: 87%

Population Genetics and Signatures of Selection in Early Neolithic European Farmers

Childebayeva

Rohrlach

Barquera

et al. 2022

Molecular Biology and Evolution

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Human expansion in the course of the Neolithic transition in western Eurasia has been one of the major topics in ancient DNA (aDNA) research in the last ten years. Multiple studies have shown that the spread of agriculture and animal husbandry from the Near East across Europe was accompanied by large-scale human expansions. Moreover, changes in subsistence and migration associated with the Neolithic transition have been hypothesized to involve genetic adaptation. Here we present high quality genome-wide data from the Linear Pottery Culture (LBK) site Derenburg Meerenstieg II (DER) (N=32 individuals) in Central Germany. Population genetic analyses show that the DER individuals carried predominantly Anatolian Neolithic-like ancestry and a very limited degree of local hunter-gatherer admixture, similar to other early European farmers. Increasing the LBK cohort size to ∼100 individuals allowed us to perform various frequency- and haplotype-based analyses to investigate signatures of selection associated with changes following the adoption of the Neolithic lifestyle. In addition, we developed a new method called AIMLESS (Admixture-informed Maximum-likelihood Estimation for Selection Scans) that allowed us test for selection signatures in an admixture-aware fashion. Focusing on the intersection of results from these selection scans, we identified various loci associated with immune function (JAK1, HLA-DQB1) and metabolism (LMF1, LEPR, SORBS1), as well as skin color (SLC24A5, CD82) and folate synthesis (MTHFR, NBPF3). Our findings shed light on the evolutionary pressures, such as infectious disease and changing diet, that were faced by the early farmers of Western Eurasia.

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“…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: R a F Tmentioning

confidence: 99%

“…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: R a F Tmentioning

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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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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Neolithic genomes reveal a distinct ancient HLA allele pool and population transformation in Europe

Cited by 6 publications

References 62 publications

Mobility and Social Change: Understanding the European Neolithic Period after the Archaeogenetic Revolution

Mobility and Social Change: Understanding the European Neolithic Period after the Archaeogenetic Revolution

Population Genetics and Signatures of Selection in Early Neolithic European Farmers

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

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