Spatial and temporal heterogeneity in human mobility patterns in Holocene Southwest Asia and the East Mediterranean

Koptekin, Dilek; Yüncü, Eren; Rodríguez-Varela, Ricardo; Altınışık, N. Ezgi; Psonis, Nikolaos; Kashuba, Natalia; Yorulmaz, Sevgi; George, Robert; Kazancı, Duygu Deniz; Kaptan, Damla; Gürün, Kanat; Vural, Kıvılcım Başak; Gemici, Hasan Can; Vassou, Despoina; Daskalaki, Evangelia; Karamurat, Cansu; Lagerholm, Vendela Kempe; Erdal, Ömür Dilek; Kırdök, Emrah; Marangoni, Aurelio; Schachner, Andreas; Üstündağ, Handan; Shengelia, Ramaz; Bitadze, Liana; Elashvili, Mikheil; Stravopodi, Eleni; Özbaşaran, Mihriban; Duru, Güneş; Nafplioti, Argyro; Rose, Charles Brian; Gencer, Tuğba; Darbyshire, Gareth; Gavashelishvili, Alexander; Pitskhelauri, Konstantine; Çevik, Özlem; Vuruşkan, Osman; Kyparissi‐Apostolika, Nina; Büyükkarakaya, Ali Metin; Oğuzhanoğlu, Umay; Günel, Sevinç; Tabakaki, Eugenia; Aliev, Akper; Ibrahimov, Anar; Shadlinski, Vaqif; Σαμψών, Αδαμάντιος; Kılınç, Gülşah Merve; Atakuman, Çiğdem; Stamatakis, Alexandros; Poulakakis, Nikos; Erdal, Yılmaz Selim; Pavlidis, Pavlos; Storå, Jan; Özer, Füsun; Götherström, Anders; Somel, Mehmet

doi:10.1016/j.cub.2022.11.034

Cited by 18 publications

(23 citation statements)

References 117 publications

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“…We thus collected BAM files for 71 ancient human genomes belonging to a time range between c.2,800–45,000 years Before Present (BP) ( S2 Table ) [ 56 , 62 – 86 ]. These were chosen to bear diverse characteristics, including mean coverage (0.04×-26×, median = 3.45×), population origin (West Eurasia, East Eurasia, and North America), the laboratory of origin (10 different laboratories), the use of shotgun vs. whole-genome capture protocols, or the use of uracil–DNA–glycosylase (UDG) treatment [ 87 ].…”

Section: Resultsmentioning

confidence: 99%

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

et al. 2022

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To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low genome coverage (<1×) and short fragments (<80 bps), precluding standard CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, tailored for genotyping CNVs at low coverage. Simulations and down-sampling experiments suggest that CONGA can genotype deletions >1 kbps with F-scores >0.75 at ≥1×, and distinguish between heterozygous and homozygous states. We used CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages ranging from 0.44×-26× (median 4×) and average read lengths 52-121 bps (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are highly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.

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Section: Resultsmentioning

confidence: 99%

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

et al. 2022

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“…A model was rejected if the tail probability associated with the model was less than 0.05, or if the ancestry contribution associated with any source was outside the [0, 1] interval. Following the tradition in the literature, 87 if a target could be modeled as both a combination of two sources and only one of the two sources, we preferred the model which required only one source. To test for “proto-Paleo-Eskimo” (PPE) geneflow into present-day PNW populations, we followed two different strategies for target populations: 1) for each PNW population, only using unmasked genomes with less than 1% European ancestry based on ADMIXTURE results ( Table S3 ); and 2) using masked genomes for each PNW population ( Table S4 ).…”

Section: Methodsmentioning

confidence: 99%

A paleogenome from a Holocene individual supports genetic continuity in Southeast Alaska

Aqil¹,

Gill²,

Gökçümen³

et al. 2023

iScience

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“…This mobility seems to have contributed to the present-day genetic structure of these populations. Parallel to contemporaneous populations in the Eastern Mediterranean and Southwest Asia 35 , increasing interconnectivity was also paired with increasing long-distance gene flow patterned by the historical, geopolitical, and even environmental conditions of the time, maintaining population structure in the region 36 .…”

Section: Iron Age Mobility Shaped the Present-day Distribution Of Anc...mentioning

confidence: 98%

A Genetic History of Continuity and Mobility in the Iron Age Central Mediterranean

Moots

Antonio

Sawyer

et al. 2022

Preprint

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The Iron Age saw the expansion of Phoenician and Greek colonies across the Mediterranean and the rise of Carthage as the major maritime power of the region. These events were facilitated by the ease of long-distance travel following major advances in seafaring. We know from the archaeological record that trade goods and materials were moving across great distances in unprecedented quantities, but it is unclear how these patterns correlate with human mobility. To investigate population mobility and interactions directly, we sequenced the genomes of 30 ancient individuals from Carthaginian and Etruscan port cities around the central Mediterranean, in Tunisia, Sardinia, and central Italy. At all three locations, there is a meaningful contribution of autochthonous populations (from Bronze Age North Africa, Sardinia, and Italy, respectively), as well as highly heterogeneous ancestry including many individuals with ancestry from other parts of the Mediterranean region. These results highlight both the role of autochthonous populations and the extreme interconnectedness of populations in the Iron Age Mediterranean. By studying these trans-Mediterranean neighbors together, we explore the complex interplay between local continuity and mobility that shaped the Iron Age societies of the central Mediterranean.

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Spatial and temporal heterogeneity in human mobility patterns in Holocene Southwest Asia and the East Mediterranean

Cited by 18 publications

References 117 publications

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

A paleogenome from a Holocene individual supports genetic continuity in Southeast Alaska

A Genetic History of Continuity and Mobility in the Iron Age Central Mediterranean

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