Evidence map›Paper›PMID 29246100›Full record

ArticleBMC genetics2017

Investigating population continuity with ancient DNA under a spatially explicit simulation framework.

Nuno Miguel Silva, Jeremy Rio, Mathias Currat

Abstract read
In one paragraph

Article in BMC genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Sometimes hidden but always there: the assumptions underlying genetic inference of demographic histories.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Review
  7. Article
  8. Article
  9. FHeredity · 2019
    Article
  10. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Nuno Miguel SilvaAGP lab, Department of Genetics & Evolution - Anthropology Unit, University of Geneva, Geneva, Switzerland.
Jeremy RioAGP lab, Department of Genetics & Evolution - Anthropology Unit, University of Geneva, Geneva, Switzerland.
Mathias CurratAGP lab, Department of Genetics & Evolution - Anthropology Unit, University of Geneva, Geneva, Switzerland. mathias.currat@unige.ch.ORCID http://orcid.org/0000-0001-5211-8922

Funding

European Research Council Marie Curie initial training BEAN (GA 289966)Swiss NSF grant 31003A_156853
6 · The paper itself

Abstract

backgroundRecent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called "serial samples", may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples.

resultsWe first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes.

conclusionsHere, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.

Indexed as

Biological EvolutionComputer SimulationDNA, AncientDNA, MitochondrialEmigration and ImmigrationEuropeGenetics, PopulationGenetic VariationHumansWhite PeopleDNA, AncientDNA, MitochondrialAncient DNAEuropean NeolithicPopulation continuityPopulation geneticsSerial coalescentSpatially-explicit simulations

Identifiers

PMID29246100
PMCPMC5731203

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.