Evidence map›Paper›PMID 39081397›Full record

SynthesisAmerican journal of biological anthropology2023

Spatiotemporal fluctuations of population structure in the Americas revealed by a meta-analysis of the first decade of archaeogenomes.

Andre Luiz Campelo Dos Santos, Henry Socrates Lavalle Sullasi, Omer Gokcumen, John Lindo, Michael DeGiorgio

Abstract readMeta-Analysis
In one paragraph

Synthesis in American journal of biological anthropology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Andre Luiz Campelo Dos SantosDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, USA.ORCID 0000-0002-5577-1967
Henry Socrates Lavalle SullasiDepartment of Archaeology, Federal University of Pernambuco, Recife, Pernambuco, Brazil.ORCID 0000-0002-0690-6781
Omer GokcumenDepartment of Biological Sciences, University at Buffalo, Buffalo, New York, USA.ORCID 0000-0003-4371-679X
John LindoDepartment of Anthropology, Emory University, Atlanta, Georgia, USA.ORCID 0000-0002-2533-8505
Michael DeGiorgioDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, USA.ORCID 0000-0003-4908-7234

Funding

Identifying complex modes of adaptation from population-genomic dataR35GM128590 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI Michael DeGiorgio · 2018 to 2026
$2.8M
NIGMS NIH HHS R35 GM128590
6 · The paper itself

Abstract

Objectives: Since 2010, genome-wide data from hundreds of ancient Native Americans have contributed to the understanding of Americas' prehistory. However, these samples have never been studied as a single dataset, and distinct relationships among themselves and with present-day populations may have never come to light. Here, we reassess genomic diversity and population structure of 223 ancient Native Americans published between 2010 and 2019. Materials and Methods: The genomic data from ancient Americas was merged with a worldwide reference panel of 278 present-day genomes from the Simons Genome Diversity Project and then analyzed through ADMIXTURE, Results: We find largely similar population structures in ancient and present-day Americas. However, the population structure of contemporary Native Americans, traced here to at least 10,000 years before present, is noticeably less diverse than their ancient counterparts, a possible outcome of the European contact. Additionally, in the past there were greater levels of population structure in North than in South America, except for ancient Brazil, which harbors comparatively high degrees of structure. Moreover, we find a component of genetic ancestry in the ancient dataset that is closely related to that of present-day Oceanic populations but does not correspond to the previously reported Australasian signal. Lastly, we report an expansion of the Ancient Beringian ancestry, previously reported for only one sample. Discussion: Overall, our findings support a complex scenario for the settlement of the Americas, accommodating the occurrence of founder effects and the emergence of ancestral mixing events at the regional level.

Indexed as

Genome, HumanAmericasArchaeologyGenetics, PopulationGenetic VariationHumansIndians, North Americanancestryancient genomicsmeta-analysisnative Americanspopulation structure

Identifiers

PMID39081397
PMCPMC11288623

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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.