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  Tracking human population structure through time from whole genome sequences

Wang, K., Mathieson, I., O'Connell, J., & Schiffels, S. (2020). Tracking human population structure through time from whole genome sequences. PLoS Genetics, 16(3): e1008552, pp. 1-24. doi:10.1371/journal.pgen.1008552.

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 Urheber:
Wang, Ke1, Autor           
Mathieson, Iain, Autor
O'Connell, Jared, Autor
Schiffels, Stephan1, Autor           
Affiliations:
1Archaeogenetics, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2074310              

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Schlagwörter: African,demography, gene flow, human, introgression, simulation
 Zusammenfassung: The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyse the population separation history. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.Author Summary Human demographic history is reflected in specific patterns of shared mutations between the genomes from different populations. Here we aim to unravel this pattern to infer population structure through time with a new approach, called MSMC-IM. Based on estimates of coalescence rates within and across populations, MSMC-IM fits a time-dependent migration model to the pairwise rate of coalescences. We implemented this approach as an extension to existing software (MSMC2), and tested it with simulations exhibiting different histories of admixture and gene flow. We then applied it to the genomes from 15 worldwide populations to reveal their pairwise separation history ranging from a few thousand up to several million years ago. Among other results, we find evidence for remarkably deep population structure in some African population pairs, suggesting that deep ancestry dating to one million years ago and older is still present in human populations in small amounts today.

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Sprache(n): eng - English
 Datum: 2020-03-092020-03
 Publikationsstatus: Erschienen
 Seiten: 24
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: Introduction

Results
- Estimating pairwise coalescence rates with MSMC2 and fitting an IM
model
- Evaluating MSMC-IM with simulated data
- Deep ancestry in Africa
- Complex divergence between African and Non-African populations
- Separations outside of Africa
- Robustness to phasing and processing artifacts

Discussion

Materials and methods
- MSMC2
- MSMC-IM model
- Simulations
- Processing genomic Data
- Running MSMC-IM
- Robustness tests
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1371/journal.pgen.1008552
DOI: 10.1101/585265
Anderer: shh2325
 Art des Abschluß: -

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Titel: PLoS Genetics
  Andere : PLoS Genet.
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 16 (3) Artikelnummer: e1008552 Start- / Endseite: 1 - 24 Identifikator: ISSN: 1553-7390
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180

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Titel: bioRxiv
Genre der Quelle: Zeitschrift
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Affiliations:
Ort, Verlag, Ausgabe: Cold Spring Harbor : Cold Spring Harbor Laboratory
Seiten: - Band / Heft: - Artikelnummer: 585265 Start- / Endseite: - Identifikator: URI: https://www.biorxiv.org/