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Haplotype-based inference of recent effective population size in modern and ancient DNA samples

Author

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  • Romain Fournier

    (University of Oxford)

  • Zoi Tsangalidou

    (University of Oxford)

  • David Reich

    (Harvard Medical School
    Broad Institute of Harvard and MIT
    Harvard University
    Harvard Medical School)

  • Pier Francesco Palamara

    (University of Oxford
    University of Oxford)

Abstract

Individuals sharing recent ancestors are likely to co-inherit large identical-by-descent (IBD) genomic regions. The distribution of these IBD segments in a population may be used to reconstruct past demographic events such as effective population size variation, but accurate IBD detection is difficult in ancient DNA data and in underrepresented populations with limited reference data. In this work, we introduce an accurate method for inferring effective population size variation during the past ~2000 years in both modern and ancient DNA data, called HapNe. HapNe infers recent population size fluctuations using either IBD sharing (HapNe-IBD) or linkage disequilibrium (HapNe-LD), which does not require phasing and can be computed in low coverage data, including data sets with heterogeneous sampling times. HapNe shows improved accuracy in a range of simulated demographic scenarios compared to currently available methods for IBD-based and LD-based inference of recent effective population size, while requiring fewer computational resources. We apply HapNe to several modern populations from the 1,000 Genomes Project, the UK Biobank, the Allen Ancient DNA Resource, and recently published samples from Iron Age Britain, detecting multiple instances of recent effective population size variation across these groups.

Suggested Citation

  • Romain Fournier & Zoi Tsangalidou & David Reich & Pier Francesco Palamara, 2023. "Haplotype-based inference of recent effective population size in modern and ancient DNA samples," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43522-6
    DOI: 10.1038/s41467-023-43522-6
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    1. Clare Bycroft & Colin Freeman & Desislava Petkova & Gavin Band & Lloyd T. Elliott & Kevin Sharp & Allan Motyer & Damjan Vukcevic & Olivier Delaneau & Jared O’Connell & Adrian Cortes & Samantha Welsh &, 2018. "The UK Biobank resource with deep phenotyping and genomic data," Nature, Nature, vol. 562(7726), pages 203-209, October.
    2. Heng Li & Richard Durbin, 2011. "Inference of human population history from individual whole-genome sequences," Nature, Nature, vol. 475(7357), pages 493-496, July.
    3. Ashot Margaryan & Daniel J. Lawson & Martin Sikora & Fernando Racimo & Simon Rasmussen & Ida Moltke & Lara M. Cassidy & Emil Jørsboe & Andrés Ingason & Mikkel W. Pedersen & Thorfinn Korneliussen & Hel, 2020. "Population genomics of the Viking world," Nature, Nature, vol. 585(7825), pages 390-396, September.
    4. Jack Kamm & Jonathan Terhorst & Richard Durbin & Yun S. Song, 2020. "Efficiently Inferring the Demographic History of Many Populations With Allele Count Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1472-1487, July.
    5. P. G. Bissiri & C. C. Holmes & S. G. Walker, 2016. "A general framework for updating belief distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(5), pages 1103-1130, November.
    6. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    7. Juba Nait Saada & Georgios Kalantzis & Derek Shyr & Fergus Cooper & Martin Robinson & Alexander Gusev & Pier Francesco Palamara, 2020. "Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
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    1. Bing Guo & Victor Borda & Roland Laboulaye & Michele D. Spring & Mariusz Wojnarski & Brian A. Vesely & Joana C. Silva & Norman C. Waters & Timothy D. O’Connor & Shannon Takala-Harrison, 2024. "Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

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