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Cited by 371Genomics and Phylogenetic StudiesForensic and Genetic ResearchGenetic diversity and population structure

Genome-Wide Inference of Ancestral Recombination Graphs

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Rasmussen, Matthew D., Hubisz, Melissa J., Gronau, Ilan, Siepel, Adam·2014·PLoS Genetics
DOI 10.1371/journal.pgen.1004342PMC PMC4022496
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Abstract

The complex correlation structure of a collection of orthologous DNA sequences is uniquely captured by the "ancestral recombination graph" (ARG), a complete record of coalescence and recombination events in the history of the sample. However, existing methods for ARG inference are computationally intensive, highly approximate, or limited to small numbers of sequences, and, as a consequence, explicit ARG inference is rarely used in applied population genomics. Here, we introduce a new algorithm for ARG inference that is efficient enough to apply to dozens of complete mammalian genomes. The key idea of our approach is to sample an ARG of [Formula: see text] chromosomes conditional on an ARG of [Formula: see text] chromosomes, an operation we call "threading." Using techniques based on hidden Markov models, we can perform this threading operation exactly, up to the assumptions of the sequentially Markov coalescent and a discretization of time. An extension allows for threading of subtrees instead of individual sequences. Repeated application of these threading operations results in highly efficient Markov chain Monte Carlo samplers for ARGs. We have implemented these methods in a computer program called ARGweaver. Experiments with simulated data indicate that ARGweaver converges rapidly to the posterior distribution over ARGs and is effective in recovering various features of the ARG for dozens of sequences generated under realistic parameters for human populations. In applications of ARGweaver to 54 human genome sequences from Complete Genomics, we find clear signatures of natural selection, including regions of unusually ancient ancestry associated with balancing selection and reductions in allele age in sites under directional selection. The patterns we observe near protein-coding genes are consistent with a primary influence from background selection rather than hitchhiking, although we cannot rule out a contribution from recurrent selective sweeps.

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  • ArgWeaver requires prior knowledge of demographic model parameters.

    “ArgWeaver (4), which is widely considered the gold standard in ARG inference, requires prior knowledge of demographic model parameters.”

    From An ancestral recombination graph of human, Neanderthal, and Denisovan genomes (2021) · cites this paper as [4]

    The Methods > Data Analysis passage says the authors ran ARGweaver assuming a population size based on an empirical estimate, so the analysis used a specified parameter. But the Discussion says they sampled genealogies under a naive, panmictic prior and obtained information about population structure even with a noninformative prior. The paper therefore does not establish that ARGweaver requires prior knowledge of demographic model parameters. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • BEAGLE, ArgWeaver, and Rent+ were designed for small datasets and require substantial time and/or memory to be used with large sequencing panels.

    “BEAGLE (3), ArgWeaver (4), and Rent+ (5) were designed for small datasets and require substantial time and/or memory to be used with large sequencing panels.”

    From An ancestral recombination graph of human, Neanderthal, and Denisovan genomes (2021) · cites this paper as [4]

    For ARGweaver, the Results (Analysis of Real Data) report 5.7 CPU-years to analyze 54 genomes, and the Discussion identifies long running times as a barrier and scaling to thousands of genomes as future work. This supports the concern about using ARGweaver with large panels, but the paper does not say it was designed for small datasets. The separate claims about BEAGLE and Rent+ are attached to other citations. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Based on ARGweaver allele age estimates, TCC to T rate acceleration seems to have occurred between 25,000 and 60,000 years ago, not long after Europeans diverged from Asians.

    “Based on these estimates, TCC → T rate acceleration seems to have occurred between 25,000 and 60,000 y ago, not long after Europeans diverged from Asians (SI Appendix, section 4).”

    From Evidence for recent, population-specific evolution of the human mutation rate (2015) · cites this paper as [24]

  • A new class of methods bases population genetic inference on reconstructed coalescent information and has promising test power and resolution for inferring selection.

    “In the last few years, a new class of methods has emerged, which base the population genetic inference on reconstructed coalescent information 23,33,34 .These methods manifested promising test power and resolution for inferring selection, as the genome-wide coalescent trees provide a complete record of genealogies, mutations, and recombination 33 .”

    From A Chronological Atlas of Natural Selection in the Human Genome during the Past Half-million Years (2015) · cites this paper as [33]

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Authors
Rasmussen, M. D., Hubisz, M. J., Gronau, I., & Siepel, A.
Affiliations
  • Cornell University (US)
  • European Bioinformatics Institute (GB)
Corresponding author
  • Rasmussen, Matthew D.
  • Siepel, Adam
ORCID
Venue
PLoS Genetics
Publisher
Public Library of Science (PLoS)
Published
2014-05-15
Volume
10
Issue
5
Pages
e1004342
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
DOI
10.1371/journal.pgen.1004342
PMC
PMC4022496
OpenAlex
W2137706757
Semantic Scholar
ba7a79e9daa8da0f51d5014c68d24f0962dd36ec
Cited by
371
References
115
Citations by year
2026: 24 · 2025: 36 · 2024: 38 · 2023: 26 · 2022: 31 · 2021: 29 · 2020: 30 · 2019: 28 · 2018: 54 · 2017: 13 · 2016: 29 · 2015: 21 · 2014: 10 · 2013: 1 · 2012: 1
FWCI
9.92
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Genetics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Science Foundation (1053575)
  • University of Texas at Austin
  • European Bioinformatics Institute
  • National Institutes of Health (OCI-1053575)
  • National Institute of General Medical Sciences (R01GM102192, GM102192)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Keywords
ancestral recombination graph, threading, hidden Markov models, orthologous sequences, human genome sequence, natural selection signatures, balancing selection, directional selection, background selection, hitchhiking, allele age, coalescence
MeSH terms
Algorithms, Computer Simulation, Humans, Markov Chains, Models, Genetic, Monte Carlo Method, Recombination, Genetic, Selection, Genetic, Genome, Human, Evolution, Molecular

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