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Recoverability of ancestral recombination graph topologies

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  • Hayman, Elizabeth
  • Ignatieva, Anastasia
  • Hein, Jotun

Abstract

Recombination is a powerful evolutionary process that shapes the genetic diversity observed in the populations of many species. Reconstructing genealogies in the presence of recombination from sequencing data is a very challenging problem, as this relies on mutations having occurred on the correct lineages in order to detect the recombination and resolve the ordering of coalescence events in the local trees. We investigate the probability of reconstructing the true topology of ancestral recombination graphs (ARGs) under the coalescent with recombination and gene conversion. We explore how sample size and mutation rate affect the inherent uncertainty in reconstructed ARGs, which sheds light on the theoretical limitations of ARG reconstruction methods. We illustrate our results using estimates of evolutionary rates for several organisms; in particular, we find that for parameter values that are realistic for SARS-CoV-2, the probability of reconstructing genealogies that are close to the truth is low.

Suggested Citation

  • Hayman, Elizabeth & Ignatieva, Anastasia & Hein, Jotun, 2023. "Recoverability of ancestral recombination graph topologies," Theoretical Population Biology, Elsevier, vol. 154(C), pages 27-39.
  • Handle: RePEc:eee:thpobi:v:154:y:2023:i:c:p:27-39
    DOI: 10.1016/j.tpb.2023.07.004
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    References listed on IDEAS

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    1. Nicola F. Müller & Kathryn E. Kistler & Trevor Bedford, 2022. "A Bayesian approach to infer recombination patterns in coronaviruses," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Jenkins, Paul A. & Song, Yun S., 2011. "The effect of recurrent mutation on the frequency spectrum of a segregating site and the age of an allele," Theoretical Population Biology, Elsevier, vol. 80(2), pages 158-173.
    3. Andrew H Chan & Paul A Jenkins & Yun S Song, 2012. "Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster," PLOS Genetics, Public Library of Science, vol. 8(12), pages 1-28, December.
    4. Matthew D Rasmussen & Melissa J Hubisz & Ilan Gronau & Adam Siepel, 2014. "Genome-Wide Inference of Ancestral Recombination Graphs," PLOS Genetics, Public Library of Science, vol. 10(5), pages 1-27, May.
    5. Hobolth, Asger & Wiuf, Carsten, 2009. "The genealogy, site frequency spectrum and ages of two nested mutant alleles," Theoretical Population Biology, Elsevier, vol. 75(4), pages 260-265.
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