 Recoverability of ancestral recombination graph topologiesElizabeth Hayman, Anastasia Ignatieva and Jotun Hein Theoretical Population Biology, 2023, vol. 154, issue C, 27-39 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. Keywords: Recombination detection; Ancestral recombination graph; Coalescent; Gene conversion (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:thpobi:v:154:y:2023:i:c:p:27-39 DOI: 10.1016/j.tpb.2023.07.004 Access Statistics for this article Theoretical Population Biology is currently edited by Jeremy Van Cleve More articles in Theoretical Population Biology from Elsevier |
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