Department of Mathematics, University of Oxford, Andrew Wiles Building, Oxford OX2 6GG, UK.
Department of Statistics, University of Warwick, Coventry CV4 7AL, UK; Department of Statistics, University of Oxford, 24-29 St Giles', Oxford OX1 3LB, UK.
Theor Popul Biol. 2023 Dec;154:27-39. doi: 10.1016/j.tpb.2023.07.004. Epub 2023 Aug 5.
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.
重组是一种强大的进化过程，它塑造了许多物种群体中观察到的遗传多样性。从测序数据中重建存在重组的系统发育是一个极具挑战性的问题，因为这依赖于突变是否发生在正确的谱系上，以便检测重组并解决局部树中融合事件的排序。我们研究了在重组和基因转换的合并下，重建祖先重组图（ARG）真实拓扑的概率。我们探讨了样本量和突变率如何影响重建 ARG 中的固有不确定性，这为 ARG 重建方法的理论局限性提供了启示。我们使用几种生物体的进化率估计值来说明我们的结果；特别是，我们发现对于 SARS-CoV-2 来说，参数值是现实的，重建接近真实的系统发育的概率很低。
