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.

重组是一个强大的进化过程，它塑造了许多物种种群中观察到的遗传多样性。在存在重组的情况下从测序数据重建谱系是一个非常具有挑战性的问题，因为这依赖于正确谱系上发生的突变，以便检测重组并解决本地树中合并事件的顺序。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。我们探索样本大小和突变率如何影响重建 ARG 的固有不确定性，这揭示了 ARG 重建方法的理论局限性。我们使用对几种生物体进化速率的估计来说明我们的结果；特别是，我们发现对于 SARS-CoV-2 来说现实的参数值，重建接近事实的谱系的概率很低。