重新审视系统发育学中横向基因转移的随机模型
Revisiting a random model of lateral gene transfer in phylogenetics
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中文总结 AI 辅助
研究系统发育学中横向基因转移的随机模型，通过聚焦两物种和三物种最简单情况，推导基因树和位点模式概率，探讨LGT和ILS能否区分，为相关研究提供了新视角及未来工作方向。
中文摘要 AI 辅助
诸如不完全谱系分选（ILS）和网状进化（例如由杂交和横向基因转移（LGT）引起）等过程会导致基因树和物种树之间不一致，使系统发育推断复杂化。虽然多物种合并模型对ILS有丰富理论理解，但LGT概率模型受关注较少。本文重新审视一个基本LGT模型，其中随机LGT事件按具有恒定转移速率的泊松过程发生。聚焦两物种和三物种的最简单情况，推导基因树和位点模式概率并讨论其对模型可识别性的影响，还探讨LGT和ILS能否在此概率模型下区分，最后讨论了实证应用及未来工作方向。
英文摘要
Processes such as incomplete lineage sorting (ILS) and reticulate evolution (arising, for example, from hybridization and lateral gene transfer (LGT)) are known to cause discordance between gene trees and species trees, complicating phylogenetic inference. While the multispecies coalescent model has led to a rich theoretical understanding of ILS, probabilistic models for LGT have received comparatively less attention. Here, we revisit a basic LGT model in which random LGT events occur according to a Poisson process with a constant transfer rate. Focusing on the simplest cases of two and three species, we derive gene tree and site pattern probabilities and discuss their implications for model identifiability. We also address the question of whether LGT and ILS can be distinguished from one another under these probabilistic models. We discuss empirical applications and outline directions for future work.
