CRISPR-Cas9-based genome editing combined with single-cell sequencing enables the tracing of the history of cell divisions, or cellular lineage, in tissues and whole organisms. Although standard phylogenetic approaches may be applied to reconstruct cellular lineage trees from this data, the unique features of the CRISPR-Cas9 editing process motivate the development of specialized models that describe the evolution of CRISPR-Cas9-induced mutations. Here, we introduce the “star homoplasy” evolutionary model that constrains a phylogenetic character to mutate at most once along a lineage, capturing the “non-modifiability” property of CRISPR-Cas9 mutations. We derive a combinatorial characterization of star homoplasy phylogenies and use this characterization to develop an algorithm, “Startle”, that computes a maximum parsimony star homoplasy phylogeny. We demonstrate that Startle infers more accurate phylogenies on simulated lineage tracing data compared with existing methods and finds parsimonious phylogenies with fewer metastatic migrations on lineage tracing data from mouse metastatic lung adenocarcinoma.

基于 CRISPR-Cas9 的基因组编辑与单细胞测序相结合，能够追踪组织和整个生物体中的细胞分裂或细胞谱系的历史。尽管标准系统发生方法可用于根据这些数据重建细胞谱系树，但 CRISPR-Cas9 编辑过程的独特特征激发了描述 CRISPR-Cas9 诱导突变进化的专门模型的开发。在这里，我们引入了“星同质性”进化模型，该模型限制系统发育特征沿谱系最多突变一次，从而捕获了 CRISPR-Cas9 突变的“不可修改性”特性。我们推导了星同型系统发育的组合特征，并使用该特征开发了一种算法“Startle”，该算法计算最大简约星同型系统发育。我们证明，与现有方法相比，Startle 在模拟谱系追踪数据上推断出更准确的系统发育，并在小鼠转移性肺腺癌的谱系追踪数据上发现了具有较少转移迁移的简约系统发育。