AI 中文总结
研究针对比对不稳定和富含插入缺失进化时系统发育推断不可靠的问题，采用Ladderpath无比对距离方法，将序列分解为阶梯子计算成对距离，经多数据集验证其能恢复拓扑结构，在特定模拟和基因组分析中表现良好，可补充标准流程。
AI 中文摘要
系统发育推断传统上依赖于替换模型下的比对字符，但当比对不稳定或进化由插入、缺失、重复和其他结构变化主导时，该框架变得不太可靠。我们采用Ladderpath作为一种用于系统发育推断的无比对距离方法。受算法信息论的启发，Ladderpath将序列分解为层次组织的派生、可重复使用的单元（“阶梯子”，而不是固定长度的k-mer），并据此计算成对距离。前提是共享的派生序列结构，包括那些难以用按列替换表示的重复或重复使用的片段，可以保留系统发育信息。噬菌体T7已知谱系、富含cpSSR重复的标记和细胞色素c蛋白质数据集证实，Ladderpath恢复的拓扑结构与已知实验历史或基于比对的既定方法一致。其优势在压力下显现：在块易位和插入缺失主导的模拟中，Ladderpath保持稳定，而依赖比对的流程则恶化；在香蕉线粒体和质体基因组上，它可扩展到基因组长度，并捕捉到细胞器历史之间的预期差异，所有这些都来自未比对的输入。这些结果支持Ladderpath作为一种无比对、基于结构信息的方法，在高阶序列结构携带系统发育信号的情况下可以补充标准流程。
英文摘要
Phylogenetic inference traditionally relies on aligned characters under substitution models, but this framework becomes less reliable when alignments are unstable or when evolution is dominated by insertions, deletions, repeats, and other structural changes. We adapt Ladderpath as an alignment-free distance approach for phylogenetic inference. Motivated by algorithmic information theory, Ladderpath decomposes sequences into derived, reusable units (``ladderons'', rather than fixed-length $k$-mers) organized hierarchically, from which pairwise distances are computed. The premise is that shared derived sequence structure, including repeated or reused segments that are poorly represented by column-wise substitutions, can retain phylogenetic information. The bacteriophage T7 known lineage, the cpSSR repeat-rich marker, and a cytochrome~$c$ protein dataset confirm that Ladderpath recovers topologies consistent with the known experimental history or with established alignment-based methods. Its advantage emerges under stress: in block-translocation and indel-dominated simulations Ladderpath remains stable while alignment-dependent pipelines deteriorate; on banana mitochondrial and plastome genomes it scales to genome length and captures the expected contrast between organellar histories, all from unaligned input. These results support Ladderpath as an alignment-free, structurally informed method that could complement standard pipelines in cases where higher-order sequence structure carries phylogenetic signal.
