The fundamental Hennigian principle, grouping solely on synapomorphy, is seldom used in modern phylogenetics. In the submitted paper, we apply this principle in reanalyzing five datasets comprising 197 complete plastid genomes (plastomes). We focused on the latter because plastome-based DNA sequence data gained dramatic popularity in molecular systematics during the last decade. We show that pattern-cladistic analyses based on complete plastid genome sequences can successfully resolve affinities between plant taxa, simultaneously simplifying both the genomic and analytical frameworks of phylogenetic studies. We developed “Matrix to Newick” (M2N), a program to represent the standard molecular alignment of plastid genomes in the form of trees or relationships directly. Thus, massive plastome-based DNA sequence data can be successfully represented in a relational form rather than as a standard molecular alignment. Application of methods of median supertree construction (the Average Consensus method has been used as an example in this study) or Maximum Parsimony analysis to relational representations of plastome sequence data may help systematist to avoid the complicated assumption-based frameworks of Maximum Likelihood or Bayesian phylogenetics that are most used today in massive plastid sequence data analyses. We also found that significant amounts of pure genomic information that typically accommodate the majority of current plastid phylogenomic studies can be effectively dropped by systematists if they focus on the pattern-cladistics or relational analyses of plastome-based molecular data. The proposed pattern-cladistic approach is a powerful and straightforward heuristic alternative to modern plastome-based phylogenetics.

亨尼格的基本原理仅根据共源性进行分组，在现代系统发育学中很少使用。在提交的论文中，我们应用这一原理重新分析了包含 197 个完整质体基因组（质体）的 5 个数据集。我们关注后者是因为基于质体的 DNA 序列数据在过去十年中在分子系统学中获得了极大的普及。我们表明，基于完整质体基因组序列的模式分支分析可以成功解决植物类群之间的亲和力，同时简化系统发育研究的基因组和分析框架。我们开发了“Matrix to Newick”（M2N）程序，该程序以树或关系的形式直接表示质体基因组的标准分子比对。因此，大量基于质体的 DNA 序列数据可以成功地以关系形式表示，而不是作为标准分子比对。将中位超级树构建方法（本研究中使用平均一致性方法作为示例）或最大简约分析应用于质体序列数据的关系表示可能有助于系统学家避免最大似然或贝叶斯系统发育学的复杂的基于假设的框架目前最常用于大规模质体序列数据分析。我们还发现，如果系统学家专注于基于质体的分子数据的模式分支学或关系分析，通常可以容纳大多数当前质体系统发育学研究的大量纯基因组信息可以被系统学家有效地丢弃。所提出的模式分支方法是现代基于质体的系统发育学的一种强大而直接的启发式替代方法。