Data from: Simple chained guide trees give poorer multiple sequence alignments than inferred trees in simulation and phylogenetic benchmarks

Multiple sequence aligners typically work by progressively aligning the most closely related sequences or group of sequences according to guide trees. In PNAS, Boyce et al. report that alignments reconstructed using simple chained trees (i.e., comb-like topologies) with random leaf assignment performed better in protein structure-based benchmarks than those reconstructed using phylogenies estimated from the data as guide trees. The authors state that this result could turn decades of research in the field on its head. In light of this statement, it is important to check immediately whether their result holds under evolutionary criteria: recovery of homologous sequence residues and inference of phylogenetic trees from the alignments. We have done this and the results are entirely opposed to Boyce et al.’s findings.

多序列比对工具（Multiple Sequence Aligner）通常依据指导树（Guide Tree），通过渐进式比对亲缘关系最近的序列或序列簇来完成比对流程。《美国国家科学院院刊》（Proceedings of the National Academy of Sciences, PNAS）刊载的研究中，博伊斯等人（Boyce et al.）报告称：相较于以从数据中估算得到的系统发育树（Phylogenetic Tree）作为指导树所构建的比对结果，采用带有随机叶节点分配的简单链式树（即梳状拓扑结构，comb-like topologies）所重构的多序列比对，在基于蛋白质结构的基准测试中表现更优。作者们指出，该研究结果或将彻底颠覆该领域数十年来的研究范式。鉴于此论断，亟需验证其结果在进化标准下是否成立——即同源序列残基的恢复以及从比对结果中推断系统发育树这两项核心指标。我们已完成该项验证，所得结果与博伊斯等人的研究发现完全相悖。