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.

多序列比对器（multiple sequence aligner）通常依据引导树（guide tree），通过逐步比对亲缘关系最近的序列或序列组来完成比对工作。Boyce等人在《美国国家科学院院刊》（PNAS）中发表研究称，使用带有随机叶节点分配的简单链式树（即梳状拓扑结构）构建的序列比对结果，在基于蛋白质结构的基准测试中，表现优于以从数据中估算得到的系统发育树作为引导树所构建的比对结果。作者指出，这一发现或将彻底颠覆该领域数十年来的研究思路。鉴于此表述，我们有必要即刻验证其结论在进化标准下是否成立：即同源序列残基的恢复效果，以及从比对结果中推导系统发育树的可靠性。我们已完成该项验证，所得结果与Boyce等人的研究结论完全相悖。