Department of Evolution and Ecology and Center for Population Biology, University of California, Davis, CA 95616, USA.
Syst Biol. 2010 Jan;59(1):42-58. doi: 10.1093/sysbio/syp075. Epub 2009 Nov 11.
As phylogenetic data sets grow in size and number, objective methods to summarize this information are becoming increasingly important. Supermatrices can combine existing data directly and in principle provide effective syntheses of phylogenetic information that may reveal new relationships. However, several serious difficulties exist in the construction of large supermatrices that must be overcome before these approaches will enjoy broad utility. We present analyses that examine the performance of sparse supermatrices constructed from large sequence databases for the reconstruction of species-level phylogenies. We develop a largely automated informatics pipeline that allows for the construction of sparse supermatrices from GenBank data. In doing so, we develop strategies for alleviating some of the outstanding impediments to accurate phylogenetic inference using these approaches. These include taxonomic standardization, automated alignment, and the identification of rogue taxa. We use turtles as an exemplar clade and present a well-supported species-level phylogeny for two-thirds of all turtle species based on a approximately 50 kb supermatrix consisting of 93% missing data. Finally, we discuss some of the remaining pitfalls and concerns associated with supermatrix analyses, provide comparisons to supertree approaches, and suggest areas for future research.
随着系统发育数据集的规模和数量不断增长，总结这些信息的客观方法变得越来越重要。超级矩阵可以直接合并现有数据，并原则上提供有效的系统发育信息综合，从而可能揭示新的关系。然而，在这些方法得到广泛应用之前，构建大型超级矩阵存在几个严重的困难，必须克服这些困难。我们进行了分析，以检验从大型序列数据库构建稀疏超级矩阵来重建种系发生关系的性能。我们开发了一个主要自动化的信息学管道，允许从 GenBank 数据构建稀疏超级矩阵。在这样做的过程中，我们开发了一些策略来缓解使用这些方法进行准确系统发育推断的一些突出障碍。这些策略包括分类标准化、自动比对和识别流氓分类单元。我们以海龟为例，展示了基于大约 50kb 的超级矩阵的近三分之二海龟物种的支持良好的种系发生关系，该超级矩阵由 93%的缺失数据组成。最后，我们讨论了与超级矩阵分析相关的一些剩余陷阱和问题，提供了与超级树方法的比较，并提出了未来研究的方向。
