Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

中文翻译：

---

线粒体数据系统发育分析中的蛋白质结构、序列进化模型和数据类型效应：鸟类案例研究

系统基因组学分析彻底改变了生物多样性的研究，但它们表明，估计的树拓扑结构可能至少部分取决于所分析的基因组子集。例如，如果分析蛋白质编码或非编码数据，鸟类命令的树木估计会有所不同。鸟树是一个很好的研究系统，因为命令之间关系的历史信号非常弱，这应该允许识别微妙的非历史信号，而命令的单系性得到强烈证实，允许识别强烈的非历史信号。预计在跨膜螺旋中发现的线粒体编码蛋白中的疏水性氨基酸已被假设与非历史信号相关。我们通过比较来自 420 种鸟类的线粒体蛋白的跨膜螺旋和膜外片段的进化来检验这一假设，这些鸟类来自大多数鸟类目。我们估计了两种结构环境的氨基酸交换能力，并使用每种数据类型评估了系统发育分析的性能。我们将这些相对交换率与使用各种核和线粒体编码蛋白估计的跨膜螺旋置换矩阵计算的值进行了比较，使我们能够将鸟类特异性线粒体模型与跨膜蛋白进化的一般模型进行比较。为了补充我们的氨基酸分析，我们检查了蛋白质结构对核苷酸进化模式的影响。氨基酸和核苷酸的跨膜和膜外序列进化模型表现出显着差异，但没有证据表明存在强烈的拓扑数据类型效应。然而，将蛋白质结构纳入线粒体编码蛋白质的分析可改善模型拟合。因此，我们相信考虑蛋白质结构将改进对鸟类和其他分类群有丝分裂基因组数据的分析。