Data from: Analysis of a rapid evolutionary radiation using ultraconserved elements (UCEs): Evidence for a bias in some multi-species coalescent methods

Rapid evolutionary radiations are expected to require large amounts of sequence data to resolve. To resolve these types of relationships many systematists believe that it will be necessary to collect data by next-generation sequencing (NGS) and use multispecies coalescent (“species tree”) methods. Ultraconserved element (UCE) sequence capture is becoming a popular method to leverage the high throughput of NGS to address problems in vertebrate phylogenetics. Here we examine the performance of UCE data for gallopheasants (true pheasants and allies), a clade that underwent a rapid radiation 10–15 Ma. Relationships among gallopheasant genera have been difficult to establish. We used this rapid radiation to assess the performance of species tree methods, using ∼600 kilobases of DNA sequence data from ∼1500 UCEs. We also integrated information from traditional markers (nuclear intron data from 15 loci and three mitochondrial gene regions). Species tree methods exhibited troubling behavior. Two methods [Maximum Pseudolikelihood for Estimating Species Trees (MP-EST) and Accurate Species TRee ALgorithm (ASTRAL)] appeared to perform optimally when the set of input gene trees was limited to the most variable UCEs, though ASTRAL appeared to be more robust than MP-EST to input trees generated using less variable UCEs. In contrast, the rooted triplet consensus method implemented in Triplec performed better when the largest set of input gene trees was used. We also found that all three species tree methods exhibited a surprising degree of dependence on the program used to estimate input gene trees, suggesting that the details of likelihood calculations (e.g., numerical optimization) are important for loci with limited phylogenetic information. As an alternative to summary species tree methods we explored the performance of SuperMatrix Rooted Triple - Maximum Likelihood (SMRT-ML), a concatenation method that is consistent even when gene trees exhibit topological differences due to the multispecies coalescent. We found that SMRT-ML performed well for UCE data. Our results suggest that UCE data have excellent prospects for the resolution of difficult evolutionary radiations, though specific attention may need to be given to the details of the methods used to estimate species trees.快速辐射演化（Rapid evolutionary radiation）通常需要依托大量序列数据方可获得精准解析。针对此类演化关系的解析，众多系统分类学家认为，需通过下一代测序（Next-Generation Sequencing, NGS）获取数据，并采用多物种溯祖（multispecies coalescent）方法，即“物种树（species tree）”推断技术。超保守元件（Ultraconserved Element, UCE）序列捕获技术正逐渐成为利用NGS高通量特性解决脊椎动物系统发育问题的主流方法。 本研究以真雉类及其近缘类群为例，评估UCE数据的应用性能——该演化支在1000万至1500万年前经历了快速辐射演化，其各属间的系统发育关系长期难以确定。我们依托约1500个UCE位点得到的约600千碱基对DNA序列数据，结合15个基因座的核内含子序列与3个线粒体基因区域的传统分子标记数据，对多种物种树推断方法的性能进行了系统性评估。 研究发现，各类物种树推断方法展现出令人担忧的表现差异：两种方法——最大伪似然物种树推断法（Maximum Pseudolikelihood for Estimating Species Trees, MP-EST）与精确物种树算法（Accurate Species TRee ALgorithm, ASTRAL）——在输入基因树集限定于变异度最高的UCE时表现最优；不过相较于MP-EST，ASTRAL对由低变异度UCE生成的输入基因树具有更强的鲁棒性。与之相反，Triplec软件中实现的有根三联体共识法，在使用规模最大的输入基因树集时表现更佳。 此外，三种物种树推断方法均对用于生成输入基因树的软件表现出出人意料的依赖性，这提示：对于系统发育信息有限的基因座而言，似然性计算的细节（如数值优化过程）至关重要。作为汇总式物种树推断方法的替代方案，我们探究了超矩阵有根三联体最大似然法（SuperMatrix Rooted Triple - Maximum Likelihood, SMRT-ML）的性能——这是一种即使基因树因多物种溯祖效应出现拓扑结构差异，仍能保持统计一致性的串联式推断方法。研究结果表明，SMRT-ML在UCE数据上表现优异。 综上，本研究结果证实，UCE数据在解析疑难快速辐射演化事件方面具备极佳的应用前景，但仍需针对性关注物种树推断方法的细节参数与实现流程。