Data from: Analysis of phylogenomic datasets reveals conflict, concordance, and gene duplications with examples from animals and plants

Background: The use of transcriptomic and genomic datasets for phylogenetic reconstruction has become increasingly common as researchers attempt to resolve recalcitrant nodes with increasing amounts of data. The large size and complexity of these datasets introduce significant phylogenetic noise and conflict into subsequent analyses. The sources of conflict may include hybridization, incomplete lineage sorting, or horizontal gene transfer, and may vary across the phylogeny. For phylogenetic analysis, this noise and conflict has been accommodated in one of several ways: by binning gene regions into subsets to isolate consistent phylogenetic signal; by using gene-tree methods for reconstruction, where conflict is presumed to be explained by incomplete lineage sorting (ILS); or through concatenation, where noise is presumed to be the dominant source of conflict. The results provided herein emphasize that analysis of individual homologous gene regions can greatly improve our understanding of the underlying conflict within these datasets. Results: Here we examined two published transcriptomic datasets, the angiosperm group Caryophyllales and the aculeate Hymenoptera, for the presence of conflict, concordance, and gene duplications in individual homologs across the phylogeny. We found significant conflict throughout the phylogeny in both datasets and in particular along the backbone. While some nodes in each phylogeny showed patterns of conflict similar to what might be expected with ILS alone, the backbone nodes also exhibited low levels of phylogenetic signal. In addition, certain nodes, especially in the Caryophyllales, had highly elevated levels of strongly supported conflict that cannot be explained by ILS alone. Conclusion: This study demonstrates that phylogenetic signal is highly variable in phylogenomic data sampled across related species and poses challenges when conducting species tree analyses on large genomic and transcriptomic datasets. Further insight into the conflict and processes underlying these complex datasets is necessary to improve and develop adequate models for sequence analysis and downstream applications. To aid this effort, we developed the open source software phyparts (https://bitbucket.org/blackrim/phyparts), which calculates unique, conflicting, and concordant bipartitions, maps gene duplications, and outputs summary statistics such as internode certainy (ICA) scores and node-specific counts of gene duplications.研究背景：随着研究者尝试借助日益扩增的数据量解析疑难系统发育节点，转录组（transcriptomic）与基因组（genomic）数据集在系统发育重建中的应用愈发普遍。此类数据集规模庞大且结构复杂，会在后续分析中引入显著的系统发育噪声与系统发育冲突。冲突的来源可能包括杂交、不完全谱系分选（incomplete lineage sorting, ILS）或水平基因转移，且在系统发育树的不同区域存在差异。针对这类系统发育分析中的噪声与冲突，目前已有多种处理方案：将基因区域划分为子集以分离一致性的系统发育信号；采用基因树分析法开展重建，此时默认冲突由不完全谱系分选（ILS）导致；或是采用串联拼接分析法，此时默认噪声为冲突的主要来源。本研究结果表明，对单个同源基因区域的分析，可极大提升我们对这类数据集内部潜在冲突的认知。 研究结果：本研究对两份已发表的转录组数据集展开分析，分别为被子植物石竹目（Caryophyllales）与膜翅目针尾部类群，以探究整个系统发育树中单个同源基因的冲突、一致性及基因重复情况。我们在两份数据集的整个系统发育树中均发现了显著的冲突，尤其在主干分支处。尽管两类群的部分节点呈现出仅由不完全谱系分选（ILS）即可解释的冲突模式，但主干分支同时也表现出较低水平的系统发育信号。此外，部分节点（尤以石竹目类群为甚）的强支持冲突水平显著升高，这类冲突无法仅通过不完全谱系分选（ILS）解释。 研究结论：本研究证实，在近缘类群的系统发育组学数据中，系统发育信号存在高度异质性，这为基于大型基因组与转录组数据集开展物种树分析带来了挑战。我们需要进一步深入解析这类复杂数据集背后的冲突与潜在过程，才能优化并开发出适用于序列分析及下游应用的合理模型。为助力该研究方向，我们开发了开源软件phyparts（https://bitbucket.org/blackrim/phyparts），该工具可计算唯一、冲突及一致性二分拓扑结构，映射基因重复事件，并输出分支间置信度（internode certainty, ICA）得分及节点特异性基因重复计数等汇总统计量。