Reconstructing the Tree of Life: Are molecular phylogenies really better than morphological ones?

重建生命之树：分子系统发育真的比形态学更好吗？

• 批准号: 1923592
• 金额: --
• 依托单位: University of Bath
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1923592
• 关键词: Reconstructing; Tree; Life; molecular; phylogenies

The phenomenon of evolutionary convergence has intriguing implications for the extent to whichevolution may be predictable (https://theconversation.com/what-do-aliens-look-like-the-clue-is-inevolution-63899).However, it often makes it difficult to reconstruct evolutionary relationships withaccuracy. In particular, it is often assumed that convergence is a problem that particularly bedevilsmorphological phylogenies, making them less accurate(http://www.42evolution.org/videos/researcher/professor-matthew-wills/), but is this really thecase?It is increasingly easy to generate phylogenetic trees from molecular data, with analyses routinelyconcatenating sequences from many tens or hundreds of genes. Despite their data-richunderpinnings, new molecular trees often contain surprises, and frequently imply relationships thatare at odds with established and traditional hypotheses derived from morphological data. One suchexample is the phylogeny of mammal orders: the 'new mammal phylogeny' overturns many'traditional' groups (Fig. 1). Another example is the arthropods. How are we to view these conflicts?Should we necessarily conclude that the new molecular trees are likely to be the correct ones; swayedby the mass of molecular data and greater complexity of analytical models? To do so implies that manydecades of comparative anatomy and morphological scholarship have yielded data that are - at best- simply more noisy and error prone than the data from molecules. At worst, it may indicate thatconvergence within morphological data implies relationships that are positively misleading.Since phylogeny cannot be known with certainty, there can be no objective test of accuracy. However,it is possible to assess the congruence of competing trees with independent sources of data onevolutionary history. Firstly, where the stratigraphic first occurrence dates of terminals (species,genera and higher taxa) are known with reasonable accuracy, the extent of implied ghosts lineages(relative to theoretical limits) offers an index of the 'goodness of fit' to the fossil record. Secondly, thebiogeographical or palaeobiogeographical distributions of many groups contain a residualevolutionary signal, and this can also be tested for its fit to competing trees. While neither stratigraphynor biogeography necessarily offers foolproof discrimination in any particular case, their applicationto a large statistical sample of cases - different major clades, different taxonomic levels, different agesof radiations - allows for some level of generality. The project will also identify which clades underwhich circumstances are most prone to morphological convergence, and therefore most suitablyanalysed with molecular data.The student will acquire an interdisciplinary and transferrable skill set: bioinformatics, phylogenetics,statistics and palaeontology.

进化趋同现象对于进化可预测的程度具有有趣的意义（https://theconversation.com/what-do-aliens-look-like-the-clue-is-inevolution-63899）。然而，它通常使得准确重建进化关系变得困难。特别是，人们通常认为收敛是一个特别困扰形态系统发育的问题，使其不太准确（http://www.42evolution.org/videos/researcher/professor-matthew-wills/），但事实真是如此吗？从分子数据生成系统发育树变得越来越容易，分析通常连接序列 来自数十或数百个基因。尽管有丰富的数据基础，新的分子树常常包含惊喜，并且经常暗示与从形态学数据得出的既定假设和传统假设不一致的关系。哺乳动物目系统发育就是这样一个例子：“新哺乳动物系统发育”颠覆了许多“传统”类群（图1）。另一个例子是节肢动物。我们如何看待这些冲突？我们是否应该得出结论：新的分子树很可能是正确的？受到大量分子数据和更复杂的分析模型的影响吗？这样做意味着数十年的比较解剖学和形态学学术所产生的数据充其量只是比分子数据更嘈杂且更容易出错。在最坏的情况下，它可能表明形态学数据内的趋同意味着具有积极误导性的关系。由于无法确定系统发育，因此无法对准确性进行客观测试。然而，评估具有独立的进化历史数据源的竞争树的一致性是可能的。首先，当终端（种、属和高等分类群）的地层首次出现日期以合理的精度已知时，隐含的幽灵谱系的范围（相对于理论极限）提供了与化石记录“拟合优度”的指数。其次，许多群体的生物地理或古生物地理分布包含残余进化信号，这也可以测试其与竞争树的拟合度。虽然地层学和生物地理学都不一定能在任何特定情况下提供万无一失的区分，但它们对大量统计样本的应用——不同的主要分支、不同的分类水平、不同的辐射年龄——允许一定程度的普遍性。该项目还将确定哪些进化枝在什么情况下最容易发生形态趋同，因此最适合用分子数据进行分析。学生将获得跨学科和可转移的技能：生物信息学、系统发育学、统计学和古生物学。