Kjer Karl M, Simon Chris, Yavorskaya Margarita, Beutel Rolf G
Department of Entomology and Nematology, University of California-Davis, 1282 Academic Surge, Davis, CA 95616, USA
Department of Ecology and Evolutionary Biology, University of Connecticut, 75 North Eagleville Road, Storrs, CT 06269-3043, USA.
J R Soc Interface. 2016 Aug;13(121). doi: 10.1098/rsif.2016.0363.
The phylogeny of insects has been both extensively studied and vigorously debated for over a century. A relatively accurate deep phylogeny had been produced by 1904. It was not substantially improved in topology until recently when phylogenomics settled many long-standing controversies. Intervening advances came instead through methodological improvement. Early molecular phylogenetic studies (1985-2005), dominated by a few genes, provided datasets that were too small to resolve controversial phylogenetic problems. Adding to the lack of consensus, this period was characterized by a polarization of philosophies, with individuals belonging to either parsimony or maximum-likelihood camps; each largely ignoring the insights of the other. The result was an unfortunate detour in which the few perceived phylogenetic revolutions published by both sides of the philosophical divide were probably erroneous. The size of datasets has been growing exponentially since the mid-1980s accompanied by a wave of confidence that all relationships will soon be known. However, large datasets create new challenges, and a large number of genes does not guarantee reliable results. If history is a guide, then the quality of conclusions will be determined by an improved understanding of both molecular and morphological evolution, and not simply the number of genes analysed.
一个多世纪以来,昆虫的系统发育一直是广泛研究和激烈争论的主题。到1904年已经产生了一个相对准确的深层系统发育关系。直到最近系统发育基因组学解决了许多长期存在的争议,其拓扑结构才得到实质性改善。相反,在此期间的进展来自方法学的改进。早期的分子系统发育研究(1985 - 2005年),以少数几个基因为主导,提供的数据集太小,无法解决有争议的系统发育问题。加剧缺乏共识的是,这一时期的特点是理念两极分化,个体要么属于简约分析阵营,要么属于最大似然分析阵营;双方在很大程度上都忽视了对方的见解。结果是出现了一个不幸的弯路,在哲学分歧的双方发表的少数被认为的系统发育革命可能是错误的。自20世纪80年代中期以来,数据集的规模呈指数级增长,同时伴随着一种信心,即所有的关系很快就会被知晓。然而,大型数据集带来了新的挑战,大量的基因并不能保证得到可靠的结果。如果以历史为鉴,那么结论的质量将取决于对分子和形态进化的更好理解,而不仅仅是所分析基因的数量。