Department of Zoology, The Natural History Museum, London, UK.
Cell Mol Biol Lett. 2010 Jun;15(2):311-41. doi: 10.2478/s11658-010-0010-8. Epub 2010 Mar 5.
The comparative and evolutionary analysis of molecular data has allowed researchers to tackle biological questions that have long remained unresolved. The evolution of DNA and amino acid sequences can now be modeled accurately enough that the information conveyed can be used to reconstruct the past. The methods to infer phylogeny (the pattern of historical relationships among lineages of organisms and/or sequences) range from the simplest, based on parsimony, to more sophisticated and highly parametric ones based on likelihood and Bayesian approaches. In general, molecular systematics provides a powerful statistical framework for hypothesis testing and the estimation of evolutionary processes, including the estimation of divergence times among taxa. The field of molecular systematics has experienced a revolution in recent years, and, although there are still methodological problems and pitfalls, it has become an essential tool for the study of evolutionary patterns and processes at different levels of biological organization. This review aims to present a brief synthesis of the approaches and methodologies that are most widely used in the field of molecular systematics today, as well as indications of future trends and state-of-the-art approaches.
分子数据的比较和进化分析使研究人员能够解决长期以来悬而未决的生物学问题。现在,DNA 和氨基酸序列的进化可以被准确地建模,以至于所传达的信息可以被用来重建过去。推断系统发育(生物谱系和/或序列之间历史关系的模式)的方法从最简单的基于简约性的方法到更复杂和高度参数化的基于似然性和贝叶斯方法的方法都有。一般来说,分子系统学为假设检验和进化过程的估计提供了一个强大的统计框架,包括估计分类群之间的分歧时间。近年来,分子系统学领域发生了一场革命,尽管仍然存在方法问题和陷阱,但它已成为研究不同层次生物组织的进化模式和过程的重要工具。本综述旨在简要综合当今分子系统学领域最广泛使用的方法和方法,并指出未来的趋势和最新方法。