Martin Darren P
Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, Observatory, South Africa.
Methods Mol Biol. 2009;537:185-205. doi: 10.1007/978-1-59745-251-9_9.
Recombination between nucleotide sequences is a major process influencing the evolution of most species on Earth. While its evolutionary value is a matter of quite intense debate, so too is the influence of recombination on evolutionary analysis methods that assume nucleotide sequences replicate without recombining. The crux of the problem is that when nucleic acids recombine, the daughter or recombinant molecules no longer have a single evolutionary history. All analysis methods that derive increased power from correctly inferring evolutionary relationships between sequences will therefore be at least mildly sensitive to the effects of recombination. The importance of considering recombination in evolutionary studies is underlined by the bewildering array of currently available methods and software tools for analysing and characterising it in various classes of nucleotide sequence datasets. Here we will examine the use of some of these tools to derive and test recombination hypotheses for datasets containing a moderate degree of nucleotide sequence diversity.
核苷酸序列之间的重组是影响地球上大多数物种进化的一个主要过程。虽然其进化价值是一个激烈争论的话题,但重组对假设核苷酸序列在不发生重组的情况下进行复制的进化分析方法的影响也是如此。问题的关键在于,当核酸发生重组时,子代或重组分子不再具有单一的进化历史。因此,所有通过正确推断序列之间的进化关系而获得更强分析能力的分析方法,至少会对重组的影响有一定程度的敏感性。目前有各种各样用于分析和表征各类核苷酸序列数据集中重组情况的方法和软件工具,这凸显了在进化研究中考虑重组的重要性。在这里,我们将研究如何使用其中一些工具来推导和检验包含中等程度核苷酸序列多样性的数据集的重组假设。