Hein J
Center for Molecular Genetics, University of California, San Diego, La Jolla 92093.
Math Biosci. 1990 Mar;98(2):185-200. doi: 10.1016/0025-5564(90)90123-g.
The parsimony principle states that a history of a set of sequences that minimizes the amount of evolution is a good approximation to the real evolutionary history of the sequences. This principle is applied to the reconstruction of the evolution of homologous sequences where recombinations or horizontal transfer can occur. First it is demonstrated that the appropriate structure to represent the evolution of sequences with recombinations is a family of trees each describing the evolution of a segment of the sequence. Two trees for neighboring segments will differ by exactly the transfer of a subtree within the whole tree. This leads to a metric between trees based on the smallest number of such operations needed to convert one tree into the other. An algorithm is presented that calculates this metric. This metric is used to formulate a dynamic programming algorithm that finds the most parsimonious history that fits a given set of sequences. The algorithm is potentially very practical, since many groups of sequences defy analysis by methods that ignore recombinations. These methods give ambiguous or contradictory results because the sequence history cannot be described by one phylogeny, but only a family of phylogenies that each describe the history of a segment of the sequences. The generalization of the algorithm to reconstruct gene conversions and the possibility for heuristic versions of the algorithm for larger data sets are discussed.
简约原则指出，使进化量最小化的一组序列的历史是对这些序列真实进化历史的良好近似。该原则适用于同源序列进化的重建，在这种情况下可能会发生重组或水平转移。首先证明，用于表示有重组的序列进化的合适结构是一族树，每棵树描述序列一段的进化。相邻段的两棵树将仅因整棵树内一个子树的转移而不同。这导致基于将一棵树转换为另一棵树所需的此类操作的最小数量的树之间的度量。提出了一种计算此度量的算法。此度量用于制定动态规划算法，该算法找到适合给定序列集的最简约历史。该算法可能非常实用，因为许多序列组无法通过忽略重组的方法进行分析。这些方法给出模糊或矛盾的结果，因为序列历史不能由一个系统发育来描述，而只能由一族系统发育来描述，每个系统发育描述序列一段的历史。讨论了该算法对基因转换重建的推广以及针对更大数据集的启发式算法版本的可能性。
