Alrubaian Jasem, Danielson Phillip, Walker David, Dores Robert M
University of Kuwait, Department of Biological Sciences, 13060, Kuwait City, Kuwait.
Peptides. 2002 Mar;23(3):443-52. doi: 10.1016/s0196-9781(01)00643-x.
Procedures for performing cladistic analyses can provide powerful tools for understanding the evolution of neuropeptide and polypeptide hormone coding genes. These analyses can be done on either amino acid data sets or nucleotide data sets and can utilize several different algorithms that are dependent on distinct sets of operating assumptions and constraints. In some cases, the results of these analyses can be used to gauge phylogenetic relationships between taxa. Selecting the proper cladistic analysis strategy is dependent on the taxonomic level of analysis and the rate of evolution within the orthologous genes being evaluated. For example, previous studies have shown that the amino acid sequence of proopiomelanocortin (POMC), the common precursor for the melanocortins and beta-endorphin, can be used to resolve phylogenetic relationships at the class and order level. This study tested the hypothesis that POMC sequences could be used to resolve phylogenetic relationships at the family taxonomic level. Cladistic analyses were performed on amphibian POMC sequences characterized from the marine toad, Bufo marinus (family Bufonidae; this study), the spadefoot toad, Spea multiplicatus (family Pelobatidae), the African clawed frog, Xenopus laevis (family Pipidae) and the laughing frog, Rana ridibunda (family Ranidae). In these analyses the sequence of Australian lungfish POMC was used as the outgroup. The analyses were done at the amino acid level using the maximum parsimony algorithm and at the nucleotide level using the maximum likelihood algorithm. For the anuran POMC genes, analysis at the nucleotide level using the maximum likelihood algorithm generated a cladogram with higher bootstrap values than the maximum parsimony analysis of the POMC amino acid data set. For anuran POMC sequences, analysis of nucleotide sequences using the maximum likelihood algorithm would appear to be the preferred strategy for resolving phylogenetic relationships at the family taxonomic level.
进行分支系统分析的程序可为理解神经肽和多肽激素编码基因的进化提供强大工具。这些分析可基于氨基酸数据集或核苷酸数据集进行，并可采用几种不同的算法，这些算法依赖于不同的操作假设和限制条件。在某些情况下，这些分析的结果可用于衡量分类单元之间的系统发育关系。选择合适的分支系统分析策略取决于分析的分类水平以及所评估的直系同源基因内的进化速率。例如，先前的研究表明，促肾上腺皮质激素原（POMC）的氨基酸序列，即促黑素细胞激素和β-内啡肽的共同前体，可用于解析纲和目水平的系统发育关系。本研究检验了一个假设，即POMC序列可用于解析科级分类水平的系统发育关系。对从海蟾蜍（Bufo marinus，蟾蜍科；本研究）、锄足蟾（Spea multiplicatus，锄足蟾科）、非洲爪蟾（Xenopus laevis，负子蟾科）和泽蛙（Rana ridibunda，蛙科）中获得的两栖类POMC序列进行了分支系统分析。在这些分析中，澳大利亚肺鱼POMC的序列用作外类群。分析在氨基酸水平上使用最大简约算法进行，在核苷酸水平上使用最大似然算法进行。对于无尾目POMC基因，在核苷酸水平上使用最大似然算法进行分析所生成的系统发育树的自展值高于对POMC氨基酸数据集进行的最大简约分析。对于无尾目POMC序列，在科级分类水平上解析系统发育关系时，使用最大似然算法分析核苷酸序列似乎是首选策略。
