Suppr超能文献

密码子简并模型的系统发育效用。

The phylogenetic utility of the codon-degeneracy model.

作者信息

McClellan D A

机构信息

Department of Biological Sciences and Museum of Natural Science, Louisiana State University, Baton Rouge, LA 70803, USA.

出版信息

J Mol Evol. 2000 Sep;51(3):185-93. doi: 10.1007/s002390010080.

Abstract

The codon-degeneracy model (CDM) predicts relative frequencies of substitution for any set of homologous protein-coding DNA sequences based on patterns of nucleotide degeneracy, codon composition, and the assumption of selective neutrality. However, at present, the CDM is reliant on outside estimates of transition bias. A new method by which the power of the CDM can be used to find a synonymous transition bias that is optimal for any given phylogenetic tree topology is presented. An example is illustrated that utilizes optimized transition biases to generate CDM GF-scores for every possible phylogenetic tree for pocket gophers of the genus Orthogeomys. The resulting distribution of CDM GF-scores is compared and contrasted with the results of maximum parsimony and maximum likelihood methods. Although convergence on a single tree topology by the CDM and another method indicates greater support for that particular tree, the value of CDM GF-score as the sole optimality criterion for phylogeny reconstruction remains to be determined. It is clear, however, that the a priori estimation of an optimum transition bias from codon composition has a direct application to differentiating between alternative trees.

摘要

密码子简并模型(CDM)基于核苷酸简并模式、密码子组成以及选择性中性假设,预测任何一组同源蛋白质编码DNA序列的替代相对频率。然而,目前CDM依赖于外部对转换偏差的估计。本文提出了一种新方法,利用CDM的能力来找到对于任何给定系统发育树拓扑结构最优的同义转换偏差。文中给出了一个示例,利用优化的转换偏差为Orthogeomys属囊鼠的每一个可能的系统发育树生成CDM GF分数。将所得的CDM GF分数分布与最大简约法和最大似然法的结果进行比较和对比。尽管CDM和另一种方法在单一树拓扑结构上的收敛表明对该特定树有更大的支持,但CDM GF分数作为系统发育重建的唯一最优性标准的价值仍有待确定。然而,很明显,从密码子组成对最优转换偏差进行先验估计可直接应用于区分替代树。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验