DNA SEQUENCE COMPLEXITY AND MUTATIONAL DYNAMICS

DNA序列在其局部区域显示出巨大的统计异质性。 组成特征 该项目正在调查 序列复杂性中镶嵌现象的可能原因，特别是 突变偏好、中长期组合 限制以及特定功能和结构的相关性 序列类 A.局部复杂性的分布：使用局部复杂性的形式定义 DNA序列的组成复杂性， Salamon/Konopka最大熵关系已经被探索： 功能等同的DNA序列的集合， 这个集合的所有序列之间的复杂性似乎是随机的， 可能与这些序列的平均复杂度一致。 它 现在已经表明，这种最大熵效应如下： 几乎任何突变机制的动力学结果， 结合了对低复杂性的偏见，例如， 在人类中观察到的替代突变的邻居依赖性偏倚 基因突变 B。中程复杂性分布的羽状结构：DNA 长度范围为40至200个核苷酸的片段具有以下分布： 具有新颖的结构规则性的成分复杂性 （“羽化”）。 这还没有完全解释，但部分取决于 组合约束和部分上的非均匀表示 不同的复杂性类别。 项目意义：该项目开始提供详细的 对统计数据中发现的一些令人困惑的特征的解释 DNA序列的分析，包括所谓的“长 距离相关性”由其他研究小组从光谱 分析.

DNA sequences show enormous statistical heterogeneity in their local compositional characteristics. This project is investigating the possible causes of the mosaicism in sequence complexity, particularly the roles of mutational biases, medium and long range combinatorial constraints, and correlates of specific functional and structural classes of sequence. A. Distributions of local complexity: Using formal definitions of local compositional complexity of DNA subsequences, the robustness of the Salamon/Konopka maximum entropy relationship has been explored: Given a functionally equivalent set of DNA sequences, the distribution of complexity among all subsequences of this set appears to be as random as possible consistent with the mean complexity of these subsequences. It has now been shown that this maximum entropy effect follows as a consequence of the dynamics of almost any mutational mechanism that incorporates a bias toward low-complexity, for example the neighbor-dependent biases in substitution mutations observed in human genomic mutations. B. Feathered structure of medium range complexity distributions: DNA segments of length range 40 to 200 nucleotides have distributions of compositional complexity with a novel regularity of structure ("feathering"). This is not yet fully explained but depends partly on combinatorial constraints and partly on the nonuniform representation of different complexity classes in natural DNA sequences. Significance of project: The project is beginning to provide detailed explanations for some of the puzzling features found from statistical analyses of DNA sequences, including aspects of the so-called "long range correlations" inferred by other research groups from spectral analysis.