Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift
Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift
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DOI：
10.1073/pnas.1016719108
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发表时间：
2011-06-21
影响因子：
11.1
通讯作者：
Gilchrist, Michael A.
中科院分区：
文献类型：
--
作者：
Shah, Premal;Gilchrist, Michael A.
遗传密码是冗余的，大多数氨基酸使用多个密码子。在许多生物体中，密码子的使用偏向于特定的密码子。理解驱动密码子使用偏好（CUB）进化的适应性和非适应性力量一直是分子生物学和进化生物学领域的一个激烈关注和争论的领域。然而，它们在形成CUB基因组模式中的相对重要性仍然没有解决。使用蛋白质翻译和群体遗传学的嵌套模型，我们发现，观察到的基因水平的变化，CUB在酿酒酵母几乎可以完全解释为选择有效的核糖体利用，遗传漂变，偏置突变。在单个基因内观察到的密码子计数与我们的模型预测之间的相关性为0.96。虽然各种因素的形状模式的CUB在基因内的单个位点的水平，我们的研究结果表明，选择有效的核糖体的使用是一个核心力量，在基因组规模塑造密码子的使用。此外，我们的模型允许直接估计密码子特异性突变率和延伸时间，并且可以很容易地应用于具有高通量表达数据集的任何生物体。更一般地说，我们已经开发了一个自然的框架，将分子过程模型整合到群体遗传学模型中，以定量估计基本生物过程（如蛋白质翻译）的参数。
The genetic code is redundant with most amino acids using multiple codons. In many organisms, codon usage is biased toward particular codons. Understanding the adaptive and nonadaptive forces driving the evolution of codon usage bias (CUB) has been an area of intense focus and debate in the fields of molecular and evolutionary biology. However, their relative importance in shaping genomic patterns of CUB remains unsolved. Using a nested model of protein translation and population genetics, we show that observed gene level variation of CUB in Saccharomyces cerevisiae can be explained almost entirely by selection for efficient ribosomal usage, genetic drift, and biased mutation. The correlation between observed codon counts within individual genes and our model predictions is 0.96. Although a variety of factors shape patterns of CUB at the level of individual sites within genes, our results suggest that selection for efficient ribosome usage is a central force in shaping codon usage at the genomic scale. In addition, our model allows direct estimation of codon-specific mutation rates and elongation times and can be readily applied to any organism with high-throughput expression datasets. More generally, we have developed a natural framework for integrating models of molecular processes to population genetics models to quantitatively estimate parameters underlying fundamental biological processes, such a protein translation.