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Unlocking a signal of introgression from codons in Lachancea kluyveri using a mutation-selection model.
BMC Evolutionary Biology ( IF 3.4 ) Pub Date : 2020-08-26 , DOI: 10.1186/s12862-020-01649-w
Cedric Landerer 1, 2, 3 , Brian C O'Meara 1, 2 , Russell Zaretzki 2, 4 , Michael A Gilchrist 1, 2
Affiliation  

For decades, codon usage has been used as a measure of adaptation for translational efficiency and translation accuracy of a gene’s coding sequence. These patterns of codon usage reflect both the selective and mutational environment in which the coding sequences evolved. Over this same period, gene transfer between lineages has become widely recognized as an important biological phenomenon. Nevertheless, most studies of codon usage implicitly assume that all genes within a genome evolved under the same selective and mutational environment, an assumption violated when introgression occurs. In order to better understand the effects of introgression on codon usage patterns and vice versa, we examine the patterns of codon usage in Lachancea kluyveri, a yeast which has experienced a large introgression. We quantify the effects of mutation bias and selection for translation efficiency on the codon usage pattern of the endogenous and introgressed exogenous genes using a Bayesian mixture model, ROC SEMPPR, which is built on mechanistic assumptions about protein synthesis and grounded in population genetics. We find substantial differences in codon usage between the endogenous and exogenous genes, and show that these differences can be largely attributed to differences in mutation bias favoring A/T ending codons in the endogenous genes while favoring C/G ending codons in the exogenous genes. Recognizing the two different signatures of mutation bias and selection improves our ability to predict protein synthesis rate by 42% and allowed us to accurately assess the decaying signal of endogenous codon mutation and preferences. In addition, using our estimates of mutation bias and selection, we identify Eremothecium gossypii as the closest relative to the exogenous genes, providing an alternative hypothesis about the origin of the exogenous genes, estimate that the introgression occurred ∼6×108 generation ago, and estimate its historic and current selection against mismatched codon usage. Our work illustrates how mechanistic, population genetic models like ROC SEMPPR can separate the effects of mutation and selection on codon usage and provide quantitative estimates from sequence data.

中文翻译:

使用突变选择模型,从Lachancea kluyveri的密码子中获得渗入信号。

几十年来,密码子使用已被用作适应性度量,以适应​​基因编码序列的翻译效率和翻译准确性。这些密码子使用方式反映了编码序列在其中进化的选择性和突变环境。在同一时期,谱系之间的基因转移已被广泛认为是重要的生物学现象。尽管如此,大多数密码子使用的研究都隐含地假设基因组内的所有基因都是在相同的选择性和突变环境下进化的,这种渗入发生时就违反了这一假设。为了更好地了解基因渗入对密码子使用方式的影响,反之亦然,我们研究了Lachancea kluyveri(一种经历了较大渗入度的酵母)中密码子使用方式。我们使用基于蛋白质合成的机械假设并基于种群遗传学的贝叶斯混合模型ROC SEMPPR来量化突变偏倚和翻译效率选择对内源和渗入外源基因密码子使用模式的影响。我们发现内源性基因与外源性基因之间的密码子使用存在实质性差异,并且表明这些差异可以很大程度上归因于突变偏倚的差异,有利于内源性基因中的A / T终止密码子,而有利于外源性基因中的C / G终止密码子。认识到突变偏向和选择的两个不同特征,使我们预测蛋白质合成率的能力提高了42%,并使我们能够准确评估内源密码子突变和偏好的衰减信号。此外,使用我们对突变偏倚和选择的估计,我们将棉球毛虫确定为与外源基因最接近的亲缘种,提供了关于外源基因起源的另一种假设,估计了基因渗入发生在大约6×108代之前,并估计了其历史和当前针对密码子使用不匹配的选择。我们的工作说明了机械的群体遗传模型(例如ROC SEMPPR)如何分离突变和选择对密码子使用的影响,并提供来自序列数据的定量估计。并针对不匹配的密码子使用情况估算其历史和当前选择。我们的工作说明了机械的群体遗传模型(如ROC SEMPPR)如何分离突变和选择对密码子使用的影响,并提供来自序列数据的定量估计。并针对不匹配的密码子使用情况估算其历史和当前选择。我们的工作说明了机械的群体遗传模型(例如ROC SEMPPR)如何分离突变和选择对密码子使用的影响,并提供来自序列数据的定量估计。
更新日期:2020-08-26
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