Purifying (negative) natural selection is a hallmark of functional biological sequences, and can be detected in protein-coding genes using the ratio of nonsynonymous to synonymous substitutions per site (d_N/d_S). However, when two genes overlap the same nucleotide sites in different frames, synonymous changes in one gene may be nonsynonymous in the other, perturbing d_N/d_S. Thus, scalable methods are needed to estimate functional constraint specifically for overlapping genes (OLGs). We propose OLGenie, which implements a modification of the Wei–Zhang method. Assessment with simulations and controls from viral genomes (58 OLGs and 176 non-OLGs) demonstrates low false-positive rates and good discriminatory ability in differentiating true OLGs from non-OLGs. We also apply OLGenie to the unresolved case of HIV-1’s putative antisense protein gene, showing significant purifying selection. OLGenie can be used to study known OLGs and to predict new OLGs in genome annotation. Software and example data are freely available at https://github.com/chasewnelson/OLGenie (last accessed April 10, 2020).

中文翻译：

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OLGenie：估计自然选择以预测功能重叠的基因。

纯化（阴性）自然选择是功能性生物学序列的标志，可以使用每个位点的非同义替换与同义替换的比率（d _N / d _S）在蛋白质编码基因中进行检测。但是，当两个基因在不同框架中重叠相同核苷酸位点时，一个基因中的同义变化可能在另一个基因中不同义，从而扰乱了d _N / d _S。因此，需要可扩展的方法来估计专门针对重叠基因（OLG）的功能约束。我们提出了OLGenie，它实现了对Wei-Zhang方法的修改。用病毒基因组（58个OLG和176个非OLG）的模拟和对照进行评估表明，在将真正的OLG与非OLG区别开来时，假阳性率低且具有良好的区分能力。我们还将OLGenie应用于未解决的HIV-1推定反义蛋白基因案例，显示出重要的纯化选择。OLGenie可用于研究已知的OLG，并预测基因组注释中的新OLG。软件和示例数据可从https://github.com/chasewnelson/OLGenie免费获得（最新访问时间为2020年4月10日）。