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遗传上位性的进化足迹。

Evolutionary footprint of epistasis.

机构信息

Sorbonne Université, Institute de Biologie Paris-Seine, Laboratoire de Biologie Computationelle et Quantitative, Paris, France.

出版信息

PLoS Comput Biol. 2018 Sep 17;14(9):e1006426. doi: 10.1371/journal.pcbi.1006426. eCollection 2018 Sep.

Abstract

Variation of an inherited trait across a population cannot be explained by additive contributions of relevant genes, due to epigenetic effects and biochemical interactions (epistasis). Detecting epistasis in genomic data still represents a significant challenge that requires a better understanding of epistasis from the mechanistic point of view. Using a standard Wright-Fisher model of bi-allelic asexual population, we study how compensatory epistasis affects the process of adaptation. The main result is a universal relationship between four haplotype frequencies of a single site pair in a genome, which depends only on the epistasis strength of the pair defined regarding Darwinian fitness. We demonstrate the existence, at any time point, of a quasi-equilibrium between epistasis and disorder (entropy) caused by random genetic drift and mutation. We verify the accuracy of these analytic results by Monte-Carlo simulation over a broad range of parameters, including the topology of the interacting network. Thus, epistasis assists the evolutionary transit through evolutionary hurdles leaving marks at the level of haplotype disequilibrium. The method allows determining selection coefficient for each site and the epistasis strength of each pair from a sequence set. The resulting ability to detect clusters of deleterious mutation close to full compensation is essential for biomedical applications. These findings help to understand the role of epistasis in multiple compensatory mutations in viral resistance to antivirals and immune response.

摘要

遗传性状在群体中的变异不能用相关基因的加性贡献来解释,这是由于表观遗传效应和生化相互作用(上位性)的影响。在基因组数据中检测上位性仍然是一个重大挑战,需要从机制的角度更好地理解上位性。我们使用二倍体无性种群的标准 Wright-Fisher 模型,研究补偿性上位性如何影响适应过程。主要结果是基因组中单一位点对的四个单倍型频率之间的普遍关系,该关系仅取决于关于达尔文适合度的该对的上位性强度来定义。我们证明了在任何时间点,由随机遗传漂变和突变引起的上位性和无序(熵)之间存在准平衡。我们通过广泛的参数(包括相互作用网络的拓扑结构)的蒙特卡罗模拟验证了这些分析结果的准确性。因此,上位性通过在单倍型不平衡水平上留下痕迹来协助进化过渡通过进化障碍。该方法允许从序列集中确定每个位点的选择系数和每个对的上位性强度。因此,检测接近完全补偿的有害突变簇的能力对于生物医学应用至关重要。这些发现有助于理解上位性在抗病毒药物和免疫反应中病毒耐药性的多个补偿性突变中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c7c/6177197/db47b0968cac/pcbi.1006426.g001.jpg

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