Ferretti Luca, Schmiegelt Benjamin, Weinreich Daniel, Yamauchi Atsushi, Kobayashi Yutaka, Tajima Fumio, Achaz Guillaume
Evolution Paris-Seine (UMR 7138) and Atelier de Bio-Informatique, UPMC, Paris, France; SMILE, CIRB (UMR 7241), Collège de France, Paris, France; The Pirbright Institute, Woking, United Kingdom.
Institute for Theoretical Physics, University of Cologne, Germany.
J Theor Biol. 2016 May 7;396:132-43. doi: 10.1016/j.jtbi.2016.01.037. Epub 2016 Feb 20.
Genotypic fitness landscapes are constructed by assessing the fitness of all possible combinations of a given number of mutations. In the last years, several experimental fitness landscapes have been completely resolved. As fitness landscapes are high-dimensional, simple measures of their structure are used as statistics in empirical applications. Epistasis is one of the most relevant features of fitness landscapes. Here we propose a new natural measure of the amount of epistasis based on the correlation of fitness effects of mutations. This measure has a natural interpretation, captures well the interaction between mutations and can be obtained analytically for most landscape models. We discuss how this measure is related to previous measures of epistasis (number of peaks, roughness/slope, fraction of sign epistasis, Fourier-Walsh spectrum) and how it can be easily extended to landscapes with missing data or with fitness ranks only. Furthermore, the dependence of the correlation of fitness effects on mutational distance contains interesting information about the patterns of epistasis. This dependence can be used to uncover the amount and nature of epistatic interactions in a landscape or to discriminate between different landscape models.
基因型适应度景观是通过评估给定数量突变的所有可能组合的适应度来构建的。在过去几年中，几个实验性适应度景观已被完全解析。由于适应度景观是高维的，其结构的简单度量在实证应用中被用作统计量。上位性是适应度景观最相关的特征之一。在此，我们基于突变适应度效应的相关性提出一种新的上位性数量自然度量。该度量具有自然的解释，能很好地捕捉突变之间的相互作用，并且对于大多数景观模型都可以通过解析得到。我们讨论了这种度量与先前的上位性度量（峰的数量、粗糙度/斜率、符号上位性分数、傅里叶 - 沃尔什谱）的关系，以及它如何能够轻松扩展到存在缺失数据或仅有适应度排名的景观。此外，适应度效应相关性对突变距离的依赖性包含了关于上位性模式的有趣信息。这种依赖性可用于揭示景观中上位性相互作用的数量和性质，或区分不同的景观模型。
