Liberman Gilad, Benichou Jennifer I C, Maman Yaakov, Glanville Jacob, Alter Idan, Louzoun Yoram
Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat-Gan 5290002, Israel.
Department of Mathematics, Bar Ilan University, Ramat-Gan 5290002, Israel.
Nucleic Acids Res. 2016 Mar 18;44(5):e46. doi: 10.1093/nar/gkv1198. Epub 2015 Nov 19.
Incremental selection within a population, defined as limited fitness changes following mutation, is an important aspect of many evolutionary processes. Strongly advantageous or deleterious mutations are detected using the synonymous to non-synonymous mutations ratio. However, there are currently no precise methods to estimate incremental selection. We here provide for the first time such a detailed method and show its precision in multiple cases of micro-evolution. The proposed method is a novel mixed lineage tree/sequence based method to detect within population selection as defined by the effect of mutations on the average number of offspring. Specifically, we propose to measure the log of the ratio between the number of leaves in lineage trees branches following synonymous and non-synonymous mutations. The method requires a high enough number of sequences, and a large enough number of independent mutations. It assumes that all mutations are independent events. It does not require of a baseline model and is practically not affected by sampling biases. We show the method's wide applicability by testing it on multiple cases of micro-evolution. We show that it can detect genes and inter-genic regions using the selection rate and detect selection pressures in viral proteins and in the immune response to pathogens.
群体内的增量选择，定义为突变后有限的适应性变化，是许多进化过程的一个重要方面。使用同义突变与非同义突变的比率来检测强有利或有害突变。然而，目前尚无精确方法来估计增量选择。我们在此首次提供了这样一种详细方法，并在多个微进化案例中展示了其精确性。所提出的方法是一种基于新颖的混合谱系树/序列的方法，用于检测群体内由突变对后代平均数量的影响所定义的选择。具体而言，我们提议测量同义突变和非同义突变后谱系树分支中叶子数量之比的对数。该方法需要足够多的序列和足够多的独立突变。它假定所有突变都是独立事件。它不需要基线模型，并且实际上不受抽样偏差的影响。我们通过在多个微进化案例上进行测试来展示该方法的广泛适用性。我们表明，它可以使用选择率检测基因和基因间区域，并检测病毒蛋白和对病原体免疫反应中的选择压力。
