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HIV-1在一项长期实验中的平行进化

Parallel Evolution of HIV-1 in a Long-Term Experiment.

作者信息

Bertels Frederic, Leemann Christine, Metzner Karin J, Regoes Roland R

机构信息

Department of Environmental Systems Sciences, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.

Department of Microbial Population Biology, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.

出版信息

Mol Biol Evol. 2019 Nov 1;36(11):2400-2414. doi: 10.1093/molbev/msz155.

Abstract

One of the most intriguing puzzles in biology is the degree to which evolution is repeatable. The repeatability of evolution, or parallel evolution, has been studied in a variety of model systems, but has rarely been investigated with clinically relevant viruses. To investigate parallel evolution of HIV-1, we passaged two replicate HIV-1 populations for almost 1 year in each of two human T-cell lines. For each of the four evolution lines, we determined the genetic composition of the viral population at nine time points by deep sequencing the entire genome. Mutations that were carried by the majority of the viral population accumulated continuously over 1 year in each evolution line. Many majority mutations appeared in more than one evolution line, that is, our experiments showed an extreme degree of parallel evolution. In one of the evolution lines, 62% of the majority mutations also occur in another line. The parallelism impairs our ability to reconstruct the evolutionary history by phylogenetic methods. We show that one can infer the correct phylogenetic topology by including minority mutations in our analysis. We also find that mutation diversity at the beginning of the experiment is predictive of the frequency of majority mutations at the end of the experiment.

摘要

生物学中最引人入胜的谜题之一是进化在多大程度上是可重复的。进化的可重复性,即平行进化,已在各种模型系统中得到研究,但很少在与临床相关的病毒中进行调查。为了研究HIV-1的平行进化,我们在两个人类T细胞系中分别传代两个重复的HIV-1群体近1年。对于这四个进化系中的每一个,我们通过对整个基因组进行深度测序,在九个时间点确定了病毒群体的遗传组成。在每个进化系中,大多数病毒群体携带的突变在1年的时间里持续积累。许多多数突变出现在不止一个进化系中,也就是说,我们的实验显示出了极高程度的平行进化。在其中一个进化系中,62%的多数突变也出现在另一个系中。这种平行性损害了我们通过系统发育方法重建进化历史的能力。我们表明,通过在分析中纳入少数突变,可以推断出正确的系统发育拓扑结构。我们还发现,实验开始时的突变多样性可预测实验结束时多数突变的频率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c28/6805227/8e0babedbcd6/msz155f1.jpg

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