High-Throughput Identification of Adaptive Mutations in Experimentally Evolved Yeast Populations.
High-Throughput Identification of Adaptive Mutations in Experimentally Evolved Yeast Populations.
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DOI：
10.1371/journal.pgen.1006339
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发表时间：
2016-10
期刊：
影响因子：
4.5
通讯作者：
Dunham MJ
中科院分区：
文献类型：
--
作者：
Payen C;Sunshine AB;Ong GT;Pogachar JL;Zhao W;Dunham MJ
高通量测序使基因筛选成为可能，可以快速识别实验进化过程中发生的突变。然而，鉴于众所周知且普遍存在的遗传搭便车现象，进化谱系中突变的存在并不构成突变具有适应性的证据，其中非适应性甚至有害突变可以在基因组中共存。有益突变和组合的基因型通过选择而达到高频率。我们使用一组单基因缺失和几乎所有基因的扩增来近似酿酒酵母中可能的有益突变谱。酿酒酵母基因组我们确定了每个突变的健身效果在三个不同的营养有限的条件下，使用合并的竞争，然后通过条形码测序。虽然大多数突变是中性或有害的，但其中约500个增加了适应性。然后，我们将这些结果与在相同的三种营养限制条件下实验进化过程中实际发生的突变进行了比较。平均而言，在实验进化过程中发生的约35%的突变被系统筛选预测为有益的。我们发现，适合度效应的分布依赖于选择条件。在磷限制和糖限制条件下，大量的有益突变几乎等同，小的影响推动了适合度的增加。在硫酸盐限制条件下，一种类型的突变，高亲和力硫酸盐转运蛋白的扩增，占主导地位。在没有这种突变的情况下，硫酸盐限制条件下的进化涉及其他基因的突变，这些基因以前没有观察到，但通过系统筛选预测到了。因此，粗略的功能筛选有可能预测和识别实验进化过程中发生的适应性突变。实验进化使我们能够在真实的时间里观察进化。基因组测序的新进展使得发现进化文化中出现的突变变得微不足道;然而，将这些突变与特定的适应性特征联系起来仍然很困难。我们评估了酵母中数千个单基因丢失和扩增的适应性影响。我们发现，在之前进行的进化实验中，实际上只检测到了数百种可能的有益突变中的一小部分。我们的研究结果提供的证据表明，35%的实验进化群体中确定的突变是有利的，有益的健身效果的分布取决于遗传背景和选择条件。此外，我们表明，有可能选择替代突变，通过阻断特别高适应性的适应途径来提高适应性。
High-throughput sequencing has enabled genetic screens that can rapidly identify mutations that occur during experimental evolution. The presence of a mutation in an evolved lineage does not, however, constitute proof that the mutation is adaptive, given the well-known and widespread phenomenon of genetic hitchhiking, in which a non-adaptive or even detrimental mutation can co-occur in a genome with a beneficial mutation and the combined genotype is carried to high frequency by selection. We approximated the spectrum of possible beneficial mutations in Saccharomyces cerevisiae using sets of single-gene deletions and amplifications of almost all the genes in the S. cerevisiae genome. We determined the fitness effects of each mutation in three different nutrient-limited conditions using pooled competitions followed by barcode sequencing. Although most of the mutations were neutral or deleterious, ~500 of them increased fitness. We then compared those results to the mutations that actually occurred during experimental evolution in the same three nutrient-limited conditions. On average, ~35% of the mutations that occurred during experimental evolution were predicted by the systematic screen to be beneficial. We found that the distribution of fitness effects depended on the selective conditions. In the phosphate-limited and glucose-limited conditions, a large number of beneficial mutations of nearly equivalent, small effects drove the fitness increases. In the sulfate-limited condition, one type of mutation, the amplification of the high-affinity sulfate transporter, dominated. In the absence of that mutation, evolution in the sulfate-limited condition involved mutations in other genes that were not observed previously—but were predicted by the systematic screen. Thus, gross functional screens have the potential to predict and identify adaptive mutations that occur during experimental evolution. Experimental evolution allows us to observe evolution in real time. New advances in genome sequencing make it trivial to discover the mutations that have arisen in evolved cultures; however, linking those mutations to particular adaptive traits remains difficult. We evaluated the fitness impacts of thousands of single-gene losses and amplifications in yeast. We discovered that only a fraction of the hundreds of possible beneficial mutations were actually detected in evolution experiments performed previously. Our results provide evidence that 35% of the mutations identified in experimentally evolved populations are advantageous and that the distribution of beneficial fitness effects depends on the genetic background and the selective conditions. Furthermore, we show that it is possible to select for alternative mutations that improve fitness by blocking particularly high-fitness routes to adaptation.
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14.9
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Gonzalez-Perez A;Lopez-Bigas N
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