Department of Genetics, Stanford University.
Mol Biol Evol. 2013 Nov;30(11):2509-18. doi: 10.1093/molbev/mst134. Epub 2013 Jul 30.
Measuring natural selection on genomic elements involved in the cis-regulation of gene expression--such as transcriptional enhancers and promoters--is critical for understanding the evolution of genomes, yet it remains a major challenge. Many studies have attempted to detect positive or negative selection in these noncoding elements by searching for those with the fastest or slowest rates of evolution, but this can be problematic. Here, we introduce a new approach to this issue, and demonstrate its utility on three mammalian transcriptional enhancers. Using results from saturation mutagenesis studies of these enhancers, we classified all possible point mutations as upregulating, downregulating, or silent, and determined which of these mutations have occurred on each branch of a phylogeny. Applying a framework analogous to Ka/Ks in protein-coding genes, we measured the strength of selection on upregulating and downregulating mutations, in specific branches as well as entire phylogenies. We discovered distinct modes of selection acting on different enhancers: although all three have experienced negative selection against downregulating mutations, the selection pressures on upregulating mutations vary. In one case, we detected positive selection for upregulation, whereas the other two had no detectable selection on upregulating mutations. Our methodology is applicable to the growing number of saturation mutagenesis data sets, and provides a detailed picture of the mode and strength of natural selection acting on cis-regulatory elements.
衡量参与基因表达顺式调控的基因组元件（如转录增强子和启动子）自然选择的力度对于理解基因组的演化至关重要，但这仍然是一个主要挑战。许多研究试图通过搜索进化最快或最慢的非编码元件来检测这些元件中的正选择或负选择，但这可能会有问题。在这里，我们引入了一种解决这个问题的新方法，并在三个哺乳动物转录增强子上展示了它的实用性。利用这些增强子的饱和诱变研究结果，我们将所有可能的点突变分类为上调、下调或沉默，并确定在系统发育的每个分支上发生了哪些突变。应用类似于蛋白质编码基因中的 Ka/Ks 的框架，我们衡量了在特定分支和整个系统发育中上调和下调突变的选择强度。我们发现不同的增强子受到不同选择模式的影响：尽管这三个增强子都经历了针对下调突变的负选择，但对上调突变的选择压力不同。在一种情况下，我们检测到了上调的正选择，而另外两种情况则没有检测到上调突变的选择。我们的方法适用于越来越多的饱和诱变数据集，提供了顺式调控元件自然选择的模式和力度的详细图片。
