It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

中文翻译：

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图1理论与图2进行基因表达研究的实验相遇。

令人信服的是，我们现在拥有基因组。随意读取和重写它的能力已经在科学史上迎来了一个辉煌的时期。但是，所有已积累的基因组数据都暴露出致命弱点：我们仍然不知道如何解释它们。许多基因受到复杂的转录调节程序的控制，这些程序由带有转录因子结合位点的DNA序列介导，DNA结合位点可以根据环境条件上调或下调基因表达。这产生了输入-输出功能，该功能描述了表达水平如何取决于被调节基因的参数，例如，取决于其调节序列中结合位点的数量和类型。近年来，可以对表情进行精确的测量，加上做出越来越复杂的理论预测的能力，使得理论与实验之间可以进行明确的对话，从而有望涵盖这一基因组的致命弱点。目的是达成对转录调控的预测性理解，使从DNA调控序列计算基因表达水平成为可能。这篇评论集中在规范的简单压抑主题上，以询问用来表征它的模型的实际效果如何。我们考虑了越来越复杂的实验的层次结构，其中将在一个级别上学习的最小参数集应用于下一个级别进行定量预测。