RNA-ligand interactions play important roles in biology and biotechnology, but they often involve complex three-dimensional folding of RNA and are difficult to predict. To systematically explore the phenotypic landscape of an RNA-ligand complex, we used microarrays to investigate all possible single and double mutants of the 49-nt RNA aptamer Broccoli bound to the fluorophore DFHBI-1T. We collected more than seven million fluorescence measurements in varying conditions, and inferred dissociation rate constants, spectral shifts, and intragenic epistasis. Our results reveal an unexpectedly complex phenotypic landscape, in which mutations near the fluorophore binding pocket modulated magnesium-, potassium- and fluorophore-binding and fluorescence spectra, while distal mutations influenced structural stability and fluorescence intensity. We trained a machine learning model that accurately predicted RNA secondary structure from local epistatic interactions, despite the presence of G-quadruplexes and other noncanonical structures. Our experimental platform will facilitate the discovery and analysis of new RNA-ligand interactions.

中文翻译：

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RNA-配体复合物的基因型-表型图

RNA-配体相互作用在生物学和生物技术中起着重要作用，但它们通常涉及RNA的复杂三维折叠，并且难以预测。为了系统地探索RNA-配体复合物的表型格局，我们使用微阵列研究了与荧光团DFHBI-1T结合的49-nt RNA适体西兰花的所有可能的单突变和双突变。我们在不同条件下收集了超过700万个荧光测量值，并推论了解离速率常数，光谱偏移和基因内上位性。我们的结果揭示了一个意想不到的复杂表型景观，其中靠近荧光团结合的突变会调制镁，钾和荧光团的结合以及荧光光谱，而远端突变会影响结构稳定性和荧光强度。尽管存在G-四链体和其他非规范结构，我们训练了一种机器学习模型，该模型可从局部上位相互作用准确预测RNA二级结构。我们的实验平台将有助于发现和分析新的RNA-配体相互作用。