Quantitative analysis of RNA-protein interactions on a massively parallel array reveals biophysical and evolutionary landscapes

被引:149
|
作者
Buenrostro, Jason D. [1 ,4 ]
Araya, Carlos L. [1 ,4 ]
Chircus, Lauren M. [1 ,3 ]
Layton, Curtis J. [1 ]
Chang, Howard Y. [2 ]
Snyder, Michael P. [1 ]
Greenleaf, William J. [1 ]
机构
[1] Stanford Univ, Dept Genet, Sch Med, Stanford, CA 94305 USA
[2] Stanford Univ, Sch Med, Program Epithelial Biol, Stanford, CA 94305 USA
[3] Stanford Univ, Sch Med, Howard Hughes Med Inst, Stanford, CA 94305 USA
[4] Stanford Univ, Sch Med, Dept Chem & Syst Biol, Stanford, CA 94305 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
LONG NONCODING RNA; R17 COAT PROTEIN; SECONDARY STRUCTURE; BINDING; EPISTASIS; AFFINITY; SPECIFICITY; MUTATIONS; COMPLEXES; CHROMATIN;
D O I
10.1038/nbt.2880
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
RNA-protein interactions drive fundamental biological processes and are targets for molecular engineering, yet quantitative and comprehensive understanding of the sequence determinants of affinity remains limited. Here we repurpose a high-throughput sequencing instrument to quantitatively measure binding and dissociation of a fluorescently labeled protein to > 10(7) RNA targets generated on a flow cell surface by in situ transcription and intermolecular tethering of RNA to DNA. Studying the MS2 coat protein, we decompose the binding energy contributions from primary and secondary RNA structure, and observe that differences in affinity are often driven by sequence-specific changes in both association and dissociation rates. By analyzing the biophysical constraints and modeling mutational paths describing the molecular evolution of MS2 from low-to high-affinity hairpins, we quantify widespread molecular epistasis and a long-hypothesized, structure-dependent preference for G: U base pairs over C: A intermediates in evolutionary trajectories. Our results suggest that quantitative analysis of RNA on a massively parallel array (RNA-MaP) provides generalizable insight into the biophysical basis and evolutionary consequences of sequence-function relationships.
引用
收藏
页码:562 / +
页数:10
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