Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure

• DOI: 10.1261/rna.064469.117
• Publication Date: 2018-01-10T01:21:01Z
• Authors: Lela Lackey; Aaztli Coria; Chanin Woods; Evonne McArthur; Alain Laederach
• Keywords: 0301 basic medicine; RNA Folding; Base Sequence; Microfilament Proteins; Genetic Variation; High-Throughput Nucleotide Sequencing; RNA-Binding Proteins; Tumor Protein, Translationally-Controlled 1; Polymorphism, Single Nucleotide; Article; Cell Line; 03 medical and health sciences; HEK293 Cells; Databases, Genetic; Biomarkers, Tumor; Humans; Thermodynamics; RNA, Messenger; Alleles

The impact of inherited and somatic mutations on messenger RNA (mRNA) structure remains poorly understood. Recent technological advances that leverage next-generation sequencing to obtain experimental structure data, such as SHAPE-MaP, can reveal structural effects of mutations, especially when these data are incorporated into structure modeling. Here, we analyze the ability of SHAPE-MaP to detect the relatively subtle structural changes caused by single-nucleotide mutations. We find that allele-specific sorting greatly improved our detection ability. Thus, we used SHAPE-MaP with a novel combination of clone-free robotic mutagenesis and allele-specific sorting to perform a rapid, comprehensive survey of noncoding somatic and inherited riboSNitches in two cancer-associated mRNAs,TPT1andLCP1. Using rigorous thermodynamic modeling of the Boltzmann suboptimal ensemble, we identified a subset of mutations that changeTPT1andLCP1RNA structure, with approximately 14% of all variants identified as riboSNitches. To confirm that these in vitro structures were biologically relevant, we tested how dependentTPT1andLCP1mRNA structures were on their environments. We performed SHAPE-MaP onTPT1andLCP1mRNAs in the presence or absence of cellular proteins and found that both mRNAs have similar overall folds in all conditions. RiboSNitches identified within these mRNAs in vitro likely exist under biological conditions. Overall, these data reveal a robust mRNA structural landscape where differences in environmental conditions and most sequence variants do not significantly alter RNA structural ensembles. Finally, predicting riboSNitches in mRNAs from sequence alone remains particularly challenging; these data will provide the community with benchmarks for further algorithmic development.