What is SHAPE and Why is it Important?

As our understanding of RNA biology increases, so do the number of functions and interactions RNA is shown to have. Coding and non-coding RNAs play a variety of roles in cells, and the structure of the RNA can be pivotal in defining and enabling these functions. Thus, the ability to probe RNA structure is critical in understanding these myriad cellular interactions. SHAPE is a method of accurately and reproducibly measuring RNA secondary structure.

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In this technique, NAI binds to free 2’-hydroxyl groups on the RNA molecule’s backbone, forming adducts with flexible, or unpaired, nucleotides. During reverse transcription, these adducts induce cDNA mutations, which are used to calculate mutation rates per nucleotide per sample. Comparing the mutation rates for each base in the NAI treated sample with a control sample allows for the calculation of reactivity scores that highlight paired and unpaired RNA bases. These analyses provide detailed insights into RNA secondary structures, information that can enable drug discovery, synthetic RNA engineering, identification of novel RNA misfolding events, and more.

SHAPE measures RNA flexibility at single nucleotide resolution in both cellular conditions (in cellulo) and purified, deproteinized RNA (in vitro). In vitro SHAPE reveals flexibility across an RNA strand. In cellulo shows flexibility in regions not bound by proteins, which can help predict RNA’s secondary structure. Combining in cellulo and in vitro mutation rates, another method called ΔSHAPE (delta SHAPE), can identify which RNA positions interact with proteins.

Ultimately, SHAPE is a complex assay that is used to interrogate RNA structure. In practice, the elucidation of RNA structure through SHAPE can play a key role in advancing therapeutic research. Let’s explore a few examples.

Long non-coding RNAs, or lncRNAs, play a variety of roles in cancer, where they can function as enhancer RNAs, decoys, and scaffolds, in addition to other roles in cross-talk and transcriptional regulation. One gene that has been shown to repress metastasis and tumor suppressor genes is called HOX transcript antisense intergenic RNA, commonly known as HOTAIR. This is a widely studied lncRNA that is known to interact with LSD1 and PRC2. These interactions are involved with cancer metastasis and thus present a potential therapeutic target, though drug development around this interaction would be aided by a thorough understanding of these interactions. By utilizing SHAPE, research has shown that the secondary structure of HOTAIR is a key factor in its interactions with LSD1 and PRC2.

Alzheimer’s Disease (AD) research is another area in which SHAPE is advancing therapeutic opportunity. According to the CDC, Alzheimer’s affected over 6 million Americans in 2021, and this number is expected to reach 14 million by 2060. APP, or Alzheimer precursor protein, is one of the progressors of AD. The translation of this protein is accelerated by the influx of Iron, and as a result, metal chelation is one of the therapeutic strategies for AD treatment. Research has utilized SHAPE to elucidate the structure of an RNA element that binds to an iron-responsive element (IRE), enabling the translation of APP, and thus the progression of the disease. This structural element, now mapped because of SHAPE, presents a potential therapeutic target for AD treatment.

The information provided by SHAPE is clearly instrumental in progressing our understanding of RNA biology and opening doors to drug development for widespread diseases. One remaining barrier for the researcher, however, is the burden of difficulty, time, and cost associated with approaching SHAPE.

While labs can perform SHAPE assays using published methods in literature, there are challenges that this approach presents. The uncertain consistency and reliability of DIY reagent preparation can introduce variability in the assay’s performance. Furthermore, there can be high barriers to entry in terms of sequencing cost. In the world of SHAPE, more is better when it comes to read depth, and as a result, sequencing costs can become astronomical when performing SHAPE experiments. And while individual SHAPE experiments themselves can be costly, to obtain ΔSHAPE data, one must run both the in cellulo and in vitro SHAPE experiments, followed by extensive bioinformatic analysis. To help researchers break through these barriers, Eclipsebio now offers a solution.

Recently, Eclipsebio performed a comprehensive SHAPE on K562 cells, a commonly used leukemia cancer cell line. The result was SHAPE db-K562, a deep sequencing database containing in cellulo, in vitro and ΔSHAPE data for all K562 transcripts. SHAPE db-K562 is delivered as a data package for a gene or genes of interest. This database enables the researcher to dive into data now, without having to prepare, optimize, perform, and analyze a SHAPE experiment of their own.

This K562 database is only the first example of Eclipsebio’s SHAPE database product family, which is going to see continued expansion. Our team committed extensive time and effort to optimize the pipeline, count and compare mutations, and produce the reactivity values that indicate the flexibility of a specific nucleotide, all of which produce data that can be translated into RNA fold diagrams.

Eclipsebio is continuously designing refined RNA technologies with the intent of accelerating research. In the case of SHAPE, Eclipse has done the heavy lifting by providing a deeply sequenced database with extensive and intricate analytics. Eclipse’s team of experts has made SHAPE data easily accessible, enabling faster breakthroughs and expediting discovery.