An impending acceleration of RNA discoveries

Jul

An impending acceleration of RNA discoveries

Ribonucleic acid (RNA) design offers unique opportunities for engineering genetic networks and nanostructures that self-assemble within living cells. Recent years have seen the creation of increasingly complex RNA devices, including proof-of-concept applications for in vivo three-dimensional scaffolding, imaging, computing, and control of biological behaviors. Expert intuition and simple design rules-the stability of double helices, the modularity of noncanonical RNA motifs, and geometric closure-have enabled these successful applications.

Going beyond heuristics, emerging algorithms may enable automated design of RNAs with nucleotide-level accuracy but, as illustrated on a recent RNA square design, are not yet fully predictive. Looking ahead, technological advances in RNA synthesis and interrogation are poised to radically accelerate the discovery and stringent testing of design methods.

Perspective: an impending acceleration

In recent years, RNA designers have leveraged simple rules for secondary structure formation, the modularity of small RNA motifs, and three-dimensional closure to produce devices and nanostructures of growing complexity.

It is particularly exciting to see these designs deployed into biological systems, suggesting future routes to biomedical devices that sense and perhaps correct cellular dysfunction. We are optimistic about the development of more quantitative and predictive theories for RNA structure design and eventually RNA functional design due to the explosion of RNA data expected in upcoming years.

The cycle of RNA design and testing can be short, especially compared to protein engineering — arbitrary RNA sequences up to hundreds of nucleotides in length are experimentally straightforward to synthesize, purify, interrogate, and evolve on the timescale of days. Current technologies offer the parallel synthesis of thousands of arbitrary DNA templates (Figure 4a and b), which can be transcribed into RNA in vitro and, in principle, in vivo (Figure 4c). Further, multiplexed single-nucleotide- resolution chemical mapping and elegant selection strategies can provide information-rich data on all of these molecules’ structures and functions, using deep-sequencing platforms with turn-around times of hours (Figure 4d). The key challenges will then be to distribute and accurately analyze these data, to update RNA modeling algorithms, and to feed back these insights into the next rounds of synthesis and mapping.