Genome-wide identification of natural RNA aptamers in prokaryotes and eukaryotes

Abstract

RNAs are well-suited to act as cellular sensors that detect and respond to metabolite changes in the environment, due to their ability to fold into complex structures. Here, we introduce a genome-wide strategy called PARCEL that experimentally identifies RNA aptamers in vitro, in a high-throughput manner. By applying PARCEL to a collection of prokaryotic and eukaryotic organisms, we have revealed 58 new RNA aptamers to three key metabolites, greatly expanding the list of natural RNA aptamers. The newly identified RNA aptamers exhibit significant sequence conservation, are highly structured and show an unexpected prevalence in coding regions. We identified a prokaryotic precursor tmRNA that binds vitamin B2 (FMN) to facilitate its maturation, as well as eukaryotic mRNAs that bind and respond to FMN, suggesting FMN as the second RNA-binding ligand to affect eukaryotic expression. PARCEL results show that RNA-based sensing and gene regulation is more widespread than previously appreciated in different organisms.

dStruct: identifying differentially reactive regions from RNA structurome profiling data

“…We observed a consistently high FDR (∼ 82%) and low detection power (< 1%). PARCEL's poor performance could be attributed to the fact that it was designed to work in conjunction with a specific SP technology [21]. As such, it does not consider untreated samples or coverage variations across a transcript, which are important issues in transcriptome-wide data from most technologies [6,30] (see Additional file 1: Section S2 for a detailed overview of PARCEL and its limitations).…”

“…In fact, recent developments have led to a diversity of structure probing or structure profiling (SP) technologies [4,5]. These technologies have made it possible to perform comparative analysis of structures of select RNAs or whole RNA structuromes simultaneously [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21].…”

“…Several methods have been developed for differential analysis of SP data [8,9,20,21,35]. They utilize two common principles.…”

“…To this end, it uses edgeR [36] to account for nucleotide-level noise and compute p values for changes in counts. Next, it chains together nucleotides with significant changes as DRRs by performing a second statistical test [21] (henceforth, we refer to this method as PARCEL). Similarly, Mizrahi et al account for nucleotide-level noise with a two-step "regression and spatial analysis" approach [20] (for convenience, we acronymize this method as RASA).…”

Engineering Cellular Signal Sensors based on CRISPR-sgRNA Reconstruction Approaches

“…These riboswitches typically contain a domain structure of aptamers, which show high specificity and affinity with the relative ligands (Figure 2 A and B). There are many aptamers that have been discovered in plants, bacteria, and fungi, which show the ability to bind specific molecules selectively and tightly, and regulate the expression of the downstream genes [31]. In natural riboswitches, nucleotide sequences that specifically bind to ligands within the aptamer domain tend to be evolutionarily conserved, and when the ligand is mutated, the nucleotide sequence can also undergo a corresponding change in specificity.…”