Study examines long-range RNA-RNA interactions of SARS-CoV-2

Study examines long-range RNA-RNA interactions of SARS-CoV-2

In a recently published study in the International Journal of Molecular Sciences Researchers examined RRIs [long-range ribonucleic acid (RNA)-RNA interactions] in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) genomes to assess evolutionary changes in SARS-CoV-2.

Studie: Variantenspezifische Analyse enthüllt eine neuartige RNA-RNA-Interaktion mit großer Reichweite in SARS-CoV-2 Orf1a. Bildnachweis: CROCOTHERY/Shutterstock

background

RRIs are essential to the life cycle of CoVs, and their detection can expand the understanding of the evolutionary characteristics of SARS-CoV-2 and potentially help predict emerging VOCs since SARS-CoV-2 is an RNA virus. Recent in vivo studies examining the RNA structure of SARS-CoV-2 have identified some long-term RRIs; However, further research is needed. Open reading frame 1a (Orf1a) and Orf1b (or Orf1ab) encode 16 nonstructural proteins involved in SARS-CoV-2 replication and transcription and are a source of variation in the SARS-CoV-2 genome.

About the study

In the present study, researchers assessed VOC-specific evolutionary changes in the SARS-CoV-2 genome based on long-term RRI assessments.

SARS-CoV-2 genome sequences (n=32,714) of Alpha VOC, Beta VOC, Delta VOC and Omicron VOC originating from 92 different nations were downloaded from the GISAID (Global Initiative on Sharing All Influenza Data) database. Eight long-range Orf1a and/or Orf1b RRIs were selected for analysis, four of which were experimentally validated (Exp) and obtained from the COMRADES experiment (Exp), and the remaining four were obtained from computational predictions (Comp) using the IntaRNA software.

Comp-RRIs were analyzed to investigate novel, long-range RRIs and the associated changes in SARS-CoV-2 evolution. In addition, the frame shifting element (FSE) was analyzed to evaluate the feature-specific evolution between VOCs. Mutation patterns within the sequences were first assessed across the genome and then using VOC. The structural changes of the RRI were evaluated by assessing VOC-specific compensatory mutations, conservation, and covarying mutations for each RRI.

Computational estimates were again performed using SHAPE information to make a more restricted estimate. Genome intervals were determined and the top five hits for each genome interval were recorded, after which interactions were ranked based on energy residues. Pairwise distances between VOC [the average number of differing bases for GISAID sequences] were calculated as a measure of dissimilarity.

No stem loops or pseudoknots were observed in the eight wide-span RRIs. To improve understanding of how SARS-CoV-2 RRIs are conserved independently of VOC, the average number of mutations per base for the sequences for all eight RRIs was compared. In addition, the mutations were categorized as compensatory or noncompensatory based on RNA base pair (bp) accommodation.

To investigate whether the RRIs had less/more variations or merely fall into the category of highly variable regions of the SARS-CoV-2 genome, the variations of the RRIs per base were compared with those of their neighboring regions [100 nucleotides (nt) upstream and downstream]. In addition, covariation analysis was performed and the sequences were grouped according to their corresponding VOCs to evaluate VOC-specific and VOC group-specific trends. To investigate whether the RRIs evolved VOC-specifically, VOC sequences were separated and further analyzed by R-scape analysis.

Results

Heterogeneous mutation rates and evolutionary patterns were observed across all RRI sites, indicating different evolutionary rates and constraints at different SARS-CoV-2 RNA sites. Exp1 and Exp4 showed a relatively high level of conservation, whereas Comp1 and Exp2 contained several compensatory mutations.

However, R-Scape statistical analyzes showed no significant covariations for any RRI, and there was no significance for the top 5 hits using the SHAPE constraint. No evidence of coevolution of the two regions of an RRI within the sequences was found. Omicron, the youngest VOC, showed the greatest sequence divergence and the highest mutation rate (2.5 × 10−6 per base per day) and Delta showed the lowest mutation rate (1.96 × 10−6).

Alpha VOCs and Beta VOCs have been found to be closer together than other VOCs. Comp4 had the highest number of structural mutations (twice as many as its neighboring regions, but the lowest percentage (~12%) of non-structural mutations due to an “identifying mutation” (Q57H) within the beta-VOC Orf3a), while Exp1 had the lowest number of mutations.

VOC-specific evolutionary changes were observed for some long-range RRIs, providing evidence for the existence of Comp1 in the beta-VOC sequences. Comp2 proved to be the top hit without the SHAPE restriction. The mutation rate of FSE was comparable to that of the eight long-term RRIs. Unexpectedly, FSE showed more variations per base than the neighboring regions, probably due to its superstructure. The Exp4 interval of the beta sequences, i.e., Beta Exp4 and Beta Comp1, showed significantly covarying base pairs despite low statistical power.

There were differences in VOCs for certain RRIs. For example, Comp1 had lower variation than neighboring regions in all VOCs except Delta, and Exp1 had lower conservation in Delta and Omicron but not in Alpha or Beta. Furthermore, Comp4 had much lower preservation in Omicron, while it was much higher in other VOCs. In Comp4, only three percent of beta mutations adjust the structure, while 90 percent of alpha mutations do.

Diploma

Overall, the study results showed that long-range RRIs in different SARS-CoV-2 VOCs could face different evolutionary pressures and that Comp1 could be a new SARS-CoV-2 long-range RRI.

Reference:

• Dukeshire, M. et al. (2022) „Variantenspezifische Analyse enthüllt eine neuartige RNA-RNA-Interaktion über große Entfernungen in SARS-CoV-2 Orf1a“, International Journal of Molecular Sciences, 23(19), S. 11050. doi: 10.3390/ijms231911050. https://www.mdpi.com/1422-0067/23/19/11050