Function and Structure of RNA



Our group studies structural and functional motifs in RNA. We use a wide range of techniques to identify and characterize loci in different types of RNA comprising of sequence analysis focusing on covariation, annotation, analysis of chemical structure probing and crosslinking data, secondary and tertiary structure prediction methods, molecular modeling, and molecular dynamics simulations. Our primary targets of research are viral genomic and subgenomic RNAs including RNA-RNA and RNA-Protein interactions within infected host cells. Systems of interest span mosquito-borne infections, Enteroviruses, Influenza, as well as marine pathogens. Additionally, we are working to identify regulatory networks at the RNA level throughout human cell differentiation.

RNA structure in viral RNA genomes

Most pandemics of recent decades can be traced to RNA viruses, including HIV, SARS, influenza, dengue, Zika, and SARS-CoV-2. These RNA viruses impose considerable social and economic burdens on our society. As these RNA viruses utilize an RNA genome, which is important for different stages of the viral life cycle, including replication, translation, and packaging, studying which folds the genome adopts at different stages is important to understand virus function. We employ techniques combining computational and high-throughput RNA structure-mapping approaches to aid in the understanding of structures within RNA virus genomes.1

RNAvigator enables rapid identification of candidate functional elements

Identifying structural elements on long and complex RNAs, such as lncRNAs and RNA viruses, can shed light to the functionality and the mechanisms of such RNAs. We developed RNAvigator, a tool able to identify elements of structural importance by using experimental SHAPE data or SHAPE-like predictions in conjunction with stability and entropy assessments. RNAvigator recognizes regions that are the most stable, unambiguous, and structured on RNA molecules, and thus potentially functional. When relying on predictions, RNAvigator uses the CROSS algorithm, a neural-network trained on experimental data that achieved an AUC 0.74 on HCV SHAPE-MaP data, and which was able to improve the predictive power of Superfold. By using RNAvigator, we are able to identify known functional regions on the complete HCV genome, including the regulatory regions CRE and IRES, and the 3’ UTR of DENV-1, a region known for the presence of structural elements essential for its replication. We envision that RNAvigator will be a useful tool to study long and complex RNA molecules by using known chemical probing data or, if they are not available, by employing predicted profiles. 2


Figure 1. (A) Graphical representation of how understanding the RNA secondary structure, by using experiments or predictions, is crucial to assess the functionality of a RNA molecule. (B) Workflow of RNAvigator explaining the differences in the two pipelines while using experimental data (SHAPE) or predicted secondary structure profiles (CROSS) as input.


Functional structures in SARS-CoV-2 variants

We investigated the RNA structure and RNA-RNA interactions of wildtype (WT) and a mutant (Δ382) SARS-CoV-2 in cells using Illumina and Nanopore platforms. We identify twelve potentially functional structural elements within the SARS-CoV-2 genome, observe that subgenomic RNAs can form different structures, and that WT and Δ382 virus genomes fold differently. Proximity ligation sequencing identify hundreds of RNA-RNA interactions within the virus genome and between the virus and host RNAs. SARS-CoV-2 genome binds strongly to mitochondrial and small nucleolar RNAs and is extensively 2’-O-methylated. 2’-O-methylation sites are enriched in viral untranslated regions, associated with increased virus pair-wise interactions, and are decreased in host mRNAs upon virus infection, suggesting that the virus sequesters methylation machinery from host RNAs towards its genome. These studies deepen our understanding of the molecular and cellular basis of SARS-CoV-2 pathogenicity and provide a platform for targeted therapy. 3



Figure 2. (a) SARS-CoV-2 structure models when the SARS-CoV-2 genome does not interact or interacts with SNORD27. SHAPE reactivity was used for constraints in this model. (b), locations of 2′-O-methylation sites found along SARS-CoV-2 genome.


RNA structures change throughout neuronal cell differentiation

The distribution, dynamics, and function of RNA structures in human development are under-explored. We systematically assayed RNA structural dynamics and their relationship with gene expression, translation, and decay during human neurogenesis. We observed that the human ESC transcriptome is globally more structurally accessible than differentiated cells and undergoes extensive RNA structure changes, particularly in the 3′ UTR. Additionally, RNA structure changes during differentiation are associated with translation and decay. We observed that RBP and miRNA binding is associated with RNA structural changes during early neuronal differentiation, and splicing is associated during later neuronal differentiation. Furthermore, our analysis suggests that RBPs are major factors in structure remodeling and co-regulate additional RBPs and miRNAs through structure. We demonstrated an example of this by showing that PUM2-induced structure changes on LIN28A enable miR-30 binding. This study deepens our understanding of the widespread and complex role of RNA-based gene regulation during human development. 4


Principal Investigator HUBER Roland G.   |    [View Bio]  
Senior Scientist I DEFALCO Louis
Senior Scientist I KULKARNI  Mandar
Research Officer CHIAM Aryeh Joseph 

Selected Publications