Clusters of mammalian conserved RNA structures in UTRs associate with RBP binding sites

Author:

Gadekar Veerendra P1234ORCID,Munk Alexander Welford12,Miladi Milad5ORCID,Junge Alexander12,Backofen Rolf5ORCID,Seemann Stefan E12ORCID,Gorodkin Jan12ORCID

Affiliation:

1. Center for non-coding RNA in Technology and Health, University of Copenhagen , Ridebanevej 9, 1870 Frederiksberg, Denmark

2. Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen , Frederiksberg, 1870 Frederiksberg, Denmark

3. Centre for Integrative Biology and Systems Medicine (IBSE), IIT Madras , Chennai, India

4. Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras , Chennai, India

5. Bioinformatics Group, Department of Computer Science, University of Freiburg , Freiburg im Breisgau, Germany

Abstract

Abstract RNA secondary structures play essential roles in the formation of the tertiary structure and function of a transcript. Recent genome-wide studies highlight significant potential for RNA structures in the mammalian genome. However, a major challenge is assigning functional roles to these structured RNAs. In this study, we conduct a guilt-by-association analysis of clusters of computationally predicted conserved RNA structure (CRSs) in human untranslated regions (UTRs) to associate them with gene functions. We filtered a broad pool of ∼500 000 human CRSs for UTR overlap, resulting in 4734 and 24 754 CRSs from the 5′ and 3′ UTR of protein-coding genes, respectively. We separately clustered these CRSs for both sets using RNAscClust, obtaining 793 and 2403 clusters, each containing an average of five CRSs per cluster. We identified overrepresented binding sites for 60 and 43 RNA-binding proteins co-localizing with the clustered CRSs. Furthermore, 104 and 441 clusters from the 5′ and 3′ UTRs, respectively, showed enrichment for various Gene Ontologies, including biological processes such as ‘signal transduction’, ‘nervous system development’, molecular functions like ‘transferase activity’ and the cellular components such as ‘synapse’ among others. Our study shows that significant functional insights can be gained by clustering RNA structures based on their structural characteristics.

Funder

Innovation Fund Denmark

Danish Research Council

Publisher

Oxford University Press (OUP)

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