Speakers – August 2017

Circular RNAs in adipogenesis and obesity

Camille ARCINAS
Research Assistant
Lei SUN Lab
Duke-NUS

Non-coding RNAs are known to be key regulators in adipogenesis and other endocrine and metabolic functions. While the dynamic mechanisms of microRNAs and lncRNAs in adipose biology have been closely studied, circular RNAs (circRNAs) represent a newly unveiled class of non-coding transcripts whose molecular and physiological significance remains largely unknown. These closed, non-polyadenylated loops are generated by the spliceosome in a backsplicing reaction that covalently links the 3’ end of a downstream exon to the 5’ end of an upstream exon at their canonical splice sites, but in scrambled order. As the expression and distribution of circular isoforms often follows tissue/developmental-stage-specific patterns, their possible application as biomarkers in diseases of genetic complexity and heterogeneity has drawn much interest. In this study, we performed deep sequencing of human and mouse total RNA libraries to establish the first comprehensive annotation and validation of species-conserved, adipose-specific circular RNA transcripts. We also employed an siRNA-mediated knockdown strategy to identify circRNAs with key functional roles in adipocyte development. Using a diet-induced model of obesity, we uncovered significant differential expression patterns of circRNAs within both adipose tissue and circulating exosomes, highlighting their potential as stable diagnostic and prognostic biomarkers that can distinguish between healthy and pathological metabolic states.


Computationlly predicting novel RNA binding proteins using protein-protein interaction networks

Wenhao JIN
Graduate Student
Gene YEO Lab
National University of Singapore

RNA-binding proteins (RBPs) play an important role in post-transcriptional gene regulation (PTGR) that controls the maturation, transport, stability and degradation of RNAs. Discovering novel RBPs and recognizing the RNA-binding potential of known proteins will help increase our understanding of the PTGR system and each protein’s function. There have been many attempts to computationally predict binding of a protein to RNA, using intrinsic protein characteristics such as sequence and structure. However, extrinsic protein characteristics such as interactions with other proteins (neighbors) have not been considered a feature to predict RNA binding potential. In this study, we construct a classifier for recognizing RNA binding proteins utilizing both the extrinsic and intrinsic properties of proteins. We recently demonstrated the predictive power of protein-protein interaction (PPI) networks for predicting RNA binding proteins. Here, we extract RNA-binding features from protein sequences with convolution neural networks. Next, a group of accurate RBP classifiers, collectively called SONAR+, is obtained by integrating the information of PPI neighbors and sequence features with deep neural network and SVM models. We find SONAR+ outperforms other classifiers and we have experimentally validated several candidate RBPs which were previously uncharacterized for RNA interaction. SONAR+ accurately and efficiently expands the list of RBPs.


Structural studies of Dicer-related RNA helicase 3 in RNA interference pathway

Kuohan LI
Graduate Student
Dahai LUO Lab
Nanyang Technological University

Double stranded RNA-dependent ATPases (DRAs) are essential for RNA metabolism in eukaryotic organisms. Dicer proteins, RIG-I like receptors (RLRs) and worm-based Dicer-related RNA helicases (DRHs) are grouped as DRAs based on their structural and sequential conserved helicase domain. Dicer processes small interfering RNA (siRNA) and microRNAs (miRNAs) into functional size RNAs for sequence specific silencing activities. RLRs, including RIG-I (retinoic acid-inducible gene I), MDA5 (melanoma differentiation-associated gene 5) and LGP2 (laboratory of genetics and physiology 2), play crucial roles in the induction of type I interferon. Dicer-related RNA helicases 1 and 3 (DRH-1 and DRH-3) are involved in antiviral defence via RNA interference pathway in Caenorhabditis elegans (C. elegans). However, the structure and function of DRHs at the molecular level remain elusive. In this study, we combined X-ray crystallography and hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS) methods to probe both molecular structure and protein dynamics information of DRH-3. We have solved the crystal structure of DRH-3 N-terminal domain (NTD) at 2.60 Å resolution, and two crystal structures of DRH-3 C-terminal domains (CTD) in complex with 5’-triphosphate 8-mer ssRNA and 5’-triphosphate 12-mer dsRNA, respectively. The HDX-MS result shows that, in solution, full-length DRH-3 selectively binds to short 5’- triphosphate dsRNAs and the NTD does not interact with helicase domain and CTD in RNA recognition.