RNA in situ conformation sequencing (RIC-seq) in naive and primed mouse embryonic stem cells
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ABSTRACT:
PROVIDER: PRJEB85071 | ENA |
REPOSITORIES: ENA
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Project description:Highly structured RNA molecules usually interact with each other, and associate with various RNA-binding proteins, to regulate critical biological processes. However, RNA structures and interactions in intact cells remain largely unknown. Here, by coupling proximity ligation mediated by RNA-binding proteins with deep sequencing, we report an RNA in situ conformation sequencing (RIC-seq) technology for the global profiling of intra- and intermolecular RNA–RNA interactions. This technique not only recapitulates known RNA secondary structures and tertiary interactions, but also facilitates the generation of three-dimensional (3D) interaction maps of RNA in human cells. Using these maps, we identify noncoding RNA targets globally, and discern RNA topological domains and trans-interacting hubs. We reveal that the functional connectivity of enhancers and promoters can be assigned using their pairwise-interacting RNAs. Furthermore, we show that CCAT1-5L—a super-enhancer hub RNA—interacts with RNA-binding protein hnRNPK, as well as RNA derived from the MYC promoter and enhancer, to boost MYC transcription by modulating chromatin looping. Our study demonstrates the power and applicability of RIC-seq in discovering the 3D structures, interactions and regulatory roles of RNA.
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Project description:This study aims to profile the transcriptomes of single naive and primed human embryonic stem cells. Cells from the H9 line were cultured to select for naive or primed phenotypes, and a sequencing library was generated from each single cell using the Smart-seq2 method. This was repeated for multiple experimental batches, i.e., independent cultures. Batch 1 consists of sequencing runs 2383 and 2384; batch 2 consists of runs 2678, 2679, 2739 and 2740; and batch 3 consists of runs 2780 and 2781. Transcriptional profiles for all cells were obtained from the sequencing data and used to explore substructure and heterogeneity in the population for each phenotype.
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