
Abstract The pervasive transcription of our genome presents a possibility of revealing new genomic functions by investigating RNA interactions. Current methods for mapping RNA–RNA interactions have to rely on an ‘anchor’ protein or RNA and often require molecular perturbations. Here we present the MARIO ( Ma pping R NA i nteractome in viv o ) technology to massively reveal RNA–RNA interactions from unperturbed cells. We mapped tens of thousands of endogenous RNA–RNA interactions from mouse embryonic stem cells and brain. We validated seven interactions by RNA antisense purification and one interaction using single-molecule RNA–FISH. The experimentally derived RNA interactome is a scale-free network, which is not expected from currently perceived promiscuity in RNA–RNA interactions. Base pairing is observed at the interacting regions between long RNAs, including transposon transcripts, suggesting a class of regulatory sequences acting in trans . In addition, MARIO data reveal thousands of intra-molecule interactions, providing in vivo data on high-order RNA structures.
1.1 Normal biological development and functioning, Science, Bioinformatics and Computational Biology, Fluorescence, Article, Mice, Underpinning research, Genetics, Animals, In Situ Hybridization, Conserved Sequence, Embryonic Stem Cells, In Situ Hybridization, Fluorescence, Sequence Analysis, RNA, Human Genome, Q, Brain, Reproducibility of Results, Biological Sciences, Biological Evolution, Gene Expression Regulation, Nucleic Acid Conformation, RNA, Generic health relevance, Sequence Analysis, Biotechnology
1.1 Normal biological development and functioning, Science, Bioinformatics and Computational Biology, Fluorescence, Article, Mice, Underpinning research, Genetics, Animals, In Situ Hybridization, Conserved Sequence, Embryonic Stem Cells, In Situ Hybridization, Fluorescence, Sequence Analysis, RNA, Human Genome, Q, Brain, Reproducibility of Results, Biological Sciences, Biological Evolution, Gene Expression Regulation, Nucleic Acid Conformation, RNA, Generic health relevance, Sequence Analysis, Biotechnology
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