Project description:Long non-coding RNAs (lncRNAs) are increasingly recognized as important players in transcription and epigenetic-driven cell diversification. So far, lncRNA function in more dynamic transcriptional reprogramming, i.e drug response, has been largely unexplored. Here, we investigated the regulatory circuits induced by chemotherapy in glioblastoma, the most aggressive and clinically refractory brain cancer. We performed a detailed characterization of the cellular and transcriptional response of glioblastoma stem-like cells to the alkylating agent temozolomide (TMZ). We found that in addition to mRNAs, TMZ affects the expression of a large number of non-coding RNAs (miRNAs, snoRNAs, lncRNAs). Our global transcriptome analysis provides a comprehensive characterization of regulatory circuits involving transcription factors, mRNAs, miRNAs and lncRNAs. To analyse the putative functions of these largely unknown RNA molecules, we developed a pipeline to integrate small and large RNA-seq data from multiple public databases and our own experiments. This led to the identification of the RNA interactome of glioblastoma and allowed us to define regulatory loops mediated by lncRNAs. We identified 22 key lncRNAs involved in transcriptional regulatory motifs, and three lncRNAs associated with patient prognosis, independent of other known response predictors. The investigation of TMZ-induced molecular networks in glioblastoma highlights novel coding and non-coding RNA-based predictors of glioblastoma chemoresistance, as well as potential targets to counteract such resistance.
Project description:Long non-coding RNAs (lncRNAs) are increasingly recognized as important players in transcription and epigenetic-driven cell diversification. So far, lncRNA function in more dynamic transcriptional reprogramming, i.e drug response, has been largely unexplored. Here, we investigated the regulatory circuits induced by chemotherapy in glioblastoma, the most aggressive and clinically refractory brain cancer. We performed a detailed characterization of the cellular and transcriptional response of glioblastoma stem-like cells to the alkylating agent temozolomide (TMZ). We found that in addition to mRNAs, TMZ affects the expression of a large number of non-coding RNAs (miRNAs, snoRNAs, lncRNAs). Our global transcriptome analysis provides a comprehensive characterization of regulatory circuits involving transcription factors, mRNAs, miRNAs and lncRNAs. To analyse the putative functions of these largely unknown RNA molecules, we developed a pipeline to integrate small and large RNA-seq data from multiple public databases and our own experiments. This led to the identification of the RNA interactome of glioblastoma and allowed us to define regulatory loops mediated by lncRNAs. We identified 22 key lncRNAs involved in transcriptional regulatory motifs, and three lncRNAs associated with patient prognosis, independent of other known response predictors. The investigation of TMZ-induced molecular networks in glioblastoma highlights novel coding and non-coding RNA-based predictors of glioblastoma chemoresistance, as well as potential targets to counteract such resistance.
Project description:Many biological processes are regulated by RNA-RNA interactions 1, nonetheless it remains formidable to analyze the entire RNA interactome. We developed a method, MARIO (MApping Rna-rna Interactions in vivO), to map protein-assisted RNA-RNA interactions in vivo. By circumventing the selection for a specific RNA-binding protein 2-5, our approach vastly expands the identifiable portion of the RNA interactome. Using this technology, we mapped the RNA interactome in mouse embryonic stem cells, which was composed of 46,780 RNA-RNA interactions. The RNA interactome was a scale-free network, with several lincRNAs and mRNAs emerging as hubs. We validated an interaction between two hubs, Malat1 and Slc2a3 using single molecule RNA fluorescence in situ hybridization. Base pairing was observed at the interaction sites of long RNAs, and was particularly strong in transposonRNA-mRNA and lincRNA-mRNA interactions. This reveals a new type of regulatory sequences acting in trans. Consistent with their hypothesized roles, the RNA interaction sites were more evolutionarily conserved than other regions of the transcripts. MARIO also provided new information on RNA structures, by simultaneously revealing the footprint of single stranded regions and the spatially proximal sites of each RNA. The unbiased mapping of the protein-assisted RNA interactome with minimum perturbation of cell physiology will greatly expand our capacity to investigate RNA functions. Three (3) ESC samples with different treatment (different digestion size and/or crosslinking method) and one (1) MEF sample were included to test our new approach for RNA-interactome mapping and the different samples were analyzed to show RNA interactome differences between them.
Project description:Many biological processes are regulated by RNA-RNA interactions 1, nonetheless it remains formidable to analyze the entire RNA interactome. We developed a method, MARIO (MApping Rna-rna Interactions in vivO), to map protein-assisted RNA-RNA interactions in vivo. By circumventing the selection for a specific RNA-binding protein 2-5, our approach vastly expands the identifiable portion of the RNA interactome. Using this technology, we mapped the RNA interactome in mouse embryonic stem cells, which was composed of 46,780 RNA-RNA interactions. The RNA interactome was a scale-free network, with several lincRNAs and mRNAs emerging as hubs. We validated an interaction between two hubs, Malat1 and Slc2a3 using single molecule RNA fluorescence in situ hybridization. Base pairing was observed at the interaction sites of long RNAs, and was particularly strong in transposonRNA-mRNA and lincRNA-mRNA interactions. This reveals a new type of regulatory sequences acting in trans. Consistent with their hypothesized roles, the RNA interaction sites were more evolutionarily conserved than other regions of the transcripts. MARIO also provided new information on RNA structures, by simultaneously revealing the footprint of single stranded regions and the spatially proximal sites of each RNA. The unbiased mapping of the protein-assisted RNA interactome with minimum perturbation of cell physiology will greatly expand our capacity to investigate RNA functions. Three (3) ESC samples were treated with one (1) type of antisense oligonucleotides as is described in Kretz M. et al. (Nature. 2013 Jan 10;493(7431):231-5) to show the RNA interaction among specific RNAs and verify the results from MARIO
Project description:Many biological processes are regulated by RNA-RNA interactions 1, nonetheless it remains formidable to analyze the entire RNA interactome. We developed a method, MARIO (MApping Rna-rna Interactions in vivO), to map protein-assisted RNA-RNA interactions in vivo. By circumventing the selection for a specific RNA-binding protein 2-5, our approach vastly expands the identifiable portion of the RNA interactome. Using this technology, we mapped the RNA interactome in mouse embryonic stem cells, which was composed of 46,780 RNA-RNA interactions. The RNA interactome was a scale-free network, with several lincRNAs and mRNAs emerging as hubs. We validated an interaction between two hubs, Malat1 and Slc2a3 using single molecule RNA fluorescence in situ hybridization. Base pairing was observed at the interaction sites of long RNAs, and was particularly strong in transposonRNA-mRNA and lincRNA-mRNA interactions. This reveals a new type of regulatory sequences acting in trans. Consistent with their hypothesized roles, the RNA interaction sites were more evolutionarily conserved than other regions of the transcripts. MARIO also provided new information on RNA structures, by simultaneously revealing the footprint of single stranded regions and the spatially proximal sites of each RNA. The unbiased mapping of the protein-assisted RNA interactome with minimum perturbation of cell physiology will greatly expand our capacity to investigate RNA functions.
Project description:Glioblastoma (GBM) is the most aggressive of all primary brain tumours. Here, we perform a multi-omics approach to map the promoter-enhancer interactome and the regulatory landscape of glioblastoma, including RNA-seq, ChIP-seq of histone marks (H3K4me3, H3K27ac, H3K27me3), H3K4me3 HiChIP and ATAC-seq.
Project description:Glioblastoma (GBM) is the most aggressive of all primary brain tumours. Here, we perform a multi-omics approach to map the promoter-enhancer interactome and the regulatory landscape of glioblastoma, including RNA-seq, ChIP-seq of histone marks, HiChIP and ATAC-seq.