Mus musculus
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ABSTRACT:
PROVIDER: PRJNA389580 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Transcriptome analysis of gene expression and single-nucleotide-resolution m6A sites in normal and mettl3 cKO testis samples
| PRJNA389575 | ENA
Project description:Transcriptome analysis of gene expression and single-nucleotide-resolution m6A sites in normal and mettl3 cKO testis samples (RNA-Seq)
| PRJNA389581 | ENA
Project description:We show that N6-methyladenosine (m6A), the most abundant internal modification in mRNA/lncRNA with still poorly characterized function, alters RNA structure to facilitate the access of RBM for heterogeneous nuclear ribonucleoprotein C (hnRNP C). We term this mechanism m6A-switch. Through combining PAR-CLIP with Me-RIP, we identify 39,060 m6A-switches among hnRNP C binding sites transcriptome-wide. We show that m6A-methyltransferases METTL3 or METTL14 knockdown decreases hnRNP C binding at 16,582 m6A-switches. Taken together, 2,798 m6A-switches of high confidence are identified to mediate RNA-hnRNP C interactions and affect diverse biological processes including cell cycle regulation. These findings reveal the biological importance of m6A and provide insights into the sophisticated regulation of RNA-RBP interactions through m6A-induced RNA structural remodeling. Measure the m6A methylated hnRNP C binding sites transcriptome-wide by PARCLIP-MeRIP; measure the differential hnRNP C occupancies upon METTL3/METTL14 knockdown by PAR-CLIP; measure RNA abundance and splicing level changes upon HNRNPC, METTL3 and METTL14 knockdown
2015-02-27 | E-GEOD-56010 | biostudies-arrayexpress
Project description:N6-methyladenosine (m6A) is the most prevalent internal modification found in mammalian messenger and non-coding RNAs. The discoveries of functionally significant demethylases that reverse this methylation as well as the recently revealed m6A distributions in mammalian transcriptomes strongly indicate regulatory functions of this modification. Here we report the identification and characterization of the mammalian nuclear RNA N6-adenosine methyltransferase core (RNMTC) complex. Besides METTL3, a methyltransferase which was the only known component of RNMTC in the past, we discovered that a previously uncharacterized methyltransferase, METTL14, exhibits a N6-adenosine methyltransferase activity higher than METTL3. Together with WTAP, the third component that dramatically affects the cellular m6A level, these three proteins form the core complex that orchestrates m6A deposition on mammalian nuclear RNA. Biochemistry assays, imaging experiments, as well as transcriptome-wide analyses of the binding sites and their effects on m6A methylation support methylation function and reveal new insights of RNMTC. PAR-CLIP and m6A-seq in HeLa cells
2013-11-29 | E-GEOD-46705 | biostudies-arrayexpress
Project description:N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing, such as RNA stability and translation. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites in the transcriptome with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present several experimental and computational innovations that significantly improve transcriptome-wide detection of m6A sites. Based on the recently developed iCLIP2 protocol, the optimised miCLIP2 results in high-complexity libraries using less input material, leading to a more comprehensive representation of m6A sites. Next, we established a robust computational pipeline to identify true m6A sites from our miCLIP2 data. The analyses are calibrated with data from Mettl3 knockout cells to learn the characteristics of m6A deposition, including a significant number of m6A sites outside of DRACH motifs. In order to make these results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.
2021-06-05 | GSE163499 | GEO
Project description:N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing, such as RNA stability and translation. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites in the transcriptome with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present several experimental and computational innovations that significantly improve transcriptome-wide detection of m6A sites. Based on the recently developed iCLIP2 protocol, the optimised miCLIP2 results in high-complexity libraries using less input material, leading to a more comprehensive representation of m6A sites. Next, we established a robust computational pipeline to identify true m6A sites from our miCLIP2 data. The analyses are calibrated with data from Mettl3 knockout cells to learn the characteristics of m6A deposition, including a significant number of m6A sites outside of DRACH motifs. In order to make these results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.
2021-06-05 | GSE163492 | GEO
Project description:N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing, such as RNA stability and translation. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites in the transcriptome with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present several experimental and computational innovations that significantly improve transcriptome-wide detection of m6A sites. Based on the recently developed iCLIP2 protocol, the optimised miCLIP2 results in high-complexity libraries using less input material, leading to a more comprehensive representation of m6A sites. Next, we established a robust computational pipeline to identify true m6A sites from our miCLIP2 data. The analyses are calibrated with data from Mettl3 knockout cells to learn the characteristics of m6A deposition, including a significant number of m6A sites outside of DRACH motifs. In order to make these results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.
2021-06-05 | GSE163491 | GEO
Project description:Here we determine the map of RNA methylation (m6A) in mouse embrionic stem cells, and Mettl3 knock out cells Examination of m6A modification sites on the transcriptome of mouse Embryonic stem cells and Embryonic Mettl3 knock out cells, using a m6A specific antibody.
2014-10-16 | E-GEOD-52662 | biostudies-arrayexpress
Project description:N6-methyladenosine (m6A) is a common modification of mRNA, with potential roles in fine-tuning the RNA life cycle, but little is known about the pathways regulating this process and its physiological role. Here, we used mass-spectrometry to identify a dense network of proteins physically interacting with METTL3, a core component of the methyltransferase complex, and show that two of them, WTAP and KIAA1429, are required for methylation. Combining high resolution m6A-Seq with knockdown of WTAP allowed us to define accurate maps, at near single-nucleotide resolution, of sites of mRNA methylation across four dynamic programs in human and mouse, including development, differentiation, reprogramming and immune response. Internal WTAP-dependent methylation sites were largely static across the different surveyed conditions and present in the majority of mRNAs. However, methylations were found at much lower levels within highly expressed mRNAs, and methylation is inversely correlated with mRNA stability, consistent with a role in establishing an overall basal, cell-type invariant, distribution of degradation rates. In addition, we identify thousands of WTAP-independent methylation sites at transcription initiation sites, forming part of the mRNA cap structure. We show that the methylations occur at the first transcribed nucleotide, and find that thousands of transcripts are present in different isoforms differing in the methylation state of the first transcribed nucleotide, a previously unappreciated complexity of the transcriptome. Together, our data sheds new light on the proteomic and transcriptional underpinnings of this epitranscriptomic modification in mammals. Examination of m6A methylation across different knockdowns using shRNAs in mouse embryonic fibroblasts, in embyronic and adult brains, and in dendritic cell stimulated with LPS.
2014-07-18 | E-GEOD-55575 | biostudies-arrayexpress
Project description:N6-methyladenosine (m6A) is a common modification of mRNA, with potential roles in fine-tuning the RNA life cycle, but little is known about the pathways regulating this process and its physiological role. Here, we used mass-spectrometry to identify a dense network of proteins physically interacting with METTL3, a core component of the methyltransferase complex, and show that two of them, WTAP and KIAA1429, are required for methylation. Combining high resolution m6A-Seq with knockdown of WTAP allowed us to define accurate maps, at near single-nucleotide resolution, of sites of mRNA methylation across four dynamic programs in human and mouse, including development, differentiation, reprogramming and immune response. Internal WTAP-dependent methylation sites were largely static across the different surveyed conditions and present in the majority of mRNAs. However, methylations were found at much lower levels within highly expressed mRNAs, and methylation is inversely correlated with mRNA stability, consistent with a role in establishing an overall basal, cell-type invariant, distribution of degradation rates. In addition, we identify thousands of WTAP-independent methylation sites at transcription initiation sites, forming part of the mRNA cap structure. We show that the methylations occur at the first transcribed nucleotide, and find that thousands of transcripts are present in different isoforms differing in the methylation state of the first transcribed nucleotide, a previously unappreciated complexity of the transcriptome. Together, our data sheds new light on the proteomic and transcriptional underpinnings of this epitranscriptomic modification in mammals. Examination of m6A methylation in human Hek293 and A549 cell lines, in human embryonic stem cells (ESCs) undergoing differentiation to neural progenitor cells (NPCs), in OKMS inducible fibroblasts reprogrammed into iPSC, and upon knockdown of factors using siRNAs or shRNAs.
2014-07-18 | E-GEOD-55572 | biostudies-arrayexpress