MiCLIP analysis of m6A sites in LNCaP and RWPE cells
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ABSTRACT:
PROVIDER: PRJNA676163 | ENA |
REPOSITORIES: ENA
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Project description:Genomic and transcriptomic alterations are insufficient to explain the variance in protein expression seen in cancer. Recent evidence has highlighted the role of N6-methyladenosine (m6A) in the regulation of mRNA expression, stability and translation, supporting a potential role for post-transcriptional regulation mediated by m6A in cancer. Here we explore prostate cancer as an exemplar cancer and generate the first prostate m6A maps, and further examined how low levels of N6-adenosine-methyltransferase (METTL3) associates with advanced prostate cancer and results in altered expression at the level of transcription, translation, and protein. In particular extracellular matrix proteins have a high number of m6A sites and show significant changes in expression with METTL3 knock-down. We also discovered the upregulation of a hepatocyte nuclear factor-driven gene signature that is associated with therapy resistance in prostate cancer. Significantly, METTL3 knock-down rendered the cells resistant to androgen receptor antagonists, implicating changes in m6A as a mechanism for therapy resistance in metastatic prostate cancer.
2021-06-07 | GSE161303 | GEO
Project description:GP61-primed effector CD4+ T cells were isolated from Ctrl or Mettl3-deficient SMARTA mice. Total RNAs were extracted with TRIzol reagent, and mRNAs were then isolated with Dynabeads® mRNA purification kit, followed by stardard m6A-miCLIP-SMARTer-seq with some modifications. Raw sequencing reads were aligned to the mouse genome (mm10) with BWA, and then m6A sites were determined.
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Project description:To identify m6A sites on endogenous nuclear RNAs, we performed miCLIP to identify m6A sites in PANC-1 cells. To identify NKAP binding sites on endogenous nuclear RNAs, we performed iCLIP for flag-tag NKAP to analyze the nuclear RNA binding with NKAP in the same cells.
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Project description:To understand the global effect of H3K36me3 on m6A modification, we compared the m6A profiling in SETD2 knockdown and control HepG2 cells by miCLIP-seq, and found the depletion of H3K36me3 by SETD2 silencing globally reduced m6A in the human transcriptome.
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Project description:m6A modification in effector CD4+ T cells [m6A-miCLIP-seq]
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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: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:We have developed a modified eCLIP-based method (meCLIP) to identify m6A residues at single-nucleotide resolution. By coupling the improvements of eCLIP with an easy-to-use computational pipeline, we have successfully identified over 50,000 unique m6A residues in the two breast cancer cell lines that were analyzed (MCF-7 and MDA-MB-231) and over 8,000 unique residues in HEK-293 cells. We compared these residues to the sites called using the currently most utilized m6A identification method (miCLIP).
2020-12-31 | GSE147440 | GEO
Project description:N6-methyladenosine (m6A) is a widespread reversible chemical modification of RNAs, implicated in many aspects of RNA metabolism. Little quantitative information exists as to either how many transcript copies of particular genes are m6A modified (âm6A levelsâ), or the relationship of m6A modification(s) to alternative RNA isoforms. To deconvolute the m6A epitranscriptome, we developed m6A level and isoform-characterization sequencing (m6A-LAIC-seq). We found that cells exhibit a broad range of non-stoichiometric m6A levels with cell type specificity. At the level of isoform characterization, we discovered widespread differences in use of tandem alternative polyadenylation (APA) sites by methylated and nonmethylated transcript isoforms of individual genes. Strikingly, there is a strong bias for methylated transcripts to be coupled with proximal APA sites, resulting in shortened 3â untranslated regions (3â-UTRs), while nonmethylated transcript isoforms tend to use distal APA sites. m6A-LAIC-seq yields a new perspective on transcriptome complexity and links APA usage to m6A modifications. m6A-LAIC-seq of H1-ESC and GM12878 cell lines, each cell line has two replicates
2016-06-24 | E-GEOD-66086 | biostudies-arrayexpress