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Genome-wide identification of mRNA 5-methylcytosine in mammals | Nature Structural & Molecular Biology
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Accurate and systematic transcriptome-wide detection of 5-methylcytosine (m5C) has proved challenging, and there are conflicting views about the prevalence of this modification in mRNAs. Here we report an experimental and computational framework that robustly identified mRNA m5C sites and determined sequence motifs and structural features associated with the modification using a set of high-confidence sites. We developed a quantitative atlas of RNA m5C sites in human and mouse tissues based on our framework. In a given tissue, we typically identified several hundred exonic m5C sites. About 62β70% of the sites had low methylation levels (<20% methylation), while 8β10% of the sites were moderately or highly methylated (>40% methylation). Cross-species analysis revealed that species, rather than tissue type, was the primary determinant of methylation levels, indicating strong cis-directed regulation of RNA methylation. Combined, these data provide a valuable resource for identifying the regulation and functions of RNA methylation. A quantitative atlas of RNA m5C sites in human and mouse tissues based on a new discovery pipeline allows the identification of sequence motifs and structural features associated with the modification and provides a resource for future studies.
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nature portfolio journals permissions reprints nature portfolio privacy policy web-based tools sequencing service advertising zymo research social media sun yat-sen university development simulating rna-seq datasets nsun2-mediated m5c methylation nsun2-mediated cytosine-5 methylation bs-seq data generated rna-dependent chromatin targeting nature+ nature 534 nature 554 nature 462 nature 538 nature 550 nature 485 nature cross-species analysis revealed rna editing single base deletion /sysu-zhanglab/rna-m5c systematic transcriptome-wide detection high-throughput sequencing reads c-cutoff filter based rna sequencing data simulated paired-end reads springerlink instant access subjects computational biology gene-specific conversion rates permissions fast gapped-read alignment high-confidence m5c sites raw sequencing data manuscript editing bs-seq protocols high-confidence sites called m5c rip-seq yeast reveals m5c messenger rna modifications author correspondence standard deviation based rna methylation pathways c-position coverage cutoffs
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headline:Genome-wide identification of mRNA 5-methylcytosine in mammals
description:Accurate and systematic transcriptome-wide detection of 5-methylcytosine (m5C) has proved challenging, and there are conflicting views about the prevalence of this modification in mRNAs. Here we report an experimental and computational framework that robustly identified mRNA m5C sites and determined sequence motifs and structural features associated with the modification using a set of high-confidence sites. We developed a quantitative atlas of RNA m5C sites in human and mouse tissues based on our framework. In a given tissue, we typically identified several hundred exonic m5C sites. About 62Γ’ΒΒ70% of the sites had low methylation levels (<20% methylation), while 8Γ’ΒΒ10% of the sites were moderately or highly methylated (>40% methylation). Cross-species analysis revealed that species, rather than tissue type, was the primary determinant of methylation levels, indicating strong cis-directed regulation of RNA methylation. Combined, these data provide a valuable resource for identifying the regulation and functions of RNA methylation. A quantitative atlas of RNA m5C sites in human and mouse tissues based on a new discovery pipeline allows the identification of sequence motifs and structural features associated with the modification and provides a resource for future studies.
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description:Accurate and systematic transcriptome-wide detection of 5-methylcytosine (m5C) has proved challenging, and there are conflicting views about the prevalence of this modification in mRNAs. Here we report an experimental and computational framework that robustly identified mRNA m5C sites and determined sequence motifs and structural features associated with the modification using a set of high-confidence sites. We developed a quantitative atlas of RNA m5C sites in human and mouse tissues based on our framework. In a given tissue, we typically identified several hundred exonic m5C sites. About 62Γ’ΒΒ70% of the sites had low methylation levels (<20% methylation), while 8Γ’ΒΒ10% of the sites were moderately or highly methylated (>40% methylation). Cross-species analysis revealed that species, rather than tissue type, was the primary determinant of methylation levels, indicating strong cis-directed regulation of RNA methylation. Combined, these data provide a valuable resource for identifying the regulation and functions of RNA methylation. A quantitative atlas of RNA m5C sites in human and mouse tissues based on a new discovery pipeline allows the identification of sequence motifs and structural features associated with the modification and provides a resource for future studies.
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