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      DNA methylation directs microRNA biogenesis in mammalian cells

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          Abstract

          MicroRNA (miRNA) biogenesis initiates co-transcriptionally, but how the Microprocessor machinery pinpoints the locations of short precursor miRNA sequences within long flanking regions of the transcript is not known. Here we show that miRNA biogenesis depends on DNA methylation. When the regions flanking the miRNA coding sequence are highly methylated, the miRNAs are more highly expressed, have greater sequence conservation, and are more likely to drive cancer-related phenotypes than miRNAs encoded by unmethylated loci. We show that the removal of DNA methylation from miRNA loci leads to their downregulation. Further, we found that MeCP2 binding to methylated miRNA loci halts RNA polymerase II elongation, leading to enhanced processing of the primary miRNA by Drosha. Taken together, our data reveal that DNA methylation directly affects miRNA biogenesis.

          Abstract

          Long primary transcripts of microRNAs are co-transcriptionally cleaved by the enzyme Drosha. Here the authors suggest that DNA methylation in miRNA loci in mammalian cells increases Drosha binding, slowing RNA polymerase II elongation to enhance miRNA biogenesis.

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          Most cited references77

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

            High-throughput mRNA sequencing (RNA-Seq) holds the promise of simultaneous transcript discovery and abundance estimation 1-3 . We introduce an algorithm for transcript assembly coupled with a statistical model for RNA-Seq experiments that produces estimates of abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the time series revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development.
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              TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

              TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.
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                Author and article information

                Contributors
                gilast@post.tau.ac.il
                carmitlevy@post.tau.ac.il
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 December 2019
                11 December 2019
                2019
                : 10
                : 5657
                Affiliations
                [1 ]ISNI 0000 0004 1937 0546, GRID grid.12136.37, Department of Human Genetics and Biochemistry, , Sackler Faculty of Medicine, ; Tel Aviv University, 69978 Tel Aviv, Israel
                [2 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Present Address: Ludwig Institute for Cancer Research and Department of Cellular and Molecular Medicine, , University of California at San Diego, ; La Jolla, CA 92093 USA
                Author information
                http://orcid.org/0000-0001-7201-6341
                http://orcid.org/0000-0001-6364-9307
                Article
                13527
                10.1038/s41467-019-13527-1
                6906426
                31827083
                1607ba6a-1a06-4603-be33-dc0b09c1be7d
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 July 2017
                : 28 October 2019
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                © The Author(s) 2019

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                dna methylation,mirnas
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                dna methylation, mirnas

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