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      A Novel Class of MicroRNA Recognition Elements That Function Only in Open Reading Frames

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          Abstract

          MicroRNA (miRNA) are well known to target 3’ untranslated regions (3’UTR) in mRNAs to silence gene expression at post-transcriptional levels. Multiple reports have also indicated the capability of miRNAs to target protein-coding sequences (CDS); however, miRNAs have been generally believed to function in a similar mechanism(s) regardless of the location of their action sites. We herein report a class of miRNA recognition elements (MREs) that exclusively function in CDS regions in humans. Through functional and mechanistic characterization of these “unusual” MREs, we demonstrate that CDS-targeted miRNAs require extensive base pairings in the 3’ side rather than the 5’ seed; cause gene silencing in an Argonaute-dependent, but GW182-independent manner; and repress translation by inducing transient ribosome stalling instead of mRNA destabilization. These findings reveal distinct mechanisms and functional consequences for miRNAs to target CDS versus 3’UTR and suggest that CDS-targeted miRNAs may enlist a translational quality control (QC)-related mechanism to regulate translation in mammalian cells.

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          Most cited references 44

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          Is Open Access

          featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

           ,  ,   (2013)
          Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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            Gene silencing by microRNAs: contributions of translational repression and mRNA decay.

            Despite their widespread roles as regulators of gene expression, important questions remain about target regulation by microRNAs. Animal microRNAs were originally thought to repress target translation, with little or no influence on mRNA abundance, whereas the reverse was thought to be true in plants. Now, however, it is clear that microRNAs can induce mRNA degradation in animals and, conversely, translational repression in plants. Recent studies have made important advances in elucidating the relative contributions of these two different modes of target regulation by microRNAs. They have also shed light on the specific mechanisms of target silencing, which, although it differs fundamentally between plants and animals, shares some common features between the two kingdoms.
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              Argonaute2 is the catalytic engine of mammalian RNAi.

              Gene silencing through RNA interference (RNAi) is carried out by RISC, the RNA-induced silencing complex. RISC contains two signature components, small interfering RNAs (siRNAs) and Argonaute family proteins. Here, we show that the multiple Argonaute proteins present in mammals are both biologically and biochemically distinct, with a single mammalian family member, Argonaute2, being responsible for messenger RNA cleavage activity. This protein is essential for mouse development, and cells lacking Argonaute2 are unable to mount an experimental response to siRNAs. Mutations within a cryptic ribonuclease H domain within Argonaute2, as identified by comparison with the structure of an archeal Argonaute protein, inactivate RISC. Thus, our evidence supports a model in which Argonaute contributes "Slicer" activity to RISC, providing the catalytic engine for RNAi.
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                Author and article information

                Journal
                101186374
                31761
                Nat Struct Mol Biol
                Nat. Struct. Mol. Biol.
                Nature structural & molecular biology
                1545-9993
                1545-9985
                24 September 2018
                08 October 2018
                November 2018
                08 April 2019
                : 25
                : 11
                : 1019-1027
                Affiliations
                [1 ]State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Wuhan University, Wuhan, China
                [2 ]Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
                [3 ]Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, School of Medicine, Yangzhou University, Yangzhou, China
                [4 ]Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Shanghai, China
                [5 ]Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, University of California, San Diego, La Jolla, California, USA
                [6 ]Center for RNA Molecular Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
                [7 ]Institute for Advanced Studies, Wuhan University, Wuhan, China
                Author notes

                Author contributions

                ZQC, KZ, XZ, YZ, TN, and XDF designed the experiments; ZQC, KZ, XZ and WR performed most experiments; JZ, BZ, ZGC, DW and YZ analyzed the data; YaZ and LW performed the deadenylation assay; RC, QL, YX, and QY contributed to additional data. ZQC, KZ, YZ, TN and XDF wrote the paper.

                [8 ]Corresponding authors: Yu Zhou, yu.zhou@ 123456whu.edu.cn , Phone: +86 27 68756749, Xiang-Dong Fu, xdfu@ 123456ucsd.edu , Phone: +1 858-534-4937
                Article
                NIHMS1505440
                10.1038/s41594-018-0136-3
                6219929
                30297778

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                Molecular biology

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