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      Specific RNP capture with antisense LNA/DNA mixmers

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          Abstract

          RNA-binding proteins (RBPs) play essential roles in RNA biology, responding to cellular and environmental stimuli to regulate gene expression. Important advances have helped to determine the (near) complete repertoires of cellular RBPs. However, identification of RBPs associated with specific transcripts remains a challenge. Here, we describe “specific ribonucleoprotein (RNP) capture,” a versatile method for the determination of the proteins bound to specific transcripts in vitro and in cellular systems. Specific RNP capture uses UV irradiation to covalently stabilize protein–RNA interactions taking place at “zero distance.” Proteins bound to the target RNA are captured by hybridization with antisense locked nucleic acid (LNA)/DNA oligonucleotides covalently coupled to a magnetic resin. After stringent washing, interacting proteins are identified by quantitative mass spectrometry. Applied to in vitro extracts, specific RNP capture identifies the RBPs bound to a reporter mRNA containing the Sex-lethal (Sxl) binding motifs, revealing that the Sxl homolog sister of Sex lethal (Ssx) displays similar binding preferences. This method also revealed the repertoire of RBPs binding to 18S or 28S rRNAs in HeLa cells, including previously unknown rRNA-binding proteins.

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          Most cited references93

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Mfold web server for nucleic acid folding and hybridization prediction.

            M Zuker (2003)
            The abbreviated name, 'mfold web server', describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and 'energy dot plots', are available for the folding of single sequences. A variety of 'bulk' servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as 'MFOLDROOT'.
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              Linear models and empirical bayes methods for assessing differential expression in microarray experiments.

              The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model. The purpose of this paper is to develop the hierarchical model of Lonnstedt and Speed (2002) into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples. The model is reset in the context of general linear models with arbitrary coefficients and contrasts of interest. The approach applies equally well to both single channel and two color microarray experiments. Consistent, closed form estimators are derived for the hyperparameters in the model. The estimators proposed have robust behavior even for small numbers of arrays and allow for incomplete data arising from spot filtering or spot quality weights. The posterior odds statistic is reformulated in terms of a moderated t-statistic in which posterior residual standard deviations are used in place of ordinary standard deviations. The empirical Bayes approach is equivalent to shrinkage of the estimated sample variances towards a pooled estimate, resulting in far more stable inference when the number of arrays is small. The use of moderated t-statistics has the advantage over the posterior odds that the number of hyperparameters which need to estimated is reduced; in particular, knowledge of the non-null prior for the fold changes are not required. The moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom. The moderated t inferential approach extends to accommodate tests of composite null hypotheses through the use of moderated F-statistics. The performance of the methods is demonstrated in a simulation study. Results are presented for two publicly available data sets.
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                Author and article information

                Journal
                RNA
                RNA
                RNA
                RNA
                Cold Spring Harbor Laboratory Press
                1355-8382
                1469-9001
                August 2017
                August 2017
                : 23
                : 8
                : 1290-1302
                Affiliations
                [1 ]European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
                [2 ]German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
                [3 ]Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, United Kingdom
                Author notes
                Article
                9509184 RA
                10.1261/rna.060798.117
                5513073
                28476952
                f7ad17a9-6d5c-425d-bd1d-f7498d362de7
                © 2017 Rogell et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society

                This article, published in RNA, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 17 January 2017
                : 25 April 2017
                Page count
                Pages: 13
                Funding
                Funded by: European Research Council , open-funder-registry 10.13039/501100000781;
                Award ID: ERC-2011-ADG_20110310
                Funded by: Medical Research Council Career Development Award , open-funder-registry 10.13039/501100000265;
                Award ID: MR/L019434/1
                Categories
                Method

                rna-binding proteins,rna interactome,ribosomal rna,rna–protein interactions,specific rnp capture

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