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      Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion

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          Abstract

          To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

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          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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            Identification of novel transcripts in annotated genomes using RNA-Seq.

            We describe a new 'reference annotation based transcript assembly' problem for RNA-Seq data that involves assembling novel transcripts in the context of an existing annotation. This problem arises in the analysis of expression in model organisms, where it is desirable to leverage existing annotations for discovering novel transcripts. We present an algorithm for reference annotation-based transcript assembly and show how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation. The methods described in this article are implemented in the Cufflinks suite of software for RNA-Seq, freely available from http://bio.math.berkeley.edu/cufflinks. The software is released under the BOOST license. cole@broadinstitute.org; lpachter@math.berkeley.edu Supplementary data are available at Bioinformatics online.
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              Metabolism and regulation of canonical histone mRNAs: life without a poly(A) tail.

              The canonical histone proteins are encoded by replication-dependent genes and must rapidly reach high levels of expression during S phase. In metazoans the genes that encode these proteins produce mRNAs that, instead of being polyadenylated, contain a unique 3' end structure. By contrast, the synthesis of the variant, replication-independent histones, which are encoded by polyadenylated mRNAs, persists outside of S phase. Accurate positioning of both histone types in chromatin is essential for proper transcriptional regulation, the demarcation of heterochromatic boundaries and the epigenetic inheritance of gene expression patterns. Recent results suggest that the coordinated synthesis of replication-dependent and variant histone mRNAs is achieved by signals that affect formation of the 3' end of the replication-dependent histone mRNAs.
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                Author and article information

                Contributors
                Shanrong.Zhao@pfizer.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                19 March 2018
                19 March 2018
                2018
                : 8
                : 4781
                Affiliations
                [1 ]ISNI 0000 0000 8800 7493, GRID grid.410513.2, Precision Medicine, Early Clinical Development, , Pfizer Worldwide Research and Development, ; Cambridge, 02139 MA USA
                [2 ]ISNI 0000 0000 8800 7493, GRID grid.410513.2, Inflammation & Immunology Research Unit, Pfizer Worldwide Research and Development, ; Cambridge, MA 02139 USA
                Author information
                http://orcid.org/0000-0003-4735-4212
                Article
                23226
                10.1038/s41598-018-23226-4
                5859127
                29556074
                dbfcd7c8-5a2a-49c0-a06e-017549475faf
                © The Author(s) 2018

                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
                : 7 February 2018
                : 7 March 2018
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