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      Measuring the tail: Methods for poly(A) tail profiling

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          Abstract

          The 3′‐end poly(A) tail is an important and potent feature of most mRNA molecules that affects mRNA fate and translation efficiency. Polyadenylation is a posttranscriptional process that occurs in the nucleus by canonical poly(A) polymerases (PAPs). In some specific instances, the poly(A) tail can also be extended in the cytoplasm by noncanonical poly(A) polymerases (ncPAPs). This epitranscriptomic regulation of mRNA recently became one of the most interesting aspects in the field. Advances in RNA sequencing technologies and software development have allowed the precise measurement of poly(A) tails, identification of new ncPAPs, expansion of the function of known enzymes, discovery and a better understanding of the physiological role of tail heterogeneity, and recognition of a correlation between tail length and RNA translatability. Here, we summarize the development of polyadenylation research methods, including classic low‐throughput approaches, Illumina‐based genome‐wide analysis, and advanced state‐of‐art techniques that utilize long‐read third‐generation sequencing with Pacific Biosciences and Oxford Nanopore Technologies platforms. A boost in technical opportunities over recent decades has allowed a better understanding of the regulation of gene expression at the mRNA level.

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          • RNA Methods > RNA Analyses In Vitro and In Silico

          Abstract

          A development of the methods used to study the length and composition of poly(A) tails, uncovering the 3′‐end tailing as a much more complex and impactful process than previously thought.

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          Most cited references138

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          Full-length RNA-seq from single cells using Smart-seq2.

          Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ∼2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1-3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA(-)) RNA.
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            The Architecture of SARS-CoV-2 Transcriptome

            Summary SARS-CoV-2 is a betacoronavirus responsible for the COVID-19 pandemic. Although the SARS-CoV-2 genome was reported recently, its transcriptomic architecture is unknown. Utilizing two complementary sequencing techniques, we present a high-resolution map of the SARS-CoV-2 transcriptome and epitranscriptome. DNA nanoball sequencing shows that the transcriptome is highly complex owing to numerous discontinuous transcription events. In addition to the canonical genomic and 9 subgenomic RNAs, SARS-CoV-2 produces transcripts encoding unknown ORFs with fusion, deletion, and/or frameshift. Using nanopore direct RNA sequencing, we further find at least 41 RNA modification sites on viral transcripts, with the most frequent motif, AAGAA. Modified RNAs have shorter poly(A) tails than unmodified RNAs, suggesting a link between the modification and the 3′ tail. Functional investigation of the unknown transcripts and RNA modifications discovered in this study will open new directions to our understanding of the life cycle and pathogenicity of SARS-CoV-2.
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              Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome

              The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions 15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.
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                Author and article information

                Contributors
                adziembowski@iimcb.gov.pl
                smroczek@iimcb.gov.pl
                Journal
                Wiley Interdiscip Rev RNA
                Wiley Interdiscip Rev RNA
                10.1002/(ISSN)1757-7012
                WRNA
                Wiley Interdisciplinary Reviews. RNA
                John Wiley & Sons, Inc. (Hoboken, USA )
                1757-7004
                1757-7012
                26 May 2022
                Jan-Feb 2023
                : 14
                : 1 ( doiID: 10.1002/wrna.v14.1 )
                : e1737
                Affiliations
                [ 1 ] Institute of Genetics and Biotechnology, Faculty of Biology University of Warsaw Warsaw Poland
                [ 2 ] Laboratory of RNA Biology International Institute of Molecular and Cell Biology Warsaw Poland
                [ 3 ] Department of Embryology, Faculty of Biology University of Warsaw Warsaw Poland
                Author notes
                [*] [* ] Correspondence

                Andrzej Dziembowski, Laboratory of RNA Biology, International Institute of Molecular and Cell Biology, 02‐109, Warsaw, Poland.

                Email: adziembowski@ 123456iimcb.gov.pl

                Seweryn Mroczek, Laboratory of RNA Biology, International Institute of Molecular and Cell Biology, 02‐109 Warsaw, Poland.

                Email: smroczek@ 123456iimcb.gov.pl

                Author information
                https://orcid.org/0000-0002-0531-8451
                https://orcid.org/0000-0001-9531-1298
                https://orcid.org/0000-0001-8492-7572
                https://orcid.org/0000-0001-5026-1741
                Article
                WRNA1737
                10.1002/wrna.1737
                10078590
                35617484
                982a2b3d-5ad7-4380-8cbc-2fd0e536d289
                © 2022 The Authors. WIREs RNA published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 April 2022
                : 11 February 2022
                : 15 April 2022
                Page count
                Figures: 7, Tables: 2, Pages: 27, Words: 19635
                Funding
                Funded by: Fundacja na Rzecz Nauki Polskiej , doi 10.13039/501100001870;
                Funded by: Narodowe Centrum Nauki , doi 10.13039/501100004281;
                Award ID: UMO‐2020/37/N/NZ2/02893
                Award ID: UMO‐2020/38/E/NZ2/00372
                Categories
                RNA Analyses In Vitro and In Silico
                Advanced Review
                Advanced Reviews
                Custom metadata
                2.0
                January/February 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.7 mode:remove_FC converted:06.04.2023

                3′‐end tailing,poly(a) tail,regulation of gene expression,rna,rna sequencing

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