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      TERA-Seq: true end-to-end sequencing of native RNA molecules for transcriptome characterization

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      , , ,
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          Direct sequencing of single, native RNA molecules through nanopores has a strong potential to transform research in all aspects of RNA biology and clinical diagnostics. The existing platform from Oxford Nanopore Technologies is unable to sequence the very 5′ ends of RNAs and is limited to polyadenylated molecules. Here, we develop True End-to-end RN A Sequencing (TERA-Seq), a platform that addresses these limitations, permitting more thorough transcriptome characterization. TERA-Seq describes both poly- and non-polyadenylated RNA molecules and accurately identifies their native 5′ and 3′ ends by ligating uniquely designed adapters that are sequenced along with the transcript. We find that capped, full-length mRNAs in human cells show marked variation of poly(A) tail lengths at the single molecule level. We report prevalent capping downstream of canonical transcriptional start sites in otherwise fully spliced and polyadenylated molecules. We reveal RNA processing and decay at single molecule level and find that mRNAs decay cotranslationally, often from their 5′ ends, while frequently retaining poly(A) tails. TERA-Seq will prove useful in many applications where true end-to-end direct sequencing of single, native RNA molecules and their isoforms is desirable.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                18 November 2021
                24 August 2021
                24 August 2021
                : 49
                : 20
                : e115
                Affiliations
                Department of Pathology and Laboratory Medicine, Division of Neuropathology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA 19104, USA
                Department of Biochemistry and Molecular Biology, Sidney Kimmel Medical College, Thomas Jefferson University , Philadelphia, PA 19107, USA
                Department of Pathology and Laboratory Medicine, Division of Neuropathology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA 19104, USA
                Laboratory of Genetics and Genomics, National Institute on Aging, Intramural Research Program, National Institutes of Health , Baltimore, MD 21224, USA
                Department of Pathology and Laboratory Medicine, Division of Neuropathology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA 19104, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 215 746 0014; Email: mourelaz@ 123456uphs.upenn.edu
                Correspondence may also be addressed to Fadia Ibrahim. Tel: +1 215 503 4564; Email: fadia.ibrahim@ 123456jefferson.edu

                The authors wish it to be known that, in their opinion, the first three authors should be regarded as Joint First Authors.

                Author information
                https://orcid.org/0000-0002-4344-765X
                https://orcid.org/0000-0002-3076-4840
                https://orcid.org/0000-0002-3158-1763
                https://orcid.org/0000-0002-9852-1845
                Article
                gkab713
                10.1093/nar/gkab713
                8599856
                34428294
                25e43d94-42b4-4303-9993-9c997752fa2c
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 18 August 2021
                : 31 July 2021
                : 06 January 2021
                Page count
                Pages: 18
                Funding
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: GM133154
                Funded by: National Institute on Aging, DOI 10.13039/100000049;
                Categories
                AcademicSubjects/SCI00010
                Narese/9
                Methods Online

                Genetics
                Genetics

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