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      Functional integration of a semi-synthetic azido-queuosine derivative into translation and a tRNA modification circuit

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          Abstract

          Substitution of the queuine nucleobase precursor preQ 1 by an azide-containing derivative (azido-propyl-preQ 1) led to incorporation of this clickable chemical entity into tRNA via transglycosylation in vitro as well as in vivo in Escherichia coli, Schizosaccharomyces pombe and human cells. The resulting semi-synthetic RNA modification, here termed Q-L1, was present in tRNAs on actively translating ribosomes, indicating functional integration into aminoacylation and recruitment to the ribosome. The azide moiety of Q-L1 facilitates analytics via click conjugation of a fluorescent dye, or of biotin for affinity purification. Combining the latter with RNAseq showed that TGT maintained its native tRNA substrate specificity in S . pombe cells. The semi-synthetic tRNA modification Q-L1 was also functional in tRNA maturation, in effectively replacing the natural queuosine in its stimulation of further modification of tRNA Asp with 5-methylcytosine at position 38 by the tRNA methyltransferase Dnmt2 in S. pombe. This is the first demonstrated in vivo integration of a synthetic moiety into an RNA modification circuit, where one RNA modification stimulates another. In summary, the scarcity of queuosinylation sites in cellular RNA, makes our synthetic q/Q system a ‘minimally invasive’ system for placement of a non-natural, clickable nucleobase within the total cellular RNA.

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          Most cited references79

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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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
                14 October 2022
                28 September 2022
                28 September 2022
                : 50
                : 18
                : 10785-10800
                Affiliations
                Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz , 55128 Mainz, Germany
                Institute of Biology, Humboldt-Universität zu Berlin , 10117 Berlin, Germany
                Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz , 55128 Mainz, Germany
                Department of Organic Chemistry, University of Innsbruck , 6020 Innsbruck, Austria
                Department of Chemistry – Biochemistry, Johannes Gutenberg-University Mainz , 55128 Mainz, Germany
                Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz , 55128 Mainz, Germany
                Division of Biochemistry, Mannheim Institute for Innate Immunoscience (MI3), Medical Faculty Mannheim, Heidelberg University , Mannheim, Germany
                Department of Organic Chemistry, University of Innsbruck , 6020 Innsbruck, Austria
                Institute of Biology, Humboldt-Universität zu Berlin , 10117 Berlin, Germany
                Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz , 55128 Mainz, Germany
                Author notes
                To whom correspondence should be addressed. Tel: +49 6131 39 25731; Fax: +49 6131 39 20373; Email: mhelm@ 123456uni-mainz.de
                Correspondence may also be addressed to Ann E. Ehrenhofer-Murray. Tel: +49 30 2093 49630; Fax: +49 30 2093 49641; Email: ann.ehrenhofer-murray@ 123456hu-berlin.de

                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/0000-0003-0740-8618
                https://orcid.org/0000-0003-1625-1181
                https://orcid.org/0000-0003-2661-6105
                https://orcid.org/0000-0001-8709-1942
                https://orcid.org/0000-0002-0154-0928
                Article
                gkac822
                10.1093/nar/gkac822
                9561289
                36169220
                a30e1815-2787-4bd4-8239-8922d727575f
                © The Author(s) 2022. 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 License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 September 2022
                : 09 September 2022
                : 15 June 2022
                Page count
                Pages: 16
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Award ID: TRR-319 TP C03
                Award ID: SPP1784
                Award ID: HE 3397/13-2
                Award ID: HE 3397/14-2
                Award ID: TRR-319 TP A06
                Award ID: TRR-319 TP B05
                Award ID: DFG SPP1784
                Funded by: Austrian Science Fund, DOI 10.13039/501100002428;
                Award ID: P31691
                Award ID: F8011-B
                Funded by: Johannes Gutenberg University;
                Categories
                AcademicSubjects/SCI00010
                Synthetic Biology and Bioengineering

                Genetics
                Genetics

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