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      The N-glycosylation defect in Lec5 and Lec9 CHO cells is caused by absence of the DHRSX gene

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          Abstract

          Glycosylation-deficient Chinese hamster ovary (CHO) cell lines have been instrumental in the discovery of N-glycosylation machinery. Yet, the molecular causes of the glycosylation defects in the Lec5 and Lec9 mutants have been elusive, even though for both cell lines a defect in dolichol formation from polyprenol was previously established. We recently found that dolichol synthesis from polyprenol occurs in three steps consisting of the conversion of polyprenol to polyprenal by DHRSX, the reduction of polyprenal to dolichal by SRD5A3 and the reduction of dolichal to dolichol, again by DHRSX.

          This led us to investigate defective dolichol synthesis in Lec5 and Lec9 cells. Both cell lines showed increased levels of polyprenol and its derivatives, concomitant with decreased levels of dolichol and derivatives, but no change in polyprenal levels, suggesting DHRSX deficiency. Accordingly, N-glycan synthesis and changes in polyisoprenoid levels were corrected by complementation with human DHRSX but not with SRD5A3. Furthermore, the typical polyprenol dehydrogenase and dolichal reductase activities of DHRSX were absent in membrane preparations derived from Lec5 and Lec9 cells, while the reduction of polyprenal to dolichal, catalyzed by SRD5A3, was unaffected. Long-read whole genome sequencing of Lec5 and Lec9 cells did not reveal mutations in the ORF of SRD5A3, but the genomic region containing DHRSX was absent. Lastly, we established the sequence of Chinese hamster DHRSX and validated that this protein has similar kinetic properties to the human enzyme. Our work therefore identifies the basis of the dolichol synthesis defect in CHO Lec5 and Lec9 cells.

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          Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

          Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today’s sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license.
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            Assembly of long, error-prone reads using repeat graphs

            Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.
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              Fast and accurate de novo genome assembly from long uncorrected reads

              The assembly of long reads from Pacific Biosciences and Oxford Nanopore Technologies typically requires resource-intensive error-correction and consensus-generation steps to obtain high-quality assemblies. We show that the error-correction step can be omitted and that high-quality consensus sequences can be generated efficiently with a SIMD-accelerated, partial-order alignment–based, stand-alone consensus module called Racon. Based on tests with PacBio and Oxford Nanopore data sets, we show that Racon coupled with miniasm enables consensus genomes with similar or better quality than state-of-the-art methods while being an order of magnitude faster.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                2692-8205
                18 June 2024
                : 2024.06.18.599300
                Affiliations
                [1 ]Metabolic Research Group, de Duve Institute & WELRI, Université Catholique de Louvain, 1200 Brussels, Belgium
                [2 ]Laboratory for Molecular Diagnosis, Center for Human Genetics, KU Leuven, Leuven 3000, Belgium
                [3 ]Univ. Lille, CNRS, UMR 8576 – UGSF - Unité de Glycobiologie Structurale et Fonctionnelle, F- 59000 Lille, France
                [4 ]Laboratory for Cytogenetics and Genome Research, Department of Human Genetics, KU Leuven, B-3000 Leuven, Belgium.
                [5 ]Department of Cell Biology, Albert Einstein College of Medicine, New York, NY, USA.
                [6 ]Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT 06511, USA.
                [7 ]Department of Pharmacology, Yale School of Medicine, New Haven, CT 06511, USA.
                Author notes
                [#]

                These authors contributed equally

                Author information
                http://orcid.org/0000-0003-2252-8730
                Article
                10.1101/2024.06.18.599300
                11212957
                38948797
                cfd5912e-3b23-4ebe-8095-7067239b3d4f

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

                History
                Funding
                Funded by: French National Agency
                Award ID: ANR-21-CE14-0049-01
                Funded by: CNRS IRP GLYCOCDG project, FWO senior postdoctoral fellowship
                Award ID: 1289023N
                Funded by: Jaeken-Theunissen CDG Fund, Mizutani Foundation for Glycoscience
                Award ID: 210119
                Award ID: 240097
                Funded by: CELSA fund, KU Leuven Global PhD Partnership
                Award ID: 3M200250
                Funded by: ERC consolidator
                Award ID: #771704
                Funded by: Fondation Médicale Reine Elisabeth, FNRS equipment grant and research credit, ARC UCLouvain, FWO-FNRS WEAVE program
                Award ID: G061524N
                Funded by: Fonds Baillet-Latour, NIH
                Award ID: R01 GM105399
                Categories
                Article

                glycosylation,n-linked glycosylation,glycobiology,glycoprotein biosynthesis,glycoconjugate,isoprenoid,lipid synthesis,dolichol,polyprenol,polyprenal,cho glycosylation mutants

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