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      Epstein-Barr Virus (EBV) Is Mostly Latent and Clonal in Angioimmunoblastic T Cell Lymphoma (AITL)

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      Cancers
      MDPI AG

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          Abstract

          The Epstein-Barr virus (EBV) is associated with angioimmunoblastic T cell lymphoma (AITL), a peripheral T lymphoma of poor prognosis in at least 90% of cases. The role of EBV in this pathology is unknown. Using next-generation sequencing, we sequenced the entire EBV genome in biopsies from 18 patients with AITL, 16 patients with another EBV-associated lymphoma, and 2 controls. We chose an EBV target capture method, given the high specificity of this technique, followed by a second capture to increase sensitivity. We identified two main viral strains in AITL, one of them associated with the mutations BNRF1 S542N and BZLF1 A206S and with mutations in the EBNA-3 and LMP-2 genes. This strain was characterized in patients with short post-diagnosis survival. The main mutations found during AITL on the most mutated latency or tegument genes were identified and discussed. We showed that the virus was clonal in all the AITL samples, suggesting that it may be involved in this pathology. Additionally, EBV was latent in all the AITL samples; for one sample only, the virus was found to be latent and probably replicative, depending on the cells. These various elements support the role of EBV in AITL.

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          Most cited references73

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                CANCCT
                Cancers
                Cancers
                MDPI AG
                2072-6694
                June 2022
                June 12 2022
                : 14
                : 12
                : 2899
                Article
                10.3390/cancers14122899
                9221046
                35740565
                20ad3b5c-45a6-4b16-8a15-14aa8039565e
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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