SARS-CoV-2 infection induces epigenetic changes in the LTR69 subfamily of endogenous retroviruses

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Abstract

Accumulating evidence suggests that endogenous retroviruses (ERVs) play an important role in the host response to infection and the development of disease. By analyzing ChIP-sequencing data sets, we show that SARS-CoV-2 infection induces H3K27 acetylation of several loci within the LTR69 subfamily of ERVs. Using functional assays, we identified one SARS-CoV-2-activated LTR69 locus, termed Dup69, which exhibits regulatory activity and is responsive to the transcription factors IRF3 and p65/RELA. LTR69_Dup69 is located about 500 bp upstream of a long non-coding RNA gene (ENSG00000289418) and within the PTPRN2 gene encoding a diabetes-associated autoantigen. Both ENSG00000289418 and PTPRN2 showed a significant increase in expression upon SARS-CoV-2 infection. Thus, our study sheds light on the interplay of exogenous with endogenous viruses and helps to understand how ERVs regulate gene expression during infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13100-023-00299-1.

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

Michael Love, Wolfgang Huber, Simon Anders (2014)

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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STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

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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Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2012)

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

Ankit Arora: aankit@instem.res.in

Vikas Bansal: vikas.bansal@dzne.de

Journal

Journal ID (nlm-ta): Mob DNA

Journal ID (iso-abbrev): Mob DNA

Title: Mobile DNA

Publisher: BioMed Central (London )

ISSN (Electronic): 1759-8753

Publication date (Electronic): 4 September 2023

Publication date PMC-release: 4 September 2023

Publication date Collection: 2023

Volume: 14

Electronic Location Identifier: 11

Affiliations

[1 ]GRID grid.475408.a, ISNI 0000 0004 4905 7710, Institute for Stem Cell Science and Regenerative Medicine, ; Bengaluru, India

[2 ]GRID grid.411544.1, ISNI 0000 0001 0196 8249, Institute for Medical Virology and Epidemiology of Viral Diseases, , University Hospital Tübingen, ; Tübingen, Germany

[3 ]GRID grid.5386.8, ISNI 000000041936877X, Department of Molecular Biology and Genetics, , Cornell University, ; Ithaca, NY 14853 USA

[4 ]GRID grid.424247.3, ISNI 0000 0004 0438 0426, German Center for Neurodegenerative Diseases (DZNE), ; Tübingen, Germany

Article

Publisher ID: 299

DOI: 10.1186/s13100-023-00299-1

PMC ID: 10476400

PubMed ID: 37667401

SO-VID: 6165952b-c285-4bd8-93d6-4c484e8b91cc

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 12 April 2023

Date accepted : 21 August 2023

Funding

Funded by: Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE) in der Helmholtz-Gemeinschaft (4203)

Open Access :

Open Access funding enabled and organized by Projekt DEAL.

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: sars-cov-2,transposable elements,endogenous retroviruses,solo-ltrs,ltr69

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ScienceOpen disciplines: Genetics

Keywords: sars-cov-2, transposable elements, endogenous retroviruses, solo-ltrs, ltr69

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SARS-CoV-2 infection induces epigenetic changes in the LTR69 subfamily of endogenous retroviruses

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Supplementary Information

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Novel Coronavirus Disease COVID-19

Most cited references 38

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

STAR: ultrafast universal RNA-seq aligner.

Fast gapped-read alignment with Bowtie 2.

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