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Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors

Integration of retroviral vectors in the human genome follows non random patterns that favor insertional deregulation of gene expression and may cause risks of insertional mutagenesis when used in clinical gene therapy. Understanding how viral vectors integrate into the human genome is a key issue i...

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Autores principales: Ambrosi, Alessandro, Glad, Ingrid K., Pellin, Danilo, Cattoglio, Claudia, Mavilio, Fulvio, Di Serio, Clelia, Frigessi, Arnoldo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3228801/
https://www.ncbi.nlm.nih.gov/pubmed/22144885
http://dx.doi.org/10.1371/journal.pcbi.1002292
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author Ambrosi, Alessandro
Glad, Ingrid K.
Pellin, Danilo
Cattoglio, Claudia
Mavilio, Fulvio
Di Serio, Clelia
Frigessi, Arnoldo
author_facet Ambrosi, Alessandro
Glad, Ingrid K.
Pellin, Danilo
Cattoglio, Claudia
Mavilio, Fulvio
Di Serio, Clelia
Frigessi, Arnoldo
author_sort Ambrosi, Alessandro
collection PubMed
description Integration of retroviral vectors in the human genome follows non random patterns that favor insertional deregulation of gene expression and may cause risks of insertional mutagenesis when used in clinical gene therapy. Understanding how viral vectors integrate into the human genome is a key issue in predicting these risks. We provide a new statistical method to compare retroviral integration patterns. We identified the positions where vectors derived from the Human Immunodeficiency Virus (HIV) and the Moloney Murine Leukemia Virus (MLV) show different integration behaviors in human hematopoietic progenitor cells. Non-parametric density estimation was used to identify candidate comparative hotspots, which were then tested and ranked. We found 100 significative comparative hotspots, distributed throughout the chromosomes. HIV hotspots were wider and contained more genes than MLV ones. A Gene Ontology analysis of HIV targets showed enrichment of genes involved in antigen processing and presentation, reflecting the high HIV integration frequency observed at the MHC locus on chromosome 6. Four histone modifications/variants had a different mean density in comparative hotspots (H2AZ, H3K4me1, H3K4me3, H3K9me1), while gene expression within the comparative hotspots did not differ from background. These findings suggest the existence of epigenetic or nuclear three-dimensional topology contexts guiding retroviral integration to specific chromosome areas.
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spelling pubmed-32288012011-12-05 Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors Ambrosi, Alessandro Glad, Ingrid K. Pellin, Danilo Cattoglio, Claudia Mavilio, Fulvio Di Serio, Clelia Frigessi, Arnoldo PLoS Comput Biol Research Article Integration of retroviral vectors in the human genome follows non random patterns that favor insertional deregulation of gene expression and may cause risks of insertional mutagenesis when used in clinical gene therapy. Understanding how viral vectors integrate into the human genome is a key issue in predicting these risks. We provide a new statistical method to compare retroviral integration patterns. We identified the positions where vectors derived from the Human Immunodeficiency Virus (HIV) and the Moloney Murine Leukemia Virus (MLV) show different integration behaviors in human hematopoietic progenitor cells. Non-parametric density estimation was used to identify candidate comparative hotspots, which were then tested and ranked. We found 100 significative comparative hotspots, distributed throughout the chromosomes. HIV hotspots were wider and contained more genes than MLV ones. A Gene Ontology analysis of HIV targets showed enrichment of genes involved in antigen processing and presentation, reflecting the high HIV integration frequency observed at the MHC locus on chromosome 6. Four histone modifications/variants had a different mean density in comparative hotspots (H2AZ, H3K4me1, H3K4me3, H3K9me1), while gene expression within the comparative hotspots did not differ from background. These findings suggest the existence of epigenetic or nuclear three-dimensional topology contexts guiding retroviral integration to specific chromosome areas. Public Library of Science 2011-12-01 /pmc/articles/PMC3228801/ /pubmed/22144885 http://dx.doi.org/10.1371/journal.pcbi.1002292 Text en Ambrosi et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Ambrosi, Alessandro
Glad, Ingrid K.
Pellin, Danilo
Cattoglio, Claudia
Mavilio, Fulvio
Di Serio, Clelia
Frigessi, Arnoldo
Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors
title Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors
title_full Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors
title_fullStr Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors
title_full_unstemmed Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors
title_short Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors
title_sort estimated comparative integration hotspots identify different behaviors of retroviral gene transfer vectors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3228801/
https://www.ncbi.nlm.nih.gov/pubmed/22144885
http://dx.doi.org/10.1371/journal.pcbi.1002292
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