γ-TRIS: a graph-algorithm for comprehensive identification of vector genomic insertion sites

Abstract Summary Retroviruses and their vector derivatives integrate semi-randomly in the genome of host cells and are inherited by their progeny as stable genetic marks. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites in...

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Veröffentlicht in:Bioinformatics Jg. 36; H. 5; S. 1622 - 1624
Hauptverfasser: Calabria, Andrea, Beretta, Stefano, Merelli, Ivan, Spinozzi, Giulio, Brasca, Stefano, Pirola, Yuri, Benedicenti, Fabrizio, Tenderini, Erika, Bonizzoni, Paola, Milanesi, Luciano, Montini, Eugenio
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Oxford University Press 01.03.2020
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ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Zusammenfassung:Abstract Summary Retroviruses and their vector derivatives integrate semi-randomly in the genome of host cells and are inherited by their progeny as stable genetic marks. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites in gene therapy or virally infected patients, essential for monitoring the evolution of genetically modified cells in vivo. However, since ∼30% of insertions land in low complexity or repetitive regions of the host cell genome, they cannot be correctly assigned and are currently discarded, limiting the accuracy and predictive power of clonal tracking studies. Here, we present γ-TRIS, a new graph-based genome-free alignment tool for identifying insertion sites even if embedded in low complexity regions. By using γ-TRIS to reanalyze clinical studies, we observed improvements in clonal quantification and tracking. Availability and implementation Source code at https://bitbucket.org/bereste/g-tris. Supplementary information Supplementary data are available at Bioinformatics online.
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The authors wish it to be known that, in their opinion, Andrea Calabria, Stefano Beretta and Ivan Merelli should be regarded as Joint First Authors.
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btz747