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.

Calabria, A., Beretta, S., Merelli, I., Spinozzi, G., Brasca, S., Pirola, Y., et al. (2020). γ-TRIS: A graph-algorithm for comprehensive identification of vector genomic insertion sites. BIOINFORMATICS, 36(5), 1622-1624 [10.1093/bioinformatics/btz747].

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

Beretta S.
Co-primo
;
Spinozzi G.;Pirola Y.;Bonizzoni P.;
2020

Abstract

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.
Articolo in rivista - Articolo scientifico
graph; genome-free; insertion sites
English
2020
36
5
1622
1624
none
Calabria, A., Beretta, S., Merelli, I., Spinozzi, G., Brasca, S., Pirola, Y., et al. (2020). γ-TRIS: A graph-algorithm for comprehensive identification of vector genomic insertion sites. BIOINFORMATICS, 36(5), 1622-1624 [10.1093/bioinformatics/btz747].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/265940
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