uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Computational and molecular tools for scalable rAAV-mediated genome editing
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
2015 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 43, no 5, e30Article in journal (Refereed) Published
Abstract [en]

The rapid discovery of potential driver mutations through large-scale mutational analyses of human cancers generates a need to characterize their cellular phenotypes. Among the techniques for genome editing, recombinant adeno-associated virus (rAAV)-mediated gene targeting is suited for knock-in of single nucleotide substitutions and to a lesser degree for gene knock-outs. However, the generation of gene targeting constructs and the targeting process is time-consuming and labor-intense. To facilitate rAAV-mediated gene targeting, we developed the first software and complementary automation-friendly vector tools to generate optimized targeting constructs for editing human protein encoding genes. By computational approaches, rAAV constructs for editing similar to 71% of bases in protein-coding exons were designed. Similarly, similar to 81% of genes were predicted to be targetable by rAAV-mediated knock-out. A Gateway-based cloning system for facile generation of rAAV constructs suitable for robotic automation was developed and used in successful generation of targeting constructs. Together, these tools enable automated rAAV targeting construct design, generation as well as enrichment and expansion of targeted cells with desired integrations.

Place, publisher, year, edition, pages
2015. Vol. 43, no 5, e30
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:uu:diva-252714DOI: 10.1093/nar/gku1286ISI: 000352487100003PubMedID: 25488813OAI: oai:DiVA.org:uu-252714DiVA: diva2:811302
Available from: 2015-05-11 Created: 2015-05-11 Last updated: 2017-12-04Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Authority records BETA

Stoimenov, IvayloAli, Muhammad AkhtarPandzic, TatjanaSjöblom, Tobias

Search in DiVA

By author/editor
Stoimenov, IvayloAli, Muhammad AkhtarPandzic, TatjanaSjöblom, Tobias
By organisation
Experimental and Clinical Oncology
In the same journal
Nucleic Acids Research
Cancer and Oncology

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 596 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf