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Flow cytometry-based functional selection of RNA interference triggers for efficient epi-allelic analysis of therapeutic targets

BACKGROUND: The dose-response relationship is a fundamental pharmacological parameter necessary to determine therapeutic thresholds. Epi-allelic hypomorphic analysis using RNA interference (RNAi) can similarly correlate target gene dosage with cellular phenotypes. This however requires a set of RNAi...

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Detalles Bibliográficos
Autores principales: Micklem, David R, Blø, Magnus, Bergström, Petra, Hodneland, Erlend, Tiron, Crina, Høiby, Torill, Gjerdrum, Christine, Hammarsten, Ola, Lorens, James B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074332/
https://www.ncbi.nlm.nih.gov/pubmed/24952598
http://dx.doi.org/10.1186/1472-6750-14-57
Descripción
Sumario:BACKGROUND: The dose-response relationship is a fundamental pharmacological parameter necessary to determine therapeutic thresholds. Epi-allelic hypomorphic analysis using RNA interference (RNAi) can similarly correlate target gene dosage with cellular phenotypes. This however requires a set of RNAi triggers empirically determined to attenuate target gene expression to different levels. RESULTS: In order to improve our ability to incorporate epi-allelic analysis into target validation studies, we developed a novel flow cytometry-based functional screening approach (CellSelectRNAi) to achieve unbiased selection of shRNAs from high-coverage libraries that knockdown target gene expression to predetermined levels. Employing a Gaussian probability model we calculated that knockdown efficiency is inferred from shRNA sequence frequency profiles derived from sorted hypomorphic cell populations. We used this approach to generate a hypomorphic epi-allelic cell series of shRNAs to reveal a functional threshold for the tumor suppressor p53 in normal and transformed cells. CONCLUSION: The unbiased CellSelectRNAi flow cytometry-based functional screening approach readily provides an epi-allelic series of shRNAs for graded reduction of target gene expression and improved phenotypic validation.