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Therapeutic Discovery for Friedreich Ataxia Using Random shRNA Selection

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MLA citation style (9th ed.)

Kaur, Avinash, Cotticelli, M, and Xia, Shujuan. Therapeutic Discovery for Friedreich Ataxia Using Random Shrna Selection. . 1120. mushare.marian.edu/concern/generic_works/ed208918-8893-4c86-b4b5-eb93fed6947c?locale=it.

APA citation style (7th ed.)

K. Avinash, C. M, & X. Shujuan. (1120). Therapeutic Discovery for Friedreich Ataxia Using Random shRNA Selection. https://mushare.marian.edu/concern/generic_works/ed208918-8893-4c86-b4b5-eb93fed6947c?locale=it

Chicago citation style (CMOS 17, author-date)

Kaur, Avinash, Cotticelli, M., and Xia, Shujuan. Therapeutic Discovery for Friedreich Ataxia Using Random Shrna Selection. 1120. https://mushare.marian.edu/concern/generic_works/ed208918-8893-4c86-b4b5-eb93fed6947c?locale=it.

Note: These citations are programmatically generated and may be incomplete.

2 fold, either as a vector-expressed shRNA or as a transfected siRNA. We randomly mutagenized gFA2 to create a gFA2 variant sub-library. We screened this sub-library in primary FA fibroblasts and identified two gFA2 variants, gFA2.8 and gFA2.10, that further increase frataxin expression. Microarray analyses of primary FA fibroblasts expressing another hit shRNA, gFA11, revealed alterations in ~350 mRNAs. Bioinformatic pathway analyses indicated significant changes in mRNAs involved in cytokine secretion; we confirmed significant changes in cytokine secretion induced by gFA11 biochemically. Ingenuity Pathway Analysis revealed that inhibition of a known transcription factor, or treatment of cells with a previously studied chemical compound, induced a statistically similar pattern of gene expression to that induced by gFA11. Inhibition of the transcription factor using a directed siRNA in primary FA fibroblasts, as well as treatment of the cells with the chemical compound, recapitulated the phenotype induced by gFA11, namely reversal of decreased growth/survival in mitochondrial stress media. We are currently planning similar microarray and bioinformatics analyses of the optimized versions of gFA2. Combined with microarray analyses and bioinformatic pattern-matching, our random, shRNA library screens potentially yield, 1) small-RNA therapeutic candidates, 2) conventional chemical-compound therapeutic candidates, 3) drug-target candidates, and 4) elucidation of disease mechanisms, which may inform additional therapeutic initiatives.

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