A computational analysis of antisense off-targets in prokaryotic organisms
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© 2014 .The adoption of antisense gene silencing as a novel disinfectant for prokaryotic organisms is hindered by poor silencing efficiencies. Few studies have considered the effects of off-targets on silencing efficiencies, especially in prokaryotic organisms. In this computational study, a novel algorithm was developed that determined and sorted the number of off-targets as a function of alignment length in Escherichia coli K-12 MG1655 and Mycobacterium tuberculosis H37Rv. The mean number of off-targets per a single location was calculated to be 14.1. ±. 13.3 and 36.1. ±. 58.5 for the genomes of E. coli K-12 MG1655 and M. tuberculosis H37Rv, respectively. Furthermore, when the entire transcriptome was analyzed, it was found that there was no general gene location that could be targeted to minimize or maximize the number of off-targets. In an effort to determine the effects of off-targets on silencing efficiencies, previously published studies were used. Analyses with acpP, ino1, and marORAB revealed a statistically significant relationship between the number of short alignment length off-targets hybrids and the efficacy of the antisense gene silencing, suggesting that the minimization of off-targets may be beneficial for antisense gene silencing in prokaryotic organisms.
Published Version (Please cite this version)10.1016/j.ygeno.2014.11.010
Publication InfoGunsch, Claudia K; & Worley-Morse, TO (2015). A computational analysis of antisense off-targets in prokaryotic organisms. Genomics, 105(2). pp. 123-130. 10.1016/j.ygeno.2014.11.010. Retrieved from http://hdl.handle.net/10161/11463.
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Theodore Kennedy Associate Professor
Dr. Gunsch’s research focuses characterizing and engineering environmental microbiomes. Students and postdoctoral associates in her group apply fundamental concepts from the fields of microbiology, genomics and bioinformatics to environmental engineering applications. Current research projects focus on exploring ballast water microbiomes, exploring correlations between microbial adaptation and evolution stemming from their exposure to contaminants, characterizing the fate of genetica