Optimizing complex phenotypes through model-guided multiplex genome engineering

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Optimizing complex phenotypes through model-guided multiplex genome engineering

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Title: Optimizing complex phenotypes through model-guided multiplex genome engineering
Author: Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.; Landon, Matthieu; Rohland, Nadin; Aach, John; Lajoie, Marc J.; Church, George M.

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Citation: Kuznetsov, Gleb, Daniel B. Goodman, Gabriel T. Filsinger, Matthieu Landon, Nadin Rohland, John Aach, Marc J. Lajoie, and George M. Church. 2017. “Optimizing complex phenotypes through model-guided multiplex genome engineering.” Genome Biology 18 (1): 100. doi:10.1186/s13059-017-1217-z. http://dx.doi.org/10.1186/s13059-017-1217-z.
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Abstract: We present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.∆A. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1217-z) contains supplementary material, which is available to authorized users.
Published Version: doi:10.1186/s13059-017-1217-z
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445303/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:33029937
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