Validating genome-wide CRISPR-Cas9 function improves screening in the oleaginous yeast Yarrowia lipolytica

Schwartz, Cory; Cheng, Jan-Fang; Evans, Robert; Schwartz, Christopher A.; Wagner, James M.; Anglin, Scott; Beitz, Adam; Pan, Weihua; Lonardi, Stefano; Blenner, Mark; Alper, Hal S.; Yoshikuni, Yasuo; Wheeldon, Ian

doi:10.1016/j.ymben.2019.06.007

Title: Validating genome-wide CRISPR-Cas9 function improves screening in the oleaginous yeast Yarrowia lipolytica

Journal Article · Sun Jun 16 00:00:00 EDT 2019 · Metabolic Engineering

DOI:https://doi.org/10.1016/j.ymben.2019.06.007· OSTI ID:1597716

Schwartz, Cory ^[1]; Cheng, Jan-Fang ^[2]; Evans, Robert ^[2]; Schwartz, Christopher A. ^[3]; Wagner, James M. ^[4]; Anglin, Scott ^[5]; Beitz, Adam ^[5]; Pan, Weihua ^[1]; Lonardi, Stefano ^[1]; Blenner, Mark ^[5]; Alper, Hal S. ^[4]; Yoshikuni, Yasuo ^[2]; Wheeldon, Ian ^[1]

Univ. of California, Riverside, CA (United States)
USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
United States Military Academy, West Point, NY (United States)
Univ. of Texas, Austin, TX (United States)
Clemson Univ., Clemson, SC (United States)

Genome-wide mutational screens are central to understanding the genetic underpinnings of evolved and engineered phenotypes. The widespread adoption of CRISPR-Cas9 genome editing has enabled such screens in many organisms, but identifying functional sgRNAs still remains a challenge. Here, we developed a methodology to quantify the cutting efficiency of each sgRNA in a genome-scale library, and in doing so improve screens in the biotechnologically important yeast Yarrowia lipolytica. Screening in the presence and absence of native DNA repair enabled high-throughput quantification of sgRNA function leading to the identification of high efficiency sgRNAs that cover 94% of genes. Library validation enhanced the classification of essential genes by identifying inactive guides that create false negatives and mask the effects of successful disruptions. Quantification of guide effectiveness also creates a dataset from which determinants of CRISPR-Cas9 can be identified. Finally, application of the library identified novel mutations for metabolic engineering of high lipid accumulation.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC); National Science Foundation (NSF)

Grant/Contract Number:: AC02-05CH11231; CSP-503076; NSF 1706545; N00014-15-1-2785; NSF 1706134; NSF 1526742

OSTI ID:: 1597716

Alternate ID(s):: OSTI ID: 1779369

Journal Information:: Metabolic Engineering, Vol. 55, Issue C; ISSN 1096-7176

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 47 works

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