2022
DOI: 10.1038/s41467-022-28540-0
|View full text |Cite
|
Sign up to set email alerts
|

Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica

Abstract: Genome-wide functional genetic screens have been successful in discovering genotype-phenotype relationships and in engineering new phenotypes. While broadly applied in mammalian cell lines and in E. coli, use in non-conventional microorganisms has been limited, in part, due to the inability to accurately design high activity CRISPR guides in such species. Here, we develop an experimental-computational approach to sgRNA design that is specific to an organism of choice, in this case the oleaginous yeast Yarrowia… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
46
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
3
2
1

Relationship

2
4

Authors

Journals

citations
Cited by 33 publications
(46 citation statements)
references
References 51 publications
0
46
0
Order By: Relevance
“…The pooled guide libraries contain single guide RNAs (sgRNAs) that target more than 98.5% of the protein-coding sequences with 6-and 8-fold coverage for Cas9 and Cas12a, respectively. Guide activity in these libraries was previously reported 9,16 ; a cutting score (CS), defined as the - log 2 ratio of normalized read counts obtained in PO1f Cas9/12a ΔKU70 to counts in the control strain, was determined for each guide ( Fig. 1a ).…”
Section: Resultsmentioning
confidence: 99%
See 4 more Smart Citations
“…The pooled guide libraries contain single guide RNAs (sgRNAs) that target more than 98.5% of the protein-coding sequences with 6-and 8-fold coverage for Cas9 and Cas12a, respectively. Guide activity in these libraries was previously reported 9,16 ; a cutting score (CS), defined as the - log 2 ratio of normalized read counts obtained in PO1f Cas9/12a ΔKU70 to counts in the control strain, was determined for each guide ( Fig. 1a ).…”
Section: Resultsmentioning
confidence: 99%
“…Thus, we sought to test the performance of acCRISPR using computationally predicted sgRNA activity scores. Among the large set of guide prediction tools available for Cas9, we selected DeepGuide 16 , uCRISPR 24 , Designer v1 25 , Designer v2 26 , SSC 27 , CRISPRscan 28 , and CRISPRspec 29 ( Fig. 4 and Supplementary File 9 ).…”
Section: Resultsmentioning
confidence: 99%
See 3 more Smart Citations