TY - JOUR
T1 - Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
AU - Doench, John G.
AU - Fusi, Nicolo
AU - Sullender, Meagan
AU - Hegde, Mudra
AU - Vaimberg, Emma W.
AU - Donovan, Katherine F.
AU - Smith, Ian
AU - Tothova, Zuzana
AU - Wilen, Craig
AU - Orchard, Robert
AU - Virgin, Herbert W.
AU - Listgarten, Jennifer
AU - Root, David E.
N1 - Funding Information:
We thank M. Tomko, M. Greene, A. Brown, D. Alan and T. Green for software engineering support, and T. Nguyen, N. Tran and X. Yang for library production support (Broad Institute). Z.T. is funded by NIH 5K12CA087723-12, ASCO Young Investigator Award, LLS Special Fellow Award. J.G.D. is a Merkin Institute Fellow and is supported by the Next Generation Fund at the Broad Institute of MIT and Harvard.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - CRISPR-Cas9-based genetic screens are a powerful new tool in biology. By simply altering the sequence of the single-guide RNA (sgRNA), one can reprogram Cas9 to target different sites in the genome with relative ease, but the on-target activity and off-target effects of individual sgRNAs can vary widely. Here, we use recently devised sgRNA design rules to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results. Additionally, we profile the off-target activity of thousands of sgRNAs and develop a metric to predict off-target sites. We incorporate these findings from large-scale, empirical data to improve our computational design rules and create optimized sgRNA libraries that maximize on-target activity and minimize off-target effects to enable more effective and efficient genetic screens and genome engineering.
AB - CRISPR-Cas9-based genetic screens are a powerful new tool in biology. By simply altering the sequence of the single-guide RNA (sgRNA), one can reprogram Cas9 to target different sites in the genome with relative ease, but the on-target activity and off-target effects of individual sgRNAs can vary widely. Here, we use recently devised sgRNA design rules to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results. Additionally, we profile the off-target activity of thousands of sgRNAs and develop a metric to predict off-target sites. We incorporate these findings from large-scale, empirical data to improve our computational design rules and create optimized sgRNA libraries that maximize on-target activity and minimize off-target effects to enable more effective and efficient genetic screens and genome engineering.
UR - https://www.scopus.com/pages/publications/84957605863
U2 - 10.1038/nbt.3437
DO - 10.1038/nbt.3437
M3 - Article
C2 - 26780180
AN - SCOPUS:84957605863
SN - 1087-0156
VL - 34
SP - 184
EP - 191
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 2
ER -