PT  - JOURNAL ARTICLE
AU  - Lin Yang
AU  - Yuqing Zhu
AU  - Hua Yu
AU  - Sitong Chen
AU  - Yulan Chu
AU  - He Huang
AU  - Jin Zhang
AU  - Wei Li
TI  - Linking genotypes with multiple phenotypes in single-cell CRISPR screens
AID  - 10.1101/658146
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 658146
4099  - http://biorxiv.org/content/early/2019/06/03/658146.short
4100  - http://biorxiv.org/content/early/2019/06/03/658146.full
AB  - CRISPR/Cas9 based functional screening coupled with single-cell RNA-seq (“single-cell CRISPR screening”) unravels gene regulatory networks and enhancer-gene regulations in a large scale. We propose scMAGeCK, a computational framework to systematically identify genes and non-coding elements associated with multiple expression-based phenotypes in single-cell CRISPR screening. scMAGeCK identified genes and enhancers that modulate the expression of a known proliferation marker, MKI67 (Ki-67), a result that resembles the outcome of proliferation-linked CRISPR screening. We further performed single-cell CRISPR screening on mouse embryonic stem cells (mESC), and identified key genes associated with different pluripotency states. scMAGeCK enabled an unbiased construction of genotype-phenotype network, where multiple phenotypes can be regulated by different gene perturbations. Finally, we studied key factors that improve the statistical power of single-cell CRISPR screens, including target gene expression and the number of guide RNAs (gRNAs) per cell. Collectively, scMAGeCK is a novel and effective computational tool to study genotype-phenotype relationships at a single-cell level.