Project description:Optimized sgRNA design to maximize activity and minimize off-target effects for genetic screens with CRISPR-Cas9 raw sequence reads
Project description:The development of CRISPR genetic screening tools has improved functional genomics, as these tools enable precise genomic editing, provide broad access to genomic regions beyond protein-coding genes, and have fewer off-target effects than other functional genomics modalities, allowing for novel applications with smaller library sizes compared to prior technologies. Pooled functional genomics screens require high cellular coverage per perturbation to accurately quantify phenotypes and average out phenotype-independent variability across the population. While more compact libraries have decreased the number of cells needed for a given screen, the cell coverage required for large-scale CRISPR screens still poses technical hurdles to screen in more challenging systems, such as iPSC-derived and primary cells. A major factor that influences cell coverage is screening library uniformity, as larger variation in individual guide RNA abundance requires higher cell coverage to reliably measure low-abundance guides. In this work, we have systematically optimized guide RNA cloning procedures to decrease bias. We implement these protocols to demonstrate that CRISPRi screens using 10-fold fewer cells than the current standard provides equivalent statistically significant hit-calling results to screens run at higher coverage, opening the possibility of conducting genome-wide and other large-scale CRISPR screens in technically challenging models.
Project description:Systematic mapping of genetic interactions and interrogation of the functions of sizeable genomic segments in mammalian cells represent important goals of biomedical research. To advance these goals, we present a CRISPR-based screening system for combinatorial genetic manipulation that employs co-expression of Cas9 and Cas12a nucleases and machine learning-optimized libraries of hybrid Cas9-Cas12a guide RNAs. This system, named CHyMErA (Cas Hybrid for Multiplexed Editing and Screening Applications), outperforms genetic screens using Cas9 or Cas12a editing alone. Application of CHyMErA to the ablation of mammalian paralog gene pairs reveals extensive genetic interactions and uncovers phenotypes normally masked by functional redundancy. Application of CHyMErA in a chemo-genetic interaction screen identifies genes that impact cell growth in response to mTOR pathway inhibition. Moreover, by systematically targeting thousands of alternative splicing events, CHyMErA identifies exons underlying human cell line fitness. CHyMErA thus represents an effective screening approach for genetic interaction mapping and the functional analysis of sizeable genomic regions, such as alternative exons.
Project description:Systematic mapping of genetic interactions and interrogation of the functions of sizeable genomic segments in mammalian cells represent important goals of biomedical research. To advance these goals, we present a CRISPR-based screening system for combinatorial genetic manipulation that employs co-expression of Cas9 and Cas12a nucleases and machine learning-optimized libraries of hybrid Cas9-Cas12a guide RNAs. This system, named CHyMErA (Cas Hybrid for Multiplexed Editing and Screening Applications), outperforms genetic screens using Cas9 or Cas12a editing alone. Application of CHyMErA to the ablation of mammalian paralog gene pairs reveals extensive genetic interactions and uncovers phenotypes normally masked by functional redundancy. Application of CHyMErA in a chemo-genetic interaction screen identifies genes that impact cell growth in response to mTOR pathway inhibition. Moreover, by systematically targeting thousands of alternative splicing events, CHyMErA identifies exons underlying human cell line fitness. CHyMErA thus represents an effective screening approach for genetic interaction mapping and the functional analysis of sizeable genomic regions, such as alternative exons.
Project description:Single-cell CRISPR screens allow for the exploration of mammalian gene function and genetic regulatory networks, but their utility has been limited in part by their reliance on indirect sgRNA indexing. Here, we present direct capture Perturb-seq, a versatile screening approach in which expressed sgRNAs are sequenced alongside single-cell transcriptomes. Direct capture Perturb-seq enables the detection of multiple distinct sgRNAs expressed from a single vector within individual cells and thus allows pooled single-cell CRISPR screens to be easily paired with combinatorial perturbation libraries. We demonstrate that this approach allows high-throughput investigations of genetic interactions, and we leverage this ability to dissect epistatic interactions between cholesterol biogenesis and DNA repair. We also show that targeting individual genes with multiple sgRNAs per cell improves the efficacy of CRISPR interference and activation, facilitating the use of compact, highly active CRISPR libraries for single-cell screens. Lastly, we show that hybridization-based target enrichment permits sensitive, specific sequencing of informative transcripts from single-cell RNA-seq experiments.