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Cellecta offers quality pooled lentiviral CRISPR sgRNA libraries for unbiased phenotypic knockout screens in mammalian cell systems. Pooled libraries of many thousands of defined single-guide RNA (sgRNA or gRNA) sequences enable disruption (or “knockout”) of thousands of genes throughout a cell population in a single experiment. Screening this cell population for a specific phenotype (e.g., viability) then, enables the identification of specific genes driving that phenotype, such as a drug response or disease phenotype.
In keeping with our mission to provide accessible advanced technology to accelerate functional genomic analysis, Cellecta provides CRISPR libraries in both plasmid and pre-packaged forms with large portions for immediate use. All libraries are provided with complete sequence information on the vectors, inserts, and guides expressed, as well as Next-Generation Sequencing (NGS) data showing the number of reads per sgRNA as well as the distribution of the sgRNA of the library.
Guide designs for Cellecta’s libraries incorporate state-of-the-art design criteria to ensure the most effective knockout possible. In addition, the region of the sgRNA interacting with the Cas9 nuclease has been optimized for higher efficiency knockout by incorporating the “HEAT” design. We have shown that specific modifications to the Cas9-binding region of sgRNA significantly improve the effectiveness of gene knockout and that CRISPR libraries containing constructs with these modified sgRNA sequences generate stronger and more robust results than those with the standard sgRNA.
Guide designs for Cellecta’s libraries incorporate state-of-the-art design criteria to ensure the most effective knockout possible. In addition, the region of the sgRNA interacting with the Cas9 nuclease has been optimized for higher efficiency knockout by incorporating the “HEAT” design. We have shown that specific modifications to the Cas9-binding region of sgRNA significantly improve the effectiveness of gene knockout and that CRISPR libraries containing constructs with these modified sgRNA sequences generate stronger and more robust results than those with the standard sgRNA.
sgRNA Structure Optimization Screen Data: Waterfall plots display the depletion fold of positive and negative controls within the library for each design. The HEAT design shows best performance.
Pooled CRISPR sgRNA Lentiviral Libraries are transduced into cells to disrupt thousands of genes simultaneously across different cells in a large population. Selection of cells with a phenotype of interest (e.g., viability or activation of a reporter) then leads to enrichment or depletion of particular sgRNA that target genes functionally important in regulating the phenotype. These CRISPR gene pertubation screens, then, enable researchers to identify the specific genes required for general viability or other selectable phenotypes in virtually any mammalian cell system.
The most commonly run perturbation screen identifies essential genes by transducing a population of cells with a pooled library of shRNA or sgRNA constructs. Some of the sgRNA will make the cells they are expressed in grow less under the screen conditions due to the disruption of the genes they target, and so these sgRNA will decrease as the host cells die, relative to the whole population. Conversely, other effectors may make the host cells more fit by knocking out genes that inhibit rapid grown under the culture conditions, and these guides will increase.
On completion of the screen, genomic DNA from the whole population is isolated and the frequency of each integrated sgRNA lentiviral construct in the population is assessed by next-generation sequencing (NGS). Constructs expressing sgRNA that are lethal appear underrepresented after growth as compared to their initial representation in the pre-transduced library. This sort of “dropout viability” screen to identify essential genes is often used to look for genetic susceptibilities in cancer cells. Similar types of screens can be run for other phenotypes, such as activation of particular pathways, using reporter constructs for fluorescent labels and a FACS selection.
