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Biology subjects

Kaplan, E. G.

Publications and source records attributed to Kaplan, E. G..

2 recordsLinked to original sources

Balancing off-target and on-target considerations for optimized Cas9 CRISPR knockout library design

The continued development of high-dimensional CRISPR screen readouts, such as single-cell RNA sequencing and high-content imaging, necessitates compact libraries to enable functional interrogation at genome scale. Improved genome annotations yield library deprecation over time, further motivating an updated genome-wide design effort. Recently, we have developed an enhanced model, Rule Set 3, which leveraged an expansive training set and feature space to predict guide efficacy. However, the benefit of such advances to library design is limited by current approaches to balance predictions of on-target activity with off-target considerations. Here we present a guide selection strategy that identifies guides with sufficient off-target activity to justify omission from the library, thus avoiding the unnecessary exclusion of active guides. We pair this model with strategic design choices to create Jacquere, an updated, optimized, and validated Cas9 CRISPR knockout (CRISPRko) genome-wide library for the human genome.

genomics↗

Activity-based selection for enhanced base editor mutational scanning

Base editing is a CRISPR-based technology that enables high-throughput, nucleotide-level functional interrogation of the genome, which is essential for understanding the genetic basis of human disease and informing therapeutic development. Base editing screens have emerged as a powerful experimental approach, yet significant cell-to-cell variability in editing efficiency introduces noise that may obscure meaningful results. Here, we develop a co-selection method that enriches for cells with high base editing activity, substantially increasing editing efficiency at a target locus. We evaluate this activity-based selection method against a traditional screening approach by tiling guide RNAs across TP53, demonstrating its enhanced capacity to pinpoint specific mutations and protein regions of functional importance. We anticipate that this modular selection method will enhance the resolution of base editing screens across many applications.

genetics↗