What You Can’t See Can Hurt You:
Uncovering Regulatory Off-Target Effects in CRISPR-Edited Genomes
Brad Balderson*, Michael H. Lorenzini*, Shanna N. Lavalle, Karthyayani Sajeev, Aaron J. Ho, Madelyn Light, Olalekan H. Usman, Gavin Kurgan, Graham McVicker
*co-first authors
A longstanding barrier in genome engineering with CRISPR-Cas9 has been the inability to measure editing outcomes and their functional effects at single-cell resolution. Here we present “Superb-seq”, which captures single-cell edits and measures their effects on the transcriptome by integrating Cas9 editing, T7 transcription, and single-cell RNA sequencing. We performed Superb-seq on over 34,000 cells from three cell lines. Using seven guide RNAs to target four chromatin remodeler genes in 10,000 K562 cells, Superb-seq detected 43 total edit sites, including 36 off-target sites, and 5761 edited cells (up to 5 edits per cell). Superb-seq improved estimation of gene perturbation effects compared to Perturb-seq and its edit detection sensitivity was comparable to bulk off-target detection methods. We identified 19 off-target edits associated with differential gene expression, nine of which were cell type specific. In summary, Superb-seq illuminates the consequences of Cas9 genome editing by connecting detected single-cell edits with changes in gene expression.
Bio
I completed my Bachelors of Science with a Dual Major in Bioinformatics at the University of Queensland, followed by first class Honours in Mikael Boden’s lab also at UQ. My PhD was also in Bioinformatics, focusing on methods to characterize cell type heterogeneity using single cell RNA-seq data, particularly in very heterogeneous tissues like the brain. I also worked as a research assistant at the Institute for Molecular Biosciences at UQ, where I developed methods to detect cell-cell interactions based on spatial RNA-seq data, and also characterized tumour responses to cell cycle inhibitors in a patient-derived xenograft model of medulloblastoma. I moved to San Diego in Southern California, USA, to undertake my first post-doc at the Salk Institute/UCSD in the lab of Graham McVicker. My postdoctoral research included three major projects at the intersection of transcriptomics and genetics (molecular genetics): I identified a molecular signature associated with the loss of dopamine-sensing cells in addiction-resilient rodents; I developed analytical frameworks for the first assay to jointly measure single-cell transcriptomes and CRISPR-Cas9 editing; and I designed a deep learning technique to predict the effects of genetic variants on transcription and epigenetic regulation. I have since returned to Australia as a research fellow at IMB, working on developing deep learning methods to interpret the effect of rare variants on complex traits and disease onset.
