Abstract
Purpose :
By integrating a CRISPR/Cas9 library with transcriptomic profiling, Perturb-seq is a versatile approach for the high-throughput functional characterization of genetic and other perturbations. The recent integration of Perturb-seq with single-cell omics has further enhanced the capabilities of this technology. However, despite the recent reports of numerous in vitro single-cell Perturb-seq (scPerturb-seq) experiments, in vivo studies are still scarce. Our aim is to establish an in vivo scPerturb-seq protocol specifically for mouse retinas, enabling rapid characterization of genes associated with Inherited Retinal Diseases (IRD), among many other applications.
Methods :
We have constructed a library of guide RNAs (gRNAs) targeting 79 genes associated with Inherited Retinal Diseases (IRD). Following injection of the library into the deactivated Cas9 (dCas9) in wild-type control mice retinas, the abundance of each gRNA is quantified using Next-Generation Sequencing (NGS) at multiple time points. Furthermore, we measure the impact of each gRNA on the transcriptome through single-cell RNA sequencing (scRNAseq).
Results :
We observed a significant drop in the relative abundance of guide RNAs (gRNAs) targeting 74 out of the 79 Inherited Retinal Disease (IRD) genes. In contrast, the abundance of the negative control gRNAs remained unchanged. The scPerturb-seq analysis of this gene set enabled a detailed transcriptomic analysis, revealing intricate genetic regulatory networks and functional insights.
Conclusions :
We have established robust scPerturb-seq approach for characterizing genes function in the mouse retina in vivo. This method demonstrates high overall accuracy, with a sensitivity rate of 94%. Applying scPerturb-seq to known genes associated with IRD allows for significant insights into the disease mechanisms underlying photoreceptor cell degeneration. Moreover, by combining this approach with whole-genome sequencing of unresolved IRD cases, it is possible to conduct rapid functional validation of candidate genes linked to IRD.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.