A CRISPR/Cas9-based enhancement of high-throughput single-cell transcriptomics

Amitabh C. Pandey (), Jon Bezney, Dante DeAscanis, Ethan B. Kirsch, Farin Ahmed, Austin Crinklaw, Kumari Sonal Choudhary, Tony Mandala, Jeffrey Deason, Jasmin S. Hamidi, Azeem Siddique, Sridhar Ranganathan, Keith Brown, Jon Armstrong, Steven Head, Phillip Ordoukhanian, Lars M. Steinmetz and Eric J. Topol
Additional contact information
Amitabh C. Pandey: Tulane University School of Medicine
Jon Bezney: The Scripps Research Institute
Dante DeAscanis: Jumpcode Genomics
Ethan B. Kirsch: The Scripps Research Institute
Farin Ahmed: The Scripps Research Institute
Austin Crinklaw: Jumpcode Genomics
Kumari Sonal Choudhary: Jumpcode Genomics
Tony Mandala: The Scripps Research Institute
Jeffrey Deason: Jumpcode Genomics
Jasmin S. Hamidi: The Scripps Research Institute
Azeem Siddique: Jumpcode Genomics
Sridhar Ranganathan: Jumpcode Genomics
Keith Brown: Jumpcode Genomics
Jon Armstrong: Jumpcode Genomics
Steven Head: The Scripps Research Institute
Phillip Ordoukhanian: The Scripps Research Institute
Lars M. Steinmetz: Stanford University School of Medicine
Eric J. Topol: The Scripps Research Institute

Nature Communications, 2025, vol. 16, issue 1, 1-17

Abstract: Abstract Single-cell RNA-seq (scRNAseq) struggles to capture the cellular heterogeneity of transcripts within individual cells due to the prevalence of highly abundant and ubiquitous transcripts, which can obscure the detection of biologically distinct transcripts expressed up to several orders of magnitude lower levels. To address this challenge, here we introduce single-cell CRISPRclean (scCLEAN), a molecular method that globally recomposes scRNAseq libraries, providing a benefit that cannot be recapitulated with deeper sequencing. scCLEAN utilizes the programmability of CRISPR/Cas9 to target and remove less than 1% of the transcriptome while redistributing approximately half of reads, shifting the focus toward less abundant transcripts. We experimentally apply scCLEAN to both heterogeneous immune cells and homogenous vascular smooth muscle cells to demonstrate its ability to uncover biological signatures in different biological contexts. We further emphasize scCLEAN’s versatility by applying it to a third-generation sequencing method, single-cell MAS-Seq, to increase transcript-level detection and discovery. Here we show the possible utility of scCLEAN across a wide array of human tissues and cell types, indicating which contexts this technology proves beneficial and those in which its application is not advisable.

Date: 2025
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DOI: 10.1038/s41467-025-59880-2

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