Dissecting cellular ecosystem with single-cell CRISPR screens

Clustered regularly interspaced short palindromic repeats (CRISPR) screens represent a transformative force in biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications. Traditional screening approaches predominantly hinge on cell fitness or established markers, which inherently constrain their abilities for unbiased biological discovery. By contrast, single-cell CRISPR screening technologies, which combine pooled CRISPR screens with an array of sophisticated single-cell omics platforms, permit comprehensive profiling of the transcriptome and epigenome following individual genetic manipulations within complex cellular ecosystems. Over the past decade, a panoply of single-cell CRISPR platforms has emerged, each tailored to address specific experimental challenges. Iterative refinements in protocols have bolstered precision, scalability, and reproducibility, thereby enormously advancing functional genomics and translational research. However, technical obstacles such as perturbation efficiency, scalability, and data integration persist, necessitating cross-disciplinary collaboration and innovation. As single-cell CRISPR platforms evolve to incorporate spatial resolution, multi-omics integration, and AI-guided design, they are poised to bridge the gap between genetic perturbation and system-level interpretation. Here, we summarize recent advances in single-cell CRISPR technologies, outline their applications, and provide a comparative framework to guide platform selection (Perturb-seq, CROP-seq, ECCITE-seq, Direct-seq, and Mosaic-seq).

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Publication Details

Journal
Blood Science
Published
2025-12-01
DOI
https://doi.org/10.1097/bs9.0000000000000266
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Dissecting cellular ecosystem with single-cell CRISPR screens

Zi‐Jian Lan, Zhirui Liu, Shuquan Rao, Yao Yao et al.
Blood Science
Single-cell and spatial transcriptomics
article

Dissecting cellular ecosystem with single-cell CRISPR screens

Zi‐Jian Lan, Zhirui Liu, Shuquan Rao, Yao Yao, Xiaoli Kang
article en

Abstract

Clustered regularly interspaced short palindromic repeats (CRISPR) screens represent a transformative force in biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications. Traditional screening approaches predominantly hinge on cell fitness or established markers, which inherently constrain their abilities for unbiased biological discovery. By contrast, single-cell CRISPR screening technologies, which combine pooled CRISPR screens with an array of sophisticated single-cell omics platforms, permit comprehensive profiling of the transcriptome and epigenome following individual genetic manipulations within complex cellular ecosystems. Over the past decade, a panoply of single-cell CRISPR platforms has emerged, each tailored to address specific experimental challenges. Iterative refinements in protocols have bolstered precision, scalability, and reproducibility, thereby enormously advancing functional genomics and translational research. However, technical obstacles such as perturbation efficiency, scalability, and data integration persist, necessitating cross-disciplinary collaboration and innovation. As single-cell CRISPR platforms evolve to incorporate spatial resolution, multi-omics integration, and AI-guided design, they are poised to bridge the gap between genetic perturbation and system-level interpretation. Here, we summarize recent advances in single-cell CRISPR technologies, outline their applications, and provide a comparative framework to guide platform selection (Perturb-seq, CROP-seq, ECCITE-seq, Direct-seq, and Mosaic-seq).

Blood ScienceVol. 7(4)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Institute of Hematology & Blood Diseases Hospital (CN), Tianjin haihe hospital (CN)
Openalex Percentile: Top 65%
Single-cell and spatial transcriptomics
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Dissecting cellular ecosystem with single-cell CRISPR screens — Zi‐Jian Lan, Zhirui Liu, et al. · Blood Science (2025) | TGRS Research Map | TGRS