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Nat. Cell Biol., Feb 26 2025, | https://doi.org/10.1038/s41556-025-01626-9
Decoding heterogeneous single-cell perturbation responses
Bicna Song 1,2, Dingyu Liu 3,4, Weiwei Dai 5,6, Natalie F. McMyn 5, Qingyang Wang 7, Dapeng Yang 3, Adam Krejci 8, Anatoly Vasilyev 8, Nicole Untermoser 8, Anke Loregger 8, Dongyuan Song 9,15, Breanna Williams 3, Bess Rosen 3,10, Xiaolong Cheng 1,2, Lumen Chao 1,2, Hanuman T. Kale 3, Hao Zhang 5, Yarui Diao 11, Tilmann Bürckstümmer 8, Janet D. Siliciano 5, Jingyi Jessica Li 7,9,12,13,14, Robert F. Siliciano 5,6, Danwei Huangfu 3 & Wei Li 1,2,*
1Center for Genetic Medicine Research, Children’s National Hospital, Washington, DC, USA.
2Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA.
3Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA.
4Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
5Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
6Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
7Department of Statistics and Data Science, University of California, Los Angeles, CA, USA.
8Myllia Biotechnology GmbH, Vienna, Austria.
9Bioinformatics Interdepartmental PhD Program, University of California, Los Angeles, CA, USA.
10Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA.
11Department of Cell Biology, Duke University Medical Center, Durham, NC, USA.
12Department of Human Genetics, University of California, Los Angeles, CA, USA.
13Department of Biostatistics, University of California, Los Angeles, CA, USA.
14Department of Computational Medicine, University of California, Los Angeles, CA, USA.
15Present address: Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA.
2Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA.
3Developmental Biology Program, Sloan Kettering Institute, New York City, NY, USA.
4Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
5Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
6Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
7Department of Statistics and Data Science, University of California, Los Angeles, CA, USA.
8Myllia Biotechnology GmbH, Vienna, Austria.
9Bioinformatics Interdepartmental PhD Program, University of California, Los Angeles, CA, USA.
10Weill Cornell Graduate School of Medical Sciences, Weill Cornell Medicine, New York, NY, USA.
11Department of Cell Biology, Duke University Medical Center, Durham, NC, USA.
12Department of Human Genetics, University of California, Los Angeles, CA, USA.
13Department of Biostatistics, University of California, Los Angeles, CA, USA.
14Department of Computational Medicine, University of California, Los Angeles, CA, USA.
15Present address: Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA.
*Corresponding author: correspondence to Wei Li
Abstract
Understanding how cells respond differently to perturbation is crucial in cell biology, but existing methods often fail to accurately quantify and interpret heterogeneous single-cell responses. Here we introduce the perturbation-response score (PS), a method to quantify diverse perturbation responses at a single-cell level. Applied to single-cell perturbation datasets such as Perturb-seq, PS outperforms existing methods in quantifying partial gene perturbations. PS further enables single-cell dosage analysis without needing to titrate perturbations, and identifies 'buffered' and 'sensitive' response patterns of essential genes, depending on whether their moderate perturbations lead to strong downstream effects. PS reveals differential cellular responses on perturbing key genes in contexts such as T cell stimulation, latent HIV-1 expression and pancreatic differentiation. Notably, we identified a previously unknown role for the coiled-coil domain containing 6 (CCDC6) in regulating liver and pancreatic cell fate decisions. PS provides a powerful method for dose-to-function analysis, offering deeper insights from single-cell perturbation data.
논문정보
- Research article
- 2025년 02월 (BRIC 등록일 2025-03-04)
- 국외 연구진
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