Large-scale, spatially resolved panoramic CRISPR screening in native tissue environments using Perturb-DBiT
17 affiliations
- 1Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- 2Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- 3Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
- 4Aspect Analytics, Genk, Belgium
- 5Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
- 6Department of Cell Biology, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT, USA
- 7Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, USA
- 8Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- 9Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- 10Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. [email protected]
- 11Systems Biology Institute, Integrated Science and Technology Center, West Haven, CT, USA. [email protected]
- 12Yale Stem Cell Center and Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA. [email protected]
- 13Department of Biomedical Engineering, Yale University, New Haven, CT, USA. [email protected]
- 14Department of Pathology, Yale University School of Medicine, New Haven, CT, USA. [email protected]
- 15Human and Translational Immunology, Yale University School of Medicine, New Haven, CT, USA. [email protected]
- 16Systems Biology Institute, Integrated Science and Technology Center, West Haven, CT, USA. [email protected]
- 17Yale Stem Cell Center and Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA. [email protected]
Abstract
Spatially resolved in vivo CRISPR screening integrates gene editing with spatial transcriptomics to examine how genetic perturbations alter gene expression within native tissue environments. However, current methods are limited to small perturbation panels and the detection of a narrow subset of protein-coding RNAs. We present Perturb-DBiT, a distinct and versatile approach for the simultaneous co-sequencing of spatial total RNA whole-transcriptome and single-guide RNAs (sgRNAs), base-by-base, on the same tissue section. This method enables unbiased discovery of how genetic perturbations influence RNA regulation, cellular dynamics, and tissue architecture in situ. Applying Perturb-DBiT to a human cancer metastatic colonization model, we mapped large panels of sgRNAs across tumor colonies in consecutive tissue sections alongside their corresponding total RNA transcriptomes. This revealed novel insights into how perturbations affect long non-coding RNA (lncRNA) co-variation, microRNA-mRNA interactions, and global and distinct tRNA alterations in amino acid metabolism linked to tumor migration and growth. By integrating transcriptional pseudotime trajectories, we further uncovered the impact of perturbations on clonal dynamics and cooperation. In an immune-competent syngeneic mouse model, Perturb-DBiT enabled investigation of genetic perturbations within the tumor immune microenvironment, revealing distinct and synergistic effects on immune infiltration and suppression. Perturb-DBiT provides a spatially resolved comprehensive view of how genetic knockouts influence diverse molecular and cellular responses including small and large RNA regulation, tumor proliferation, migration, metastasis, and immune interactions, offering a panoramic perspective on perturbation responses in complex tissues.
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BibTeX
@article{baysoy2026largescale,
title = {{Large-scale, spatially resolved panoramic CRISPR screening in native tissue environments using Perturb-DBiT}},
author = {Alev Baysoy and Xiaolong Tian and Paul A. Renauer and Feifei Zhang and Zhiliang Bai and Hao Shi and Mingyu Yang and Dingyao Zhang and Miao Liu and Haikuo Li and Bo Tao and Archibald Enninful and Yao Lu and Fu Gao and Guangchuan Wang and Wanqiu Zhang and Thao Tran and Nathan Heath Patterson and Jie Sheng and Shuozhen Bao and Chuanpeng Dong and Xin Shan and Binfan Chen and Mei Zhong and Sherri Rankin and Cliff S. Guy and Yan Wang and Jon P. Connelly and Shondra M. Pruett‐Miller and Daifeng Wang and Mina L. Xu and Mark Gerstein and Hongbo Chi and Sidi Chen and Rong Fan},
journal = {Nature Biotechnology},
year = {2026},
month = jun,
doi = {10.1038/s41587-026-03127-y},
url = {https://doi.org/10.1038/s41587-026-03127-y},
note = {CC BY},
}
RIS
TY - JOUR
TI - Large-scale, spatially resolved panoramic CRISPR screening in native tissue environments using Perturb-DBiT
AU - Alev Baysoy
AU - Xiaolong Tian
AU - Paul A. Renauer
AU - Feifei Zhang
AU - Zhiliang Bai
AU - Hao Shi
AU - Mingyu Yang
AU - Dingyao Zhang
AU - Miao Liu
AU - Haikuo Li
AU - Bo Tao
AU - Archibald Enninful
AU - Yao Lu
AU - Fu Gao
AU - Guangchuan Wang
AU - Wanqiu Zhang
AU - Thao Tran
AU - Nathan Heath Patterson
AU - Jie Sheng
AU - Shuozhen Bao
AU - Chuanpeng Dong
AU - Xin Shan
AU - Binfan Chen
AU - Mei Zhong
AU - Sherri Rankin
AU - Cliff S. Guy
AU - Yan Wang
AU - Jon P. Connelly
AU - Shondra M. Pruett‐Miller
AU - Daifeng Wang
AU - Mina L. Xu
AU - Mark Gerstein
AU - Hongbo Chi
AU - Sidi Chen
AU - Rong Fan
PY - 2026
DA - 2026/06/11
JO - Nature Biotechnology
DO - 10.1038/s41587-026-03127-y
UR - https://doi.org/10.1038/s41587-026-03127-y
AB - Spatially resolved in vivo CRISPR screening integrates gene editing with spatial transcriptomics to examine how genetic perturbations alter gene expression within native tissue environments. However, current methods are limited to small perturbation panels and the detection of a narrow subset of protein-coding RNAs. We present Perturb-DBiT, a distinct and versatile approach for the simultaneous co-sequencing of spatial total RNA whole-transcriptome and single-guide RNAs (sgRNAs), base-by-base, on the same tissue section. This method enables unbiased discovery of how genetic perturbations influence RNA regulation, cellular dynamics, and tissue architecture in situ. Applying Perturb-DBiT to a human cancer metastatic colonization model, we mapped large panels of sgRNAs across tumor colonies in consecutive tissue sections alongside their corresponding total RNA transcriptomes. This revealed novel insights into how perturbations affect long non-coding RNA (lncRNA) co-variation, microRNA-mRNA interactions, and global and distinct tRNA alterations in amino acid metabolism linked to tumor migration and growth. By integrating transcriptional pseudotime trajectories, we further uncovered the impact of perturbations on clonal dynamics and cooperation. In an immune-competent syngeneic mouse model, Perturb-DBiT enabled investigation of genetic perturbations within the tumor immune microenvironment, revealing distinct and synergistic effects on immune infiltration and suppression. Perturb-DBiT provides a spatially resolved comprehensive view of how genetic knockouts influence diverse molecular and cellular responses including small and large RNA regulation, tumor proliferation, migration, metastasis, and immune interactions, offering a panoramic perspective on perturbation responses in complex tissues.
SN - 0733-222X
SN - 1087-0156
SN - 1546-1696
SN - 2331-3684
ER -