Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells
- bioRxiv. 2025 Jan 23:2025.01.21.633969. doi: 10.1101/2025.01.21.633969.
- 1. Department of Internal Medicine, Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 2. Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 3. Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 4. Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 5. Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 6. Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 7. Quantitative Biomedical Research Center, Peter O'Donnell Jr School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 8. Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 9. Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 10. Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 11. Peter O'Donnell Jr Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 12. Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- 13. Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Perturb-seq is a powerful approach to systematically assess how genes and enhancers impact the molecular and cellular pathways of development and disease. However, technical challenges have limited its application in stem cell-based systems. Here, we benchmarked Perturb-seq across multiple CRISPRi modalities, on diverse genomic targets, in multiple human pluripotent stem cells, during directed differentiation to multiple lineages, and across multiple sgRNA delivery systems. To ensure cost-effective production of large-scale Perturb-seq datasets as part of the Impact of Genomic Variants on Function (IGVF) consortium, our optimized protocol dynamically assesses experiment quality across the weeks-long procedure. Our analysis of 1,996,260 sequenced cells across benchmarking datasets reveals shared regulatory networks linking disease-associated enhancers and genes with downstream targets during cardiomyocyte differentiation. This study establishes open tools and resources for interrogating genome function during stem cell differentiation.
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