Genome-scale perturb-seq in primary human CD4+ T cells maps context-specific regulators of T cell programs and human immune traits
(1) Zhu R (2) Dann E (3) Yan J (4) Reyes Retana J (5) Goto R (6) Guitche RC (7) Brixi L (8) Ota M (9) Hartman A (10) Roth TL (11) Satpathy AT (12) Pritchard JK (13) Marson A
Zhu, Dann, et al. developed a transcriptome-wide and transcription factor genome-wide CRISPRi knockdown perturb-seq platform for human CD4+ T cells to comprehensively identify functional gene networks. Four T cell donors were utilized, and deep single-cell RNAseq was conducted under 3 conditions: resting, 8, and 48 hours after stimulation. Multiple patterns (positive and negative; few or many genes affected), context-specific effects (resting vs. stimulated; Th1 vs. Th2), and complex cytokine regulatory patterns were observed. Integration with GWAS studies confirmed and extended known linkages, and revealed new autoimmune targets.
Contributed by Ed Fritsch
(1) Zhu R (2) Dann E (3) Yan J (4) Reyes Retana J (5) Goto R (6) Guitche RC (7) Brixi L (8) Ota M (9) Hartman A (10) Roth TL (11) Satpathy AT (12) Pritchard JK (13) Marson A
Zhu, Dann, et al. developed a transcriptome-wide and transcription factor genome-wide CRISPRi knockdown perturb-seq platform for human CD4+ T cells to comprehensively identify functional gene networks. Four T cell donors were utilized, and deep single-cell RNAseq was conducted under 3 conditions: resting, 8, and 48 hours after stimulation. Multiple patterns (positive and negative; few or many genes affected), context-specific effects (resting vs. stimulated; Th1 vs. Th2), and complex cytokine regulatory patterns were observed. Integration with GWAS studies confirmed and extended known linkages, and revealed new autoimmune targets.
Contributed by Ed Fritsch
ABSTRACT: Gene regulatory networks encode the fundamental logic of cellular functions, but systematic network mapping remains challenging, especially in cell states relevant to human biology and disease. Here, we perturbed all expressed genes across 22 million primary human CD4(+) T cells from four donors and developed a probe-based perturb-seq platform to measure the transcriptome effects in cells at rest and after stimulation. These data allowed us to map genes regulating immune pathways, including previously uncharacterized regulators of cytokine production. Importantly, active regulators and the gene programs they control changed dramatically across stimulation conditions. Perturbation signatures enabled us to model T cell states observed in population-scale transcriptomic atlases, nominating regulators of T cell polarization and of age-related phenotypes. Finally, we leveraged perturb-seq to implicate context-specific gene regulatory pathways in autoimmune disease risk. Our study provides a foundational resource and new approaches to decode T cell function and human immune traits.
Author Info:
(1) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA; Department of Genetics, Stanford University, Stanford, CA, USA. Electronic address: ronghui.zhu@gladston
e.ucsf.edu. (2) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA; Department of Genetics, Stanford University, Stanford, CA, USA. Electronic address: emmadann@stanford.edu. (3) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. (4) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. (5) Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. (6) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA; University of San Francisco, San Francisco, CA, USA. (7) Department of Genetics, Stanford University, Stanford, CA, USA. (8) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA; Department of Genetics, Stanford University, Stanford, CA, USA; Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. (9) Department of Genetics, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA; Arc Institute, Palo Alto, CA, USA. (10) Department of Pathology, Stanford University, Stanford, CA, USA; Arc Institute, Palo Alto, CA, USA; Program in Immunology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Weill Foundation West Coast Cancer Hub, Stanford, CA, USA. (11) Department of Genetics, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA; Program in Immunology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Weill Foundation West Coast Cancer Hub, Stanford, CA, USA. (12) Department of Genetics, Stanford University, Stanford, CA, USA; Department of Biology, Stanford University, Stanford, CA, USA. Electronic address: pritch@stanford.edu. (13) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA; Weill Foundation West Coast Cancer Hub, Stanford, CA, USA; Department of Medicine, University of California, San Francisco, San Francisco, CA, USA; University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA; Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA; Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. Electronic address: alex.marson@gladstone.ucsf.edu.
