PUBLICATION
Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT
- Authors
- Raj, B., Gagnon, J.A., Schier, A.F.
- ID
- ZDB-PUB-181026-6
- Date
- 2018
- Source
- Nature Protocols 13(11): 2685-2713 (Other)
- Registered Authors
- Raj, Bushra, Schier, Alexander
- Keywords
- none
- MeSH Terms
-
- Animals
- Animals, Genetically Modified
- Brain/growth & development
- Brain/metabolism
- CRISPR-Associated Protein 9/genetics*
- CRISPR-Associated Protein 9/metabolism
- CRISPR-Cas Systems*
- Cell Lineage/genetics*
- Clustered Regularly Interspaced Short Palindromic Repeats
- Embryo, Nonmammalian
- Gene Editing/methods*
- Gene Library
- Organ Specificity
- RNA, Guide, Kinetoplastida/genetics
- RNA, Guide, Kinetoplastida/metabolism
- Single-Cell Analysis/methods
- Transcriptome*
- Zebrafish/genetics*
- Zebrafish/growth & development
- Zebrafish/metabolism
- PubMed
- 30353175 Full text @ Nat. Protoc.
Citation
Raj, B., Gagnon, J.A., Schier, A.F. (2018) Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT. Nature Protocols. 13(11):2685-2713.
Abstract
Lineage relationships among the large number of heterogeneous cell types generated during development are difficult to reconstruct in a high-throughput manner. We recently established a method, scGESTALT, that combines cumulative editing of a lineage barcode array by CRISPR-Cas9 with large-scale transcriptional profiling using droplet-based single-cell RNA sequencing (scRNA-seq). The technique generates edits in the barcode array over multiple timepoints using Cas9 and pools of single-guide RNAs (sgRNAs) introduced during early and late zebrafish embryonic development, which distinguishes it from similar Cas9 lineage-tracing methods. The recorded lineages are captured, along with thousands of cellular transcriptomes, to build lineage trees with hundreds of branches representing relationships among profiled cell types. Here, we provide details for (i) generating transgenic zebrafish; (ii) performing multi-timepoint barcode editing; (iii) building scRNA-seq libraries from brain tissue; and (iv) concurrently amplifying lineage barcodes from captured single cells. Generating transgenic lines takes 6 months, and performing barcode editing and generating single-cell libraries involve 7 d of hands-on time. scGESTALT provides a scalable platform to map lineage relationships between cell types in any system that permits genome editing during development, regeneration, or disease.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping