PUBLICATION

Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain

Authors
Raj, B., Wagner, D.E., McKenna, A., Pandey, S., Klein, A.M., Shendure, J., Gagnon, J.A., Schier, A.F.
ID
ZDB-PUB-180403-3
Date
2018
Source
Nature Biotechnology   36(5): 442-450 (Journal)
Registered Authors
Raj, Bushra, Schier, Alexander
Keywords
none
Datasets
GEO:GSE105010
MeSH Terms
  • Animals
  • Brain/cytology
  • Brain/growth & development
  • CRISPR-Cas Systems/genetics*
  • Cell Lineage/genetics
  • Gene Editing/methods
  • Humans
  • Mice
  • Sequence Analysis, RNA/methods*
  • Single-Cell Analysis/methods*
  • Transcriptome/genetics*
  • Zebrafish
PubMed
29608178 Full text @ Nat Biotechnol.
Abstract
The lineage relationships among the hundreds of cell types generated during development are difficult to reconstruct. A recent method, GESTALT, used CRISPR-Cas9 barcode editing for large-scale lineage tracing, but was restricted to early development and did not identify cell types. Here we present scGESTALT, which combines the lineage recording capabilities of GESTALT with cell-type identification by single-cell RNA sequencing. The method relies on an inducible system that enables barcodes to be edited at multiple time points, capturing lineage information from later stages of development. Sequencing of ∼60,000 transcriptomes from the juvenile zebrafish brain identified >100 cell types and marker genes. Using these data, we generate lineage trees with hundreds of branches that help uncover restrictions at the level of cell types, brain regions, and gene expression cascades during differentiation. scGESTALT can be applied to other multicellular organisms to simultaneously characterize molecular identities and lineage histories of thousands of cells during development and disease.
Genes / Markers
Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping