Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Bastiaan Spanjaard - , Helmholtz-Zentrum Dresden-Rossendorf (Author)
  • Bo Hu - , Helmholtz-Zentrum Dresden-Rossendorf (Author)
  • Nina Mitic - , Helmholtz-Zentrum Dresden-Rossendorf (Author)
  • Pedro Olivares-Chauvet - , Helmholtz-Zentrum Dresden-Rossendorf (Author)
  • Sharan Janjuha - , German Research Foundation (Author)
  • Nikolay Ninov - , Chair of Cell Biology and Regeneration of β-Cells, German Research Foundation, DFG Ctr Regenerat Therapies Dresden Cluster Exc (Author)
  • Jan Philipp Junker - , Helmholtz-Zentrum Dresden-Rossendorf (Author)

Abstract

A key goal of developmental biology is to understand how a single cell is transformed into a full-grown organism comprising many different cell types. Single-cell RNA-sequencing (scRNA-seq) is commonly used to identify cell types in a tissue or organ(1). However, organizing the resulting taxonomy of cell types into lineage trees to understand the developmental origin of cells remains challenging. Here we present LINNAEUS (lineage tracing by nuclease-activated editing of ubiquitous sequences)-a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes, generated by genome editing of transgenic reporter genes, we reconstruct developmental lineage trees in zebrafish larvae, and in heart, liver, pancreas, and telencephalon of adult fish. LINNAEUS provides a systematic approach for tracing the origin of novel cell types, or known cell types under different conditions.

Details

Original languageEnglish
Pages (from-to)469–473
Number of pages5
JournalNature biotechnology
Volume36
Issue number5
Publication statusPublished - May 2018
Peer-reviewedYes

External IDs

PubMed 29644996
Scopus 85045136951

Keywords

Keywords

  • Single cells, Stem-cells, Zebrafish embryo, Expression, Dynamics, Progenitors, Tracking, Design, Model