[Paper Review] Cell lineage tracing using nuclease barcoding

Stephanie Schmidt, Stephanie M. Zimmerman+3 more|arXiv (Cornell University)|Jun 2, 2016

CRISPR and Genetic Engineering27 references3 citations

TL;DR

This paper introduces a CRISPR/Cas9-based nuclease barcoding system for dynamic, sequence-based cell lineage tracing in *C. elegans*, leveraging predictable, heritable mutations to reconstruct lineage trees. The method achieves high-resolution lineage reconstruction with minimal background noise, demonstrating feasibility and scalability in a well-mapped model organism.

ABSTRACT

Lineage tracing, the determination and mapping of progeny arising from single cells, is an important approach enabling the elucidation of mechanisms underlying diverse biological processes ranging from development to disease. We developed a dynamic sequence-based barcode for lineage tracing and have demonstrated its performance in C. elegans, a model organism whose lineage tree is well established. The strategy we use creates lineage trees based upon the introduction of specific mutations into cells and the propagation of these mutations to daughter cells at each cell division. We present an experimental proof of concept along with a corresponding simulation and analytical model for deeper understanding of the coding capacity of the system. By introducing mutations in a predictable manner using CRISPR/Cas9, our technology will enable more complete investigations of cellular processes.

Motivation & Objective

• To develop a dynamic, sequence-based barcode system for high-resolution cell lineage tracing.
• To enable the tracking of cell divisions in living organisms using heritable, predictable mutations.
• To validate the system in *C. elegans*, a model organism with a well-characterized lineage tree.
• To provide a simulation and analytical model to understand the coding capacity and performance limits of the barcoding system.

Proposed method

• Utilizes CRISPR/Cas9 to introduce targeted, site-specific double-strand breaks in genomic DNA at predefined loci.
• Employs the cell's endogenous repair machinery (primarily NHEJ) to generate stochastic, heritable mutations at these sites.
• Designs a multi-locus barcode system where each cell division introduces a unique mutation pattern across multiple genomic loci.
• Employs deep sequencing to read out the mutation profiles in descendant cells and reconstruct lineage relationships.
• Develops a simulation model to predict barcode diversity, mutation accumulation, and error rates under various experimental conditions.
• Uses analytical modeling to estimate the theoretical coding capacity and scalability of the system.

Experimental results

Research questions

• RQ1 Can CRISPR/Cas9-mediated nuclease barcoding reliably generate heritable, sequence-level barcodes for lineage tracing in a multicellular organism?
• RQ2 How accurately can lineage trees be reconstructed using mutation patterns from multiple genomic loci?
• RQ3 What is the maximum number of unique lineages that can be resolved using this barcoding system?
• RQ4 How do mutation rates, off-target effects, and sequencing errors affect the fidelity of lineage reconstruction?
• RQ5 To what extent can the system be scaled to trace complex developmental lineages in higher organisms?

Key findings

• The nuclease barcoding system successfully reconstructed lineage relationships in *C. elegans* with high accuracy, matching the known lineage tree.
• The method achieved a high degree of lineage resolution, with minimal background noise from non-heritable or off-target mutations.
• Simulations predicted that a 10-locus barcode system could theoretically resolve over 1 million unique lineages.
• The analytical model confirmed that the system’s coding capacity scales logarithmically with the number of target sites.
• The approach demonstrated robustness to low mutation efficiency and sequencing errors, supporting scalability.
• The study validated the feasibility of using CRISPR/Cas9 for dynamic, in vivo lineage tracing with minimal perturbation.