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Integrating lineage across individuals with phylogenetic tree comparison

The cell lineage tree describes every cell division from the fertilized egg to the adult. Tracing cell lineage trees informs our understanding of the processes that sculpt development and disease. We established a new method for tracing lineage trees that uses CRISPR to incrementally add genetic “scars” to cells and their descendants. These scars are stored in the genome of every cell, and can be recovered using DNA or RNA sequencing from single cells alongside their molecular identity. We use the relatedness of scars between cells to compute estimates of an individual’s cell lineage tree. However, we lack methods to quantify the accuracy of each branch in the tree, and how to compare and integrate trees across individuals.

Here we propose an experimental and mathematical framework for computing CRISPR lineage trees. This project brings together expertise in genome editing, sequencing, and phylogenetics. First, we will experimentally recover genetic scars from hundreds of thousands of cells across many individual animals. Second, we will adapt phylogenetic methods for tree reconstruction and comparison to determine the most likely lineage tree for each individual. Third, we will merge lineage trees from all individuals to generate a “meta tree,” and quantify tree variance across all branches of the meta tree. This project will generate a platform for lineage comparison between individuals, opening a new door into our understanding of healthy and diseased development.


College of Science
School of Biological Sciences
Project Owner

Aaron Quinlan
School of Medicine
Human Genetics

Blair Sullivan
College of Engineering
School of Computing

Project Info

Funded Project Amount

Developmental biology, phylogenetics, cell lineage tree, single-cell sequencing

Project Status
Funded 2020
Last Updated: 1/23/20