Year: 2020
Type: article
Abstract: The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. First, we introduce Cassiopeia-a suite of scalable maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date, 34,557 human cells continuously traced over 15 generations, and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together, these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia.
Source: Genome biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,990
Funders: Howard Hughes Medical Institute, Damon Runyon Cancer Research Foundation, Life Sciences Research Foundation, National Institutes of Health, University of California, San Francisco, National Institute on Drug Abuse, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases
Awards: G1723340172, G2297564190, G3926501084, Center for Genome Editing and Recording, G5052434461, BMI Bioinformatics Training Grant, G5520316217, G7676091009, Profiling chromatin-associated long noncoding RNAs in numerous biological contexts, Harnessing CRISPR for Targeted and Inducible Epigenomic Reprogramming, G9000020761, G9000043206, G9000281473, G9000337821
OpenAlex ID: W3015748341