ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2025
A Bayesian phylodynamic inference framework for single-cell CRISPR/Cas9 lineage tracing barcode data with dependent target sites.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Can you trust your reconstructed lineage tree? A homoplasy-based approach for irreversible evolution.bioRxiv : the preprint server for biology · 2026Article
- SciPhy: A Bayesian phylogenetic framework using sequential genetic lineage tracing data.Nature communications · 2026Article
- Charting single-cell lineages with synthetic and natural barcodes.Nature reviews. Genetics · 2026Review
- Assessing the inference of single-cell phylogenies and population dynamics from CRISPR lineage recordings.PLoS computational biology · 2026Article
- Age-dependent Phylodynamics with Application to Single-cell Lineage Trees.Molecular biology and evolution · 2026Article
- VINE: Variational inference for scalable Bayesian reconstruction of species and cell-lineage phylogenies.bioRxiv : the preprint server for biology · 2026Article
- TyCHE enables time-resolved lineage tracing of heterogeneously-evolving populations.bioRxiv : the preprint server for biology · 2025Article
- Detecting branching rate heterogeneity with tree balance statistics in lineage tracing trees.bioRxiv : the preprint server for biology · 2025Article
- "A mathematical theory of evolution": phylogenetic models dating back 100 years.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- A Bayesian phylodynamic inference framework for single-cell CRISPR/Cas9 lineage tracing barcode data with dependent target sites.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
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4 authors.
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Abstract
Analysing single-cell lineage relationships of an organism is crucial towards understanding the fundamental cellular dynamics that drive development. Clustered regularly interspaced short palindromic repeats (CRISPR)-based dynamic lineage tracing relies on recent advances in genome editing and sequencing technologies to generate inheritable, evolving genetic barcode sequences that enable reconstruction of such cell lineage trees, also referred to as phylogenetic trees. Recent work generated custom computational strategies to produce robust tree estimates from such data. We further capitalize on these advancements and introduce GESTALT analysis using Bayesian inference (GABI), which extends the analysis of genome editing of synthetic target arrays for lineage tracing (GESTALT) data to a fully integrated Bayesian phylogenetic inference framework in software BEAST 2. This implementation allows users to represent the uncertainty in reconstructed trees and enables their scaling in absolute time. Furthermore, based on such time-scaled lineage trees, the underlying processes of growth, differentiation and apoptosis are quantified through so-called phylodynamic inference, typically relying on a birth-death or coalescent model. After validating its implementation, we demonstrate that our methodology results in robust estimates of growth dynamics characteristic of early
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