ArticleNature ecology & evolution2024
Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data.
Article in Nature ecology & evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Rates of Evolution Differ Between Cell Types Identified by Single-Cell RNAseq in Threespine Stickleback.Molecular ecology · 2026Article
- Unify learns cellular evolution with universal multimodal embeddings.Nature communications · 2026Article
- Microglia and neuroinflammation: function, heterogeneity, and crosstalk.Cellular & molecular immunology · 2026Review
- Single-cell analyses of tissue regeneration in two true jellyfish.Molecular biology and evolution · 2026Article
- Comparative analysis of the cellular landscape in mammalian striatum.Nature communications · 2026Article
- Evolutionary conservation and divergence of phagocytic and coagulation programs across bilaterian circulating immune cells.Molecular biology and evolution · 2026Article
- Evolutionarily informed gene sets reveal conserved and lineage-modified transcriptional programs during vertebrate forebrain evolution.bioRxiv : the preprint server for biology · 2026Article
- Hemipteran insects experience recurrent and synergistic molecular evolution adapting to diet shift.BMC biology · 2025Article
- From nociception in aneural animals to human suffering: toward a comparative biology of pain.The Journal of experimental biology · 2025Review
- Review
- The cellular substrate of evolutionary novelty.Current biology : CB · 2025Review
- On the evolution of microglia.Zoological research · 2025Article
- Advances and applications in single-cell and spatial genomics.Science China. Life sciences · 2025Review
- Deep-time gene expression shift reveals an ancient change in avian muscle phenotypes.PLoS genetics · 2025Article
- Benchmarking cross-species single-cell RNA-seq data integration methods: towards a cell type tree of life.Nucleic acids research · 2025Article
- Single-Cell Transcriptomics Reveals Evolutionary Reconfiguration of Embryonic Cell Fate Specification in the Sea Urchin Heliocidaris erythrogramma.Genome biology and evolution · 2025Article
- Identifying cell types by lasso-constraint regularized Gaussian graphical model based on weighted distance penalty.Briefings in bioinformatics · 2024Article
- A macroevolutionary analysis of European Late Upper Palaeolithic stone tool shape using a Bayesian phylodynamic framework.Royal Society open science · 2024Article
- Integrating phylogenies into single-cell RNA sequencing analysis allows comparisons across species, genes, and cells.PLoS biology · 2024Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The origin and evolution of cell types has emerged as a key topic in evolutionary biology. Driven by rapidly accumulating single-cell datasets, recent attempts to infer cell type evolution have largely been limited to pairwise comparisons because we lack approaches to build cell phylogenies using model-based approaches. Here we approach the challenges of applying explicit phylogenetic methods to single-cell data by using principal components as phylogenetic characters. We infer a cell phylogeny from a large, comparative single-cell dataset of eye cells from five distantly related mammals. Robust cell type clades enable us to provide a phylogenetic, rather than phenetic, definition of cell type, allowing us to forgo marker genes and phylogenetically classify cells by topology. We further observe evolutionary relationships between diverse vessel endothelia and identify the myelinating and non-myelinating Schwann cells as sister cell types. Finally, we examine principal component loadings and describe the gene expression dynamics underlying the function and identity of cell type clades that have been conserved across the five species. A cell phylogeny provides a rigorous framework towards investigating the evolutionary history of cells and will be critical to interpret comparative single-cell datasets that aim to ask fundamental evolutionary questions.
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