PUBLICATION

Mapping single-cell atlases throughout Metazoa unravels cell type evolution

Authors
Tarashansky, A.J., Musser, J.M., Khariton, M., Li, P., Arendt, D., Quake, S.R., Wang, B.
ID
ZDB-PUB-210505-5
Date
2021
Source
eLIFE   10: (Journal)
Registered Authors
Arendt, Detlev
Keywords
computational biology, evolutionary biology, mouse, planarian, systems biology, xenopus, zebrafish
MeSH Terms
  • Algorithms*
  • Animals
  • Evolution, Molecular
  • Female
  • Mice/genetics
  • Mutation, Missense
  • Planarians/genetics
  • Research Design
  • Single-Cell Analysis/methods*
  • Transcriptome*
  • Xenopus/genetics
  • Zebrafish/genetics
PubMed
33944782 Full text @ Elife
Abstract
Comparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex gene histories and diversifications in expression programs. Previously, we introduced the self-assembling manifold (SAM) algorithm to robustly reconstruct manifolds from single-cell data (Tarashansky et al., 2019). Here, we build on SAM to map cell atlas manifolds across species. This new method, SAMap, identifies homologous cell types with shared expression programs across distant species within phyla, even in complex examples where homologous tissues emerge from distinct germ layers. SAMap also finds many genes with more similar expression to their paralogs than their orthologs, suggesting paralog substitution may be more common in evolution than previously appreciated. Lastly, comparing species across animal phyla, spanning mouse to sponge, reveals ancient contractile and stem cell families, which may have arisen early in animal evolution.
Genes / Markers
Figures
Show all Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping