Mapping single-cell atlases throughout Metazoa unravels cell type evolution.
Alexander J TarashanskyJacob M MusserMargarita KharitonPengyang LiDetlev ArendtStephen R QuakeBo WangPublished in: eLife (2021)
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 sponge to mouse, reveals ancient contractile and stem cell families, which may have arisen early in animal evolution.
Keyphrases
- single cell
- rna seq
- poor prognosis
- high throughput
- stem cells
- genome wide
- dna damage
- lymph node
- cell therapy
- high resolution
- public health
- machine learning
- binding protein
- skeletal muscle
- gene expression
- dna repair
- dna methylation
- bone marrow
- multidrug resistant
- high density
- oxidative stress
- gram negative
- big data
- genetic diversity
- copy number
- genome wide analysis
- mass spectrometry