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Mapping single-cell atlases throughout Metazoa unravels cell type evolution

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,...

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Autores principales: Tarashansky, Alexander J, Musser, Jacob M, Khariton, Margarita, Li, Pengyang, Arendt, Detlev, Quake, Stephen R, Wang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139856/
https://www.ncbi.nlm.nih.gov/pubmed/33944782
http://dx.doi.org/10.7554/eLife.66747
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author Tarashansky, Alexander J
Musser, Jacob M
Khariton, Margarita
Li, Pengyang
Arendt, Detlev
Quake, Stephen R
Wang, Bo
author_facet Tarashansky, Alexander J
Musser, Jacob M
Khariton, Margarita
Li, Pengyang
Arendt, Detlev
Quake, Stephen R
Wang, Bo
author_sort Tarashansky, Alexander J
collection PubMed
description 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.
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spelling pubmed-81398562021-05-24 Mapping single-cell atlases throughout Metazoa unravels cell type evolution Tarashansky, Alexander J Musser, Jacob M Khariton, Margarita Li, Pengyang Arendt, Detlev Quake, Stephen R Wang, Bo eLife Computational and Systems Biology 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. eLife Sciences Publications, Ltd 2021-05-04 /pmc/articles/PMC8139856/ /pubmed/33944782 http://dx.doi.org/10.7554/eLife.66747 Text en © 2021, Tarashansky et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Tarashansky, Alexander J
Musser, Jacob M
Khariton, Margarita
Li, Pengyang
Arendt, Detlev
Quake, Stephen R
Wang, Bo
Mapping single-cell atlases throughout Metazoa unravels cell type evolution
title Mapping single-cell atlases throughout Metazoa unravels cell type evolution
title_full Mapping single-cell atlases throughout Metazoa unravels cell type evolution
title_fullStr Mapping single-cell atlases throughout Metazoa unravels cell type evolution
title_full_unstemmed Mapping single-cell atlases throughout Metazoa unravels cell type evolution
title_short Mapping single-cell atlases throughout Metazoa unravels cell type evolution
title_sort mapping single-cell atlases throughout metazoa unravels cell type evolution
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139856/
https://www.ncbi.nlm.nih.gov/pubmed/33944782
http://dx.doi.org/10.7554/eLife.66747
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