MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate
Single-cell RNA sequencing (scRNA-seq) provides a leap forward in resolving cellular diversity and developmental trajectories but fails to comprehensively delineate the spatial organization and precise cellular makeup of individual embryos. Here, we reconstruct from scRNA-seq and light sheet imaging...
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Veröffentlicht in: | Cell 2020-05, Vol.181 (4), p.922-935.e21 |
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creator | Sladitschek, Hanna L. Fiuza, Ulla-Maj Pavlinic, Dinko Benes, Vladimir Hufnagel, Lars Neveu, Pierre A. |
description | Single-cell RNA sequencing (scRNA-seq) provides a leap forward in resolving cellular diversity and developmental trajectories but fails to comprehensively delineate the spatial organization and precise cellular makeup of individual embryos. Here, we reconstruct from scRNA-seq and light sheet imaging data a canonical digital embryo that captures the genome-wide gene expression trajectory of every single cell at every cell division in the 18 lineages up to gastrulation in the ascidian Phallusia mammillata. By using high-coverage scRNA-seq, we devise a computational framework that stratifies single cells of individual embryos into cell types without prior knowledge. Unbiased transcriptome data analysis mapped each cell’s physical position and lineage history, yielding the complete history of gene expression at the genome-wide level for every single cell in a developing embryo. A comparison of individual embryos reveals both extensive reproducibility between symmetric embryo sides and a large inter-embryonic variability due to small differences in embryogenesis timing.
[Display omitted]
•Integration of scRNA-seq and imaging data yield a canonical digital embryo•Cell type classification without prior knowledge•De novo reconstruction of the lineage history and spatial organization of the embryo•Timing differences contribute to inter-embryo variability in gene expression
The complete gene expression history and physical position of every single cell at every cell division in an embryo up to gastrulation is reconstructed using a combination of single-cell transcriptomics and light sheet imaging. |
doi_str_mv | 10.1016/j.cell.2020.03.055 |
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[Display omitted]
•Integration of scRNA-seq and imaging data yield a canonical digital embryo•Cell type classification without prior knowledge•De novo reconstruction of the lineage history and spatial organization of the embryo•Timing differences contribute to inter-embryo variability in gene expression
The complete gene expression history and physical position of every single cell at every cell division in an embryo up to gastrulation is reconstructed using a combination of single-cell transcriptomics and light sheet imaging.</description><identifier>ISSN: 0092-8674</identifier><identifier>EISSN: 1097-4172</identifier><identifier>DOI: 10.1016/j.cell.2020.03.055</identifier><identifier>PMID: 32315617</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Animals ; ascidian ; cell fate specification ; Cell Lineage - genetics ; cell type classification ; Chordata - genetics ; Computational Biology - methods ; embryogenesis ; Gastrulation - genetics ; gene expression noise ; Gene Expression Profiling - methods ; Gene Expression Regulation, Developmental - genetics ; light sheet imaging ; lineage reconstruction ; Reproducibility of Results ; Sequence Analysis, RNA - methods ; Single-Cell Analysis - methods ; single-cell RNA sequencing ; spatial reconstruction ; Transcriptome - genetics ; Urochordata - genetics</subject><ispartof>Cell, 2020-05, Vol.181 (4), p.922-935.e21</ispartof><rights>2020 The Author(s)</rights><rights>Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.</rights><rights>2020 The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c455t-a92a70572ab1ed625e2a5d44005aaf6d35aa72c4dd852fe3496ae322db1be7053</citedby><cites>FETCH-LOGICAL-c455t-a92a70572ab1ed625e2a5d44005aaf6d35aa72c4dd852fe3496ae322db1be7053</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.cell.2020.03.055$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32315617$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sladitschek, Hanna L.</creatorcontrib><creatorcontrib>Fiuza, Ulla-Maj</creatorcontrib><creatorcontrib>Pavlinic, Dinko</creatorcontrib><creatorcontrib>Benes, Vladimir</creatorcontrib><creatorcontrib>Hufnagel, Lars</creatorcontrib><creatorcontrib>Neveu, Pierre A.</creatorcontrib><title>MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate</title><title>Cell</title><addtitle>Cell</addtitle><description>Single-cell RNA sequencing (scRNA-seq) provides a leap forward in resolving cellular diversity and developmental trajectories but fails to comprehensively delineate the spatial organization and precise cellular makeup of individual embryos. Here, we reconstruct from scRNA-seq and light sheet imaging data a canonical digital embryo that captures the genome-wide gene expression trajectory of every single cell at every cell division in the 18 lineages up to gastrulation in the ascidian Phallusia mammillata. By using high-coverage scRNA-seq, we devise a computational framework that stratifies single cells of individual embryos into cell types without prior knowledge. Unbiased transcriptome data analysis mapped each cell’s physical position and lineage history, yielding the complete history of gene expression at the genome-wide level for every single cell in a developing embryo. A comparison of individual embryos reveals both extensive reproducibility between symmetric embryo sides and a large inter-embryonic variability due to small differences in embryogenesis timing.
[Display omitted]
•Integration of scRNA-seq and imaging data yield a canonical digital embryo•Cell type classification without prior knowledge•De novo reconstruction of the lineage history and spatial organization of the embryo•Timing differences contribute to inter-embryo variability in gene expression
The complete gene expression history and physical position of every single cell at every cell division in an embryo up to gastrulation is reconstructed using a combination of single-cell transcriptomics and light sheet imaging.</description><subject>Animals</subject><subject>ascidian</subject><subject>cell fate specification</subject><subject>Cell Lineage - genetics</subject><subject>cell type classification</subject><subject>Chordata - genetics</subject><subject>Computational Biology - methods</subject><subject>embryogenesis</subject><subject>Gastrulation - genetics</subject><subject>gene expression noise</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation, Developmental - genetics</subject><subject>light sheet imaging</subject><subject>lineage reconstruction</subject><subject>Reproducibility of Results</subject><subject>Sequence Analysis, RNA - methods</subject><subject>Single-Cell Analysis - methods</subject><subject>single-cell RNA sequencing</subject><subject>spatial reconstruction</subject><subject>Transcriptome - genetics</subject><subject>Urochordata - genetics</subject><issn>0092-8674</issn><issn>1097-4172</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kU9v1DAQxS0EokvhC3BAPnJJ8N94gxASWmhBKuKw7dmatWe7XiV2aieV-u1JtKWCC6c5zHu_Gb1HyFvOas548-FYO-y6WjDBaiZrpvUzsuKsNZXiRjwnK8ZaUa0bo87Iq1KOjLG11volOZNCct1wsyLbnykPh7TFu4_0Yuo6ug3xtsNqM5PpdYZYXA7DmHqkXx8i9MEVejPQMdFLKGOeOhhDijRECnRzSNnDiK_Jiz10Bd88znNyc_HtevO9uvp1-WPz5apySuuxglaAYdoI2HH0jdAoQHulGNMA-8bLeRjhlPdrLfYoVdsASiH8ju9wNspz8vnEHaZdj95hHDN0dsihh_xgEwT77yaGg71N99YIadaNmgHvHwE53U1YRtuHsmQKEdNUrJCtbLRUcrklTlKXUykZ909nOLNLG_ZoF6dd2rBM2rmN2fTu7wefLH_inwWfTgKcY7oPmG1xAaNDHzK60foU_sf_DZaKnIo</recordid><startdate>20200514</startdate><enddate>20200514</enddate><creator>Sladitschek, Hanna L.</creator><creator>Fiuza, Ulla-Maj</creator><creator>Pavlinic, Dinko</creator><creator>Benes, Vladimir</creator><creator>Hufnagel, Lars</creator><creator>Neveu, Pierre A.</creator><general>Elsevier Inc</general><general>Cell Press</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20200514</creationdate><title>MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate</title><author>Sladitschek, Hanna L. ; Fiuza, Ulla-Maj ; Pavlinic, Dinko ; Benes, Vladimir ; Hufnagel, Lars ; Neveu, Pierre A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-a92a70572ab1ed625e2a5d44005aaf6d35aa72c4dd852fe3496ae322db1be7053</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Animals</topic><topic>ascidian</topic><topic>cell fate specification</topic><topic>Cell Lineage - genetics</topic><topic>cell type classification</topic><topic>Chordata - genetics</topic><topic>Computational Biology - methods</topic><topic>embryogenesis</topic><topic>Gastrulation - genetics</topic><topic>gene expression noise</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation, Developmental - genetics</topic><topic>light sheet imaging</topic><topic>lineage reconstruction</topic><topic>Reproducibility of Results</topic><topic>Sequence Analysis, RNA - methods</topic><topic>Single-Cell Analysis - methods</topic><topic>single-cell RNA sequencing</topic><topic>spatial reconstruction</topic><topic>Transcriptome - genetics</topic><topic>Urochordata - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sladitschek, Hanna L.</creatorcontrib><creatorcontrib>Fiuza, Ulla-Maj</creatorcontrib><creatorcontrib>Pavlinic, Dinko</creatorcontrib><creatorcontrib>Benes, Vladimir</creatorcontrib><creatorcontrib>Hufnagel, Lars</creatorcontrib><creatorcontrib>Neveu, Pierre A.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cell</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sladitschek, Hanna L.</au><au>Fiuza, Ulla-Maj</au><au>Pavlinic, Dinko</au><au>Benes, Vladimir</au><au>Hufnagel, Lars</au><au>Neveu, Pierre A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate</atitle><jtitle>Cell</jtitle><addtitle>Cell</addtitle><date>2020-05-14</date><risdate>2020</risdate><volume>181</volume><issue>4</issue><spage>922</spage><epage>935.e21</epage><pages>922-935.e21</pages><issn>0092-8674</issn><eissn>1097-4172</eissn><abstract>Single-cell RNA sequencing (scRNA-seq) provides a leap forward in resolving cellular diversity and developmental trajectories but fails to comprehensively delineate the spatial organization and precise cellular makeup of individual embryos. Here, we reconstruct from scRNA-seq and light sheet imaging data a canonical digital embryo that captures the genome-wide gene expression trajectory of every single cell at every cell division in the 18 lineages up to gastrulation in the ascidian Phallusia mammillata. By using high-coverage scRNA-seq, we devise a computational framework that stratifies single cells of individual embryos into cell types without prior knowledge. Unbiased transcriptome data analysis mapped each cell’s physical position and lineage history, yielding the complete history of gene expression at the genome-wide level for every single cell in a developing embryo. A comparison of individual embryos reveals both extensive reproducibility between symmetric embryo sides and a large inter-embryonic variability due to small differences in embryogenesis timing.
[Display omitted]
•Integration of scRNA-seq and imaging data yield a canonical digital embryo•Cell type classification without prior knowledge•De novo reconstruction of the lineage history and spatial organization of the embryo•Timing differences contribute to inter-embryo variability in gene expression
The complete gene expression history and physical position of every single cell at every cell division in an embryo up to gastrulation is reconstructed using a combination of single-cell transcriptomics and light sheet imaging.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32315617</pmid><doi>10.1016/j.cell.2020.03.055</doi><oa>free_for_read</oa></addata></record> |
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subjects | Animals ascidian cell fate specification Cell Lineage - genetics cell type classification Chordata - genetics Computational Biology - methods embryogenesis Gastrulation - genetics gene expression noise Gene Expression Profiling - methods Gene Expression Regulation, Developmental - genetics light sheet imaging lineage reconstruction Reproducibility of Results Sequence Analysis, RNA - methods Single-Cell Analysis - methods single-cell RNA sequencing spatial reconstruction Transcriptome - genetics Urochordata - genetics |
title | MorphoSeq: Full Single-Cell Transcriptome Dynamics Up to Gastrulation in a Chordate |
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