XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment
Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that e...
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creator | Lee, Youjin Bogdanoff, Derek Wang, Yutong Hartoularos, George C Woo, Jonathan M Mowery, Cody T Nisonoff, Hunter M Lee, David S Sun, Yang Lee, James Mehdizadeh, Sadaf Cantlon, Joshua Shifrut, Eric Ngyuen, David N Roth, Theodore L Song, Yun S Marson, Alexander Chow, Eric D Ye, Chun Jimmie |
description | Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue. |
doi_str_mv | 10.1126/sciadv.abg4755 |
format | Article |
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To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.</description><identifier>ISSN: 2375-2548</identifier><identifier>EISSN: 2375-2548</identifier><identifier>DOI: 10.1126/sciadv.abg4755</identifier><identifier>PMID: 33883145</identifier><language>eng</language><publisher>United States: American Association for the Advancement of Science</publisher><subject>Animals ; Cancer ; Gene Expression Profiling ; Mice ; Neoplasms - genetics ; SciAdv r-articles ; Sequence Analysis, RNA ; Single-Cell Analysis ; Systems Biology ; Transcriptome ; Tumor Microenvironment - genetics ; Whole Exome Sequencing</subject><ispartof>Science advances, 2021-04, Vol.7 (17)</ispartof><rights>Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).</rights><rights>Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). 2021 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c456t-560bb8e3e78dc8110ebaf56c777fe0676d327afe0e092591088e82f0d704b9d33</citedby><cites>FETCH-LOGICAL-c456t-560bb8e3e78dc8110ebaf56c777fe0676d327afe0e092591088e82f0d704b9d33</cites><orcidid>0000-0001-7796-7779 ; 0000-0002-2489-1122 ; 0000-0001-6827-0128 ; 0000-0003-1357-8111 ; 0000-0001-6808-2717 ; 0000-0002-3970-9573 ; 0000-0002-1762-1677 ; 0000-0002-0734-9868 ; 0000-0003-2939-013X ; 0000-0001-6539-4272 ; 0000-0001-6560-3783 ; 0000-0002-2734-5776 ; 0000-0003-1700-3737 ; 0000-0002-9344-8060 ; 0000-0001-6980-2368 ; 0000-0001-8079-918X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059935/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059935/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33883145$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Youjin</creatorcontrib><creatorcontrib>Bogdanoff, Derek</creatorcontrib><creatorcontrib>Wang, Yutong</creatorcontrib><creatorcontrib>Hartoularos, George C</creatorcontrib><creatorcontrib>Woo, Jonathan M</creatorcontrib><creatorcontrib>Mowery, Cody T</creatorcontrib><creatorcontrib>Nisonoff, Hunter M</creatorcontrib><creatorcontrib>Lee, David S</creatorcontrib><creatorcontrib>Sun, Yang</creatorcontrib><creatorcontrib>Lee, James</creatorcontrib><creatorcontrib>Mehdizadeh, Sadaf</creatorcontrib><creatorcontrib>Cantlon, Joshua</creatorcontrib><creatorcontrib>Shifrut, Eric</creatorcontrib><creatorcontrib>Ngyuen, David N</creatorcontrib><creatorcontrib>Roth, Theodore L</creatorcontrib><creatorcontrib>Song, Yun S</creatorcontrib><creatorcontrib>Marson, Alexander</creatorcontrib><creatorcontrib>Chow, Eric D</creatorcontrib><creatorcontrib>Ye, Chun Jimmie</creatorcontrib><title>XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment</title><title>Science advances</title><addtitle>Sci Adv</addtitle><description>Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.</description><subject>Animals</subject><subject>Cancer</subject><subject>Gene Expression Profiling</subject><subject>Mice</subject><subject>Neoplasms - genetics</subject><subject>SciAdv r-articles</subject><subject>Sequence Analysis, RNA</subject><subject>Single-Cell Analysis</subject><subject>Systems Biology</subject><subject>Transcriptome</subject><subject>Tumor Microenvironment - genetics</subject><subject>Whole Exome Sequencing</subject><issn>2375-2548</issn><issn>2375-2548</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkU1rGzEQhkVpiIPra45Bx17WkVarj-2hEEKbBEwKSQptL0K7O2sr7EqOtF7ifx8Fu8Y5zTB65p0ZvQidUzKnNBeXsbamGeemWhaS80_oLGeSZzkv1OejfIJmMT4TQmghBKflKZowphSjBT9D8c_ff_DyDT-uzWBN121xgOi7ERocrVt2kNXQdfjh_gpHeNmAq1M1MSOYLmJ4XSc8Wu_wCgYIfgkO7LDF1uFhBXjY9D7g3tbBgxtt8K4HN3xBJ23qhtk-TtHvnz-erm-zxa-bu-urRVYXXAwZF6SqFDCQqqkVpQQq03JRSylbIEKKhuXSpBRImfOSEqVA5S1pJCmqsmFsir7vdNebqoemTqOD6fQ62N6ErfbG6o8vzq700o9aEV6WjCeBr3uB4NPtcdC9je__YRz4TdQ5p0IVVORlQuc7NJ0aY4D2MIYS_W6W3pml92alhovj5Q74f2vYG-7Gle0</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Lee, Youjin</creator><creator>Bogdanoff, Derek</creator><creator>Wang, Yutong</creator><creator>Hartoularos, George C</creator><creator>Woo, Jonathan M</creator><creator>Mowery, Cody T</creator><creator>Nisonoff, Hunter M</creator><creator>Lee, David S</creator><creator>Sun, Yang</creator><creator>Lee, James</creator><creator>Mehdizadeh, Sadaf</creator><creator>Cantlon, Joshua</creator><creator>Shifrut, Eric</creator><creator>Ngyuen, David N</creator><creator>Roth, Theodore L</creator><creator>Song, Yun S</creator><creator>Marson, Alexander</creator><creator>Chow, Eric D</creator><creator>Ye, Chun Jimmie</creator><general>American Association for the Advancement of Science</general><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><orcidid>https://orcid.org/0000-0001-7796-7779</orcidid><orcidid>https://orcid.org/0000-0002-2489-1122</orcidid><orcidid>https://orcid.org/0000-0001-6827-0128</orcidid><orcidid>https://orcid.org/0000-0003-1357-8111</orcidid><orcidid>https://orcid.org/0000-0001-6808-2717</orcidid><orcidid>https://orcid.org/0000-0002-3970-9573</orcidid><orcidid>https://orcid.org/0000-0002-1762-1677</orcidid><orcidid>https://orcid.org/0000-0002-0734-9868</orcidid><orcidid>https://orcid.org/0000-0003-2939-013X</orcidid><orcidid>https://orcid.org/0000-0001-6539-4272</orcidid><orcidid>https://orcid.org/0000-0001-6560-3783</orcidid><orcidid>https://orcid.org/0000-0002-2734-5776</orcidid><orcidid>https://orcid.org/0000-0003-1700-3737</orcidid><orcidid>https://orcid.org/0000-0002-9344-8060</orcidid><orcidid>https://orcid.org/0000-0001-6980-2368</orcidid><orcidid>https://orcid.org/0000-0001-8079-918X</orcidid></search><sort><creationdate>20210401</creationdate><title>XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment</title><author>Lee, Youjin ; 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subjects | Animals Cancer Gene Expression Profiling Mice Neoplasms - genetics SciAdv r-articles Sequence Analysis, RNA Single-Cell Analysis Systems Biology Transcriptome Tumor Microenvironment - genetics Whole Exome Sequencing |
title | XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment |
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