An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment
The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses...
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Veröffentlicht in: | Journal of mammary gland biology and neoplasia 2021-03, Vol.26 (1), p.29-42 |
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description | The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses have contributed to understand the cellular and transcriptional heterogeneity of this complex tissue. Here, we integrate scRNA-seq data from three foundational reports that have explored the mammary gland cell populations throughout development at single-cell level using 10× Chromium Drop-Seq. We center our analysis on post-natal development of the mammary gland, from puberty to post-involution. The new integrated study corresponds to RNA sequences from 53,686 individual cells, which greatly outnumbers the three initial data sets. The large volume of information provides new insights, as a better resolution of the previously detected Procr
+
stem-like cell subpopulation or the identification of a novel group of MECs expressing immune-like markers. Moreover, here we present new pseudo-temporal trajectories of MEC populations at two resolution levels, that is either considering all mammary cell subtypes or focusing specifically on the luminal lineages. Interestingly, the luminal-restricted analysis reveals distinct expression patterns of various genes that encode milk proteins, suggesting specific and non-redundant roles for each of them. In summary, our data show that the application of bioinformatic tools to integrate multiple scRNA-seq data-sets helps to describe and interpret the high level of plasticity involved in gene expression regulation throughout mammary gland post-natal development. |
doi_str_mv | 10.1007/s10911-021-09488-1 |
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+
stem-like cell subpopulation or the identification of a novel group of MECs expressing immune-like markers. Moreover, here we present new pseudo-temporal trajectories of MEC populations at two resolution levels, that is either considering all mammary cell subtypes or focusing specifically on the luminal lineages. Interestingly, the luminal-restricted analysis reveals distinct expression patterns of various genes that encode milk proteins, suggesting specific and non-redundant roles for each of them. In summary, our data show that the application of bioinformatic tools to integrate multiple scRNA-seq data-sets helps to describe and interpret the high level of plasticity involved in gene expression regulation throughout mammary gland post-natal development.</description><identifier>ISSN: 1083-3021</identifier><identifier>EISSN: 1573-7039</identifier><identifier>DOI: 10.1007/s10911-021-09488-1</identifier><identifier>PMID: 33913090</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Animals ; Cancer Research ; Cell death ; Cell differentiation ; Chromium ; Computational Biology - methods ; Epithelial cells ; Epithelial Cells - physiology ; Female ; Gene expression ; Gene Expression Regulation, Developmental ; Gene regulation ; Mammary gland ; Mammary Glands, Animal - cytology ; Mammary Glands, Animal - physiology ; Medicine ; Medicine & Public Health ; Mice ; Oncology ; Original Paper ; Puberty ; Sequence Analysis, RNA - methods ; Single-Cell Analysis - methods ; Transcription ; Transcriptome</subject><ispartof>Journal of mammary gland biology and neoplasia, 2021-03, Vol.26 (1), p.29-42</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-57eb26ab73e28013f9fb1cbf35255eeff239ee71aabbd41cbeba87c9a52bf0e23</citedby><cites>FETCH-LOGICAL-c375t-57eb26ab73e28013f9fb1cbf35255eeff239ee71aabbd41cbeba87c9a52bf0e23</cites><orcidid>0000-0002-0229-8870</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10911-021-09488-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10911-021-09488-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33913090$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>García Solá, Martín E.</creatorcontrib><creatorcontrib>Stedile, Micaela</creatorcontrib><creatorcontrib>Beckerman, Inés</creatorcontrib><creatorcontrib>Kordon, Edith C.</creatorcontrib><title>An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment</title><title>Journal of mammary gland biology and neoplasia</title><addtitle>J Mammary Gland Biol Neoplasia</addtitle><addtitle>J Mammary Gland Biol Neoplasia</addtitle><description>The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses have contributed to understand the cellular and transcriptional heterogeneity of this complex tissue. Here, we integrate scRNA-seq data from three foundational reports that have explored the mammary gland cell populations throughout development at single-cell level using 10× Chromium Drop-Seq. We center our analysis on post-natal development of the mammary gland, from puberty to post-involution. The new integrated study corresponds to RNA sequences from 53,686 individual cells, which greatly outnumbers the three initial data sets. The large volume of information provides new insights, as a better resolution of the previously detected Procr
+
stem-like cell subpopulation or the identification of a novel group of MECs expressing immune-like markers. Moreover, here we present new pseudo-temporal trajectories of MEC populations at two resolution levels, that is either considering all mammary cell subtypes or focusing specifically on the luminal lineages. Interestingly, the luminal-restricted analysis reveals distinct expression patterns of various genes that encode milk proteins, suggesting specific and non-redundant roles for each of them. In summary, our data show that the application of bioinformatic tools to integrate multiple scRNA-seq data-sets helps to describe and interpret the high level of plasticity involved in gene expression regulation throughout mammary gland post-natal development.</description><subject>Animals</subject><subject>Cancer Research</subject><subject>Cell death</subject><subject>Cell differentiation</subject><subject>Chromium</subject><subject>Computational Biology - methods</subject><subject>Epithelial cells</subject><subject>Epithelial Cells - physiology</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Developmental</subject><subject>Gene regulation</subject><subject>Mammary gland</subject><subject>Mammary Glands, Animal - cytology</subject><subject>Mammary Glands, Animal - physiology</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Mice</subject><subject>Oncology</subject><subject>Original Paper</subject><subject>Puberty</subject><subject>Sequence Analysis, RNA - methods</subject><subject>Single-Cell Analysis - methods</subject><subject>Transcription</subject><subject>Transcriptome</subject><issn>1083-3021</issn><issn>1573-7039</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kc2OFCEUhStG4_zoC7gwJG7clPLTNMWy0zOOk_SoieOaAH1pq0NBCVRPfB5fdKjpURMXLgiE-51zL5ymeUXwO4KxeJ8JloS0mNYlF13XkifNKeGCtQIz-bSeccdaVusnzVnOe4yx7Jb8eXPCmCQMS3za_FoFdB0K7JIu_QHQ1z7sPLQWvEe3SYdsUz-WOPQWrYrXGUWHyndAX2IubdBFe3QTpwzoRg-DTj_Rlddhi1bex7uMLvps4wHqdZV9gjt0AQfwcRwgzMraYA-2xNRDRn14MN5MQx9qbR2HUacyky-aZ077DC8f9_Pm24fL2_XHdvP56nq92rSWCV5aLsDQpTaCAe0wYU46Q6xxjFPOAZyjTAIIorUx20WtgNGdsFJzahwGys6bt0ffMcUfE-Sihjp__QkdoL5RUU6kkJLiGX3zD7qPU6pzz9SCcbFcLLtK0SNlU8w5gVNj6udfUgSrOUJ1jFDViNRDhIpU0etH68kMsP0j-Z1ZBdgRyLUUdpD-9v6P7T1Wv6o0</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>García Solá, Martín E.</creator><creator>Stedile, Micaela</creator><creator>Beckerman, Inés</creator><creator>Kordon, Edith C.</creator><general>Springer US</general><general>Springer Nature B.V</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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0229-8870</orcidid></search><sort><creationdate>20210301</creationdate><title>An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment</title><author>García Solá, Martín E. ; Stedile, Micaela ; Beckerman, Inés ; Kordon, Edith C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-57eb26ab73e28013f9fb1cbf35255eeff239ee71aabbd41cbeba87c9a52bf0e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Animals</topic><topic>Cancer Research</topic><topic>Cell death</topic><topic>Cell differentiation</topic><topic>Chromium</topic><topic>Computational Biology - methods</topic><topic>Epithelial cells</topic><topic>Epithelial Cells - physiology</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Regulation, Developmental</topic><topic>Gene regulation</topic><topic>Mammary gland</topic><topic>Mammary Glands, Animal - cytology</topic><topic>Mammary Glands, Animal - physiology</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Mice</topic><topic>Oncology</topic><topic>Original Paper</topic><topic>Puberty</topic><topic>Sequence Analysis, RNA - methods</topic><topic>Single-Cell Analysis - methods</topic><topic>Transcription</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>García Solá, Martín E.</creatorcontrib><creatorcontrib>Stedile, Micaela</creatorcontrib><creatorcontrib>Beckerman, Inés</creatorcontrib><creatorcontrib>Kordon, Edith C.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of mammary gland biology and neoplasia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>García Solá, Martín E.</au><au>Stedile, Micaela</au><au>Beckerman, Inés</au><au>Kordon, Edith C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment</atitle><jtitle>Journal of mammary gland biology and neoplasia</jtitle><stitle>J Mammary Gland Biol Neoplasia</stitle><addtitle>J Mammary Gland Biol Neoplasia</addtitle><date>2021-03-01</date><risdate>2021</risdate><volume>26</volume><issue>1</issue><spage>29</spage><epage>42</epage><pages>29-42</pages><issn>1083-3021</issn><eissn>1573-7039</eissn><abstract>The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses have contributed to understand the cellular and transcriptional heterogeneity of this complex tissue. Here, we integrate scRNA-seq data from three foundational reports that have explored the mammary gland cell populations throughout development at single-cell level using 10× Chromium Drop-Seq. We center our analysis on post-natal development of the mammary gland, from puberty to post-involution. The new integrated study corresponds to RNA sequences from 53,686 individual cells, which greatly outnumbers the three initial data sets. The large volume of information provides new insights, as a better resolution of the previously detected Procr
+
stem-like cell subpopulation or the identification of a novel group of MECs expressing immune-like markers. Moreover, here we present new pseudo-temporal trajectories of MEC populations at two resolution levels, that is either considering all mammary cell subtypes or focusing specifically on the luminal lineages. Interestingly, the luminal-restricted analysis reveals distinct expression patterns of various genes that encode milk proteins, suggesting specific and non-redundant roles for each of them. In summary, our data show that the application of bioinformatic tools to integrate multiple scRNA-seq data-sets helps to describe and interpret the high level of plasticity involved in gene expression regulation throughout mammary gland post-natal development.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>33913090</pmid><doi>10.1007/s10911-021-09488-1</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-0229-8870</orcidid></addata></record> |
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subjects | Animals Cancer Research Cell death Cell differentiation Chromium Computational Biology - methods Epithelial cells Epithelial Cells - physiology Female Gene expression Gene Expression Regulation, Developmental Gene regulation Mammary gland Mammary Glands, Animal - cytology Mammary Glands, Animal - physiology Medicine Medicine & Public Health Mice Oncology Original Paper Puberty Sequence Analysis, RNA - methods Single-Cell Analysis - methods Transcription Transcriptome |
title | An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment |
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