Single-cell transcriptomic profiling of the aging mouse brain
The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of...
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| Veröffentlicht in: | Nature neuroscience 2019-10, Vol.22 (10), p.1696-1708 |
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| creator | Ximerakis, Methodios Lipnick, Scott L. Innes, Brendan T. Simmons, Sean K. Adiconis, Xian Dionne, Danielle Mayweather, Brittany A. Nguyen, Lan Niziolek, Zachary Ozek, Ceren Butty, Vincent L. Isserlin, Ruth Buchanan, Sean M. Levine, Stuart S. Regev, Aviv Bader, Gary D. Levin, Joshua Z. Rubin, Lee L. |
| description | The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand–receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at
https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain
) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.
A single-cell transcriptomic atlas of the aging mouse brain reveals coordinated and cell-type-specific aging signatures across multiple cell populations. Catalogs of aging-related genes, pathways and ligand–receptor interactions are reported. |
| doi_str_mv | 10.1038/s41593-019-0491-3 |
| format | Article |
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https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain
) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.
A single-cell transcriptomic atlas of the aging mouse brain reveals coordinated and cell-type-specific aging signatures across multiple cell populations. Catalogs of aging-related genes, pathways and ligand–receptor interactions are reported.</description><identifier>ISSN: 1097-6256</identifier><identifier>EISSN: 1546-1726</identifier><identifier>DOI: 10.1038/s41593-019-0491-3</identifier><identifier>PMID: 31551601</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>101/1 ; 13/31 ; 13/51 ; 14/19 ; 14/32 ; 38/39 ; 38/90 ; 38/91 ; 631/337/2019 ; 631/378/2611 ; 631/378/87 ; 631/80 ; 64/60 ; Aging ; Aging (artificial) ; Aging - genetics ; Animal Genetics and Genomics ; Animals ; Behavioral Sciences ; Biological Techniques ; Biomedical and Life Sciences ; Biomedicine ; Brain ; Brain - cytology ; Brain - growth & development ; Brain cells ; Cell Communication - genetics ; Cell Lineage - genetics ; Datasets ; Gene Expression Profiling ; Gene Expression Regulation - genetics ; Genetic aspects ; High-Throughput Nucleotide Sequencing ; Male ; Mice ; Mice, Inbred C57BL ; Nervous system ; Neurobiology ; Neurons - physiology ; Neurosciences ; Physiological aspects ; Resource ; Ribosomes - genetics ; Single-Cell Analysis ; Transcription ; Transcriptome - genetics</subject><ispartof>Nature neuroscience, 2019-10, Vol.22 (10), p.1696-1708</ispartof><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2019</rights><rights>COPYRIGHT 2019 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Oct 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c516t-28bc1a99f6b8f2a7127649d050bb666c77f3f7baaf619c8d065830c8bbf9d1813</citedby><cites>FETCH-LOGICAL-c516t-28bc1a99f6b8f2a7127649d050bb666c77f3f7baaf619c8d065830c8bbf9d1813</cites><orcidid>0000-0002-2815-7558 ; 0000-0002-8658-841X ; 0000-0002-8338-4323 ; 0000-0003-2496-3154 ; 0000-0003-1173-2429 ; 0000-0003-0185-8861 ; 0000-0002-0170-3598</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41593-019-0491-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41593-019-0491-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31551601$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ximerakis, Methodios</creatorcontrib><creatorcontrib>Lipnick, Scott L.</creatorcontrib><creatorcontrib>Innes, Brendan T.</creatorcontrib><creatorcontrib>Simmons, Sean K.</creatorcontrib><creatorcontrib>Adiconis, Xian</creatorcontrib><creatorcontrib>Dionne, Danielle</creatorcontrib><creatorcontrib>Mayweather, Brittany A.</creatorcontrib><creatorcontrib>Nguyen, Lan</creatorcontrib><creatorcontrib>Niziolek, Zachary</creatorcontrib><creatorcontrib>Ozek, Ceren</creatorcontrib><creatorcontrib>Butty, Vincent L.</creatorcontrib><creatorcontrib>Isserlin, Ruth</creatorcontrib><creatorcontrib>Buchanan, Sean M.</creatorcontrib><creatorcontrib>Levine, Stuart S.</creatorcontrib><creatorcontrib>Regev, Aviv</creatorcontrib><creatorcontrib>Bader, Gary D.</creatorcontrib><creatorcontrib>Levin, Joshua Z.</creatorcontrib><creatorcontrib>Rubin, Lee L.</creatorcontrib><title>Single-cell transcriptomic profiling of the aging mouse brain</title><title>Nature neuroscience</title><addtitle>Nat Neurosci</addtitle><addtitle>Nat Neurosci</addtitle><description>The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets of aging-related genes, pathways and ligand–receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell-type specific manner, even at times in opposite directions. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at
https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain
) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.
A single-cell transcriptomic atlas of the aging mouse brain reveals coordinated and cell-type-specific aging signatures across multiple cell populations. Catalogs of aging-related genes, pathways and ligand–receptor interactions are reported.</description><subject>101/1</subject><subject>13/31</subject><subject>13/51</subject><subject>14/19</subject><subject>14/32</subject><subject>38/39</subject><subject>38/90</subject><subject>38/91</subject><subject>631/337/2019</subject><subject>631/378/2611</subject><subject>631/378/87</subject><subject>631/80</subject><subject>64/60</subject><subject>Aging</subject><subject>Aging (artificial)</subject><subject>Aging - genetics</subject><subject>Animal Genetics and Genomics</subject><subject>Animals</subject><subject>Behavioral Sciences</subject><subject>Biological Techniques</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Brain</subject><subject>Brain - cytology</subject><subject>Brain - growth & development</subject><subject>Brain cells</subject><subject>Cell Communication - genetics</subject><subject>Cell Lineage - genetics</subject><subject>Datasets</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation - genetics</subject><subject>Genetic aspects</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Male</subject><subject>Mice</subject><subject>Mice, Inbred C57BL</subject><subject>Nervous system</subject><subject>Neurobiology</subject><subject>Neurons - physiology</subject><subject>Neurosciences</subject><subject>Physiological aspects</subject><subject>Resource</subject><subject>Ribosomes - genetics</subject><subject>Single-Cell Analysis</subject><subject>Transcription</subject><subject>Transcriptome - genetics</subject><issn>1097-6256</issn><issn>1546-1726</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kU9LHTEUxUNRqrX9AN2UATftIjaZTG4mCxcibRUEobbrkGSS6cj8eSYz0H577_Cs8kTJIgn53ZNz7yHkI2cnnIn6a6641IIyrimrNKfiDTnksgLKVQl7eGZaUSglHJB3Od8yxpSs9VtyILiUHBg_JKc33dj2gfrQ98Wc7Jh96jbzNHS-2KQpdj2-F1Ms5j-hsO16GaYlh8Il243vyX60fQ4fHvYj8vv7t1_nF_Tq-sfl-dkV9fjNTMvaeW61juDqWFrFSwWVbphkzgGAVyqKqJy1Ebj2dcNA1oL52rmoG15zcUQ-b3XR0t0S8myGLq-W7RjQjSlLjaKVUhrR42fo7bSkEd2tFICQlYInqrV9MN0YJ-zdr6LmDBgDrXFYSJ28QOFqAs5nGgOOJ-wWfNkpQGYOf-fWLjmby5ufuyzfsj5NOacQzSZ1g03_DGdmjdds4zUYr1njNQJrPj00t7ghNI8V__NEoNwCGZ_GNqSn7l9XvQesLauu</recordid><startdate>20191001</startdate><enddate>20191001</enddate><creator>Ximerakis, Methodios</creator><creator>Lipnick, Scott L.</creator><creator>Innes, Brendan T.</creator><creator>Simmons, Sean K.</creator><creator>Adiconis, Xian</creator><creator>Dionne, Danielle</creator><creator>Mayweather, Brittany A.</creator><creator>Nguyen, Lan</creator><creator>Niziolek, Zachary</creator><creator>Ozek, Ceren</creator><creator>Butty, Vincent L.</creator><creator>Isserlin, Ruth</creator><creator>Buchanan, Sean M.</creator><creator>Levine, Stuart S.</creator><creator>Regev, Aviv</creator><creator>Bader, Gary D.</creator><creator>Levin, Joshua Z.</creator><creator>Rubin, Lee L.</creator><general>Nature Publishing Group US</general><general>Nature Publishing Group</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>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>7TM</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</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>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-2815-7558</orcidid><orcidid>https://orcid.org/0000-0002-8658-841X</orcidid><orcidid>https://orcid.org/0000-0002-8338-4323</orcidid><orcidid>https://orcid.org/0000-0003-2496-3154</orcidid><orcidid>https://orcid.org/0000-0003-1173-2429</orcidid><orcidid>https://orcid.org/0000-0003-0185-8861</orcidid><orcidid>https://orcid.org/0000-0002-0170-3598</orcidid></search><sort><creationdate>20191001</creationdate><title>Single-cell transcriptomic profiling of the aging mouse brain</title><author>Ximerakis, Methodios ; Lipnick, Scott L. ; Innes, Brendan T. ; Simmons, Sean K. ; Adiconis, Xian ; Dionne, Danielle ; Mayweather, Brittany A. ; Nguyen, Lan ; Niziolek, Zachary ; Ozek, Ceren ; Butty, Vincent L. ; Isserlin, Ruth ; Buchanan, Sean M. ; Levine, Stuart S. ; Regev, Aviv ; Bader, Gary D. ; Levin, Joshua Z. ; Rubin, Lee L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c516t-28bc1a99f6b8f2a7127649d050bb666c77f3f7baaf619c8d065830c8bbf9d1813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>101/1</topic><topic>13/31</topic><topic>13/51</topic><topic>14/19</topic><topic>14/32</topic><topic>38/39</topic><topic>38/90</topic><topic>38/91</topic><topic>631/337/2019</topic><topic>631/378/2611</topic><topic>631/378/87</topic><topic>631/80</topic><topic>64/60</topic><topic>Aging</topic><topic>Aging (artificial)</topic><topic>Aging - 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https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain
) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.
A single-cell transcriptomic atlas of the aging mouse brain reveals coordinated and cell-type-specific aging signatures across multiple cell populations. Catalogs of aging-related genes, pathways and ligand–receptor interactions are reported.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>31551601</pmid><doi>10.1038/s41593-019-0491-3</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-2815-7558</orcidid><orcidid>https://orcid.org/0000-0002-8658-841X</orcidid><orcidid>https://orcid.org/0000-0002-8338-4323</orcidid><orcidid>https://orcid.org/0000-0003-2496-3154</orcidid><orcidid>https://orcid.org/0000-0003-1173-2429</orcidid><orcidid>https://orcid.org/0000-0003-0185-8861</orcidid><orcidid>https://orcid.org/0000-0002-0170-3598</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1097-6256 |
| ispartof | Nature neuroscience, 2019-10, Vol.22 (10), p.1696-1708 |
| issn | 1097-6256 1546-1726 |
| language | eng |
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| source | MEDLINE; Nature; SpringerLink Journals - AutoHoldings |
| subjects | 101/1 13/31 13/51 14/19 14/32 38/39 38/90 38/91 631/337/2019 631/378/2611 631/378/87 631/80 64/60 Aging Aging (artificial) Aging - genetics Animal Genetics and Genomics Animals Behavioral Sciences Biological Techniques Biomedical and Life Sciences Biomedicine Brain Brain - cytology Brain - growth & development Brain cells Cell Communication - genetics Cell Lineage - genetics Datasets Gene Expression Profiling Gene Expression Regulation - genetics Genetic aspects High-Throughput Nucleotide Sequencing Male Mice Mice, Inbred C57BL Nervous system Neurobiology Neurons - physiology Neurosciences Physiological aspects Resource Ribosomes - genetics Single-Cell Analysis Transcription Transcriptome - genetics |
| title | Single-cell transcriptomic profiling of the aging mouse brain |
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