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  1. Artikel ; Online: Mettl3-catalyzed m

    Maldonado López, Alexandra M / Ko, Eun Kyung / Huang, Sijia / Pacella, Gina / Kuprasertkul, Nina / D'souza, Carina A / Reyes Hueros, Raúl A / Shen, Hui / Stoute, Julian / Elashal, Heidi / Sinkfield, Morgan / Anderson, Amy / Prouty, Stephen / Li, Hua-Bing / Seykora, John T / Liu, Kathy Fange / Capell, Brian C

    Science advances

    2023  Band 9, Heft 35, Seite(n) eadg5234

    Abstract: ... ...

    Abstract N6
    Mesh-Begriff(e) Animals ; Mice ; Histones ; Methyltransferases/genetics ; Adenosine ; Cell Adhesion ; RNA, Messenger ; Catalysis
    Chemische Substanzen Histones ; Methyltransferases (EC 2.1.1.-) ; Adenosine (K72T3FS567) ; RNA, Messenger ; Mettl3 protein, mouse (EC 2.1.1.-)
    Sprache Englisch
    Erscheinungsdatum 2023-09-01
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2810933-8
    ISSN 2375-2548 ; 2375-2548
    ISSN (online) 2375-2548
    ISSN 2375-2548
    DOI 10.1126/sciadv.adg5234
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors

    Shaffer, Sydney M / Emert, Benjamin L / Reyes Hueros, Raúl A / Cote, Christopher / Harmange, Guillaume / Schaff, Dylan L / Sizemore, Ann E / Gupte, Rohit / Torre, Eduardo / Singh, Abhyudai / Bassett, Danielle S / Raj, Arjun

    Cell. 2020 Aug. 20, v. 182, no. 4

    2020  

    Abstract: Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring ... ...

    Abstract Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we combined Luria and Delbrück’s fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several divisions. MemorySeq revealed multiple gene modules that expressed together in rare cells within otherwise homogeneous clonal populations. These rare cell subpopulations were associated with biologically distinct behaviors like proliferation in the face of anti-cancer therapeutics. The identification of non-genetic, multigenerational fluctuations can reveal new forms of biological memory in single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.
    Schlagwörter cancer therapy ; cell division ; clones ; gene expression ; gene regulatory networks ; genes ; heritability ; memory ; sequence analysis
    Sprache Englisch
    Erscheinungsverlauf 2020-0820
    Umfang p. 947-959.e17.
    Erscheinungsort Elsevier Inc.
    Dokumenttyp Artikel
    ZDB-ID 187009-9
    ISSN 1097-4172 ; 0092-8674
    ISSN (online) 1097-4172
    ISSN 0092-8674
    DOI 10.1016/j.cell.2020.07.003
    Datenquelle NAL Katalog (AGRICOLA)

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  3. Artikel ; Online: Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors.

    Shaffer, Sydney M / Emert, Benjamin L / Reyes Hueros, Raúl A / Cote, Christopher / Harmange, Guillaume / Schaff, Dylan L / Sizemore, Ann E / Gupte, Rohit / Torre, Eduardo / Singh, Abhyudai / Bassett, Danielle S / Raj, Arjun

    Cell

    2020  Band 182, Heft 4, Seite(n) 947–959.e17

    Abstract: Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring ... ...

    Abstract Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we combined Luria and Delbrück's fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several divisions. MemorySeq revealed multiple gene modules that expressed together in rare cells within otherwise homogeneous clonal populations. These rare cell subpopulations were associated with biologically distinct behaviors like proliferation in the face of anti-cancer therapeutics. The identification of non-genetic, multigenerational fluctuations can reveal new forms of biological memory in single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.
    Mesh-Begriff(e) Cell Division ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics ; Genes, Reporter ; Humans ; In Situ Hybridization, Fluorescence ; Microscopy, Fluorescence ; Sequence Analysis, RNA ; Single-Cell Analysis/methods ; Time-Lapse Imaging ; Transcriptome
    Sprache Englisch
    Erscheinungsdatum 2020-07-30
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 187009-9
    ISSN 1097-4172 ; 0092-8674
    ISSN (online) 1097-4172
    ISSN 0092-8674
    DOI 10.1016/j.cell.2020.07.003
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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