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Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Author

Listed:
  • Alex K. Shalek

    (Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA)

  • Rahul Satija

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Xian Adiconis

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Rona S. Gertner

    (Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA)

  • Jellert T. Gaublomme

    (Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA)

  • Raktima Raychowdhury

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Schraga Schwartz

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Nir Yosef

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Christine Malboeuf

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Diana Lu

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • John J. Trombetta

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Dave Gennert

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Andreas Gnirke

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Alon Goren

    (Broad Institute of MIT and Harvard, 7 Cambridge Center
    Massachusetts General Hospital)

  • Nir Hacohen

    (Broad Institute of MIT and Harvard, 7 Cambridge Center
    Massachusetts General Hospital)

  • Joshua Z. Levin

    (Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Hongkun Park

    (Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA
    Broad Institute of MIT and Harvard, 7 Cambridge Center)

  • Aviv Regev

    (Broad Institute of MIT and Harvard, 7 Cambridge Center
    Howard Hughes Medical Institute, Massachusetts Institute of Technology)

Abstract

Single-cell RNA sequencing is used to investigate the transcriptional response of 18 mouse bone-marrow-derived dendritic cells after lipopolysaccharide stimulation; many highly expressed genes, such as key immune genes and cytokines, show bimodal variation in both transcript abundance and splicing patterns. This variation reflects differences in both cell state and usage of an interferon-driven pathway involving Stat2 and Irf7.

Suggested Citation

  • Alex K. Shalek & Rahul Satija & Xian Adiconis & Rona S. Gertner & Jellert T. Gaublomme & Raktima Raychowdhury & Schraga Schwartz & Nir Yosef & Christine Malboeuf & Diana Lu & John J. Trombetta & Dave , 2013. "Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells," Nature, Nature, vol. 498(7453), pages 236-240, June.
    • Handle: RePEc:nat:nature:v:498:y:2013:i:7453:d:10.1038_nature12172
    DOI: 10.1038/nature12172
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    Citations

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    Cited by:

    1. Andrew McDavid & Lucas Dennis & Patrick Danaher & Greg Finak & Michael Krouse & Alice Wang & Philippa Webster & Joseph Beechem & Raphael Gottardo, 2014. "Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-10, July.
    2. Angeles Arzalluz-Luque & Pedro Salguero & Sonia Tarazona & Ana Conesa, 2022. "acorde unravels functionally interpretable networks of isoform co-usage from single cell data," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. Sylvie Rato & Antonio Rausell & Miguel Muñoz & Amalio Telenti & Angela Ciuffi, 2017. "Single-cell analysis identifies cellular markers of the HIV permissive cell," PLOS Pathogens, Public Library of Science, vol. 13(10), pages 1-23, October.
    4. Rohith Palli & Mukta G Palshikar & Juilee Thakar, 2019. "Executable pathway analysis using ensemble discrete-state modeling for large-scale data," PLOS Computational Biology, Public Library of Science, vol. 15(9), pages 1-21, September.
    5. Angélique Richard & Loïs Boullu & Ulysse Herbach & Arnaud Bonnafoux & Valérie Morin & Elodie Vallin & Anissa Guillemin & Nan Papili Gao & Rudiyanto Gunawan & Jérémie Cosette & Ophélie Arnaud & Jean-Ja, 2016. "Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process," PLOS Biology, Public Library of Science, vol. 14(12), pages 1-35, December.
    6. Yael Korem & Pablo Szekely & Yuval Hart & Hila Sheftel & Jean Hausser & Avi Mayo & Michael E Rothenberg & Tomer Kalisky & Uri Alon, 2015. "Geometry of the Gene Expression Space of Individual Cells," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-27, July.
    7. Qi Liu & Charles A Herring & Quanhu Sheng & Jie Ping & Alan J Simmons & Bob Chen & Amrita Banerjee & Wei Li & Guoqiang Gu & Robert J Coffey & Yu Shyr & Ken S Lau, 2018. "Quantitative assessment of cell population diversity in single-cell landscapes," PLOS Biology, Public Library of Science, vol. 16(10), pages 1-29, October.
    8. Seungjae Lee & Yen-Chung Chen & Austin E. Gillen & J. Matthew Taliaferro & Bart Deplancke & Hongjie Li & Eric C. Lai, 2022. "Diverse cell-specific patterns of alternative polyadenylation in Drosophila," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    9. Ziye Xu & Tianyu Zhang & Hongyu Chen & Yuyi Zhu & Yuexiao Lv & Shunji Zhang & Jiaye Chen & Haide Chen & Lili Yang & Weiqin Jiang & Shengyu Ni & Fangru Lu & Zhaolun Wang & Hao Yang & Ling Dong & Feng C, 2023. "High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    10. Marco Del Giudice & Stefano Bo & Silvia Grigolon & Carla Bosia, 2018. "On the role of extrinsic noise in microRNA-mediated bimodal gene expression," PLOS Computational Biology, Public Library of Science, vol. 14(4), pages 1-26, April.
    11. Chieh Lin & Jun Ding & Ziv Bar-Joseph, 2020. "Inferring TF activation order in time series scRNA-Seq studies," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-19, February.

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