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Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling

Author

Listed:
  • Qingnan Liang

    (Baylor College of Medicine
    Baylor College of Medicine
    Baylor College of Medicine)

  • Rachayata Dharmat

    (Baylor College of Medicine
    Baylor College of Medicine
    St. Jude Children’s Research Hospital)

  • Leah Owen

    (University of Utah School of Medicine)

  • Akbar Shakoor

    (University of Utah School of Medicine)

  • Yumei Li

    (Baylor College of Medicine)

  • Sangbae Kim

    (Baylor College of Medicine)

  • Albert Vitale

    (University of Utah School of Medicine)

  • Ivana Kim

    (University of Utah School of Medicine)

  • Denise Morgan

    (University of Utah School of Medicine
    University of Utah)

  • Shaoheng Liang

    (The University of Texas MD Anderson Cancer Center)

  • Nathaniel Wu

    (Baylor College of Medicine)

  • Ken Chen

    (The University of Texas MD Anderson Cancer Center)

  • Margaret M. DeAngelis

    (University of Utah School of Medicine
    University of Utah
    University of Utah School of Medicine)

  • Rui Chen

    (Baylor College of Medicine
    Baylor College of Medicine
    Baylor College of Medicine)

Abstract

Single-cell RNA-seq is a powerful tool in decoding the heterogeneity in complex tissues by generating transcriptomic profiles of the individual cell. Here, we report a single-nuclei RNA-seq (snRNA-seq) transcriptomic study on human retinal tissue, which is composed of multiple cell types with distinct functions. Six samples from three healthy donors are profiled and high-quality RNA-seq data is obtained for 5873 single nuclei. All major retinal cell types are observed and marker genes for each cell type are identified. The gene expression of the macular and peripheral retina is compared to each other at cell-type level. Furthermore, our dataset shows an improved power for prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrate that obtaining single cell transcriptomes from human frozen tissues can provide insight missed by either human bulk RNA-seq or animal models.

Suggested Citation

  • Qingnan Liang & Rachayata Dharmat & Leah Owen & Akbar Shakoor & Yumei Li & Sangbae Kim & Albert Vitale & Ivana Kim & Denise Morgan & Shaoheng Liang & Nathaniel Wu & Ken Chen & Margaret M. DeAngelis & , 2019. "Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12917-9
    DOI: 10.1038/s41467-019-12917-9
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