June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
Single cell RNA sequencing reveals cellular and molecular complexity of adult lacrimal gland
Author Affiliations & Notes
  • Helen P Makarenkova
    Molecular Medicine, The Scripps Research Institute, La Jolla, California, United States
  • Vanessa Delcroix
    Molecular Medicine, The Scripps Research Institute, La Jolla, California, United States
  • Oliver Mauduit
    Molecular Medicine, The Scripps Research Institute, La Jolla, California, United States
  • Takeshi Umazume
    Molecular Medicine, The Scripps Research Institute, La Jolla, California, United States
  • Cintia S De Paiva
    Ocular Surface Center, Department of Ophthalmology, Baylor College of Medicine, Houston, Texas, United States
  • Footnotes
    Commercial Relationships   Helen Makarenkova, None; Vanessa Delcroix, None; Oliver Mauduit, None; Takeshi Umazume, None; Cintia De Paiva, None
  • Footnotes
    Support  NIH EY026202, EY030447
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 2049. doi:
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    • Get Citation

      Helen P Makarenkova, Vanessa Delcroix, Oliver Mauduit, Takeshi Umazume, Cintia S De Paiva; Single cell RNA sequencing reveals cellular and molecular complexity of adult lacrimal gland. Invest. Ophthalmol. Vis. Sci. 2021;62(8):2049.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Single-cell RNA sequencing using 10X Genomics platforms is an effective way to reveal the heterogeneity of the lacrimal gland, define specific cell lineages, and to identify novel or poorly studied cell types.

Methods : We used unbiased high-throughput single-cell RNA sequencing (scRNA-seq) to identify the transcriptional profiles of adult lacrimal glands and analyzed the transcriptomes of lacrimal gland cells obtained from 3 adult mice. Transcriptionally similar cells were aggregated and analyzed using R Studio, Seurat, and the recently developed Rosalind software. Validation of each cluster has been done by genetic cell lineage labeling combined with analysis of label retaining cells and immunostaining.

Results : Unsupervised clustering resulted in the identification of 21 cell clusters. We have identified 8 epithelial cell clusters: basal ductal contractile cells, expressing several actins, keratins (Krts) and Btg2 (with anti-proliferative properties); basal ductal cells of the progenitor type, expressing Krts, KIT, Wfdc2, and Cnnd, luminal ductal cells, expressing a specific marker of luminal cells Krt19, intercalated duct cells with progenitor cell properties, three different types of acinar cells, expressing Aqp5, and myoepithelial cells, expressing smooth muscle actin (Acta2) and other contractile genes. Stromal and immune cells were identified based on the expression of vimentin (Vim), Ptprc (CD45), Pecame1, and Acta2. We identified 13 types of stromal cells, including two populations of endothelial cells, pericytes - smooth muscle cells of endodermal origin, expressing Acta2 and desmin (Des), two populations of fibroblasts: matrix producing fibroblasts and growth factor expressing fibroblasts. We also identified several clusters of immune cells, such as natural killer cells, tissue specific macrophages, small clusters of cytokines producing macrophages, antigen presenting cells, mast cells, and tissue resident T cells: CD4+ T cells, CD8+ T cells and Tregs. Analysis of label retaining cells combined with lineage tracing, immunostaining and image analysis confirmed classification of lacrimal gland epithelial cells. Thus, similar to scRNA-seq data, progenitor cells have been found within the basal layer of ducts and within intercalated ducts.

Conclusions : Single cell RNA-sequencing uncovered discrete transcriptional signatures of specific cell types within poorly identified cell populations.

This is a 2021 ARVO Annual Meeting abstract.

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