Multi-species single-cell transcriptomic analysis of ocular compartment regulons

  1. Pradeep Gautam
  2. Kiyofumi Hamashima
  3. Ying Chen
  4. Yingying Zeng
  5. Bar Makovoz
  6. Bhav Harshad Parikh
  7. Hsin Yee Lee
  8. Katherine Anne Lau
  9. Xinyi Su
  10. Raymond C. B. Wong
  11. Woon-Khiong Chan
  12. Hu Li
  13. Timothy A. Blenkinsop
  14. Yuin-Han Loh

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Abstract

The retina is a widely profiled tissue in multiple species by single-cell RNA sequencing studies. However, integrative research of the retina across species is lacking. Here, we construct the first single-cell atlas of the human and porcine ocular compartments and study inter-species differences in the retina. In addition to that, we identify putative adult stem cells present in the iris tissue. We also create a disease map of genes involved in eye disorders across compartments of the eye. Furthermore, we probe the regulons of different cell populations, which include transcription factors and receptor-ligand interactions and reveal unique directional signalling between ocular cell types. In addition, we study conservation of regulons across vertebrates and zebrafish to identify common core factors. Here, we show perturbation of KLF7 gene expression during retinal ganglion cells differentiation and conclude that it plays a significant role in the maturation of retinal ganglion cells.

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  1. Version published to 10.1038/s41467-021-25968-8
  2. ScreenIT

    SciScore for 10.1101/2020.05.09.085613: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The expression profile of the selected genes was plotted on the bubble plot with the ‘DotPlot’ function in Seurat or violin plot with ‘geom_violin’ function in ggplot2 with the slight modification.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    MAGIC could restore missing values in the large sparse count matrix of single-cell RNA-seq.
    MAGIC
    suggested: (Magic, RRID:SCR_006406)
    The gene-set co-expressing with both ACE2 and TMPRSS2 was used in the gene-set enrichment analysis (GSEA) by Metascape [40] (http://metascape.org).
    Metascape
    suggested: (Metascape, RRID:SCR_016620)
    SCENIC is a powerful software which reconstructs a single-cell regulatory network based on the co-expression patterning between transcription factors (TFs) and potential target genes and the enrichment of the regulator’s binding motif.
    SCENIC
    suggested: (SCENIC, RRID:SCR_017247)
    Based on the exported NicheNet data, the network graph was created using Cytoscape [43] (version 3.7.1) with a Compound Spring Embedder layout.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    The proposed pathway of virus transmission via the route from the human eye was illustrated using BioRender (https://biorender.com).
    BioRender
    suggested: (Biorender, RRID:SCR_018361)
    Data availability: Single-cell RNA-seq data (human primary eyes) have been deposited in the Gene Expression Omnibus (GEO) under the accession code GSE147979, which will be released after publishing our previous studies (Gautam and Hamashima et al., manuscript in preparation).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  3. Version published to 10.1101/2020.05.09.085613v3 on bioRxiv
  4. Version published to 10.1101/2020.05.09.085613v1 on bioRxiv
  5. Version published to 10.1101/2020.05.09.085613v2 on bioRxiv