Single-cell RNA sequencing of sclerotome-derived fibroblasts in zebrafish
Cite this dataset
Rajan, Arsheen et al. (2023). Single-cell RNA sequencing of sclerotome-derived fibroblasts in zebrafish [Dataset]. Dryad. https://doi.org/10.5061/dryad.fttdz090c
Abstract
Despite their importance in tissue maintenance and repair, fibroblast diversity and plasticity remain poorly understood. Using single-cell RNA sequencing, we uncover distinct sclerotome-derived fibroblast populations in zebrafish, including progenitor-like perivascular/interstitial fibroblasts, and specialized fibroblasts such as tenocytes. To determine fibroblast plasticity in vivo, we develop a laser-induced tendon ablation and regeneration model. Lineage tracing reveals that laser-ablated tenocytes are quickly regenerated by preexisting fibroblasts. By combining single-cell clonal analysis and live imaging, we demonstrate that perivascular/interstitial fibroblasts actively migrate to the injury site, where they proliferate and give rise to new tenocytes. By contrast, perivascular fibroblast-derived pericytes or specialized fibroblasts, including tenocytes, exhibit no regenerative plasticity. Interestingly, active Hedgehog (Hh) signaling is required for the proliferation of activated fibroblasts to ensure efficient tenocyte regeneration. Together, our work highlights the functional diversity of fibroblasts and establishes perivascular/interstitial fibroblasts as tenocyte progenitors that promote tendon regeneration in a Hh signaling-dependent manner.
README: Single-cell RNA sequencing of sclerotome-derived fibroblasts in zebrafish
https://doi.org/10.5061/dryad.fttdz090c
Data repository containing code used to generate single-cell RNA sequencing (scRNA-seq) data in the manuscript entitled “Single-cell analysis reveals distinct fibroblast plasticity during tenocyte regeneration in zebrafish” available at: https://www.biorxiv.org/content/10.1101/2023.04.18.537403v1 (preprint).
Description of data and file structure
The sclerotome compartment of the somite (labelled by nkx3-1 expression) is the embryonic source of diverse fibroblast populations. Sclerotome-derived cells were collected by fluorescence-activated cell sorting (FACS) of mCherry-positive cells from trunks of nkx3-1:Gal4; UAS:NTR-mCherry transgenic embryos at 52 hours post fertilization (hpf). Isolated cells were sequenced using the 10X Genomics platform and the Illumina Novaseq S2. The raw counts matrix was generated using CellRanger v.5.0.0 and .loom files for trajectory analysis were generated using velocyto 0.17.16. The resulting unprocessed counts matrix was exported into R/Python for further analysis and is provided here as GSM7181573_filtered_feature_bc_matrix.h5.
Additionally, the code used for downstream analysis is provided in the following files:
R analysis.R: contains code used for pre-processing, quality control, normalization and dimension reduction, clustering, and marker exploration.
RNAvelocity.ipynb: contains code used for RNA velocity inference.
Sharing/Access information
The raw sequencing FASTQ files are available at NCBI GEO GSE229939.
UMI counts matrix is available at NCBI GEO GSE229939.
The code files are also available at https://github.com/hpeng031/Sclerotome.
Code/Software
The code provided (stored in Zenodo) utilized the following additional software/packages:
R analysis.R: This script was executed in R version 4.0.3 and used the following packages - SingleCellExperiment 1.12.0, Seurat 4.0.0, tidyverse 1.3, Matrix 1.2-18, scales, 1.1.1, cowplot 1.1.1, RCurl 1.98-1.3, dplyr 1.0.4, ggplot2 3.3.3, ggprism 1.0.3, AnnotationHub 2.22.0, and tibble 3.0.6.
RNAvelocity.ipynb: This script was executed using Python and used the following packages - numpy, pandas, matplotlib.pyplot, scanpy, igraph, scvelo, loompy, and anndata.
Funding
Canadian Institutes of Health Research, Award: PJT-169113, Project grant
Canada Foundation for Innovation, Award: 32920, John R. Evans Leaders Fund
Alberta Children's Hospital Research Institute, Award: Startup fund