Single-cell RNA sequencing (scRNA-seq) data derived from photoconverted brain endothelial cells of Danio rerio (zebrafish) were analyzed to characterize cellular heterogeneity, delineate distinct cell populations, and evaluate the expression profile of the hhex gene. Data processing followed a rigorous bioinformatics pipeline, incorporating quality control, normalization, feature selection, dimensionality reduction, clustering, and marker gene identification. Elevated hhex expression was observed in both arterial and venous endothelial cells, with notable correlations to key venous endothelial markers.
The cellular diversity of brain endothelial cells in Danio rerio was investigated using scRNA-seq data sourced from the NCBI Gene Expression Omnibus (GEO: GSE233662). The primary objectives were to resolve cellular heterogeneity, identify distinct cell populations, and quantify the expression of hhex, a gene implicated in endothelial cell biology. A standardized computational pipeline was employed to ensure robust and reproducible results, adhering to best practices in single-cell transcriptomics.
Raw gene count matrices were retrieved from NCBI GEO (accession:
GSE233662). A gene-level count matrix was constructed and encapsulated
as a SingleCellExperiment object for downstream analysis.
Quality control (QC) was conducted using the scater package
in R, with filtering criteria based on library size, number of detected
genes, and mitochondrial transcript percentage. Adaptive thresholds,
calculated using median absolute deviations, were applied to retain
approximately 500 cells. This approach diverged from the strategy
outlined in the original publication due to the low input cell count
inherent to the SMART-seq2 protocol.
The filtered dataset was normalized using deconvolution-based size
factors implemented in the scran package, followed by
log-transformation via the scater package. Highly variable
genes (HVGs) were identified to capture significant biological
variation. Dimensionality reduction was performed using Principal
Component Analysis (PCA) applied to the HVGs. Graph-based clustering,
implemented in scran, was used to partition cells into
distinct clusters based on principal components. Clusters were
visualized using Uniform Manifold Approximation and Projection (UMAP).
Marker genes for each cluster were identified using
scran::findMarkers, with significantly upregulated genes
used to annotate cell types. Expression patterns of marker genes were
visualized through heatmaps and violin plots.
Distinct cell populations were identified within the brain endothelial cells, with clusters corresponding to arterial and venous endothelial cells (ECs). The hhex gene exhibited elevated expression in both arterial and venous ECs, as visualized in violin plots. Notably, hhex expression was strongly correlated with nr2f2, dab2, and flt4, which are established markers of venous ECs, as evidenced by heatmap analyses.
The analysis revealed significant cellular heterogeneity within zebrafish brain endothelial cells, with hhex emerging as a key gene expressed across arterial and venous EC populations. The observed correlation between hhex and venous EC markers (nr2f2, dab2, flt4) suggests a potential role in venous endothelial identity or function. The use of adaptive QC thresholds was critical due to the low cell input, highlighting the need for tailored preprocessing strategies in SMART-seq2 datasets. These findings contribute to the understanding of endothelial cell diversity and provide a foundation for further investigation into hhex-mediated molecular mechanisms. However, additional studies using technologies such as 10X Genomics, which enable higher input cell numbers, are needed to increase cell type detection sensitivity. Furthermore, higher resolution data are required to validate the findings of this study and enhance the robustness of cell type annotations. These findings contribute to the understanding of endothelial cell diversity and provide a foundation for further investigation into hhex-mediated molecular mechanisms.
A comprehensive scRNA-seq analysis of zebrafish brain endothelial cells was performed, identifying distinct cell populations and characterizing hhex expression. The results underscore the utility of scRNA-seq in resolving cellular heterogeneity and highlight the significance of hhex in endothelial cell biology, particularly in venous ECs.
– Qingzhou Zhang, PhD