Updated skin transcriptomic atlas depicted by reciprocal contribution of single-nucleus RNA sequencing and single-cell RNA sequencing.

Background: Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of skin biology, but its utility is restricted by the requirement of fresh samples, inadequate dissociation-induced cell loss or death, and activation during tissue digestion. Single-nucleus RNA sequencing (snRNA-seq) can use frozen, hard-to-dissociate materials, which might be a promising method to circumvent the limitations of scRNA-seq for the skin tissue.

Objective: To profile skin cells using snRNA-seq in parallel with scRNA-seq.

Methods: We performed snRNA-seq in parallel with scRNA-seq for the bisected skin sample of one person and integrated previously published scRNA-seq data for analysis. We comparatively analyzed the differences in cell proportions and gene expression between the two methods. The differentiation trajectories of keratinocytes and fibroblasts were analyzed by Slingshot analysis.

Results: snRNA-seq was less susceptible to contamination from mitochondrial and ribosomal RNA, and exhibited a greater capacity to detect transcription factors. snRNA-seq identified more spatially and functionally relevant keratinocyte clusters that constitute cell trajectories with expected differentiation dynamics. Novel markers, e.g., LYPD3, EMP2, and CSTB, were revealed for different differentiation stages of keratinocytes, and NFIB and GRHL1 were identified as transcription factors involving in the proliferation and functional differentiation of keratinocytes. Fibroblasts were found in a state of activation in scRNA-seq. And scRNA-seq detected a greater number of immune cells.

Conclusions: We generated an updated atlas of the skin transcriptome based on the reciprocal contribution of scRNA-seq and snRNA-seq.