Novel insights into kidney disease: the scRNA-seq and spatial transcriptomics approaches: a literature review - PubMed (original) (raw)

Review

Novel insights into kidney disease: the scRNA-seq and spatial transcriptomics approaches: a literature review

Mingming Ma et al. BMC Nephrol. 2025.

Abstract

Over the past decade, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have revolutionized biomedical research, particularly in understanding cellular heterogeneity in kidney diseases. This review summarizes the application and development of scRNA-seq combined with ST in the context of kidney disease. By dissecting cellular heterogeneity at an unprecedented resolution, these advanced techniques have identified novel cell subpopulations and their dynamic interactions within the renal microenvironment. The integration of scRNA-seq with ST has been instrumental in elucidating the cellular and molecular mechanisms underlying kidney development, homeostasis, and disease progression. This approach has not only identified key cellular players in renal pathophysiology but also revealed the spatial organization of cells within the kidney, which is crucial for understanding their functional specialization. This paper highlights the transformative impact of these techniques on renal research that have paved the way for targeted therapeutic interventions and personalized medicine in the management of kidney disease.

Keywords: Cellular heterogeneity; Kidney disease; Pathology; Renal physiology; Single-cell sequencing; Spatial transcriptomics.

© 2025. The Author(s).

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1

Fig. 1

Kidney tissue is dissociated into a single cell suspension and scRNA-seq is then performed. ScRNA-seq allows the study of rare cell types, cell state and subtype heterogeneity, disease-specific cell types, and cell-to-cell interactions via ligand-receptor analysis. Computational analyses such as pseudo-time diffusion mapping analyze the similarity and diversity of cells, consent to trace differentiation processes, clonal evolution, and cell state transitions between different cell types

Fig. 2

Fig. 2

Main steps in the scRNA-seq workflow. First, the tissue of interest is dissociated to make a single-cell suspension. Single cells are then harvested for scRNA- seq analysis. Magnetic activated cell sorting relies on the immunoreactivity of cell specific antigens with magnetic beads. A fluorescence activated cell sorting platform then selects individual cells with heterogeneous tissue by detecting fluorescent labelled signals. The cells can be isolated using a variety of parameters. Smart-seq2 and CEL-Seq2 are performed in 96 or 384-well plates after sorting, while droplet systems (e.g. 10X Chromium and Drop-Seq) couple cells with barcoded beads containing a unique molecule identifier (UMI) and primers that form water in-oil droplets via a continuous oil flow. Reverse transcription and cDNA amplification are performed by PCR in Smart-Seq and 10X Chromium and by in vitro transcription (IVT) in CEL-Seq2

Fig. 3

Fig. 3

The focus of spatial transcriptomic research. (A) “Kidney development” refers to the study of how the spatial transcriptome changes during key stages in kidney development; (B) “Kidney homeostasis” refers to elucidating spatial division of discrete cellular subtypes in healthy renal tissue at a singular time point; (C) “Kidney injury microenvironment” refers to elucidating the spatial transcriptome in injured tissue niches in relation to their proximity to relevant biological traits; (D) Integration of single-cell and ST data

Fig. 4

Fig. 4

Single-cell analysis strategies for pathological kidney samples. A visual summary of the methodologies employed for single-cell analysis in pathological kidney samples: scRNA-seq, snRNA-seq and spatial transcriptomics

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