Advances in Single-Cell Sequencing for Understanding and Treating Kidney Disease

The fields of medical diagnostics, nephrology, and the sequencing of cellular genetic material are pivotal for precise quantification of kidney diseases. Single-cell sequencing, enhanced by automation and software tools, enables efficient examination of biopsies at the individual cell level. This approach shows the complex cellular mosaic that shapes organ function. By quantifying gene expression following injury, single-cell analysis provides insight into disease progression. In this review, new developments in single-cell analysis methods, spatial integration of single-cell analysis, single-nucleus RNA sequencing, and emerging methods, including expression quantitative trait loci, whole-genome sequencing, and whole-exome sequencing in nephrology, are discussed. These advancements are poised to enhance kidney disease diagnostic processes, therapeutic strategies, and patient prognosis.

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Publication Details

Journal
Computation
Published
2026-01-02
DOI
https://doi.org/10.3390/computation14010006
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
22.24
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article

Advances in Single-Cell Sequencing for Understanding and Treating Kidney Disease

Amit K. Verma, Jose L. Agraz, Claudia M. Agraz
1 citations
Computation
Single-cell and spatial transcriptomics
22.24
article

Advances in Single-Cell Sequencing for Understanding and Treating Kidney Disease

Amit K. Verma, Jose L. Agraz, Claudia M. Agraz
article en
1 citations

Abstract

The fields of medical diagnostics, nephrology, and the sequencing of cellular genetic material are pivotal for precise quantification of kidney diseases. Single-cell sequencing, enhanced by automation and software tools, enables efficient examination of biopsies at the individual cell level. This approach shows the complex cellular mosaic that shapes organ function. By quantifying gene expression following injury, single-cell analysis provides insight into disease progression. In this review, new developments in single-cell analysis methods, spatial integration of single-cell analysis, single-nucleus RNA sequencing, and emerging methods, including expression quantitative trait loci, whole-genome sequencing, and whole-exome sequencing in nephrology, are discussed. These advancements are poised to enhance kidney disease diagnostic processes, therapeutic strategies, and patient prognosis.

ComputationVol. 14(1)
Autonomous University of Campeche (MX), University of Pennsylvania (US)
Openalex Percentile: Top 4%
Single-cell and spatial transcriptomics
22.24
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Advances in Single-Cell Sequencing for Understanding and Treating Kidney Disease — Amit K. Verma, Jose L. Agraz, et al. · Computation (2026) | TGRS Research Map | TGRS