Skip to content
Review

EXPRESS: Harnessing Single-Cell Gene Regulatory Networks for Precision Health.

Aug 2026 · Journal of Investigative Medicine · pp. 10815589261483678 · 0 citations
Medicine

TL;DR

This manuscript explores the current landscape of single-cell RNA sequencing (scRNA-seq), highlighting key studies that have leveraged this technology to advance biological understanding for clinical purposes through the construction of gene regulatory networks (GRNs) from single-cell transcriptomic data.

Abstract

Cellular diversity in multicellular organisms arises from the functional specialization of individual cells and the influence of both the local tissue microenvironment and external stimuli. Understanding this heterogeneity requires accurate characterization of cell types and the molecular dynamics that define them. In this context, transcriptomic technologies at the single-cell level have become central tools, as they provide a comprehensive view of gene expression and reveal functional molecular patterns. Recent advances have dramatically expanded the number of detectable transcripts and improved data resolution, shifting from bulk measurements that averaged signals across tissues to single‑cell approaches capable of quantifying gene expression at cellular resolution. This finer resolution enables detailed investigation of cellular functions, interactions, and transitions, and supports the development of multiscale computational models. Within this landscape, biological network-based approaches, particularly gene regulatory networks, have emerged as powerful tools for interpreting the functional organization of gene circuits. These methods facilitate the identification of biomarkers, regulatory factors, and key pathways, deepening our understanding of gene regulation and cellular identity through high‑resolution transcriptomic data. Transferring this knowledge to clinical practice is what we here refer to as precision health. This manuscript explores the current landscape of single-cell RNA sequencing (scRNA-seq), highlighting key studies that have leveraged this technology to advance biological understanding for clinical purposes through the construction of gene regulatory networks (GRNs) from single-cell transcriptomic data. Furthermore, it examines how these insights could contribute to clinical applications and, ultimately, the advancement of precision health. Finally, it discusses the key challenges in data analysis and practical applications within this rapidly evolving field.

View source

Similar papers

Review Sep 2026

Single-cell and spatial transcriptomics inform mechanistic physiology in non-model animals

This review provides a physiology-centered blueprint for applying single-cell RNA sequencing, single-nucleus RNA sequencing, and spatial transcriptomics to non-model species and critically evaluates dissociation and preservation bias, genome annotation, seasonal and ecological variation, biological replication, pseudor...

Adnan Amin, W. Zaman · 0 citations
Open access Sep 2026

Constructing cell-type-specific gene regulatory networks from cell–cell communication and a global gene regulatory network

Abstract Accurately inferring cell-type-specific gene regulatory networks (GRNs) is crucial for understanding cellular heterogeneity, lineage determination, and disease progression mechanisms. Although single-cell RNA sequencing (scRNA-seq) enables high-resolution expression profiling, its inherent sparsity and high no...

Yu-Ke Xie, Bo-Wen Fu, Lai-Jun Zhong et al. · 0 citations
Sep 2026

Understanding the Cellular Spatiotemporal Dogma by Spatial and Single-cell Omics.

The biological complexity of plants arises from highly coordinated cellular activities. We propose that a "cellular spatiotemporal dogma" governs the zygote's programmed development into a complete plant and its adaptation to various environmental stresses, representing the set of principles describing how gene express...

Chao Qin, Zi-Yi Zhang, Keke Xia · 0 citations
Open access Aug 2026

Morphodynamic domains enable integration of live morphometrics and spatial transcriptomics

Tissue development emerges from the coordinated behaviors of thousands of cells, orchestrated by gene regulatory networks. Recent methodological advances now enable high-resolution live imaging of cell- and tissue-scale dynamics and the construction of spatially resolved gene expression atlases. However, quantitatively...

Adrien Leroy, Eric van Leen, M. Balakireva et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.