PPubMed5 Dec 2025

Opportunities for RNA sequencing in physiology: from big data to understanding homeostasis and heterogeneity PHYSIOLOGY AND RNA SEQUENCING

Jeremy W. Prokop, Stephanie M. Bilinovich, Ember Tokarski, Sangeetha Vishweswaraiah, Sophie VanderWeele, Akansha S. Das, Surya B. Chhetri, Alexander Dao, Sanjana Arora, Austin Goodyke, Katie L. Buelow, Mason Westgate, Elizabeth A. VanSickle, Claudia J. Edell, Lance N. Benson, Daniel B. Campbell, Caleb P. Bupp, Amanda Holsworth, Nicholas L. Hartog, Jena M. Krueger, Marcos Cordoba, Matthew Sims, Maximiliano A. Tamae Kakazu, Angela M. Peraino, Stewart F. Graham, Tim Triche Jr., Elora Hussain, Mara L. Leimanis-Laurens, Connie M. Krawczyk, Jennifer S. Pollock, Surender Rajasekaran

Abstract

RNA sequencing continues to expand in usage and methods. The next decade will likely see new technologies and techniques for processing RNA, with significant advancements in cell physiology mechanisms. The emerging market competition in sequencing is likely to drive innovation and cost reductions that will facilitate more RNA sequencing into physiology projects. The tools will be applied to broad physiological systems and model organisms, while their use for processing clinical samples will also elevate. Our knowledge of disease will be enhanced as the tools are applied. The challenges of sele

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RNA sequencing provides powerful tools for physiology, enabling insights into homeostasis, cellular heterogeneity, and disease traits.

What’s new

i.Review of emerging RNA‑sequencing technologies such as nanopore and SBX
ii.Compilation of gene‑to‑protein resources (Human Protein Atlas) and gene‑to‑cell databases (Allen Brain Map, CellxGene)
iii.Illustration of RNA‑seq applications in disease trait analysis, e.g., COPD gene‑trait mapping
iv.Discussion of how competition and cost reductions may broaden RNA‑seq accessibility

How they did it

The authors surveyed recent literature on RNA‑sequencing platforms, curated publicly available omics databases, and highlighted case studies (e.g., COPD gene‑trait analysis) to illustrate physiological applications.

What they found

CellxGene tools contain >100 million cells from >1,700 datasets for differential expression and spatial mapping
Open Target Platform scores >0.5 were used to identify top COPD‑associated genes
Nanopore direct RNA‑seq identified modification sites in iPSC‑derived mini‑brains and kidney cells, revealing enriched mitochondrial and oxidative‑phosphorylation pathways

Caveats

✕Batch effects and data complexity hinder integration of large RNA‑seq datasets
✕High‑quality samples are required for accurate long‑read sequencing
✕Cost and technical expertise remain barriers for widespread adoption of emerging platforms

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