# Opportunities for RNA sequencing in physiology: from big data to understanding homeostasis and heterogeneity

## TL;DR

RNA sequencing is transforming physiology by uncovering complex biological processes and disease mechanisms through big data.

## Contribution

The paper highlights the expanding role of RNA sequencing in physiology, emphasizing non-coding RNA and new analytical methods.

## Key findings

- Non-protein-coding RNAs like lncRNAs are now the most diverse RNA class identified through sequencing.
- Single-cell and spatial transcriptomics provide unprecedented insights into cellular and tissue physiology.
- Bulk RNA sequencing tools now enable robust deconvolution of human genes and detection of foreign RNA.

## Abstract

The quantity of physiological data has grown exponentially, yielding insights
into mechanisms of phenotypic and disease pathways. Among the powerful tools for
physiological omics is the study of RNA, where broad sequencing of RNA leads to
hypothesis generation and testing while providing observational discovery.
Emphasis has been placed on RNA molecules that code for proteins, even though
they represent a minority of total RNA. Diverse sequencing methods have rapidly
expanded the identification of non-protein-coding molecules, including
nonsense-mediated decay and long non-coding RNAs (lncRNA), which now represent
the most diverse class of RNA. Increasing attention needs to be paid to the data
processing of RNA sequencing to interpret transcript-level mapping data in the
context of protein biology, as many protein-coding genes have diverse noncoding
transcripts. Over the past several years, single-cell and spatial
transcriptomics have yielded unprecedented insights into cellular, tissue, and
organ physiology. Building on these advancements, bulk RNA sequencing tools have
begun producing robust deconvolution methods that enhance the analysis of human
genes, the detection of foreign RNA from bacteria and viruses, and provide deep
insights into complex immunological events, such as B- and T-cell recombination.
Over a million RNA-sequencing datasets have been generated, providing resources
for data scientists to reprocess data and expand larger databases. From model
organisms to complex human diseases, RNA sequencing resources continue to
transform our knowledge of the complexity of personalized disease insights.
Observational science is at the core of physiology, and growth of RNA sequencing
represents a significant tool for physiologists.