The offonome reveals on and off states of gene expression near the detection limit of RNA-seq
Year: 2025
Type: article
Abstract: RNA-seq, widely used for gene expression profiling, provides nucleotide level genome coverage and summary gene expression values. Generally, low-expressed genes are ignored due to their unfavorable signal-to-noise ratio, however, these genes may offer crucial information, such as detecting rare cells in bulk tissues. In this study, we applied an approach that transforms the expression levels of low-expressed genes into a robust dichotomized on/off state by leveraging similarities in transcript coverage shape. Applied to three human cancer cohorts from the Cancer Genome Atlas (TCGA), chosen based on tissue morphology and anatomic site, we identified genes, the "offonome" near the detection limit, consistently or occasionally off across samples. Genes in the offonome spectrum proved useful for supervised and unsupervised applications, including characterizing oncogenic pathways, and identifying rare populations of cells in bulk tissue. Interrogating the offonome is relevant to bulk tumor analyses like TCGA, potentially expediting gene investigation in low-input situations like single cell RNA-seq.
Source: Scientific Reports
Authors: Won-Young Choi, Xiaobei Zhao, Jeremiah Holt, Richa Jain, Heejoon Jo, Katherine A. Hoadley, D. Neil Hayes, Hyo Young Choi
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funder: National Cancer Institute
Awards: G324247120, G58255433
OpenAlex ID: W4416803943
