ArticleGenome biology2025
Patterns of extreme outlier gene expression suggest an edge of chaos effect in transcriptomic networks.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Integrative transcriptomic and network analysis reveals small open reading frames associated with cellular adaptive responsees and methylation-linked pathogenicity in Leptospira interrogans.Functional & integrative genomics · 2026Article
- Tissue-specific differences of gene expression variance in mutation accumulation lines of mice.Heredity · 2026Article
- Article
- Patterns of extreme outlier gene expression suggest an edge of chaos effect in transcriptomic networks.Genome biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundMost RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.
resultsOur study is based on multiple datasets, including data from outbred and inbred mice, GTEx data from humans, data from different Drosophila species, and single-nuclei sequencing data from human brain tissues. All show comparable general patterns of outlier gene expression, indicating this as a generalizable biological effect. Different individuals can harbor very different numbers of outlier genes, with some individuals showing extreme numbers in only one out of several organs. Outlier gene expression occurs as part of co-regulatory modules, some of which correspond to known pathways. In a three-generation family analysis in mice, we find that most extreme over-expression is not inherited, but appears to be sporadically generated. Genes encoding prolactin and growth hormone are also among the co-regulated genes with extreme outlier expression, both in mice and humans, for which we include also a longitudinal expression analysis for protein data.
conclusionsWe show that outlier patterns of gene expression are a biological reality occurring universally across tissues and species. Most of the outlier expression is spontaneous and not inherited. We suggest that the outlier patterns reflect edge of chaos effects that are expected for systems of non-linear interactions and feedback loops, such as gene regulatory networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.