ArticleBMC genomics2026
Evolutionary and functional constraints structure human gene research visibility.
Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Genome-scale perturbation signatures from primary human CD4bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBiomedical research effort is distributed highly unevenly across human genes, with a small subset dominating the scientific literature while thousands remain sparsely studied. Whether this imbalance reflects intrinsic biological importance or historically reinforced research bias remains unclear. Understanding how research attention relates to gene properties is essential for more systematic exploration of the human genome.
resultsHere, we quantify gene-level publication patterns and integrate sequence features, evolutionary constraint, gene age, expression, and disease associations across stratified gene sets. Using standardized MANE Select annotations, we show that publication counts follow a strongly heavy-tailed distribution. Highly studied genes cluster within a narrow GC-content regime and exhibit lower nonsynonymous substitution rates and lower dN/dS ratios, consistent with stronger long-term evolutionary constraint. In contrast, genes sampled from below rank 10,000 are enriched for evolutionarily younger loci and display moderately elevated dN and dN/dS values, reduced expression magnitude, and increased tissue specificity. At the disease level, research attention concentrates within a limited number of dominant domains, particularly cancer, respiratory, and vascular diseases, whereas congenital and rare disease categories remain comparatively underrepresented. Genes associated with orphan diseases show significantly reduced publication counts.
conclusionsTogether, these results demonstrate that research attention is systematically structured across evolutionary, molecular, and disease dimensions. The least-studied genes represent a distinct and underexplored portion of the genome, characterized by features that may reduce experimental tractability. These findings highlight the need for bias-aware research prioritization strategies to broaden discovery and ensure more comprehensive characterization of human genes.
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.