ReviewTrends in genetics : TIG2026
Beyond the baseline: mapping the context-specific regulatory landscape of disease.
Review in Trends in genetics : TIG, 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.
- Bridging precision agriculture and human medicine through comparative genetics.Nature reviews. Genetics · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Genome-wide association studies have identified thousands of intergenic variants associated with disease, most of which are presumed to act by affecting gene regulation. Standard expression quantitative trait locus (eQTL) studies were able to link many disease-associated loci to changes in gene expression. Yet, many disease-associated loci show no detectable regulatory effects in baseline bulk gene expression datasets from adult tissues. Recent work shows that, overall, standard eQTLs differ systematically from disease-associated loci, pointing to regulatory effects not captured under baseline conditions. We review emerging evidence that context-specific eQTLs, revealed under environmental perturbations, stress, or developmental transitions, resemble disease loci more closely. We highlight new in vitro systems and machine learning approaches that promise systematic identification of these context-dependent effects.
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.