ArticleNature communications2021
Tissue context determines the penetrance of regulatory DNA variation.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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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.
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Who cites it
13 citing papers in PubMed, 18 citations in OpenAlex.
- From conservation scores to language models: a feature engineering perspective on machine learning for genetic variant interpretation.Briefings in bioinformatics · 2026Review
- Iterative improvement of deep learning models using synthetic regulatory genomics.Genome research · 2025Article
- The emerging roles of long non-coding RNAs in the nervous system.Nature reviews. Neuroscience · 2025Review
- Association of TRDMT1 Gene Polymorphisms With Neuroblastoma Susceptibility: Insights From a Case-Control Study.Journal of cellular and molecular medicine · 2025Article
- Genomic context sensitizes regulatory elements to genetic disruption.Molecular cell · 2024Article
- Genomic context sensitizes regulatory elements to genetic disruption.bioRxiv : the preprint server for biology · 2024Article
- The dynamic genetic determinants of increased transcriptional divergence in spermatids.Nature communications · 2024Article
- Synthetic regulatory genomics uncovers enhancer context dependence at the Sox2 locus.Molecular cell · 2023Article
- De novo discovery of traits co-occurring with chronic obstructive pulmonary disease.Life science alliance · 2023Article
- Characterization of sequence determinants of enhancer function using natural genetic variation.eLife · 2022Article
- Evolution of transcription factor binding through sequence variations and turnover of binding sites.Genome research · 2022Article
- Genomic context sensitivity of insulator function.Genome research · 2022Article
- Addiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.
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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.