ArticleGenetics2019
Cell Specificity of Human Regulatory Annotations and Their Genetic Effects on Gene Expression.
Article in Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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.
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Who cites it
12 citing papers in PubMed.
- Identifying independent causal cell types for human diseases and risk variants.Cell genomics · 2026Article
- Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation.bioRxiv : the preprint server for biology · 2024Article
- A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids.American journal of human genetics · 2022Article
- Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction.International journal of molecular sciences · 2022Review
- A Transcription Start Site Map in Human Pancreatic Islets Reveals Functional Regulatory Signatures.Diabetes · 2021Article
- Multi-omic profiling of pituitary thyrotropic cells and progenitors.BMC biology · 2021Article
- Epigenetic cell fate in Candida albicans is controlled by transcription factor condensates acting at super-enhancer-like elements.Nature microbiology · 2020Article
- Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D.Nature communications · 2020Article
- Dissecting the regulatory activity and sequence content of loci with exceptional numbers of transcription factor associations.Genome research · 2020Article
- Complexities of Understanding Function from CKD-Associated DNA Variants.Clinical journal of the American Society of Nephrology : CJASN · 2020Review
- Quantification, Dynamic Visualization, and Validation of Bias in ATAC-Seq Data with ataqv.Cell systems · 2020Article
- Functional Genomics in Pancreatic β Cells: Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research.Frontiers in endocrinology · 2020Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Epigenomic signatures from histone marks and transcription factor (TF)-binding sites have been used to annotate putative gene regulatory regions. However, a direct comparison of these diverse annotations is missing, and it is unclear how genetic variation within these annotations affects gene expression. Here, we compare five widely used annotations of active regulatory elements that represent high densities of one or more relevant epigenomic marks-"super" and "typical" (nonsuper) enhancers, stretch enhancers, high-occupancy target (HOT) regions, and broad domains-across the four matched human cell types for which they are available. We observe that stretch and super enhancers cover cell type-specific enhancer "chromatin states," whereas HOT regions and broad domains comprise more ubiquitous promoter states. Expression quantitative trait loci (eQTL) in stretch enhancers have significantly smaller effect sizes compared to those in HOT regions. Strikingly, chromatin accessibility QTL in stretch enhancers have significantly larger effect sizes compared to those in HOT regions. These observations suggest that stretch enhancers could harbor genetically primed chromatin to enable changes in TF binding, possibly to drive cell type-specific responses to environmental stimuli. Our results suggest that current eQTL studies are relatively underpowered or could lack the appropriate environmental context to detect genetic effects in the most cell type-specific "regulatory annotations," which likely contributes to infrequent colocalization of eQTL with genome-wide association study signals.
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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.