Evidence map›Paper›PMID 30593493›Full record

ArticleGenetics2019

Cell Specificity of Human Regulatory Annotations and Their Genetic Effects on Gene Expression.

Arushi Varshney, Hadley VanRenterghem, Peter Orchard, Alan P Boyle, Michael L Stitzel, Duygu Ucar, Stephen C J Parker

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Complexities of Understanding Function from CKD-Associated DNA Variants.Clinical journal of the American Society of Nephrology : CJASN · 2020
    Review
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Arushi VarshneyDepartment of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109.ORCID 0000-0001-9177-9707
Hadley VanRenterghemDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109.
Peter OrchardDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109.ORCID 0000-0001-6097-1106
Alan P BoyleDepartment of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109.ORCID 0000-0002-2081-1105
Michael L StitzelThe Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032.ORCID 0000-0001-5630-559X
Duygu UcarThe Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032.ORCID 0000-0002-9772-3066
Stephen C J ParkerDepartment of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109 scjp@umich.edu.ORCID 0000-0001-8122-0117

Funding

University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
Context-specific and combinatorial genetic regulatory grammars in diabetesR01DK117960 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Stephen CJ Parker · 2018 to 2026
$2.8M
Synthesizing genome, epigenome, and transcriptome datasets in type 2 diabetes.R00DK099240 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PARKER, STEPHEN CJ · 2015 to 2017
$726k
NHGRI NIH HHS T32 HG000040NIDDK NIH HHS R00 DK099240NIDDK NIH HHS R01 DK117960
6 · The paper itself

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.

Indexed as

Enhancer Elements, GeneticQuantitative Trait LociTranscriptional ActivationChromatinEmbryonic Stem CellsHep G2 CellsHumansOrgan SpecificityTranscription FactorsChromatinTranscription Factorschromatinchromatin QTLexpression QTLgene regulationGWAS

Identifiers

PMID30593493
PMCPMC6366912

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.