Evidence map›Paper›PMID 32450112›Full record

ReviewToxicology2020

Genomic resources for dissecting the role of non-protein coding variation in gene-environment interactions.

Daniel Levings, Kirsten E Shaw, Sarah E Lacher

Open access · greenAbstract readReview
In one paragraph

Review in Toxicology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 56% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Polymorphism ofAnimal biotechnology · 2025
    Article
  2. Article
  3. 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

3 authors at 1 institution in 1 country.

Daniel LevingsDepartment of Biomedical Sciences, University of Minnesota Medical School, Duluth Campus, 1035 University Drive, Duluth, MN, 55812, USA.
Kirsten E ShawDepartment of Biomedical Sciences, University of Minnesota Medical School, Duluth Campus, 1035 University Drive, Duluth, MN, 55812, USA.
Sarah E LacherDepartment of Biomedical Sciences, University of Minnesota Medical School, Duluth Campus, 1035 University Drive, Duluth, MN, 55812, USA. Electronic address: selacher@umn.edu.
University of Minnesota, Duluth · US

Funding

Regulatory Precision in Stress Responsive Transcriptional NetworksR35GM119553 · NIGMS · UNIVERSITY OF MINNESOTA · PI SLATTERY, MATTHEW · 2016 to 2020
$1.9M
NIGMS NIH HHS R35 GM119553
6 · The paper itself

Abstract

The majority of single nucleotide variants (SNVs) identified in Genome Wide Association Studies (GWAS) fall within non-protein coding DNA and have the potential to alter gene expression. Non-protein coding DNA can control gene expression by acting as transcription factor (TF) binding sites or by regulating the organization of DNA into chromatin. SNVs in non-coding DNA sequences can disrupt TF binding and chromatin structure and this can result in pathology. Further, environmental health studies have shown that exposure to xenobiotics can disrupt the ability of TFs to regulate entire gene networks and result in pathology. However, there is a large amount of interindividual variability in exposure-linked health outcomes. One explanation for this heterogeneity is that genetic variation and exposure combine to disrupt gene regulation, and this eventually manifests in disease. Many resources exist that annotate common variants from GWAS and combine them with conservation, functional genomics, and TF binding data. These annotation tools provide clues regarding the biological implications of an SNV, as well as lead to the generation of hypotheses regarding potentially disrupted target genes, epigenetic markers, pathways, and cell types. Collectively this information can be used to predict how SNVs can alter an individual's response to exposure and disease risk. A basic understanding of the regulatory information contained within non-protein coding DNA is needed to predict the biological consequences of SNVs, and to determine how these SNVs impact exposure-related disease. We hope that this review will aid in the characterization of disease-associated genetic variation in the non-protein coding genome.

Indexed as

Gene-Environment InteractionGenetic VariationUntranslated RegionsAnimalsGene ExpressionGenome-Wide Association StudyGenomicsHumansPolymorphism, Single NucleotideUntranslated RegionsGene-environment interactionsGene-expressionGene-regulationNon-protein coding DNA

Identifiers

PMID32450112
PMCPMC7423718
OpenAlexW3027917491

What OpenQuestion holds

Textmetadata
LicenceTDM
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.