ArticleMolecular biology and evolution2015
Human Enhancers Are Fragile and Prone to Deactivating Mutations.
Article in Molecular biology and evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed, 18 citations in OpenAlex.
- Chromatin accessibility: biological functions, molecular mechanisms and therapeutic application.Signal transduction and targeted therapy · 2024Review
- ChromDL: a next-generation regulatory DNA classifier.Bioinformatics (Oxford, England) · 2023Article
- A survey on algorithms to characterize transcription factor binding sites.Briefings in bioinformatics · 2023Review
- ChromDL: A Next-Generation Regulatory DNA Classifier.bioRxiv : the preprint server for biology · 2023Article
- GRAFIMO: Variant and haplotype aware motif scanning on pangenome graphs.PLoS computational biology · 2021Article
- Learning and interpreting the gene regulatory grammar in a deep learning framework.PLoS computational biology · 2020Article
- Stable enhancers are active in development, and fragile enhancers are associated with evolutionary adaptation.Genome biology · 2019Article
- Dichotomy in redundant enhancers points to presence of initiators of gene regulation.BMC genomics · 2018Article
- Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties.PLoS computational biology · 2018Article
- SNPDelScore: combining multiple methods to score deleterious effects of noncoding mutations in the human genome.Bioinformatics (Oxford, England) · 2018Article
- Quantifying deleterious effects of regulatory variants.Nucleic acids research · 2017Article
- iRegNet3D: three-dimensional integrated regulatory network for the genomic analysis of coding and non-coding disease mutations.Genome biology · 2017Article
- Finding the Sources of Missing Heritability within Rare Variants Through Simulation.Bioinformatics and biology insights · 2017Article
- Emergence of the Noncoding Cancer Genome: A Target of Genetic and Epigenetic Alterations.Cancer discovery · 2016Review
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 at 1 institution in 1 country.
Funding
Abstract
To explore the underlying mechanisms whereby noncoding variants affect transcriptional regulation, we identified nucleotides capable of disrupting binding of transcription factors and deactivating enhancers if mutated (dubbed candidate killer mutations or KMs) in HepG2 enhancers. On average, approximately 11% of enhancer positions are prone to KMs. A comparable number of enhancer positions are capable of creating de novo binding sites via a single-nucleotide mutation (dubbed candidate restoration mutations or RSs). Both KM and RS positions are evolutionarily conserved and tend to form clusters within an enhancer. We observed that KMs have the most deleterious effect on enhancer activity. In contrast, RSs have a smaller effect in increasing enhancer activity. Additionally, the KMs are strongly associated with liver-related Genome Wide Association Study traits compared with other HepG2 enhancer regions. By applying our framework to lymphoblastoid cell lines, we found that KMs underlie differential binding of transcription factors and differential local chromatin accessibility. The gene expression quantitative trait loci associated with the tissue-specific genes are strongly enriched in KM positions. In summary, we conclude that the KMs have the greatest impact on the level of gene expression and are likely to be the causal variants of tissue-specific gene expression and disease predisposition.
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.