Evidence map›Paper›PMID 30709331›Full record

ArticleBMC genomics2019

CpG traffic lights are markers of regulatory regions in human genome.

Anna V Lioznova, Abdullah M Khamis, Artem V Artemov, Elizaveta Besedina, Vasily Ramensky, Vladimir B Bajic, Ivan V Kulakovskiy, Yulia A Medvedeva

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.

  1. Pooled it
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  14. Epigenomics and the kidney.Current opinion in nephrology and hypertension · 2020
    Review
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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

8 authors at 5 institutions in 2 countries.

Anna V LioznovaInstitute of Bioengineering, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, 119071, Russia.
Abdullah M KhamisComputational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
Artem V ArtemovInstitute of Bioengineering, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, 119071, Russia.
Elizaveta BesedinaFaculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, 119991, Russia.
Vasily RamenskyMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia.
Vladimir B BajicComputational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
Ivan V KulakovskiyEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia.
Yulia A MedvedevaInstitute of Bioengineering, Research Center of Biotechnology, Russian Academy of Sciences, Moscow, 119071, Russia. ju.medvedeva@gmail.com.
King Abdullah University of Science and Technology · SAMoscow Institute of Physics and Technology · RURussian Academy of Sciences · RULomonosov Moscow State University · RUVavilov Institute of General Genetics · RU

Funding

Russian Foundation for Basic Research 14-04-00180Russian Foundation for Basic Research 17-54-80033Russian Science Foundation 17-74-10188
6 · The paper itself

Abstract

backgroundDNA methylation is involved in the regulation of gene expression. Although bisulfite-sequencing based methods profile DNA methylation at a single CpG resolution, methylation levels are usually averaged over genomic regions in the downstream bioinformatic analysis.

resultsWe demonstrate that on the genome level a single CpG methylation can serve as a more accurate predictor of gene expression than an average promoter / gene body methylation. We define CpG traffic lights (CpG TL) as CpG dinucleotides with a significant correlation between methylation and expression of a gene nearby. CpG TL are enriched in all regulatory regions. Among all promoters, CpG TL are especially enriched in poised ones, suggesting involvement of DNA methylation in their regulation. Yet, binding of only a handful of transcription factors, such as NRF1, ETS, STAT and IRF-family members, could be regulated by direct methylation of transcription factor binding sites (TFBS) or its close proximity. For the majority of TF, an alternative scenario is more likely: methylation and inactivation of the whole regulatory element indirectly represses functional TF binding with a CpG TL being a reliable marker of such inactivation.

conclusionsCpG TL provide a promising insight into mechanisms of enhancer activity and gene regulation linking methylation of single CpG to gene expression. CpG TL methylation can be used as reliable markers of enhancer activity and gene expression in applications, e.g. in clinic where measuring DNA methylation is easier compared to directly measuring gene expression due to more stable nature of DNA.

Indexed as

CpG IslandsDNA MethylationGene Expression RegulationGenome, HumanRegulatory Sequences, Nucleic AcidHumansPromoter Regions, GeneticTranscription FactorsTranscription, GeneticTranscription FactorsCAGEChromatin statesCpG traffic lightsDNA methylationEnhancersETSIRFNRF1STATTranscription regulation

Identifiers

PMID30709331
PMCPMC6359853
OpenAlexW2942230700

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.