Evidence map›Paper›PMID 34360860›Full record

ArticleInternational journal of molecular sciences2021

K-mer Content Changes with Node Degree in Promoter-Enhancer Network of Mouse ES Cells.

Kinga Szyman, Bartek Wilczyński, Michał Dąbrowski

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kinga SzymanLaboratory of Bioinformatics, Nencki Institute of Experimental Biology, 02-093 Warsaw, Poland.ORCID 0000-0001-8302-5075
Bartek WilczyńskiFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, 02-097 Warsaw, Poland.ORCID 0000-0002-8134-0589
Michał DąbrowskiLaboratory of Bioinformatics, Nencki Institute of Experimental Biology, 02-093 Warsaw, Poland.ORCID 0000-0002-5335-158X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maps of Hi-C contacts between promoters and enhancers can be analyzed as networks, with cis-regulatory regions as nodes and their interactions as edges. We checked if in the published promoter-enhancer network of mouse embryonic stem (ES) cells the differences in the node type (promoter or enhancer) and the node degree (number of regions interacting with a given promoter or enhancer) are reflected by sequence composition or sequence similarity of the interacting nodes. We used counts of all k-mers (k = 4) to analyze the sequence composition and the Euclidean distance between the k-mer count vectors (k-mer distance) as the measure of sequence (dis)similarity. The results we obtained with 4-mers are interpretable in terms of dinucleotides. Promoters are GC-rich as compared to enhancers, which is known. Enhancers are enriched in scaffold/matrix attachment regions (S/MARs) patterns and depleted of CpGs. Furthermore, we show that promoters are more similar to their interacting enhancers than vice-versa. Most notably, in both promoters and enhancers, the GC content and the CpG count increase with the node degree. As a consequence, enhancers of higher node degree become more similar to promoters, whereas higher degree promoters become less similar to enhancers. We confirmed the key results also for human keratinocytes.

Indexed as

Enhancer Elements, GeneticGene Regulatory NetworksModels, GeneticAnimalsBase CompositionComputational BiologyCpG IslandsHumansKeratinocytesMiceMouse Embryonic Stem Cells4-merCpGdinucleotideembryonic stem cellHi-CS/MAR

Identifiers

PMID34360860
PMCPMC8347099

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.