Evidence map›Paper›PMID 23325852›Full record

ArticleNucleic acids research2013

Transcription profiling during the cell cycle shows that a subset of Polycomb-targeted genes is upregulated during DNA replication.

Javier Peña-Diaz, Siv A Hegre, Endre Anderssen, Per A Aas, Robin Mjelle, Gregor D Gilfillan, Robert Lyle, Finn Drabløs, Hans E Krokan, Pål Sætrom

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 11% 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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 57 citations in OpenAlex.

  1. Pooled it
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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

10 authors at 2 institutions in 1 country.

Javier Peña-DiazDepartment of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway.
Siv A Hegre
Endre Anderssen
Per A Aas
Robin Mjelle
Gregor D Gilfillan
Robert Lyle
Finn Drabløs
Hans E Krokan
Pål Sætrom
Norwegian University of Science and Technology · NOOslo University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide gene expression analyses of the human somatic cell cycle have indicated that the set of cycling genes differ between primary and cancer cells. By identifying genes that have cell cycle dependent expression in HaCaT human keratinocytes and comparing these with previously identified cell cycle genes, we have identified three distinct groups of cell cycle genes. First, housekeeping genes enriched for known cell cycle functions; second, cell type-specific genes enriched for HaCaT-specific functions; and third, Polycomb-regulated genes. These Polycomb-regulated genes are specifically upregulated during DNA replication, and consistent with being epigenetically silenced in other cell cycle phases, these genes have lower expression than other cell cycle genes. We also find similar patterns in foreskin fibroblasts, indicating that replication-dependent expression of Polycomb-silenced genes is a prevalent but unrecognized regulatory mechanism.

Indexed as

DNA ReplicationUp-RegulationCell CycleCell Cycle ProteinsCell LineCpG IslandsFibroblastsGene Expression ProfilingGenes, EssentialHistonesHumansKeratinocytesLeast-Squares AnalysisModels, GeneticOligonucleotide Array Sequence AnalysisPolycomb-Group ProteinsCell Cycle ProteinsHistonesPolycomb-Group ProteinsRNA, Messenger

Identifiers

PMID23325852
PMCPMC3597645
OpenAlexW2118761159

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.