Evidence map›Paper›PMID 16171528›Full record

ArticleBMC bioinformatics2005

Chromosomal clustering of a human transcriptome reveals regulatory background.

Jan H Vogel, Anja von Heydebreck, Antje Purmann, Silke Sperling

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 23% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Jan H VogelDepartment of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jan.vogel@gmail.com
Anja von Heydebreck
Antje Purmann
Silke Sperling
Max Planck Institute for Molecular Genetics · DEMax Planck Society · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere has been much evidence recently for a link between transcriptional regulation and chromosomal gene order, but the relationship between genomic organization, regulation and gene function in higher eukaryotes remains to be precisely defined.

resultsHere, we present evidence for organization of a large proportion of a human transcriptome into gene clusters throughout the genome, which are partly regulated by the same transcription factors, share biological functions and are characterized by non-housekeeping genes. This analysis was based on the cardiac transcriptome identified by our genome-wide array analysis of 55 human heart samples. We found 37% of these genes to be arranged mainly in adjacent pairs or triplets. A significant number of pairs of adjacent genes are putatively regulated by common transcription factors (p = 0.02). Furthermore, these gene pairs share a significant number of GO functional classification terms. We show that the human cardiac transcriptome is organized into many small clusters across the whole genome, rather than being concentrated in a few larger clusters.

conclusionOur findings suggest that genes expressed in concert are organized in a linear arrangement for coordinated regulation. Determining the relationship between gene arrangement, regulation and nuclear organization as well as gene function will have broad biological implications.

Indexed as

Binding SitesChromosome MappingGene ExpressionGene OrderHumansModels, BiologicalMultigene FamilyMyocardiumTranscription FactorsTranscription Factors

Identifiers

PMID16171528
PMCPMC1261156
OpenAlexW1501572782

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.