Evidence map›Paper›PMID 18367472›Full record

ArticleNucleic acids research2008

The biological function of some human transcription factor binding motifs varies with position relative to the transcription start site.

Kannan Tharakaraman, Olivier Bodenreider, David Landsman, John L Spouge, Leonardo Mariño-Ramírez

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. LncRNACancers · 2022
    Article
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  15. Promoting developmental transcription.Development (Cambridge, England) · 2010
    Review
  16. Article
  17. Article
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

5 authors at 2 institutions in 1 country.

Kannan TharakaramanComputational Biology Branch, National Center for Biotechnology Information and National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA.
Olivier Bodenreider
David Landsman
John L Spouge
Leonardo Mariño-Ramírez
National Institutes of Health · USNational Center for Biotechnology Information · US

Funding

The Analysis of Signal Elements in Promoter Sequences.ZIALM091704 · NLM · NATIONAL LIBRARY OF MEDICINE · PI SPOUGE, JOHN · 2009 to 2017
$1.4M
Gene Regulatory Sequences from Whole Chromosomes/genomesZ01LM000084 · NLM · NATIONAL LIBRARY OF MEDICINE · PI LANDSMAN, DAVID · 1998 to 2008
$627k
Intramural NIH HHS Z99 LM999999
6 · The paper itself

Abstract

A number of previous studies have predicted transcription factor binding sites (TFBSs) by exploiting the position of genomic landmarks like the transcriptional start site (TSS). The studies' methods are generally too computationally intensive for genome-scale investigation, so the full potential of 'positional regulomics' to discover TFBSs and determine their function remains unknown. Because databases often annotate the genomic landmarks in DNA sequences, the methodical exploitation of positional regulomics has become increasingly urgent. Accordingly, we examined a set of 7914 human putative promoter regions (PPRs) with a known TSS. Our methods identified 1226 eight-letter DNA words with significant positional preferences with respect to the TSS, of which only 608 of the 1226 words matched known TFBSs. Many groups of genes whose PPRs contained a common word displayed similar expression profiles and related biological functions, however. Most interestingly, our results included 78 words, each of which clustered significantly in two or three different positions relative to the TSS. Often, the gene groups corresponding to different positional clusters of the same word corresponded to diverse functions, e.g. activation or repression in different tissues. Thus, different clusters of the same word likely reflect the phenomenon of 'positional regulation', i.e. a word's regulatory function can vary with its position relative to a genomic landmark, a conclusion inaccessible to methods based purely on sequence. Further integrative analysis of words co-occurring in PPRs also yielded 24 different groups of genes, likely identifying cis-regulatory modules de novo. Whereas comparative genomics requires precise sequence alignments, positional regulomics exploits genomic landmarks to provide a 'poor man's alignment'. By exploiting the phenomenon of positional regulation, it uses position to differentiate the biological functions of subsets of TFBSs sharing a common sequence motif.

Indexed as

Gene Expression RegulationPromoter Regions, GeneticTranscription Initiation SiteBinding SitesCluster AnalysisComputational BiologyGene Expression ProfilingGenomicsHumansTranscription FactorsTranscription Factors

Identifiers

PMID18367472
PMCPMC2377430
OpenAlexW2038641192

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.