Evidence map›Paper›PMID 18769640›Full record

ArticlePloS one2008

How to build transcriptional network models of mammalian pattern formation.

Chrissa Kioussi, Michael K Gross

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

8 citing papers in PubMed, 12 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

2 authors at 1 institution in 1 country.

Chrissa KioussiDepartment of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, Oregon, United States of America.
Michael K Gross
Oregon State University · US

Funding

Reducing Susceptibility to Environmental Stress Throughout the Life SpanP30ES000210 · NIEHS · OREGON STATE UNIVERSITY · PI BECKMAN, JOSEPH S · 1985 to 2015
$21.4M
Role of Pitx2 in Muscle Development and RegenerationR01AR054406 · NIAMS · OREGON STATE UNIVERSITY · PI KIOUSSI, CHRISSA · 2007 to 2011
$1.4M
NIAMS NIH HHS R01 AR054406NIAMS NIH HHS R01AR054406NIEHS NIH HHS P30 ES000210NIEHS NIH HHS P30ES00210
6 · The paper itself

Abstract

backgroundGenetic regulatory networks of sequence specific transcription factors underlie pattern formation in multicellular organisms. Deciphering and representing the mammalian networks is a central problem in development, neurobiology, and regenerative medicine. Transcriptional networks specify intermingled embryonic cell populations during pattern formation in the vertebrate neural tube. Each embryonic population gives rise to a distinct type of adult neuron. The homeodomain transcription factor Lbx1 is expressed in five such populations and loss of Lbx1 leads to distinct respecifications in each of the five populations. METHODOLOGY/PRINCIPAL

findingsWe have purified normal and respecified pools of these five populations from embryos bearing one or two copies of the null Lbx1(GFP) allele, respectively. Microarrays were used to show that expression levels of 8% of all transcription factor genes were altered in the respecified pool. These transcription factor genes constitute 20-30% of the active nodes of the transcriptional network that governs neural tube patterning. Half of the 141 regulated nodes were located in the top 150 clusters of ultraconserved non-coding regions. Generally, Lbx1 repressed genes that have expression patterns outside of the Lbx1-expressing domain and activated genes that have expression patterns inside the Lbx1-expressing domain. CONCLUSIONS/SIGNIFICANCE: Constraining epistasis analysis of Lbx1 to only those cells that normally express Lbx1 allowed unprecedented sensitivity in identifying Lbx1 network interactions and allowed the interactions to be assigned to a specific set of cell populations. We call this method ANCEA, or active node constrained epistasis analysis, and think that it will be generally useful in discovering and assigning network interactions to specific populations. We discuss how ANCEA, coupled with population partitioning analysis, can greatly facilitate the systematic dissection of transcriptional networks that underlie mammalian patterning.

Indexed as

Gene Regulatory NetworksModels, GeneticAnimalsBody PatterningGenes, HomeoboxHumansMammalsTranscription FactorsTranscription Factors

Identifiers

PMID18769640
PMCPMC2527684
OpenAlexW2041711534

What OpenQuestion holds

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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.