Evidence map›Paper›PMID 19883503›Full record

ArticleGenome biology2009

Regulatory interdependence of myeloid transcription factors revealed by Matrix RNAi analysis.

Yasuhiro Tomaru, Christophe Simon, Alistair Rr Forrest, Hisashi Miura, Atsutaka Kubosaki, Yoshihide Hayashizaki, Masanori Suzuki

Abstract read
In one paragraph

Article in Genome biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Gene Regulatory Network Inference from Pseudotime-Ordered scRNA-seq Data via Time-Lagged Divergence Measures.Bioinformatics research and applications : ... international symposium, ISBRA ... proceedings. ISBRA (Conference) · 2025
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  3. Time-Varying Gene Regulatory Networks Inference Using KL Divergence from Single Cell Data.Proceedings of the ... International Conference on Bioinformatics and Biomedical Technology · 2025
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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

7 authors.

Yasuhiro TomaruRIKEN Omics Science Center, RIKEN Yokohama Institute 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan. tomaru@gsc.riken.jp
Christophe Simon
Alistair Rr Forrest
Hisashi Miura
Atsutaka Kubosaki
Yoshihide Hayashizaki
Masanori Suzuki

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the move towards systems biology, we need sensitive and reliable ways to determine the relationships between transcription factors and their target genes. In this paper we analyze the regulatory relationships between 78 myeloid transcription factors and their coding genes by using the matrix RNAi system in which a set of transcription factor genes are individually knocked down and the resultant expression perturbation is quantified.

resultsUsing small interfering RNAs we knocked down the 78 transcription factor genes in monocytic THP-1 cells and monitored the perturbation of the expression of the same 78 transcription factors and 13 other transcription factor genes as well as 5 non-transcription factor genes by quantitative real-time RT-PCR, thereby building a 78 x 96 matrix of perturbation and measurement. This approach identified 876 cases where knockdown of one transcription factor significantly affected the expression of another (from a potential 7,488 combinations). Our study also revealed cell-type-specific transcriptional regulatory networks in two different cell types.

conclusionsBy considering whether the targets of a given transcription factor are naturally up- or downregulated during phorbol 12-myristate 13-acetate-induced differentiation, we could classify these edges as pro-differentiative (229), anti-differentiative (76) or neither (571) using expression profiling data obtained in the FANTOM4 study. This classification analysis suggested that several factors could be involved in monocytic differentiation, while others such as MYB and the leukemogenic fusion MLL-MLLT3 could help to maintain the initial undifferentiated state by repressing the expression of pro-differentiative factors or maintaining expression of anti-differentiative factors.

Indexed as

Models, GeneticRNA InterferenceCell DifferentiationGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansModels, BiologicalMonocytesReverse Transcriptase Polymerase Chain ReactionRNA, Small InterferingTranscription FactorsTranscription, GeneticTransfectionRNA, Small InterferingTranscription Factors

Identifiers

PMID19883503
PMCPMC2810662

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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.