Evidence map›Paper›PMID 26117544›Full record

ArticleNucleic acids research2015

Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics.

Sugata Roy, Sebastian Schmeier, Erik Arner, Tanvir Alam, Suraj P Parihar, Mumin Ozturk, Ousman Tamgue, Hideya Kawaji, Michiel J L de Hoon, Masayoshi Itoh and 9 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. [Effects ofZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
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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

19 authors.

Sugata RoyDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Sebastian SchmeierMassey University, Institute of Natural and Mathematical Sciences, Auckland, New Zealand.
Erik ArnerDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Tanvir AlamKing Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia.
Suraj P PariharInternational Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Cape Town, South Africa University of Cape Town, Health Science Faculty, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology, Cape Town, South Africa.
Mumin OzturkInternational Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Cape Town, South Africa University of Cape Town, Health Science Faculty, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology, Cape Town, South Africa.
Ousman TamgueInternational Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Cape Town, South Africa University of Cape Town, Health Science Faculty, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology, Cape Town, South Africa.
Hideya KawajiDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Preventive Medicine and Diagnosis Innovation Program (PMI), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Michiel J L de HoonDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Masayoshi ItohDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Preventive Medicine and Diagnosis Innovation Program (PMI), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Timo LassmannDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Piero CarninciDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Yoshihide HayashizakiRiken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Preventive Medicine and Diagnosis Innovation Program (PMI), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Alistair R R ForrestDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Vladimir B BajicKing Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia.
Reto GulerInternational Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Cape Town, South Africa University of Cape Town, Health Science Faculty, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology, Cape Town, South Africa.
Fantom ConsortiumDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Massey University, Institute of Natural and Mathematical Sciences, Auckland, New Zealand King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia International Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Cape Town, South Africa University of Cape Town, Health Science Faculty, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology, Cape Town, South Africa Riken Preventive Medicine and Diagnosis Innovation Program (PMI), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Frank BrombacherInternational Centre for Genetic Engineering and Biotechnology (ICGEB), Cape Town Component, Cape Town, South Africa University of Cape Town, Health Science Faculty, Institute of Infectious Diseases and Molecular Medicine (IDM), Division of Immunology, Cape Town, South Africa harukazu@gsc.riken.jp.
Harukazu SuzukiDivision of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan Riken Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan harukazu@gsc.riken.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Classically or alternatively activated macrophages (M1 and M2, respectively) play distinct and important roles for microbiocidal activity, regulation of inflammation and tissue homeostasis. Despite this, their transcriptional regulatory dynamics are poorly understood. Using promoter-level expression profiling by non-biased deepCAGE we have studied the transcriptional dynamics of classically and alternatively activated macrophages. Transcription factor (TF) binding motif activity analysis revealed four motifs, NFKB1_REL_RELA, IRF1,2, IRF7 and TBP that are commonly activated but have distinct activity dynamics in M1 and M2 activation. We observe matching changes in the expression profiles of the corresponding TFs and show that only a restricted set of TFs change expression. There is an overall drastic and transient up-regulation in M1 and a weaker and more sustainable up-regulation in M2. Novel TFs, such as Thap6, Maff, (M1) and Hivep1, Nfil3, Prdm1, (M2) among others, were suggested to be involved in the activation processes. Additionally, 52 (M1) and 67 (M2) novel differentially expressed genes and, for the first time, several differentially expressed long non-coding RNA (lncRNA) transcriptome markers were identified. In conclusion, the finding of novel motifs, TFs and protein-coding and lncRNA genes is an important step forward to fully understand the transcriptional machinery of macrophage activation.

Indexed as

Gene Expression RegulationTranscriptomeAnimalsCells, CulturedDNAGene Expression ProfilingHigh-Throughput Nucleotide SequencingInterferon-gammaInterleukin-13Interleukin-4Macrophage ActivationMacrophagesMaleMice, Inbred BALB CNucleotide MotifsPromoter Regions, GeneticDNAInterferon-gammaInterleukin-13Interleukin-4Transcription Factors

Identifiers

PMID26117544
PMCPMC4538831

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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.