Evidence map›Paper›PMID 32718981›Full record

ArticleGenome research2020

Comparative transcriptomics of primary cells in vertebrates.

Tanvir Alam, Saumya Agrawal, Jessica Severin, Robert S Young, Robin Andersson, Erik Arner, Akira Hasegawa, Marina Lizio, Jordan A Ramilowski, Imad Abugessaisa and 15 more

Abstract readComparative Study
In one paragraph

Article in Genome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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  7. Long Non-Coding RNAs in Sjögren's Disease.International journal of molecular sciences · 2024
    Review
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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

25 authors.

Tanvir AlamCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Saumya AgrawalRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Jessica SeverinRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Robert S YoungCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, United Kingdom.
Robin AnderssonThe Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark.
Erik ArnerRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Akira HasegawaRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Marina LizioRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Jordan A RamilowskiRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.ORCID 0000-0002-3156-6416
Imad AbugessaisaRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.ORCID 0000-0001-7458-801X
Yuri IshizuRIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama 230-0045, Japan.
Shohei NomaRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Hiroshi TaruiRIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama 230-0045, Japan.
Martin S TaylorMRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, United Kingdom.ORCID 0000-0001-7656-330X
Timo LassmannRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Masayoshi ItohRIKEN Preventive Medicine and Diagnosis Innovation Program, Wako 351-0198, Japan.
Takeya KasukawaRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.ORCID 0000-0001-5085-0802
Hideya KawajiRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Luigi MarchionniDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA.ORCID 0000-0002-7336-8071
Guojun ShengInternational Research Center for Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan.
Alistair R R ForrestRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
Levon M KhachigianVascular Biology and Translational Research, School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, NSW 2052 Australia.ORCID 0000-0003-3446-0323
Yoshihide HayashizakiRIKEN Preventive Medicine and Diagnosis Innovation Program, Wako 351-0198, Japan.
Piero CarninciRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.ORCID 0000-0001-7202-7243
Michiel J L de HoonRIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.ORCID 0000-0003-0489-2352

Funding

Hardwiring Mechanism into Predicting Cancer Phenotypes by Computational LearningR01CA200859 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI MARCHIONNI, LUIGI · 2016 to 2020
$1.9M
Medical Research Council MC_UU_00007/11NCI NIH HHS R01 CA200859
6 · The paper itself

Abstract

Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products involved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expression levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both promoters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are conserved, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species.

Indexed as

Evolution, MolecularTranscriptomeAnimalsChickensDogsGene Expression ProfilingGene Regulatory NetworksHumansMiceMicroRNAsNucleotide MotifsPrincipal Component AnalysisPromoter Regions, GeneticRatsSpecies SpecificityTranscription FactorsMicroRNAsTranscription Factors

Identifiers

PMID32718981
PMCPMC7397866

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.