Evidence map›Paper›PMID 25879614›Full record

ArticleBMC genomics2015

Analysis of RNA decay factor mediated RNA stability contributions on RNA abundance.

Sho Maekawa, Naoto Imamachi, Takuma Irie, Hidenori Tani, Kyoko Matsumoto, Rena Mizutani, Katsutoshi Imamura, Miho Kakeda, Tetsushi Yada, Sumio Sugano and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

27 citing papers in PubMed, 49 citations in OpenAlex.

  1. Article
  2. Metabolic labeling of RNA using ribonucleoside analogs enables the evaluation of RNA synthesis and degradation rates.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025
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  17. Diminished nuclear RNA decay uponThe EMBO journal · 2018
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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

12 authors at 3 institutions in 1 country.

Sho MaekawaDepartment of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan. smaekawa@hgc.jp.
Naoto ImamachiRadioisotope Center, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan. imamachi@ric.u-tokyo.ac.jp.
Takuma IrieDepartment of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan. tirie@hgc.jp.
Hidenori TaniResearch Institute for Environmental Management Technology, National Institute of Advanced Industrial Science and Technology (AIST), 16-1 Onogawa, Tsukuba, Ibaraki, 305-8569, Japan. h.tani@aist.go.jp.
Kyoko MatsumotoDepartment of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan. kk086409@mgs.k.u-tokyo.ac.jp.
Rena MizutaniRadioisotope Center, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan. rena@ric.u-tokyo.ac.jp.
Katsutoshi ImamuraRadioisotope Center, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan. k.imamura@ric.u-tokyo.ac.jp.
Miho KakedaRadioisotope Center, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan. 3134mk@gmail.com.
Tetsushi YadaDepartment of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan. ytetsu@bio.kyutech.ac.jp.
Sumio SuganoDepartment of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan. ssugano@k.u-tokyo.ac.jp.
Yutaka SuzukiDepartment of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan. ysuzuki@k.u-tokyo.ac.jp.
Nobuyoshi AkimitsuRadioisotope Center, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan. akimitsu@ric.u-tokyo.ac.jp.
The University of Tokyo · JPKyushu Institute of Technology · JPNational Institute of Advanced Industrial Science and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHistone epigenome data determined by chromatin immunoprecipitation sequencing (ChIP-seq) is used in identifying transcript regions and estimating expression levels. However, this estimation does not always correlate with eventual RNA expression levels measured by RNA sequencing (RNA-seq). Part of the inconsistency may arise from the variance in RNA stability, where the transcripts that are more or less abundant than predicted RNA expression from histone epigenome data are inferred to be more or less stable. However, there is little systematic analysis to validate this assumption. Here, we used stability data of whole transcriptome measured by 5'-bromouridine immunoprecipitation chase sequencing (BRIC-seq), which enabled us to determine the half-lives of whole transcripts including lincRNAs, and we integrated BRIC-seq with ChIP-seq to achieve better estimation of the eventual transcript levels and to understand the importance of post-transcriptional regulation that determine the eventual transcript levels.

resultsWe identified discrepancies between the RNA abundance estimated by ChIP-seq and measured RNA expression from RNA-seq; for number of genes and estimated that the expression level of 865 genes was controlled at the level of RNA stability in HeLa cells. ENCODE data analysis supported the idea that RNA stability control aids to determine transcript levels in multiple cell types. We identified UPF1, EXOSC5 and STAU1, well-studied RNA degradation factors, as controlling factors for 8% of cases. Computational simulations reasonably explained the changes of eventual mRNA levels attributable to the changes in the rates of mRNA half-lives. In addition, we propose a feedback circuit that includes the regulated degradation of mRNAs encoding transcription factors to maintain the steady state level of RNA abundance. Intriguingly, these regulatory mechanisms were distinct between mRNAs and lincRNAs.

conclusionsIntegrative analysis of ChIP-seq, RNA-seq and our BRIC-seq showed that transcriptional regulation and RNA degradation are independently regulated. In addition, RNA stability is an important determinant of eventual transcript levels. RNA binding proteins, such as UPF1, STAU1 and EXOSC5 may play active roles in such controls.

Indexed as

RNA StabilityAntigens, NeoplasmChromatin ImmunoprecipitationCytoskeletal ProteinsExosome Multienzyme Ribonuclease ComplexGene Expression RegulationHalf-LifeHeLa CellsHigh-Throughput Nucleotide SequencingHistonesHumansRNARNA-Binding ProteinsRNA HelicasesRNA, Long NoncodingRNA, MessengerAntigens, NeoplasmCytoskeletal ProteinsEXOSC5 protein, humanExosome Multienzyme Ribonuclease ComplexHistonesRNARNA-Binding ProteinsRNA HelicasesRNA, Long NoncodingRNA, MessengerSTAU1 protein, humanTrans-ActivatorsUPF1 protein, human

Identifiers

PMID25879614
PMCPMC4359779
OpenAlexW2135899392

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.