Evidence map›Paper›PMID 30500367›Full record

ArticleMethods (San Diego, Calif.)2019

Cell-type specific polysome profiling from mammalian tissues.

Joseph Seimetz, Waqar Arif, Sushant Bangru, Mikel Hernaez, Auinash Kalsotra

Abstract read
In one paragraph

Article in Methods (San Diego, Calif.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Frontiers in physiology · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Remodeling of the mJournal of molecular and cellular cardiology · 2021
    Article
  14. Epitranscriptomics in the Heart: a Focus on mCurrent heart failure reports · 2020
    Review
  15. Cellular and molecular basis of liver regeneration.Seminars in cell & developmental biology · 2020
    Review
  16. Article
  17. Frontiers in genetics · 2019
    Review
  18. Article
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

5 authors.

Joseph SeimetzDepartment of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA.
Waqar ArifDepartment of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA.
Sushant BangruDepartment of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA.
Mikel HernaezCarl R. Woese Institute for Genomic Biology, University of Illinois, Urbana-Champaign, IL, USA.
Auinash KalsotraDepartment of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana-Champaign, IL, USA; Cancer Center@ Illinois, University of Illinois, Urbana-Champaign, IL, USA. Electronic address: kalsotra@illinois.edu.

Funding

Training Program in Chemistry-Interface with BiologyT32GM070421 · NIGMS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI HERGENROTHER, PAUL · 2005 to 2019
$5.4M
Post-transcriptional mechanisms of gene regulation in cardiac cell growth and developmentR01HL126845 · NHLBI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI KALSOTRA, AUINASH · 2015 to 2023
$3.5M
Tissue microenvironment (TIMe) training programT32EB019944 · NIBIB · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI BHARGAVA, ROHIT, GASKINS, REX · 2016 to 2025
$1.9M
The role of SRSF1 in liver function and NASHF30DK108567 · NIDDK · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI ARIF, WAQAR · 2016 to 2020
$248k
NHLBI NIH HHS R01 HL126845NIBIB NIH HHS T32 EB019944NIDDK NIH HHS F30 DK108567NIGMS NIH HHS T32 GM070421
6 · The paper itself

Abstract

The regulation of gene expression occurs through complex relationships between transcription, processing, turnover, and translation, which are only beginning to be elucidated. We know that at least for certain messenger (m) RNAs, processing, modifications, and sequence elements can greatly influence their translational output through recognition by translation and turn-over machinery. Recently, we and others have combined high-throughput sequencing technologies with traditional biochemical methods of studying translation to extend our understanding of these relationships. Additionally, there is growing importance given to how these processes may be regulated across varied cell types as a means to achieve tissue-specific expression of proteins. Here, we provide an in-depth methodology for polysome profiling to dissect the composition of mRNAs and proteins that make up the translatome from both whole tissues and a specific cell type isolated from mammalian tissue. Also, we provide a detailed computational workflow for the analysis of the next-generation sequencing data generated from these experiments.

Indexed as

Protein BiosynthesisAnimalsBrainCell FractionationCentrifugation, Density GradientComputational BiologyGene OntologyGene Regulatory NetworksHepatocytesHigh-Throughput Nucleotide SequencingLiverMiceMolecular Sequence AnnotationMyocardiumMyocytes, CardiacNeuronsRNA, MessengerCell-type isolation from tissuesNext-generation sequencing and bioinformaticsPolysome profilingRibosomal occupancy shiftTranslation regulation

Identifiers

PMID30500367
PMCPMC6387852

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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.