Evidence map›Paper›PMID 18613714›Full record

ArticleJournal of proteome research2008

Global relationship between the proteome and transcriptome of human skeletal muscle.

Zhengping Yi, Benjamin P Bowen, Hyonson Hwang, Christopher P Jenkinson, Dawn K Coletta, Natalie Lefort, Mandeep Bajaj, Sangeeta Kashyap, Rachele Berria, Elena A De Filippis and 1 more

Abstract readComparative Study
In one paragraph

Article in Journal of proteome research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.8field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Review
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  4. Skeletal muscle DNA methylation modifications and psychopharmacologic treatment in bipolar disorder.European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology · 2019
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  11. Functional classification of skeletal muscle networks. I. Normal physiology.Journal of applied physiology (Bethesda, Md. : 1985) · 2012
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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

11 authors at 2 institutions in 1 country.

Zhengping YiCenter for Metabolic Biology, Arizona State University, Tempe, AZ 85287, USA.
Benjamin P Bowen
Hyonson Hwang
Christopher P Jenkinson
Dawn K Coletta
Natalie Lefort
Mandeep Bajaj
Sangeeta Kashyap
Rachele Berria
Elena A De Filippis
Lawrence J Mandarino
Arizona State University · USThe University of Texas Health Science Center at San Antonio · US

Funding

MOLECULAR REGULATION OF MUSCLE GLUCOSE METABOLISM IN MANR01DK047936 · NIDDK · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI MANDARINO, LAWRENCE J · 1994 to 2022
$10.7M
PGC-1 & Muscle Mitochondrial Dysfunction in DiabetesR01DK066483 · NIDDK · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI MANDARINO, LAWRENCE J · 2004 to 2018
$6.7M
Identification of Prediabetes Genes by Expression Linkage AnalysisR01DK079195 · NIDDK · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI JENKINSON, CHRISTOPHER P · 2008 to 2013
$2.5M
NIDDK NIH HHS R01 DK047936NIDDK NIH HHS R01 DK066483NIDDK NIH HHS R01 DK079195NIDDK NIH HHS R01 DK 47936NIDDK NIH HHS R01 DK 66483
6 · The paper itself

Abstract

Skeletal muscle is one of the largest tissues in the human body. Changes in mRNA and protein abundance in this tissue are central to a large number of metabolic and other disorders, including, commonly, insulin resistance. Proteomic and microarray analyses are important approaches for gaining insight into the molecular and biochemical basis for normal and pathophysiological conditions. With the use of vastus lateralis muscle obtained from two groups of healthy, nonobese subjects, we performed a detailed comparison of the muscle proteome, obtained by HPLC-ESI-MS/MS, with the muscle transcriptome, obtained using oligonucleotide microarrays. HPLC-ESI-MS/MS analysis identified 507 unique proteins as present in four out of six subjects, while 5193 distinct transcripts were called present by oligonucleotide microarrays from four out of six subjects. The majority of the proteins identified by mass spectrometry also had their corresponding transcripts detected by microarray analysis, although 73 proteins were only identified in the proteomic analysis. Reflecting the high abundance of mitochondria in skeletal muscle, 30% of proteins detected were attributed to the mitochondrion, as compared to only 9% of transcripts. On the basis of Gene Ontology annotations, proteins assigned to mitochondrial inner membrane, mitochondrial envelope, structural molecule activity, electron transport, as well as generation of precursor metabolites and energy, had more corresponding transcripts detected than would be expected by chance. On the contrary, proteins assigned to Golgi apparatus, extracellular region, lyase activity, kinase activity, and protein modification process had fewer corresponding transcripts detected than would be expected by chance. In conclusion, these results provide the first global comparison of the human skeletal muscle proteome and transcriptome to date. These data show that a combination of proteomic and transcriptic analyses will provide data that can be used to test hypotheses regarding the pathogenesis of muscle disorders as well as to generate observational data that can be used to form novel hypotheses.

Indexed as

AdultChromatography, High Pressure LiquidGene Expression ProfilingHumansMiddle AgedMuscle ProteinsMuscle, SkeletalOligonucleotide Array Sequence AnalysisProteomeSpectrometry, Mass, Electrospray IonizationTandem Mass SpectrometryMuscle ProteinsProteome

Identifiers

PMID18613714
PMCPMC2755516
OpenAlexW1968141749

What OpenQuestion holds

Textmetadata
LicenceTDM
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.