Evidence map›Paper›PMID 27637250›Full record

ArticlePhysiological genomics2016

Selection-, age-, and exercise-dependence of skeletal muscle gene expression patterns in a rat model of metabolic fitness.

Yu-Yu Ren, Lauren G Koch, Steven L Britton, Nathan R Qi, Mary K Treutelaar, Charles F Burant, Jun Z Li

Open access · bronzeAbstract read
In one paragraph

Article in Physiological genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. MuscleAtlasExplorer: a web service for studying gene expression in human skeletal muscle.Database : the journal of biological databases and curation · 2020
    Article
  5. Article
  6. Article
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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

7 authors at 1 institution in 1 country.

Yu-Yu RenDepartment of Human Genetics, University of Michigan, Ann Arbor, Michigan.
Lauren G KochDepartment of Anesthesiology, University of Michigan, Ann Arbor, Michigan; and.
Steven L BrittonDepartment of Anesthesiology, University of Michigan, Ann Arbor, Michigan; and.
Nathan R QiDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Mary K TreutelaarDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Charles F BurantDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Jun Z LiDepartment of Human Genetics, University of Michigan, Ann Arbor, Michigan; junzli@med.umich.edu.ORCID 0000-0001-6727-0812
University of Michigan · US

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
Pilot and Feasibility (P and F) ProgramP30DK089503 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Kanakadurga Singer · 2010 to 2026
$20.3M
Michigan Mouse Metabolic Phenotyping CenterU2CDK110768 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ELIAS, CAROL FUZETI · 2016 to 2021
$6.2M
Resource for Rat Genetic Models of Aerobic CapacityP40OD021331 · OD · UNIVERSITY OF TOLEDO HEALTH SCI CAMPUS · PI KOCH, LAUREN GERARD · 2015 to 2019
$1.9M
Genotype-Phenotype relationships underlying aerobic capacity and metabolic healthR01DK099034 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BRITTON, STEVEN LOYAL, BURANT, CHARLES F · 2014 to 2016
$1.4M
6 · The paper itself

Abstract

Intrinsic aerobic exercise capacity can influence many complex traits including obesity and aging. To study this connection we established two rat lines by divergent selection of untrained aerobic capacity. After 32 generations the high capacity runners (HCR) and low capacity runners (LCR) differed in endurance running distance and body fat, blood glucose, other health indicators, and natural life span. To understand the interplay among genetic differences, chronological age, and acute exercise we performed microarray-based gene expression analyses in skeletal muscle with a 2×2×2 design to simultaneously compare HCR and LCR, old and young animals, and rest and exhaustion. Transcripts for mitochondrial function are expressed higher in HCRs than LCRs at both rest and exhaustion and for both age groups. Expression of cell adhesion and extracellular matrix genes tend to decrease with age. This and other age effects are more prominent in LCRs than HCRs, suggesting that HCRs have a slower aging process and this may be partly due to their better metabolic health. Strenuous exercise mainly affects transcription regulation and cellular response. The effects of any one factor often depend on the other two. For example, there are ∼140 and ∼110 line-exercise "interacting" genes for old and young animals, respectively. Many genes highlighted in our study are consistent with prior reports, but many others are novel. The gene- and pathway-level statistics for the main effects, either overall or stratified, and for all possible interactions, represent a rich reference dataset for understanding the interdependence among lines, aging, and exercise.

Indexed as

Gene Expression Regulation, DevelopmentalPhysical Conditioning, AnimalAgingAnimalsFemaleGene Expression ProfilingModels, AnimalMuscle, SkeletalPrincipal Component AnalysisRatsaerobic capacityagingdivergent selectionexercisegene expression

Identifiers

PMID27637250
PMCPMC5243203
OpenAlexW2519600451

What OpenQuestion holds

Textmetadata
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.