Evidence map›Paper›PMID 24939925›Full record

ArticlePhysiological genomics2014

Quantitative genomics of voluntary exercise in mice: transcriptional analysis and mapping of expression QTL in muscle.

Scott A Kelly, Derrick L Nehrenberg, Kunjie Hua, Theodore Garland, Daniel Pomp

Abstract read
In one paragraph

Article in Physiological genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Relationship between gene expression networks and muscle contractile physiology differences in Anolis lizards.Journal of comparative physiology. B, Biochemical, systemic, and environmental physiology · 2022
    Article
  3. Article
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  8. Review
  9. Article
  10. Article
  11. Genetic approaches in comparative and evolutionary physiology.American journal of physiology. Regulatory, integrative and comparative physiology · 2015
    Review
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.

Scott A KellyDepartment of Zoology, Ohio Wesleyan University, Delaware, Ohio; sakelly@owu.edu.
Derrick L NehrenbergDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina; and.
Kunjie HuaDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina; and.
Theodore GarlandDepartment of Biology, University of California, Riverside, Riverside, California.
Daniel PompDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina; and.

Funding

UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Ian Michael Carroll · 1999 to 2026
$31.6M
UNC Interdisciplinary Obesity Training (IDOT)(RMI)T32MH075854 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2005 to 2009
$1.2M
Genetic Architecture of Voluntary Exercise in MiceR01DK076050 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POMP, DANIEL · 2007 to 2010
$966k
NIDDK NIH HHS DK-056350NIDDK NIH HHS DK 076050NIDDK NIH HHS P30 DK056350NIMH NIH HHS 5T32MH-075854-04
6 · The paper itself

Abstract

Motivation and ability both underlie voluntary exercise, each with a potentially unique genetic architecture. Muscle structure and function are one of many morphological and physiological systems acting to simultaneously determine exercise ability. We generated a large (n = 815) advanced intercross line of mice (G4) derived from a line selectively bred for increased wheel running (high runner) and the C57BL/6J inbred strain. We previously mapped quantitative trait loci (QTL) contributing to voluntary exercise, body composition, and changes in body composition as a result of exercise. Using brain tissue in a subset of the G4 (n = 244), we have also previously reported expression QTL (eQTL) colocalizing with the QTL for the higher-level phenotypes. Here, we examined the transcriptional landscape of hind limb muscle tissue via global mRNA expression profiles. Correlations revealed an ∼1,168% increase in significant relationships between muscle transcript expression levels and the same exercise and body composition phenotypes examined previously in the brain. The exercise trait most often significantly correlated with gene expression in the brain was running duration while in the muscle it was maximum running speed. This difference may indicate that time spent engaging in exercise behavior may be more influenced by central (neurobiological) mechanisms, while intensity of exercise may be largely controlled by peripheral mechanisms. Additionally, we used subsets of cis-acting eQTL, colocalizing with QTL, to identify candidate genes based on both positional and functional evidence. We discuss three plausible candidate genes (Insig2, Prcp, Sparc) and their potential regulatory role.

Indexed as

AnimalsChromosome MappingChromosomes, MammalianFemaleGene Expression ProfilingGenomicsHindlimbMaleMice, Inbred C57BLMotor ActivityMuscle, SkeletalOligonucleotide Array Sequence AnalysisPhysical Conditioning, AnimalQuantitative Trait Lociadipositybody weighteQTLexperimental evolutionwheel running

Identifiers

PMID24939925
PMCPMC4137147

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.