Evidence map›Paper›PMID 24918027›Full record

ArticlePeerJ2014

Quantitative trait loci for energy balance traits in an advanced intercross line derived from mice divergently selected for heat loss.

Larry J Leamy, Kari Elo, Merlyn K Nielsen, Stephanie R Thorn, William Valdar, Daniel Pomp

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.4field-weighted citation impact, top 16% 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

1 citing paper in PubMed, 20 citations in OpenAlex.

  1. The GeneG3 (Bethesda, Md.) · 2020
    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

6 authors at 3 institutions in 1 country.

Larry J Leamy *Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.
Kari Elo *Department of Animal Science, University of Nebraska, Lincoln, NE, USA.
Merlyn K NielsenDepartment of Animal Science, University of Nebraska, Lincoln, NE, USA.
Stephanie R ThornDepartment of Animal Science, University of Nebraska, Lincoln, NE, USA.
William ValdarDepartment of Genetics, University of North Carolina, Chapel Hill, NC, USA.
Daniel PompDepartment of Genetics, University of North Carolina, Chapel Hill, NC, USA.
University of Nebraska–Lincoln · USUniversity of North Carolina at Chapel Hill · USUniversity of North Carolina at Charlotte · US

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
Genetic Architecture of Voluntary Exercise in MiceR01DK076050 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POMP, DANIEL · 2007 to 2010
$966k
NIDDK NIH HHS P30 DK056350NIDDK NIH HHS R01 DK076050
6 · The paper itself

Abstract

Obesity in human populations, currently a serious health concern, is considered to be the consequence of an energy imbalance in which more energy in calories is consumed than is expended. We used interval mapping techniques to investigate the genetic basis of a number of energy balance traits in an F11 advanced intercross population of mice created from an original intercross of lines selected for increased and decreased heat loss. We uncovered a total of 137 quantitative trait loci (QTLs) for these traits at 41 unique sites on 18 of the 20 chromosomes in the mouse genome, with X-linked QTLs being most prevalent. Two QTLs were found for the selection target of heat loss, one on distal chromosome 1 and another on proximal chromosome 2. The number of QTLs affecting the various traits generally was consistent with previous estimates of heritabilities in the same population, with the most found for two bone mineral traits and the least for feed intake and several body composition traits. QTLs were generally additive in their effects, and some, especially those affecting the body weight traits, were sex-specific. Pleiotropy was extensive within trait groups (body weights, adiposity and organ weight traits, bone traits) and especially between body composition traits adjusted and not adjusted for body weight at sacrifice. Nine QTLs were found for one or more of the adiposity traits, five of which appeared to be unique. The confidence intervals among all QTLs averaged 13.3 Mb, much smaller than usually observed in an F2 cross, and in some cases this allowed us to make reasonable inferences about candidate genes underlying these QTLs. This study combined QTL mapping with genetic parameter analysis in a large segregating population, and has advanced our understanding of the genetic architecture of complex traits related to obesity.

Indexed as

Body weight and body compositionFeed intakeMetabolic rateQTL by sex interactions

Identifiers

PMID24918027
PMCPMC4045330
OpenAlexW2157722714

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.