Evidence map›Paper›PMID 20459830›Full record

ArticleBMC genomics2010

Systems genetics analysis of body weight and energy metabolism traits in Drosophila melanogaster.

Patricia Jumbo-Lucioni, Julien F Ayroles, Michelle Moses Chambers, Katherine W Jordan, Jeff Leips, Trudy Fc Mackay, Maria De Luca

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

55 citing papers in PubMed, 98 citations in OpenAlex.

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  19. Disrupted Gene Networks in Subfertile Hybrid House Mice.Molecular biology and evolution · 2020
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  20. Systems genetics of theGenome research · 2020
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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 3 institutions in 1 country.

Patricia Jumbo-LucioniDepartment of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, AL 35294-3360, USA.
Julien F Ayroles
Michelle Moses Chambers
Katherine W Jordan
Jeff Leips
Trudy Fc Mackay
Maria De Luca
North Carolina State University · USUniversity of Alabama at Birmingham · USUniversity of Maryland, Baltimore County · US

Funding

Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI James O Hill · 2000 to 2026
$31.9M
UAB CENTER FOR CLINICAL AND TRANSLATIONAL SCIENCE (CCTS) UL1: BPCAUL1RR025777 · NCRR · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI GUAY-WOODFORD, LISA MARIE · 2008 to 2011
$22.3M
UAB Diabetes Research and Training CenterP60DK079626 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI GARVEY, W TIMOTHY · 2008 to 2012
$8.4M
QUANTITATIVE TRAIT LOCI IN DROSOPHILAR01GM045146 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI ANHOLT, ROBERT R. H, MACKAY, TRUDY F. · 1991 to 2012
$5.1M
Genetic control of quantitative traits associated with the metabolic syndromeR01DK084219 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LUCA, MARIA · 2010 to 2013
$1.3M
NCRR NIH HHS UL1RR025777NIDDK NIH HHS P30-DK56336NIDDK NIH HHS P60-DK079626NIDDK NIH HHS R01 DK084219NIGMS NIH HHS R01 GM045146NIGMS NIH HHS R01 GM 45146
6 · The paper itself

Abstract

backgroundObesity and phenotypic traits associated with this condition exhibit significant heritability in natural populations of most organisms. While a number of genes and genetic pathways have been implicated to play a role in obesity associated traits, the genetic architecture that underlies the natural variation in these traits is largely unknown. Here, we used 40 wild-derived inbred lines of Drosophila melanogaster to quantify genetic variation in body weight, the content of three major metabolites (glycogen, triacylglycerol, and glycerol) associated with obesity, and metabolic rate in young flies. We chose these lines because they were previously screened for variation in whole-genome transcript abundance and in several adult life-history traits, including longevity, resistance to starvation stress, chill-coma recovery, mating behavior, and competitive fitness. This enabled us not only to identify candidate genes and transcriptional networks that might explain variation for energy metabolism traits, but also to investigate the genetic interrelationships among energy metabolism, behavioral, and life-history traits that have evolved in natural populations.

resultsWe found significant genetically based variation in all traits. Using a genome-wide association screen for single feature polymorphisms and quantitative trait transcripts, we identified 337, 211, 237, 553, and 152 novel candidate genes associated with body weight, glycogen content, triacylglycerol storage, glycerol levels, and metabolic rate, respectively. Weighted gene co-expression analyses grouped transcripts associated with each trait in significant modules of co-expressed genes and we interpreted these modules in terms of their gene enrichment based on Gene Ontology analysis. Comparison of gene co-expression modules for traits in this study with previously determined modules for life-history traits identified significant modular pleiotropy between glycogen content, body weight, competitive fitness, and starvation resistance.

conclusionsCombining a large phenotypic dataset with information on variation in genome wide transcriptional profiles has provided insight into the complex genetic architecture underlying natural variation in traits that have been associated with obesity. Our findings suggest that understanding the maintenance of genetic variation in metabolic traits in natural populations may require that we understand more fully the degree to which these traits are genetically correlated with other traits, especially those directly affecting fitness.

Indexed as

Energy MetabolismAnimalsBody WeightDrosophila melanogasterGene ExpressionGenome-Wide Association StudyQuantitative Trait LociTranscription, Genetic

Identifiers

PMID20459830
PMCPMC2880307
OpenAlexW2082615795

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.