Evidence map›Paper›PMID 28665992›Full record

ArticlePloS one2017

Gene expression allelic imbalance in ovine brown adipose tissue impacts energy homeostasis.

Shila Ghazanfar, Tony Vuocolo, Janna L Morrison, Lisa M Nicholas, Isabella C McMillen, Jean Y H Yang, Michael J Buckley, Ross L Tellam

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Shila GhazanfarData61, CSIRO, North Ryde, NSW, Australia.
Tony VuocoloCSIRO Agriculture, Queensland Biosciences Precinct, St Lucia, QLD, Australia.
Janna L MorrisonEarly Origins of Adult Health Research Group, School of Pharmacy and Medical Sciences, Sansom Institute for Health Research, The University of South Australia, Adelaide, SA, Australia.
Lisa M NicholasEarly Origins of Adult Health Research Group, School of Pharmacy and Medical Sciences, Sansom Institute for Health Research, The University of South Australia, Adelaide, SA, Australia.
Isabella C McMillenEarly Origins of Adult Health Research Group, School of Pharmacy and Medical Sciences, Sansom Institute for Health Research, The University of South Australia, Adelaide, SA, Australia.
Jean Y H YangSchool of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia.
Michael J BuckleyData61, CSIRO, North Ryde, NSW, Australia.
Ross L TellamCSIRO Agriculture, Queensland Biosciences Precinct, St Lucia, QLD, Australia.ORCID http://orcid.org/0000-0003-2353-1640
Commonwealth Scientific and Industrial Research Organisation · AUUniversity of South Australia · AUThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heritable trait variation within a population of organisms is largely governed by DNA variations that impact gene transcription and protein function. Identifying genetic variants that affect complex functional traits is a primary aim of population genetics studies, especially in the context of human disease and agricultural production traits. The identification of alleles directly altering mRNA expression and thereby biological function is challenging due to difficulty in isolating direct effects of cis-acting genetic variations from indirect trans-acting genetic effects. Allele specific gene expression or allelic imbalance in gene expression (AI) occurring at heterozygous loci provides an opportunity to identify genes directly impacted by cis-acting genetic variants as indirect trans-acting effects equally impact the expression of both alleles. However, the identification of genes showing AI in the context of the expression of all genes remains a challenge due to a variety of technical and statistical issues. The current study focuses on the discovery of genes showing AI using single nucleotide polymorphisms as allelic reporters. By developing a computational and statistical process that addressed multiple analytical challenges, we ranked 5,809 genes for evidence of AI using RNA-Seq data derived from brown adipose tissue samples from a cohort of late gestation fetal lambs and then identified a conservative subgroup of 1,293 genes. Thus, AI was extensive, representing approximately 25% of the tested genes. Genes associated with AI were enriched for multiple Gene Ontology (GO) terms relating to lipid metabolism, mitochondrial function and the extracellular matrix. These functions suggest that cis-acting genetic variations causing AI in the population are preferentially impacting genes involved in energy homeostasis and tissue remodelling. These functions may contribute to production traits likely to be under genetic selection in the population.

Indexed as

Allelic ImbalanceHomeostasisAdipose Tissue, BrownAnimalsFemaleHumansPolymorphism, Single NucleotidePregnancySheep

Identifiers

PMID28665992
PMCPMC5493397
OpenAlexW2728068685

What OpenQuestion 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 OpenQuestion graph.