↓ Skip to main content

A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle

Overview of attention for article published in Journal of Animal Science, April 2014
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
71 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle
Published in
Journal of Animal Science, April 2014
DOI 10.2527/jas.2013-7484
Pubmed ID
Authors

Y Ramayo-Caldas, M R S Fortes, N J Hudson, L R Porto-Neto, S Bolormaa, W Barendse, M Kelly, S S Moore, M E Goddard, S A Lehnert, A Reverter

Abstract

High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavour. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance and a number of meat quality traits relating to body conformation, development and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genome-wide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from three breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARGC1A, HNF4G and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the three TF. These genes belong to a wide variety of biological functions, canonical pathways and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a co-operative role for the three TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Brazil 1 1%
Unknown 69 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 24%
Student > Ph. D. Student 12 17%
Student > Master 10 14%
Student > Doctoral Student 5 7%
Student > Bachelor 3 4%
Other 6 8%
Unknown 18 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 42%
Biochemistry, Genetics and Molecular Biology 6 8%
Medicine and Dentistry 4 6%
Veterinary Science and Veterinary Medicine 3 4%
Psychology 1 1%
Other 1 1%
Unknown 26 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 April 2014.
All research outputs
#22,760,732
of 25,377,790 outputs
Outputs from Journal of Animal Science
#4,958
of 5,439 outputs
Outputs of similar age
#209,766
of 242,073 outputs
Outputs of similar age from Journal of Animal Science
#22
of 30 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,439 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 242,073 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.