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The application of transcriptomic data in the authentication of beef derived from contrasting production systems

Overview of attention for article published in BMC Genomics, September 2016
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Title
The application of transcriptomic data in the authentication of beef derived from contrasting production systems
Published in
BMC Genomics, September 2016
DOI 10.1186/s12864-016-2851-7
Pubmed ID
Authors

Torres Sweeney, Alex Lejeune, Aidan P. Moloney, Frank J. Monahan, Paul Mc Gettigan, Gerard Downey, Stephen D. E. Park, Marion T. Ryan

Abstract

Differences between cattle production systems can influence the nutritional and sensory characteristics of beef, in particular its fatty acid (FA) composition. As beef products derived from pasture-based systems can demand a higher premium from consumers, there is a need to understand the biological characteristics of pasture produced meat and subsequently to develop methods of authentication for these products. Here, we describe an approach to authentication that focuses on differences in the transcriptomic profile of muscle from animals finished in different systems of production of practical relevance to the Irish beef industry. The objectives of this study were to identify a panel of differentially expressed (DE) genes/networks in the muscle of cattle raised outdoors on pasture compared to animals raised indoors on a concentrate based diet and to subsequently identify an optimum panel which can classify the meat based on a production system. A comparison of the muscle transcriptome of outdoor/pasture-fed and Indoor/concentrate-fed cattle resulted in the identification of 26 DE genes. Functional analysis of these genes identified two significant networks (1: Energy Production, Lipid Metabolism, Small Molecule Biochemistry; and 2: Lipid Metabolism, Molecular Transport, Small Molecule Biochemistry), both of which are involved in FA metabolism. The expression of selected up-regulated genes in the outdoor/pasture-fed animals correlated positively with the total n-3 FA content of the muscle. The pathway and network analysis of the DE genes indicate that peroxisome proliferator-activated receptor (PPAR) and FYN/AMPK could be implicit in the regulation of these alterations to the lipid profile. In terms of authentication, the expression profile of three DE genes (ALAD, EIF4EBP1 and NPNT) could almost completely separate the samples based on production system (95 % authentication for animals on pasture-based and 100 % for animals on concentrate- based diet) in this context. The majority of DE genes between muscle of the outdoor/pasture-fed and concentrate-fed cattle were related to lipid metabolism and in particular β-oxidation. In this experiment the combined expression profiles of ALAD, EIF4EBP1 and NPNT were optimal in classifying the muscle transcriptome based on production system. Given the overall lack of comparable studies and variable concordance with those that do exist, the use of transcriptomic data in authenticating production systems requires more exploration across a range of contexts and breeds.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 23%
Student > Ph. D. Student 7 18%
Student > Master 6 15%
Student > Doctoral Student 3 8%
Professor 2 5%
Other 3 8%
Unknown 9 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 44%
Biochemistry, Genetics and Molecular Biology 3 8%
Nursing and Health Professions 2 5%
Unspecified 1 3%
Arts and Humanities 1 3%
Other 4 10%
Unknown 11 28%
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 28 September 2016.
All research outputs
#18,616,159
of 23,881,329 outputs
Outputs from BMC Genomics
#7,812
of 10,793 outputs
Outputs of similar age
#234,492
of 323,622 outputs
Outputs of similar age from BMC Genomics
#204
of 318 outputs
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So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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