↓ Skip to main content

Genome-wide association and genomic prediction of breeding values for fatty acid composition in subcutaneous adipose and longissimus lumborum muscle of beef cattle

Overview of attention for article published in BMC Genomic Data, November 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
45 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
Genome-wide association and genomic prediction of breeding values for fatty acid composition in subcutaneous adipose and longissimus lumborum muscle of beef cattle
Published in
BMC Genomic Data, November 2015
DOI 10.1186/s12863-015-0290-0
Pubmed ID
Authors

Liuhong Chen, Chinyere Ekine-Dzivenu, Michael Vinsky, John Basarab, Jennifer Aalhus, Mike E. R. Dugan, Carolyn Fitzsimmons, Paul Stothard, Changxi Li

Abstract

Identification of genetic variants that are associated with fatty acid composition in beef will enhance our understanding of host genetic influence on the trait and also allow for more effective improvement of beef fatty acid profiles through genomic selection and marker-assisted diet management. In this study, 81 and 83 fatty acid traits were measured in subcutaneous adipose (SQ) and longissimus lumborum muscle (LL), respectively, from 1366 purebred and crossbred beef steers and heifers that were genotyped on the Illumina BovineSNP50 Beadchip. The objective was to conduct genome-wide association studies (GWAS) for the fatty acid traits and to evaluate the accuracy of genomic prediction for fatty acid composition using genomic best linear unbiased prediction (GBLUP) and Bayesian methods. In total, 302 and 360 significant SNPs spanning all autosomal chromosomes were identified to be associated with fatty acid composition in SQ and LL tissues, respectively. Proportions of total genetic variance explained by individual significant SNPs ranged from 0.03 to 11.06 % in SQ, and from 0.005 to 24.28 % in the LL muscle. Markers with relatively large effects were located near fatty acid synthase (FASN), stearoyl-CoA desaturase (SCD), and thyroid hormone responsive (THRSP) genes. For the majority of the fatty acid traits studied, the accuracy of genomic prediction was relatively low (<0.40). Relatively high accuracies (> = 0.50) were achieved for 10:0, 12:0, 14:0, 15:0, 16:0, 9c-14:1, 12c-16:1, 13c-18:1, and health index (HI) in LL, and for 12:0, 14:0, 15:0, 10 t,12c-18:2, and 11 t,13c + 11c,13 t-18:2 in SQ. The Bayesian method performed similarly as GBLUP for most of the traits but substantially better for traits that were affected by SNPs of large effects as identified by GWAS. Fatty acid composition in beef is influenced by a few host genes with major effects and many genes of smaller effects. With the current training population size and marker density, genomic prediction has the potential to predict the breeding values of fatty acid composition in beef cattle at a moderate to relatively high accuracy for fatty acids that have moderate to high heritability.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Russia 1 2%
Brazil 1 2%
Unknown 43 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 20%
Student > Ph. D. Student 8 18%
Researcher 4 9%
Student > Bachelor 3 7%
Other 3 7%
Other 6 13%
Unknown 12 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 53%
Medicine and Dentistry 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Veterinary Science and Veterinary Medicine 1 2%
Unspecified 1 2%
Other 1 2%
Unknown 14 31%
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 22 November 2015.
All research outputs
#19,944,091
of 25,373,627 outputs
Outputs from BMC Genomic Data
#786
of 1,204 outputs
Outputs of similar age
#272,845
of 392,792 outputs
Outputs of similar age from BMC Genomic Data
#18
of 31 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 28th percentile – i.e., 28% 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 392,792 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.