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Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

Overview of attention for article published in BMC Genomics, June 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)

Mentioned by

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3 tweeters

Citations

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12 Dimensions

Readers on

mendeley
28 Mendeley
Title
Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array
Published in
BMC Genomics, June 2017
DOI 10.1186/s12864-017-3847-7
Pubmed ID
Authors

Bo Zhu, Hong Niu, Wengang Zhang, Zezhao Wang, Yonghu Liang, Long Guan, Peng Guo, Yan Chen, Lupei Zhang, Yong Guo, Heming Ni, Xue Gao, Huijiang Gao, Lingyang Xu, Junya Li

Abstract

Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle. Using the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle. We identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 6 21%
Student > Ph. D. Student 6 21%
Researcher 5 18%
Student > Doctoral Student 4 14%
Student > Master 3 11%
Other 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 54%
Unspecified 11 39%
Veterinary Science and Veterinary Medicine 1 4%
Engineering 1 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 June 2017.
All research outputs
#6,478,469
of 11,383,682 outputs
Outputs from BMC Genomics
#3,645
of 6,813 outputs
Outputs of similar age
#115,709
of 242,368 outputs
Outputs of similar age from BMC Genomics
#64
of 93 outputs
Altmetric has tracked 11,383,682 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,813 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 46th percentile – i.e., 46% 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 242,368 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.