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Genome-wide association study in Chinese Holstein cows reveal two candidate genes for somatic cell score as an indicator for mastitis susceptibility

Overview of attention for article published in BMC Genomic Data, September 2015
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Title
Genome-wide association study in Chinese Holstein cows reveal two candidate genes for somatic cell score as an indicator for mastitis susceptibility
Published in
BMC Genomic Data, September 2015
DOI 10.1186/s12863-015-0263-3
Pubmed ID
Authors

Xiao Wang, Peipei Ma, Jianfeng Liu, Qin Zhang, Yuan Zhang, Xiangdong Ding, Li Jiang, Yachun Wang, Yi Zhang, Dongxiao Sun, Shengli Zhang, Guosheng Su, Ying Yu

Abstract

Bovine mastitis is a typical inflammatory disease causing seriously economic loss. Genome-wide association study (GWAS) can be a powerful method to promote marker assistant selection of this kind of complex disease. The present study aimed to analyze and identify single nucleotide polymorphisms (SNPs) and candidate genes that associated with mastitis susceptibility traits in Chinese Holstein. Forty eight SNPs were identified significantly associated with mastitis resistance traits in Chinese Holstein cows, which are mainly located on the BTA 14. A total of 41 significant SNPs were linked to 31 annotated bovine genes. Gene Ontology and pathway enrichment revealed 5 genes involved in 32 pathways, in which, TRAPPC9 and ARHGAP39 genes participate cell differentiation and developmental pathway together. The six common genome-wide significant SNPs are found located within TRAPPC9 and flanking ARHGAP39 genes. Our data identified the six SNPs significantly associated with SCS EBVs, which suggest that their linked two genes (TRAPPC9 and ARHGAP39) are novel candidate genes of mastitis susceptibility in Holsteins.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 1%
Brazil 1 1%
Unknown 66 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 35%
Student > Master 8 12%
Student > Bachelor 6 9%
Researcher 5 7%
Student > Postgraduate 3 4%
Other 3 4%
Unknown 19 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 44%
Biochemistry, Genetics and Molecular Biology 8 12%
Veterinary Science and Veterinary Medicine 3 4%
Medicine and Dentistry 3 4%
Psychology 1 1%
Other 2 3%
Unknown 21 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 16 September 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
#192,454
of 281,197 outputs
Outputs of similar age from BMC Genomic Data
#17
of 30 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.
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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 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.