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Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle

Overview of attention for article published in BMC Genomics, September 2018
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Title
Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
Published in
BMC Genomics, September 2018
DOI 10.1186/s12864-018-5050-x
Pubmed ID
Authors

Zexi Cai, Bernt Guldbrandtsen, Mogens Sandø Lund, Goutam Sahana

Abstract

Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and post-infection healing. Low genetic heritability, environmental variations, and farm management differences further complicate the identification of links between genetic variants and mastitis resistance. Consequently, studies of the genetics of variation in mastitis resistance in dairy cattle lack agreement about the responsible genes. We associated 15,552,968 imputed whole-genome sequencing markers for 5147 Nordic Holstein cattle with mastitis resistance in a genome-wide association study (GWAS). Next, we augmented P-values for markers in genes in the associated regions using Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and mammalian phenotype database. To confirm results of gene-based analyses, we used gene expression data from E. coli-challenged cow udders. We identified 22 independent quantitative trait loci (QTL) that collectively explained 14% of the variance in breeding values for resistance to clinical mastitis (CM). Using association test statistics with multiple pieces of independent information on gene function and differential expression during bacterial infection, we suggested putative causal genes with biological relevance for 12 QTL affecting resistance to CM in dairy cattle. Combining information on the nearest positional genes, gene-based analyses, and differential gene expression data from RNA-seq, we identified putative causal genes (candidate genes with biological evidence) in QTL for mastitis resistance in Nordic Holstein cattle. The same strategy can be applied for other traits.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 18%
Researcher 17 17%
Student > Master 13 13%
Other 6 6%
Student > Bachelor 6 6%
Other 14 14%
Unknown 28 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 34%
Veterinary Science and Veterinary Medicine 12 12%
Biochemistry, Genetics and Molecular Biology 11 11%
Medicine and Dentistry 3 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 9 9%
Unknown 30 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 08 September 2018.
All research outputs
#13,550,758
of 23,102,082 outputs
Outputs from BMC Genomics
#4,996
of 10,709 outputs
Outputs of similar age
#169,925
of 336,142 outputs
Outputs of similar age from BMC Genomics
#77
of 190 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,709 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 52% of its peers.
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 336,142 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 190 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.