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Genome-Wide Signatures of Selection Reveal Genes Associated With Performance in American Quarter Horse Subpopulations

Overview of attention for article published in Frontiers in Genetics, July 2018
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Title
Genome-Wide Signatures of Selection Reveal Genes Associated With Performance in American Quarter Horse Subpopulations
Published in
Frontiers in Genetics, July 2018
DOI 10.3389/fgene.2018.00249
Pubmed ID
Authors

Felipe Avila, James R. Mickelson, Robert J. Schaefer, Molly E. McCue

Abstract

Selective breeding for athletic performance in various disciplines has resulted in population stratification within the American Quarter Horse (QH) breed. The goals of this study were to utilize high density genotype data to: (1) identify genomic regions undergoing positive selection within and among QH subpopulations; (2) investigate haplotype structure within each QH subpopulation; and (3) identify candidate genes within genomic regions of interest (ROI), as well as biological pathways, predicted to play a role in elite performance in each group. For that, 65K SNP genotyping data on 143 elite individuals from 6 QH subpopulations (cutting, halter, racing, reining, western pleasure, and working cow) were imputed to 2M SNPs. Signatures of selection were identified using FST-based (d i ) and haplotype-based (hapFLK) analyses, accompanied by identification of local haplotype structure and sharing within subpopulations (hapQTL). Regions undergoing positive selection were identified on all 31 autosomes, and ROI on 2 chromosomes were identified by all 3 methods combined. Genes within each ROI were retrieved and used to identify pathways and genes that might contribute to performance in each subpopulation. These included, among others, candidate genes associated with skeletal muscle development, metabolism, and central nervous system development. This work improves our understanding of equine breed development, and provides breeders with a better understanding of how selective breeding impacts the performance of QH populations.

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The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 18%
Student > Master 8 16%
Student > Ph. D. Student 8 16%
Other 6 12%
Student > Bachelor 2 4%
Other 4 8%
Unknown 13 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 28%
Biochemistry, Genetics and Molecular Biology 9 18%
Veterinary Science and Veterinary Medicine 5 10%
Computer Science 2 4%
Nursing and Health Professions 1 2%
Other 1 2%
Unknown 18 36%
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 19 July 2018.
All research outputs
#15,540,879
of 23,096,849 outputs
Outputs from Frontiers in Genetics
#5,530
of 12,152 outputs
Outputs of similar age
#209,198
of 329,152 outputs
Outputs of similar age from Frontiers in Genetics
#96
of 157 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
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