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Copy number variations in high and low fertility breeding boars

Overview of attention for article published in BMC Genomics, April 2015
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Title
Copy number variations in high and low fertility breeding boars
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1473-9
Pubmed ID
Authors

Tamas Revay, Anh T Quach, Laurence Maignel, Brian Sullivan, W Allan King

Abstract

In this study we applied the extreme groups / selective genotyping approach for identifying copy number variations in high and low fertility breeding boars. The fertility indicator was the calculated Direct Boar Effect on litter size (DBE) that was obtained as a by-product of the national genetic evaluation for litter size (BLUP). The two groups of animals had DBE values at the upper (high fertility) and lower (low fertility) end of the distribution from a population of more than 38,000 boars. Animals from these two diverse phenotypes were genotyped with the Porcine SNP60K chip and compared by several approaches in order to prove the feasibility of our CNV analysis and to identify putative markers of fertility. We have identified 35 CNVRs covering 36.5 Mb or ~1.3% of the porcine genome. Among these 35 CNVRs, 14 were specific to the high fertility group, while 19 CNVRs were specific to the low fertility group which overlap with 137 QTLs of various reproductive traits. The identified 35 CNVRs encompassed 50 genes, among them 40 were specific to the low fertility group, seven to the high fertility group, while three were found in regions that were present in both groups but with opposite gain/loss status. A functional analysis of several databases revealed that the genes found in CNVRs from the low fertility group have been significantly enriched in members of the innate immune system, Toll-like receptor and RIG-I-like receptor signaling and fatty acid oxidation pathways. We have demonstrated that our analysis pipeline could identify putative CNV markers of fertility, especially in case of low fertility boars.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Canada 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Researcher 6 17%
Student > Master 4 11%
Student > Bachelor 2 6%
Professor > Associate Professor 2 6%
Other 5 14%
Unknown 7 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 34%
Veterinary Science and Veterinary Medicine 5 14%
Biochemistry, Genetics and Molecular Biology 4 11%
Medicine and Dentistry 3 9%
Computer Science 3 9%
Other 1 3%
Unknown 7 20%
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 25 April 2015.
All research outputs
#18,407,102
of 22,800,560 outputs
Outputs from BMC Genomics
#8,176
of 10,649 outputs
Outputs of similar age
#192,918
of 264,200 outputs
Outputs of similar age from BMC Genomics
#213
of 260 outputs
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