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Genome wide analysis reveals single nucleotide polymorphisms associated with fatness and putative novel copy number variants in three pig breeds

Authors :
Nabeel A. Affara
Stephen Waite
Julien Bauer
Ricardo Pong-Wong
Darren K. Griffin
Christopher P. Reitter
Katie E. Fowler
Emily J Clemente
G. A. Walling
Source :
BMC Genomics, Fowler, K E, Pong-Wong, R, Bauer, J, Clemente, E J, Reitter, C P, Affara, N A, Waite, S, Walling, G A & Griffin, D K 2013, ' Genome wide analysis reveals single nucleotide polymorphisms associated with fatness and putative novel copy number variants in three pig breeds ', BMC Genomics, vol. 14, no. 1, pp. 784 . https://doi.org/10.1186/1471-2164-14-784
Publication Year :
2013
Publisher :
BioMed Central, 2013.

Abstract

Background Obesity, excess fat tissue in the body, can underlie a variety of medical complaints including heart disease, stroke and cancer. The pig is an excellent model organism for the study of various human disorders, including obesity, as well as being the foremost agricultural species. In order to identify genetic variants associated with fatness, we used a selective genomic approach sampling DNA from animals at the extreme ends of the fat and lean spectrum using estimated breeding values derived from a total population size of over 70,000 animals. DNA from 3 breeds (Sire Line Large White, Duroc and a white Pietrain composite line (Titan)) was used to interrogate the Illumina Porcine SNP60 Genotyping Beadchip in order to identify significant associations in terms of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). Results By sampling animals at each end of the fat/lean EBV (estimate breeding value) spectrum the whole population could be assessed using less than 300 animals, without losing statistical power. Indeed, several significant SNPs (at the 5% genome wide significance level) were discovered, 4 of these linked to genes with ontologies that had previously been correlated with fatness (NTS, FABP6, SST and NR3C2). Quantitative analysis of the data identified putative CNV regions containing genes whose ontology suggested fatness related functions (MCHR1, PPARĪ±, SLC5A1 and SLC5A4). Conclusions Selective genotyping of EBVs at either end of the phenotypic spectrum proved to be a cost effective means of identifying SNPs and CNVs associated with fatness and with estimated major effects in a large population of animals.

Details

Language :
English
ISSN :
14712164
Volume :
14
Database :
OpenAIRE
Journal :
BMC Genomics
Accession number :
edsair.doi.dedup.....bd27d955a0a9e041d6fbc6409933c89a
Full Text :
https://doi.org/10.1186/1471-2164-14-784