ArticleAsian-Australasian journal of animal sciences2012
A Whole Genome Association Study to Detect Single Nucleotide Polymorphisms for Blood Components (Immunity) in a Cross between Korean Native Pig and Yorkshire.
Article in Asian-Australasian journal of animal sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Evolutionary and Functional Analysis of Korean Native Pig Using Single Nucleotide Polymorphisms.Molecules and cells · 2020Article
- Genomic Analysis of IgG Antibody Response to Common Pathogens in Commercial Sows in Health-Challenged Herds.Frontiers in genetics · 2020Article
- Loci Associated With Antibody Response in Feral Swine (Frontiers in veterinary science · 2020Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to detect significant SNPs for blood components that were related to immunity using high single nucleotide polymorphism (SNP) density panels in a Korean native pig (KNP)×Yorkshire (YK) cross population. A reciprocal design of KNP×YK produced 249 F2 individuals that were genotyped for a total of 46,865 available SNPs in the Illumina porcine 60K beadchip. To perform whole genome association analysis (WGA), phenotypes were regressed on each SNP under a simple linear regression model after adjustment for sex and slaughter age. To set up a significance threshold, 0.1% point-wise p value from F distribution was used for each SNP test. Among the significant SNPs for a trait, the best set of SNP markers were determined using a stepwise regression procedure with the rates of inclusion and exclusion of each SNP out of the model at 0.001 level. A total of 54 SNPs were detected; 10, 6, 4, 4, 5, 4, 5, 10, and 6 SNPs for neutrophil, lymphocyte, monocyte, eosinophil, basophil, atypical lymph, immunoglobulin, insulin, and insulin-like growth factor-I, respectively. Each set of significant SNPs per trait explained 24 to 42% of phenotypic variance. Several pleiotropic SNPs were detected on SSCs 4, 13, 14 and 15.
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Registered trials
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