1. Risk of false positive genetic associations in complex traits with underlying population structure: A case study
- Author
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Finno, Carrie J, Aleman, Monica, Higgins, Robert J, Madigan, John E, and Bannasch, Danika L
- Subjects
Veterinary Sciences ,Agricultural ,Veterinary and Food Sciences ,Biological Sciences ,Genetics ,Prevention ,Brain Disorders ,Human Genome ,Animals ,Female ,Genome-Wide Association Study ,Genotype ,Horse Diseases ,Horses ,Male ,Neuroaxonal Dystrophies ,Polymorphism ,Single Nucleotide ,Risk ,Equine degenerative myeloencephalopathy ,Horse genome ,Single nucleotide polymorphisms ,Vitamin E ,Agricultural and Veterinary Sciences ,Agricultural ,veterinary and food sciences ,Biological sciences - Abstract
Genome-wide association (GWA) studies are widely used to investigate the genetic etiology of diseases in domestic animals. In the horse, GWA studies using 40-50,000 single nucleotide polymorphisms (SNPs) in sample sizes of 30-40 individuals, consisting of only 6-14 affected horses, have led to the discovery of genetic mutations for simple monogenic traits. Equine neuroaxonal dystrophy is a common inherited neurological disorder characterized by symmetric ataxia. A case-control GWA study was performed using genotypes from 42,819 SNP marker loci distributed across the genome in 99 clinically phenotyped Quarter horses (37 affected, 62 unaffected). A significant GWA was not achieved although a suggestive association was uncovered when only the most stringently phenotyped NAD-affected horses (n = 10) were included (chromosome 8:62130605 and 62134644 [log(1/P) = 5.56]). Candidate genes (PIK3C3, RIT2, and SYT4) within the associated region were excluded through sequencing, association testing of uncovered variants and quantitative RT-PCR. It was concluded that variants in PIK3C3, RIT2, and SYT4 are not responsible for equine neuroaxonal dystrophy. This study demonstrates the risk of false positive associations when performing GWA studies on complex traits and underlying population structure when using 40-50,000 SNP markers and small sample size.
- Published
- 2014