7 research outputs found
Phenotype variance was explained to a large degree by the associated genomic loci.
<p>Loci identified by linear mixed model (LMM) analysis were broadly defined as SNPs with r<sup>2</sup>>0.5 within 5Mb of the peak SNP. (<b>a</b>) For GCTA, 36 loci in 72.7Mb of the genome explained 48.09% of the phenotypic variance. (<b>b</b>) For GEMMA, 47 loci in 82.7Mb of the genome explained 55.88% of the phenotypic variance. (<b>c</b>) For PUMA, 65 loci in 86.58Mb of the genome explained 50.28% of the phenotypic variance in the ACL rupture trait. Whiskers represent the standard error of the mean.</p
Genetic risk scoring [42] using GWAS associated loci from linear mixed model analysis with GEMMA segregates ACL rupture disease risk in case and control Labrador Retriever dogs.
<p>(<b>a</b>) Distribution of the number of ACL rupture risk loci in case and control groups of Labrador Retriever dogs. The number of risk alleles in cases and controls is significantly different (<i>P</i><2.2E-16) (<b>b</b>) ACL rupture odds ratios of weighted genetic risk scores (wGRS) relative to the first quartile. Vertical bars represent the 95% confidence intervals. * Odds ratio is significantly different from the reference first quartile.</p
The Labrador Retriever is a dog breed with a relatively low amount of inbreeding.
<p>Whiskers represent the standard error of the mean for each analysis method (n = 237 dogs).</p
Receiver Operating Characteristic (ROC) analysis of genetic risk scoring in ACL rupture case and control Labrador Retriever dogs using GWAS associated SNPs from linear mixed model analysis.
<p>Receiver Operating Characteristic (ROC) analysis of genetic risk scoring in ACL rupture case and control Labrador Retriever dogs using GWAS associated SNPs from linear mixed model analysis.</p
ACL rupture associated loci identified by GWAS in the Labrador Retriever, a dog breed with a high disease prevalence.
<p>ACL rupture associated loci identified by GWAS in the Labrador Retriever, a dog breed with a high disease prevalence.</p
Linear mixed model GWAS corrects for population structure and identifies 99 ACL associated loci explaining a large proportion of phenotypic variance.
<p>For each linear mixed model (LMM), the QQ plots show no evidence of population stratification relative to the expected distribution. Permutation testing with each model determined genome-wide significance at (<b>a</b>) <i>P</i><3.63E-7 for GCTA (Genome-wide Complex Trait Analysis) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173810#pone.0173810.ref033" target="_blank">33</a>], 位 = 0.987 (<b>b</b>) <i>P</i><6.097E-7 for GEMMA (Genome-wide Efficient Mixed Model Association) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173810#pone.0173810.ref034" target="_blank">34</a>], 位 = 0.994 and (<b>c</b>) <i>P</i><4.01E-7 for PUMA (Penalized Unified Multiple-locus Association) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173810#pone.0173810.ref035" target="_blank">35</a>], 位 = 1.012. The plots represent analysis of 118,992 SNPs from 98 cases and 139 phenotype-negative controls. (<b>d</b>) With GCTA, 36 loci have <i>P</i><5E-4, with the most significant locus located in CFA 24, which did not meet genome-wide significance defined by minimum p-values from permutation testing. (<b>e</b>) With GEMMA, 47 loci have <i>P</i><5E-4, with the locus on CFA 24 meeting genome-wide significance defined by minimum p-values from permutation testing. (<b>f</b>) With PUMA, 65 loci were significant at <i>P</i><5E-4 and the locus on CFA 24 exceeded genome-wide significance defined by minimum p-values from permutation testing. The single SNP that met genome-wide significance lies within the gene <i>PPP1R16B</i>.</p
Functional annotation clustering of genes in regions associated with anterior cruciate ligament rupture identified by GWAS in the Labrador Retriever.
<p>Functional annotation clustering of genes in regions associated with anterior cruciate ligament rupture identified by GWAS in the Labrador Retriever.</p