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High-Density Genotypes of Inbred Mouse Strains: Improved Power and Precision of Association Mapping.

Rau CD, Parks B, Wang Y, Eskin E, Simecek P, Churchill GA, Lusis AJ - G3 (Bethesda) (2015)

Bottom Line: Human genome-wide association studies have identified thousands of loci associated with disease phenotypes.To enable well-powered studies in mice, we have generated high-density genotypes for ∼175 inbred strains of mice using the Mouse Diversity Array.The data are freely available for download, and Web-based tools provide easy access for association mapping and viewing of the underlying intensity data for individual loci.

View Article: PubMed Central - PubMed

Affiliation: Departments of Human Genetics, Medicine, Microbiology, Immunology and Molecular Genetics, UCLA, Los Angeles, California 90095-1679.

No MeSH data available.


Related in: MedlinePlus

Effects of new single-nucleotide polymorphisms (SNPs) on genome-wide association study results. In both cases, the phenotype being used is total heart weight after isoproterenol treatment. Red line indicates genome-wide significance threshold (4.1E-6). (A) Results using EMMA on the Prior genotypes reveals a single locus on chromosome 1. (B) Results using EMMA on Mouse Diversity Array (MDA) genotypes reveals four additional loci. (C) Results using EMMA on the MDA genotypes using a kinship matrix generated from the Prior genotypes does not demonstrably change the results from B).
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fig3: Effects of new single-nucleotide polymorphisms (SNPs) on genome-wide association study results. In both cases, the phenotype being used is total heart weight after isoproterenol treatment. Red line indicates genome-wide significance threshold (4.1E-6). (A) Results using EMMA on the Prior genotypes reveals a single locus on chromosome 1. (B) Results using EMMA on Mouse Diversity Array (MDA) genotypes reveals four additional loci. (C) Results using EMMA on the MDA genotypes using a kinship matrix generated from the Prior genotypes does not demonstrably change the results from B).

Mentions: To illustrate the improved performance of GWAS using the MDA genotypes, we present a new analysis of previously reported data on the role of catecholamine stimulation on heart weight (Rau et al. 2015). We performed GWA analyses of heart weight after catecholamine stimulation using the efficient mixed model algorithm (Kang et al. 2008) with both the Prior genotypes (Figure 3A) and the new MDA genotypes (Figure 3B). Using the Prior genotypes, we identified a single significant locus, while using the MDA genotypes, we identified four additional loci at genome-wide significance (P < 4.1E-6), as determined previously for the HMDP (Kang et al. 2008; Bennett et al. 2010). Each of the new loci had achieved a suggestive (P < 0.05) level of significance using the Prior genotypes, which provides an indication of the consistency of these findings; however, as only 71,000 SNPs are shared between the two datasets, the specific SNPs making up the peaks in both genotype sets were not entirely identical. Like other mixed-model algorithms (e.g., Lippert et al. 2011), EMMA uses a kinship matrix to correct for substructure in the study population. We examined whether changes to the kinship matrix might lead to this result by using the Prior kinship matrix while performing EMMA on the MDA genotypes (Figure 3C, Figure S2, Figure S3, Figure S4, Figure S5, Figure S6, Figure S7, and Figure S8). Although there were some differences in association strengths (Figure S9), the peak SNPs were not affected. When the peak SNP was shared, the SNP had nearly identical genotypes in both sets, which suggests that even small changes to the genotypes can have large effects on the results.


High-Density Genotypes of Inbred Mouse Strains: Improved Power and Precision of Association Mapping.

Rau CD, Parks B, Wang Y, Eskin E, Simecek P, Churchill GA, Lusis AJ - G3 (Bethesda) (2015)

Effects of new single-nucleotide polymorphisms (SNPs) on genome-wide association study results. In both cases, the phenotype being used is total heart weight after isoproterenol treatment. Red line indicates genome-wide significance threshold (4.1E-6). (A) Results using EMMA on the Prior genotypes reveals a single locus on chromosome 1. (B) Results using EMMA on Mouse Diversity Array (MDA) genotypes reveals four additional loci. (C) Results using EMMA on the MDA genotypes using a kinship matrix generated from the Prior genotypes does not demonstrably change the results from B).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4592984&req=5

fig3: Effects of new single-nucleotide polymorphisms (SNPs) on genome-wide association study results. In both cases, the phenotype being used is total heart weight after isoproterenol treatment. Red line indicates genome-wide significance threshold (4.1E-6). (A) Results using EMMA on the Prior genotypes reveals a single locus on chromosome 1. (B) Results using EMMA on Mouse Diversity Array (MDA) genotypes reveals four additional loci. (C) Results using EMMA on the MDA genotypes using a kinship matrix generated from the Prior genotypes does not demonstrably change the results from B).
Mentions: To illustrate the improved performance of GWAS using the MDA genotypes, we present a new analysis of previously reported data on the role of catecholamine stimulation on heart weight (Rau et al. 2015). We performed GWA analyses of heart weight after catecholamine stimulation using the efficient mixed model algorithm (Kang et al. 2008) with both the Prior genotypes (Figure 3A) and the new MDA genotypes (Figure 3B). Using the Prior genotypes, we identified a single significant locus, while using the MDA genotypes, we identified four additional loci at genome-wide significance (P < 4.1E-6), as determined previously for the HMDP (Kang et al. 2008; Bennett et al. 2010). Each of the new loci had achieved a suggestive (P < 0.05) level of significance using the Prior genotypes, which provides an indication of the consistency of these findings; however, as only 71,000 SNPs are shared between the two datasets, the specific SNPs making up the peaks in both genotype sets were not entirely identical. Like other mixed-model algorithms (e.g., Lippert et al. 2011), EMMA uses a kinship matrix to correct for substructure in the study population. We examined whether changes to the kinship matrix might lead to this result by using the Prior kinship matrix while performing EMMA on the MDA genotypes (Figure 3C, Figure S2, Figure S3, Figure S4, Figure S5, Figure S6, Figure S7, and Figure S8). Although there were some differences in association strengths (Figure S9), the peak SNPs were not affected. When the peak SNP was shared, the SNP had nearly identical genotypes in both sets, which suggests that even small changes to the genotypes can have large effects on the results.

Bottom Line: Human genome-wide association studies have identified thousands of loci associated with disease phenotypes.To enable well-powered studies in mice, we have generated high-density genotypes for ∼175 inbred strains of mice using the Mouse Diversity Array.The data are freely available for download, and Web-based tools provide easy access for association mapping and viewing of the underlying intensity data for individual loci.

View Article: PubMed Central - PubMed

Affiliation: Departments of Human Genetics, Medicine, Microbiology, Immunology and Molecular Genetics, UCLA, Los Angeles, California 90095-1679.

No MeSH data available.


Related in: MedlinePlus