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Significant gene content variation characterizes the genomes of inbred mouse strains.

ABSTRACT: The contribution to genetic diversity of genomic segmental copy number variations (CNVs) is less well understood than that of single-nucleotide polymorphisms (SNPs). While less frequent than SNPs, CNVs have greater potential to affect phenotype. In this study, we have performed the most comprehensive survey to date of CNVs in mice, analyzing the genomes of 42 Mouse Phenome Consortium priority strains. This microarray comparative genomic hybridization (CGH)-based analysis has identified 2094 putative CNVs, with an average of 10 Mb of DNA in 51 CNVs when individual mouse strains were compared to the reference strain C57BL/6J. This amount of variation results in gene content that can differ by hundreds of genes between strains. These genes include members of large families such as the major histocompatibility and pheromone receptor genes, but there are also many singleton genes including genes with expected phenotypic consequences from their deletion or amplification. Using a whole-genome association analysis, we demonstrate that complex multigenic phenotypes, such as food intake, can be associated with specific copy number changes.

SUBMITTER: Cutler G

PROVIDER: S-EPMC2099583 | biostudies-literature | 2007 Dec

REPOSITORIES: biostudies-literature

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Significant gene content variation characterizes the genomes of inbred mouse strains.

Cutler Gene G Marshall Lisa A LA Chin Ni N Baribault Helene H Kassner Paul D PD

Genome research 20071107 12

The contribution to genetic diversity of genomic segmental copy number variations (CNVs) is less well understood than that of single-nucleotide polymorphisms (SNPs). While less frequent than SNPs, CNVs have greater potential to affect phenotype. In this study, we have performed the most comprehensive survey to date of CNVs in mice, analyzing the genomes of 42 Mouse Phenome Consortium priority strains. This microarray comparative genomic hybridization (CGH)-based analysis has identified 2094 puta ...[more]

PMID: 17989247

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Project description:Mice are the most widely used animal model to study genotype to phenotype relationships. Inbred mice are genetically identical, which eliminates genetic heterogeneity and makes them particularly useful for genetic studies. Many different strains have been bred over decades and a vast amount of phenotypic data has been generated. In addition, recently whole genome sequencing-based genome-wide genotype data for many widely used inbred strains has been released. Here, we present an approach for in silico fine-mapping that uses genotypic data of 37 inbred mouse strains together with phenotypic data provided by the user to propose candidate variants and genes for the phenotype under study. Public genome-wide genotype data covering more than 74 million variant sites is queried efficiently in real-time to provide those variants that are compatible with the observed phenotype differences between strains. Variants can be filtered by molecular consequences and by corresponding molecular impact. Candidate gene lists can be generated from variant lists on the fly. Fine-mapping together with annotation or filtering of results is provided in a Bioconductor package called MouseFM. In order to characterize candidate variant lists under various settings, MouseFM was applied to two expression data sets across 20 inbred mouse strains, one from neutrophils and one from CD4+ T cells. Fine-mapping was assessed for about 10,000 genes, respectively, and identified candidate variants and haplotypes for many expression quantitative trait loci (eQTLs) reported previously based on these data. For albinism, MouseFM reports only one variant allele of moderate or high molecular impact that only albino mice share: a missense variant in the Tyr gene, reported previously to be causal for this phenotype. Performing in silico fine-mapping for interfrontal bone formation in mice using four strains with and five strains without interfrontal bone results in 12 genes. Of these, three are related to skull shaping abnormality. Finally performing fine-mapping for dystrophic cardiac calcification by comparing 9 strains showing the phenotype with eight strains lacking it, we identify only one moderate impact variant in the known causal gene Abcc6. In summary, this illustrates the benefit of using MouseFM for candidate variant and gene identification.

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Significant gene content variation characterizes the genomes of inbred mouse strains.

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Significant gene content variation characterizes the genomes of inbred mouse strains.

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