Article

Fine mapping in 94 inbred mouse strains using a high-density haplotype resource.

Center for Human Genetics Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
Genetics (impact factor: 4.01). 05/2010; 185(3):1081-95. DOI:10.1534/genetics.110.115014 pp.1081-95
Source: PubMed

ABSTRACT The genetics of phenotypic variation in inbred mice has for nearly a century provided a primary weapon in the medical research arsenal. A catalog of the genetic variation among inbred mouse strains, however, is required to enable powerful positional cloning and association techniques. A recent whole-genome resequencing study of 15 inbred mouse strains captured a significant fraction of the genetic variation among a limited number of strains, yet the common use of hundreds of inbred strains in medical research motivates the need for a high-density variation map of a larger set of strains. Here we report a dense set of genotypes from 94 inbred mouse strains containing 10.77 million genotypes over 121,433 single nucleotide polymorphisms (SNPs), dispersed at 20-kb intervals on average across the genome, with an average concordance of 99.94% with previous SNP sets. Through pairwise comparisons of the strains, we identified an average of 4.70 distinct segments over 73 classical inbred strains in each region of the genome, suggesting limited genetic diversity between the strains. Combining these data with genotypes of 7570 gap-filling SNPs, we further imputed the untyped or missing genotypes of 94 strains over 8.27 million Perlegen SNPs. The imputation accuracy among classical inbred strains is estimated at 99.7% for the genotypes imputed with high confidence. We demonstrated the utility of these data in high-resolution linkage mapping through power simulations and statistical power analysis and provide guidelines for developing such studies. We also provide a resource of in silico association mapping between the complex traits deposited in the Mouse Phenome Database with our genotypes. We expect that these resources will facilitate effective designs of both human and mouse studies for dissecting the genetic basis of complex traits.

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    Article: Mouse Phenome Database (MPD).
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    ABSTRACT: The Mouse Phenome Project was launched a decade ago to complement mouse genome sequencing efforts by promoting new phenotyping initiatives under standardized conditions and collecting the data in a central public database, the Mouse Phenome Database (MPD; http://phenome.jax.org). MPD houses a wealth of strain characteristics data to facilitate the use of the laboratory mouse in translational research for human health and disease, helping alleviate problems involving experimentation in humans that cannot be done practically or ethically. Data sets are voluntarily contributed by researchers from a variety of institutions and settings, or in some cases, retrieved by MPD staff from public sources. MPD maintains a growing collection of standardized reference data that assists investigators in selecting mouse strains for research applications; houses treatment/control data for drug studies and other interventions; offers a standardized platform for discovering genotype-phenotype relationships; and provides tools for hypothesis testing. MPD improvements and updates since our last NAR report are presented, including the addition of new tools and features to facilitate navigation and data mining as well as the acquisition of new data (phenotypic, genotypic and gene expression).
    Nucleic Acids Research 11/2011; 40(Database issue):D887-94. · 8.03 Impact Factor

Keywords

10.77 million genotypes
 
121,433 single nucleotide polymorphisms
 
15 inbred mouse strains
 
4.70 distinct segments
 
73 classical inbred strains
 
7570 gap-filling SNPs
 
8.27 million Perlegen SNPs
 
94 inbred mouse strains
 
association techniques
 
classical inbred strains
 
common use
 
genotypes imputed
 
high-density variation map
 
high-resolution linkage
 
inbred mouse strains
 
limited number
 
medical research motivates
 
mouse studies
 
significant fraction
 
silico association