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

Andrew Kirby, Hyun Min Kang, Claire M. Wade, Chris Cotsapas, Emrah Kostem, Buhm Han, Nick Furlotte, Eun Yong Kang, Manuel Rivas, Molly A. Bogue, Kelly A. Frazer, Frank M. Johnson, Erica J. Beilharz, David R. Cox, Eleazar Eskin, Mark J. Daly

Research output: Contribution to journalArticle

74 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1081-1095
Number of pages15
JournalGenetics
Volume185
Issue number3
DOIs
StatePublished - 1 Jul 2010

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Inbred Strains Mice
Haplotypes
Genotype
Single Nucleotide Polymorphism
Genome
Biomedical Research
Weapons
Chromosome Mapping
Computer Simulation
Organism Cloning
Databases
Guidelines

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Kirby, A., Kang, H. M., Wade, C. M., Cotsapas, C., Kostem, E., Han, B., ... Daly, M. J. (2010). Fine mapping in 94 inbred mouse strains using a high-density haplotype resource. Genetics, 185(3), 1081-1095. https://doi.org/10.1534/genetics.110.115014
Kirby, Andrew ; Kang, Hyun Min ; Wade, Claire M. ; Cotsapas, Chris ; Kostem, Emrah ; Han, Buhm ; Furlotte, Nick ; Kang, Eun Yong ; Rivas, Manuel ; Bogue, Molly A. ; Frazer, Kelly A. ; Johnson, Frank M. ; Beilharz, Erica J. ; Cox, David R. ; Eskin, Eleazar ; Daly, Mark J. / Fine mapping in 94 inbred mouse strains using a high-density haplotype resource. In: Genetics. 2010 ; Vol. 185, No. 3. pp. 1081-1095.
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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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Kirby, A, Kang, HM, Wade, CM, Cotsapas, C, Kostem, E, Han, B, Furlotte, N, Kang, EY, Rivas, M, Bogue, MA, Frazer, KA, Johnson, FM, Beilharz, EJ, Cox, DR, Eskin, E & Daly, MJ 2010, 'Fine mapping in 94 inbred mouse strains using a high-density haplotype resource', Genetics, vol. 185, no. 3, pp. 1081-1095. https://doi.org/10.1534/genetics.110.115014

Fine mapping in 94 inbred mouse strains using a high-density haplotype resource. / Kirby, Andrew; Kang, Hyun Min; Wade, Claire M.; Cotsapas, Chris; Kostem, Emrah; Han, Buhm; Furlotte, Nick; Kang, Eun Yong; Rivas, Manuel; Bogue, Molly A.; Frazer, Kelly A.; Johnson, Frank M.; Beilharz, Erica J.; Cox, David R.; Eskin, Eleazar; Daly, Mark J.

In: Genetics, Vol. 185, No. 3, 01.07.2010, p. 1081-1095.

Research output: Contribution to journalArticle

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T1 - Fine mapping in 94 inbred mouse strains using a high-density haplotype resource

AU - Kirby, Andrew

AU - Kang, Hyun Min

AU - Wade, Claire M.

AU - Cotsapas, Chris

AU - Kostem, Emrah

AU - Han, Buhm

AU - Furlotte, Nick

AU - Kang, Eun Yong

AU - Rivas, Manuel

AU - Bogue, Molly A.

AU - Frazer, Kelly A.

AU - Johnson, Frank M.

AU - Beilharz, Erica J.

AU - Cox, David R.

AU - Eskin, Eleazar

AU - Daly, Mark J.

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Y1 - 2010/7/1

N2 - 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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