title: Integrating QTL and high-density SNP analyses in mice to identify Insig2 as a susceptibility gene for plasma cholesterol levels.
abstract: The use of inbred strains of mice to dissect the genetic complexity of common diseases offers a viable alternative to human studies, given the control over experimental parameters that can be exercised. Central to efforts to map susceptibility loci for common diseases in mice is a comprehensive map of DNA variation among the common inbred strains of mice. Here we present one of the most comprehensive high-density, single nucleotide polymorphism (SNP) maps of mice constructed to date. This map consists of 10,350 SNPs genotyped in 62 strains of inbred mice. We demonstrate the utility of these data via a novel integrative genomics approach to mapping susceptibility loci for complex traits. By integrating in silico quantitative trait locus (QTL) mapping with progressive QTL mapping strategies in segregating mouse populations that leverage large-scale mapping of the genetic determinants of gene expression traits, we not only facilitate identification of candidate quantitative trait genes, but also protect against spurious associations that can arise in genetic association studies due to allelic association among unlinked markers. Application of this approach to our high-density SNP map and two previously described F2 crosses between strains C57BL/6J (B6) and DBA/2J and between B6 ApoE(-/-) and C3H/HeJ ApoE(-/-) results in the identification of Insig2 as a strong candidate susceptibility gene for total plasma cholesterol levels.
authors.affiliation: Rosetta Inpharmatics, LLC, Seattle, WA 98109, USA.
authors.forename: Alessandra C
authors.initials: AC
authors.lastname: Cervino
authors.forename: Guoya
authors.initials: G
authors.lastname: Li
authors.forename: Steve
authors.initials: S
authors.lastname: Edwards
authors.forename: Jun
authors.initials: J
authors.lastname: Zhu
authors.forename: Cathy
authors.initials: C
authors.lastname: Laurie
authors.forename: George
authors.initials: G
authors.lastname: Tokiwa
authors.forename: Pek Yee
authors.initials: PY
authors.lastname: Lum
authors.forename: Susanna
authors.initials: S
authors.lastname: Wang
authors.forename: Lawrence W
authors.initials: LW
authors.lastname: Castellani
authors.forename: Lawrence W
authors.initials: LW
authors.lastname: Castellini
authors.forename: Aldons J
authors.initials: AJ
authors.lastname: Lusis
authors.forename: Sonia
authors.initials: S
authors.lastname: Carlson
authors.forename: Alan B
authors.initials: AB
authors.lastname: Sachs
authors.forename: Eric E
authors.initials: EE
authors.lastname: Schadt
mesh_terms: D000818:Animals; D002784:Cholesterol / Q000097:blood*; D002874:Chromosome Mapping / Q000379:methods*; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006937:Hypercholesterolemia / Q000235:genetics* / Q000662:veterinary; D008565:Membrane Proteins / Q000235:genetics* / Q000502:physiology; D051379:Mice; D008810:Mice, Inbred C57BL; D008811:Mice, Inbred DBA; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci
chemical_list: D005819:Genetic Markers; D008565:Membrane Proteins; D002784:Cholesterol